Line hardening is regarded as a critical defense measure against malicious attacks in power systems. However, this defense strategy often ignores the uncertainty and multistage nature of malicious attacks. Moreover, with high wind power penetration in power system operation, the inherent volatility of wind power may compromise the performance of the defense strategy against malicious attacks. To address such issues, this article proposes an adaptive robust planner-attacker-operator (AR-PAO) model that accounts for both volatile wind power and multistage uncertain malicious attacks within a line hardening framework. A novel solution algorithm is then developed to solve the AR-PAO model for the optimal defense strategy, in which it improves computational efficiency. Comparative simulation results on two IEEE Reliability Test Systems validate the effectiveness of the proposed approach.

Geographically distributed data centers (DCs) offer significant spatiotemporal flexibility and are ideal candidates for demand response in power systems. This paper proposes a two-stage robust spatiotemporal optimal scheduling model for geographically distributed DCs that accounts for the uncertainty in both renewable energy generation and workload. In the first stage, a day-ahead scheduling approach is employed based on predicted workload and renewable energy generation values to determine pre-scheduling strategies. In the second stage, between the day-ahead and intraday periods, an iterative algorithm is introduced to calculate the number of reserved servers, thereby mitigating the workload overload issues arising from workload uncertainty. Power fluctuations resulting from the uncertainty of the predicted values are balanced using energy storage and generators. Finally, simulation results validate the effectiveness of the proposed algorithm in reducing overcapacity and enhancing the economic efficiency of the scheduling model.

With the advancement of aircraft electrification, the demand for electrical power has increased significantly. Consequently, intensifying challenges in power systems design—particularly in high-voltage distribution systems. The sizing of voltage levels and the optimization of weight play a crucial role in determining overall aircraft weight, directly impacting performance. This paper proposes a voltage level optimization design method for aircraft power distribution system that minimizes system weight while adhering to thermal and insulation constraints. An optimization model is constructed and solved using a multidisciplinary modeling approach. The method is validated and evaluated with parameters from aircraft of different scales, and the optimization results are analyzed.

Accurate load forecasting is essential for power system stability and operational planning. While deterministic forecasts provide point estimates, they fail to capture uncertainty, which can lead to grid imbalances or reserve misallocations. This study evaluates six non-parametric probabilistic forecasting approaches which are Adaptive Conformal Inference (ACI), Deep Quantile Regression (QR), Bayesian LSTM (BLSTM), CatBoost Quantile Regression, Mamba ACI and Mamba QR applied to short-term load forecasting. The stacked LSTM and Mamba models are first optimized via grid search and then used to generate point forecasts over which prediction intervals are constructed. Using 3.4 years of hourly load data from Tamil Nadu, India, the models are evaluated on an unseen dataset of 8.21 months based on coverage, mean interval width (MIW), Continuous Ranked Probability Score (CRPS), and Winkler score. Mamba ACI achieved the highest coverage (92.47%) with MIW of 8.5% of peak load, while LSTM ACI followed with 90.24% coverage and 5.9% MIW. CatBoost yielded the sharpest intervals (3.8% of peak) but with lower coverage (83.81%). DQR showed moderate performance, and BLSTM achieved 89.60% coverage with an MIW of 8.0% of peak load, striking a balance between reliability and sharpness. Mamba QR, though covering 90.29%, produced excessively wide intervals (26.9% of peak). The results highlight that ACI delivers the best balance between sharpness and reliability across architectures. Given the importance of coverage in avoiding forecasting-related operational risks, Mamba ACI emerges as the most practical and robust choice for uncertainty quantification in very short-term load forecasting.

Due to the complementary nature of information contained within Synthetic Aperture Radar (SAR) and optical imagery modalities, accurate registration of these images is a crucial process in remote sensing applications. However, precise matching becomes a complex challenge as a consequence of the substantial radiometric and geometric discrepancies between the two modalities. While recent techniques based on Generative Adversarial Networks (GANs) have proposed viable solutions for SAR and optical image matching, there remains significant potential for further improvements. In this paper, we propose a modified CycleGAN algorithm (OS-CycleGAN) to perform optical and SAR image matching. The loss function of the OS-CycleGAN network is defined not only to enhance the adversarial and cycle consistency losses but also to converge the latent spaces of the generators. By doing so, the latent spaces can be utilized as feature vectors or descriptors. Consequently, in addition to image translation, OS-CycleGAN’s generators provide new descriptors for the central pixels of SAR and optical patches. The method also employs decision-making modules to render the descriptors invariant to projective transformations such as rotation and shearing, as well as contrast changes. Furthermore, by disregarding SAR keypoints in areas affected by geometric distortions such as layover, foreshortening, and radar shadow, and removing optical keypoints in areas affected by optical shadow, the proposed approach mitigates outliers and improves the Correct Matches Rate (CMR). The conducted experimental results on the Sentinel-1/2 and OpenEarthMap-SAR datasets demonstrate the efficacy of the suggested method in terms of matching accuracy and robustness.

Increasing net profits and ensuring the comfort of the residents in community daily energy management is the primary mission of community power operators (CPOs). To reach these goals, the CPO may tailor a bidding strategy to pre-procure a portion of the cheaper power for the reservation to ensure a reliable power supply for scheduling programs. This paper develops a novel bi-level optimization model to resolve this challenge. In the upper level, the CPO aims to maximize net profits through customized power pre-procurement and real-time bi-directional power trading. The lower level focuses on minimizing the electricity costs of the buildings incorporating the building's thermal inertia depending on the real-time temperature variations. The proposed bi-level model presents an interdependent non-linear programming challenge. The instantiations indicate that setting different pre-order power levels for each time slot may improve net profitability for CPO.

Plug-in electric vehicles (EVs) are viewed as a step forward in the electrification of transportation, replacing conventional vehicles powered by internal combustion engines. However, to provide consistent and efficient charging, the EV charging infrastructure needs to be developed, which is capable of delivering distortion-free grid supply, even in the absence of renewable energy resources. This article presents an application of a grid-connected EV charger supplied by a grid-connected solar photovoltaic array that provides 24/7 distortion-free charging. The bidirectional charging system includes an EV battery connected to the dc bus; an independent solar-PV source connected to the ac grid through a bifunctional voltage source converter. A new conjugate gradient based adaptive control algorithm is implemented for the voltage source converter control. Real-time analysis is done using dSPACE 1202 processor. The proposed system is validated to maintain IEEE-519 standards.

This article proposes a multienergy trading market model based on price matching, aiming to foster multienergy collaboration and enhance energy utilization through individual participation. With the ongoing advancements in energy distribution and marketization, the energy Internet necessitates improved applicability and efficiency for personalized energy responses. To address these requirements, a multienergy trading market model is proposed, which enables the avoidance of user information disclosure and guarantees user trading autonomy. In addition, a joint trading mechanism is designed that accounts for multiple time scales and energy types, consequently reducing trading failures caused by overlooking energy transmission processes. By performing the proposed trading mechanism, the market operator can match various energy types using conversion devices, thereby augmenting matching efficiency. An income mechanism is also established to deter the operator from purposefully evading potential trading opportunities for personal gain. To address the proposed model, an improved hierarchical reinforcement learning algorithm is employed, which effectively overcomes challenges associated with large state action spaces and sparse rewards. Numerical examples are provided to confirm the efficacy of the proposed approach.

A sudden change in loads creates troubles in grids/microgrids (MGs) such as frequency fluctuations. For balancing between generation and demand, a Doubly fed induction generator (DFIG) has been incorporated into the Egyptian power system (EG-EPS) to provide additional inertia. The studied EG-EPS consists of three conventional power plants (reheat, non-reheat, and hydro) as the main sources of generation, with 20% DFIG participation. The existing literature highlights that the control methods employ for LFC and DFIG in MGs are insufficiently coordinated for minimizing deviations in frequency and power. This limitation arises due to narrow control constraints and inadequate sensitivity to disturbances. To this regard, this paper proposes an adaptive control-based balloon effect modulation (BE) to tune the PID controller for the Automatic Generation Control (AGC) and to tune the PI controller of the DFIG speed controller. The balloon effect tool is used to minimize the impact of system load disturbance by increasing the optimizer sensitivity and traceability. The EG-EPS is examined under the influence of a 2% step load perturbation and random load variations using dSPACE DS1006 and real-time digital simulator (RTDS) as a Hard-In-Loop (HIL) test platform. The proposed controller demonstrates superior performance compared to the conventional one in terms of overshoot, undershoot, and stabilizing time.

This paper addresses the formulation problem of a power flow for controlled islanded microgrids including battery energy storage systems. The formulation considers droop-based primary controllers, probability-based wind distributions and power curves for the distributed generation units, and sigmoid-based models for the BESS operation and the load shedding. Two case studies are addressed where different BESS conditions are selected to highlight its role in the islanded microgrid, and its impact in the microgrid operative steady-state dynamics. The obtained results corroborate the proposed power flow formulation reliability for representing the controlled islanded microgrid and its usefulness for detailed operative planning and design.

This paper introduces a Power Electronic Converter (PEC) featuring a medium-frequency AC-link and a non-rectifier stage designed to connect photovoltaic (PV) modules to the grid while extracting the maximum power from the PV array. The proposed system incorporates a Battery Energy Storage System (BESS) to mitigate the effects of partial shading. A Three-Level Bidirectional Converter (3LBDC) has been adopted to facilitate battery charging. The 3LBDC converter exhibits minimal ripple in the inductor's current, maintaining the same inductance and frequency values consistent with a traditional boost converter. An Incremental Conductance algorithm is deployed as the Maximum Power Point Tracker (MPPT) on the boost converter, enabling the extraction of available power from the PV system and subsequent injection into either the grid or BESS as necessitated by the conditions. Simulated testing of the entire system indicates that it provides a viable solution for PV-ESS grid-tied applications.

This paper proposes distributed, event-triggered, power-sharing strategies to solve the economic power dispatch (EPD) problem for virtual energy storage systems (VESS) composed of smart homes in microgrids. Existing literature on this subject requires continuous or periodic communication. In this paper we propose a dynamic, event-triggered, information delivery strategy, combined with a weighted, distributed optimization algorithm. By inheriting economic parameters, the proposed algorithm guarantees power balance at each iteration, while power capacity constraints are guaranteed by deriving a virtual energy price for each smart home. These techniques enable the proposed resilient, distributed algorithm to solve EPD problem online with reduced communications. Theoretical analyses demonstrate the convergence and optimality of the proposed algorithm, which also excludes Zeno triggering behavior. Numerical analyses and simulations demonstrate the validity and effectiveness of the proposed strategies.

False data injection attacks (FDIA) in power systems involve intentionally injecting fabricated data to compromise system integrity, reliability, and functionality. These attacks have devastating consequences for power systems, particularly when they have the potential for sequential outages. To defend against these types of attacks, the implementation of an effective defense mechanism is crucial. The defense system should have advanced security measures, like encrypted phasor measurement units (PMU), to protect the integrity and reliability of the power system infrastructure from FDIA-caused outages that happen one after the other. In order to protect against sequential outages brought on by load redistribution attacks (LRA), this paper proposes a PMU placement optimization problem. In this study, we conduct an analysis of the susceptibility of the IEEE 30 bus standard system to LRA, resulting in sequential outages. Additionally, we explore the optimal placement of PMU as a means of improving the system's defense against such vulnerabilities.

For multibus wind power plants in microgrids, it is challenging to develop a reliable, effective, and robust harmonic suppression method for harmonic voltages and currents of all buses. This paper proposes a hierarchical harmonic control method to mitigate the harmonic voltages and currents of all buses in grid-forming wind power plants. The proposed method effectively reduces the terminal harmonic voltages and currents, PCC harmonic voltage, and grid harmonic current. It achieves adaptive harmonic mitigation and automatic harmonic current sharing between wind turbine units according to the rated capacity and feeder impedance of each unit. The effectiveness of the method is verified in the planned Turkish offshore wind power plant by simulation in Digsilent/PowerFactory.

Insulated Gate Bipolar Transistor modules, known as IGBT modules, play a critical and indispensable role in a wide range of power converter applications. However, IGBT modules are not immune to failures, which can have severe consequences such as system faults, downtime, and economic losses for industries relying on their functionality. Accurately estimating the junction temperature of IGBT modules is essential for managing their thermal characteristics, performing condition monitoring and lifetime prediction. Therefore, in this paper, recent IGBT junction temperature estimation methods of are summarized. First, the package, circuit principle and failure mode of IGBT module are introduced, followed by a discussion of various junction temperature estimation methods, including methods based on optical technologies, thermal network and Finite Element Analysis models, and temperature-sensitive electrical parameters (TSEPs). Finally, future research challenges and opportunities for implementing these technologies are presented.

A fuzzy logic based online energy management system (FLEMS) is designed in this paper to achieve the optimal electricity cost in a residential Microgrid (MG). The proposed FLEMS is combined by a local energy price model (LEPM) and a fuzzy-logic strategy. The LEPM will preprocess the sampling data to estimate the electricity market and local MG status. The fuzzy-logic mimics the artificial intelligent assessment to economic issues and make decision for the charging and discharging operation for energy storage system (ESS). In the FLEMS, not only electricity price and supply-demand balance, but also ESS state of charge are considered for the efficient and stable operations. The proposed method does not relay on the accurate prediction of renewable energy source and local loads. Historical experience of the system is involved by the LEPM and guides the ESS operation in the fuzzy-logic. A real-world data based household-level residential MG model is established to validate the performance of the FLEMS. A hourly-resolution-Particle swarm optimization (PSO) with perfect day-ahead prediction is implemented as the baseline to verify the superiority of the proposed method.

In this work, a comprehensive study on the dynamic modeling and control of the reformed methanol high-temperature proton exchange membrane fuel cell (HT-PEMFC) and battery system is presented for electrical applications. A more detailed mathematical model that considers the transient dynamics of the fuel cell is adopted, providing a simplified yet accurate solution for a wide range of fuel cell operational cases. The dynamic system model incorporates the FC, balance of plan (BoP) components, buck/boost converter, and battery. The buck/boost converter operation mode is automatically switched by power management rules according to the battery voltage, achieving coordination between the FC and the battery, stable DC bus voltage, and a healthy state-of-charge (SOC) level of the battery. Simulations are conduction on MATLAB/Simulink and the results validate the effectiveness of the proposed modeling approach and power sharing strategy in achieving enhanced performance and system stability under different load cases. The research contributes for integrating HT-PEMFC systems in future electrical applications.

In order to improve the profits of electricity utility company (EUC) and gas utility company (GUC) and reduce the electricity and heat cost of users, an energy trading and pricing scheme based on three-stage game is proposed. Firstly, a three-stage optimization problem is established, and the conversion between electricity and gas is considered. Meanwhile, the conversion factor is introduced and coordinated with the energy price to adjust the balance of supply and demand. Then, the equilibrium solution of the game is obtained by using Lagrange function and backward induction method. In addition, an iterative algorithm is developed to obtain the optimal conversion factor between electricity and natural gas. Numerical results show that the profits of EUC and GUC are increased by 31.6% and 14.4%, the electricity and heat profits of energy hubs (EHs) are increased by 3% and 6.4%, and the electricity and heat cost of users are reduced by 9.25% and 14.05%. Note to Practitioners—In the multi-energy market, trading and pricing strategies have attracted more and more attention. Based on this, many scholars only studied pricing strategy to balance the supply and demand. However, in the context of multi-energy coupling, the previous pricing strategy is not effective. In this paper, we propose a new pricing strategy, with which the conversion factor can cooperate with the energy price to achieve the balance between supply and demand. The new pricing strategy can increase the profits of electricity utility companies and gas utility companies and reduce the costs of users.

The growth of electric vehicle loads increases the harmonics in the distribution grid. This article proposes a mixed step size normalized least mean fourth control algorithm (MSSNLMF) of distribution static compensator to alleviate the harmonics in the electric vehicles connected distribution grid. The overall system comprises bidirectional ac–dc, dc–dc converters, and distribution static compensator. The bidirectional converters are employed to achieve the vehicle to grid and grid to vehicle operations. A lithium-ion battery is utilized as an electric vehicle energy storage device. An adaptive MSSNLMF control algorithm is proposed to extract active and reactive power signals from the distorted load current to obtain the reference source currents. This algorithm combines the least mean fourth and normalized least mean fourth algorithms with mixed step size. The performance of the control algorithm is evaluated in the MATLAB/Simulink environment. It is experimentally verified through the real time simulation using the dSPACE (DS1202) real-time processor. The proposed MSSNLMF algorithm performs well in the DSTATCOM dc-link voltage regulation and reduction of total harmonic distortion. The source current total harmonic distortion is maintained below the allowable limit of IEEE 519-2014 standard.

Decarbonizing issues from ship transportation during visiting a port offer a few alternatives. Among them is the electrification onshore power system known as cold ironing that provides electric power from the shoreside to the visiting ship at port, replacing auxiliary engines-fossil fuel-based. This paper presents four different environmental dispatch strategies for cold ironing system to minimize both cost and environmental impact while meeting seaport operation constraints. The problem formulation was formulated as quadratic constrained programming (QCP) model and solved in GAMS optimization by using the CANOPT solver. The Pareto optimal front from the simulation offers port operators decision-making options that suit their priority objective function. Furthermore, sensitivity analysis for various load values in the optimization model gives insight into any changes in dispatching patterns as the load changes.

This paper offers a comparative analysis of Maximum Power Point Tracking (MPPTs) techniques under the spinning conditions for small satellite applications. The Nano Satellite (NanoSat) is constrained on volume and mass with body-mounted solar panels and where it is dedicated to some special orientation scenarios, depending on specific mission requirements. This results in irregular solar irradiance on the PV system; thus, it needs an efficient and effective strategy to extract the maximum power transferred to the loads in the NanoSat Electrical Power System (EPS). While the EPS can be regarded a space microgrid due to control and coordination in a small electric network of distributed generations (DGs), storage, and loads. Therefore, some well-known MPPT techniques are investigated where different scenarios are carried out among conventional Perturb and Observe (P&O), Incremental Conductance (IC), and Ripple Correlation Control (RCC) to highlight the optimal MPPT extractions for NanoSat applications. The system was developed and modeled in MATLAB/SIMULINK and the final findings demonstrate that the RCC provides smooth power compared to other ones, while the other ones offer an oscillated power under the effect of radiations change and spinning conditions for the system under test.

The virtual synchronous generator (VSG) has been extensively applied for the integration of distributed generators. For the benefit of analysis, both the reduced-order small-signal model (RSM) and full-order small-signal model (FSM) have been proposed; however, because of the different modeling approaches, the modeling accuracy may differ a lot. To provide a guideline for selecting a suitable model, an accuracy assessment has been conducted in this paper, where different grid strength cases and equilibrium points are considered. More specific, the eigenvalue analysis is adopted for comparing the dominant dynamics of the RSM and FSM. Afterwards, the responses of the RSM and FSM are compared with the nonlinear model (NM) in the Digsilent/Powerfactory to show the modeling accuracy. It has been found that the RSM is mainly suitable for the weak and relatively strong grids, while the FSM shows better accuracy in the case of an extremely strong grid and around the equilibrium point that is close to VSG's rated output.

In this paper, control of Battery Storage Systems (BSS) in power distribution grids with residential consumers as well as prosumers equipped with rooftop photovoltaic (PV) solar panels and Electric Vehicles (EV) is addressed. Different features of these Distributed Energy Resources (DERs), such as intermittent behaviour and the difference between the maximum generation time and the maximum demand, have caused several issues for electricity distributors in delivering high quality power. Smart control and scheduling of ESS and EVs is a promising approach to protect the grid against extra power injection from prosumers during day times while the benefit of household owners from DERs are still achieved. In this context, the performance of model-based controllers such as model predictive controllers (MPC) is compared with model-free data driven controllers (DDC) considering different complex scenarios that may happen in a distribution grid. The control objective is to minimize the difference between the net power exchanged with the main grid from the estimated average net load of prosumers. Our study on the real consumption data of about 40 residential consumers/prosumers in Victoria, Australia, demonstrates the strength of data-driven control approaches to deal with the complex environment of power distribution grids in the presence of DERs.

Recently, the application of unmanned aerial vehicles (UAVs) to support the base stations in cellular telecommunication networks attracts attentions. UAV-assisted base stations can provide the extra users’ demand in extreme and/ or unpredictable situations such as Olympic Games to avoid extra cost of installing ground base stations. In this paper, a PV-battery power system is presented to supply UAV-assisted base stations in cellular telecommunication networks in urban areas to prevent environmental issues as well as to reduce the cost of fulfilling the energy demand. First, the energy consumption profile of the batteries of UAVs is estimated. Afterwards, the impact of the PV system sizing and battery capacity are studied based on sensitivity analysis.

Energy disaggregation is the process of disaggregating a household's total energy consumption into its appliance-level components. One of the limitations of energy disaggregation is its generalization capacity, which can be defined as the ability of the model to analyze new households. In this article, a new energy disaggregation approach based on adversarial autoencoder (AAE) is proposed to create a generative model and enhance the generalization capacity. The proposed method has a probabilistic structure to handle uncertainties in the unseen data. By transforming the latent space from a deterministic structure to a Gaussian prior distribution, AAEs decoder transforms into a generative model. The proposed approach is validated through experimental tests using two different datasets. The experimental results exhibit a 55% MAE performance increase compared to deterministic models and 7% compared to probabilistic models. In addition, considering the predictions made when the appliances areon, the AAE improves the performance by 16% for UKDALE and 36% for REDD dataset compared to the state-of-art models. Moreover, the online analysis performance of AAE is examined in detail, and the disadvantages of instant predictions and the possible solutions are extensively discussed.

Integrated around 2004, the concept of Energy Internet (EI) could provide new windows for the industrial power system society by incorporating the features of physical systems and cyber systems simultaneously. Technically, physical systems like electricity generation resources must be controlled and managed according to the instructions received from the cyber-systems. Being equipped by the smart grid and the internet idea, the EI can yield significant benefits such as higher reliability, improved power quality and mitigated the cost and losses. In the EI structure, the multiway flow of information and communication is monitored and controlled by the widespread and heterogeneous devices including the energy router, smart meters, etc. These technologies and devices bring many security concerns for the EI. Moreover, there are emerging concerns over the way to control, predict, manage, combine, and coordinate the energy resources in the EI. However, there exist many challenges that should be investigating and addressing before formal adoption of EI in industrial power and energy systems. To this end, this special issue invites the authors from both industry and academia to submit original research works on EI challenges in the power system.

Replacement of conventional generation units with a large number of renewable energy sources RESs causes an undesirable influence to the Egyptian power system EPS frequency stability, excessive supply due to full DGs generation due to the lack of system rotating inertia. The EPS consists of several conventional generation units (i.e., non-reheating, reheating, and hydraulic power plants) with inherent nonlinearities, and RESs (i.e., solar and wind energy). In order to solve this challenge, this paper provides a tertiary modified virtual inertia control loop-based energy storage system ESS as an active solution to improve the EPS stability during contingencies, and diminish the frequency deviations and regulate the power flow. In this method, the ability to imitate damping and inertia properties are presented based on the derivative technique. A comparative study between the conventional EPS with/without virtual (inertia + damping) is also presented. The constructed results using Matlab/Simulink software show the superior effectiveness and control effect of the proposed control method in terms of accurate tracking of the reference frequency and attenuating noise over the traditional one. Finally, it was verified that the auxiliary enhanced virtual inertia mechanism assisted the EPS by suppling further power inertia to robust the frequency against RESs and load demand penetrations.

As one of the vital load types in the military shipboard power system (SPS), the pulsed load normally features with the transient high power. Thus, in the case that the SPS has a small inertia constant, the operation of pulsed loads may heavily affects the voltage stability. Benefiting from various advantages of the DC microgrid in terms of the flexibility of power source connection, generator efficiency, and fuel consumption, the DC SPS is recognized as the next-generation solution. In order to assess the impact of pulsed loads in the future DC SPS, a comprehensive time-domain simulation study in Matlab/Simulink software has been conducted in this paper, where pulsed loads with two types of profiles, namely, single-pulse signal and multiple-pulses signal, have been included in the evaluation. Especially, the effect of pulse signal parameters, including the peak power, the pulse duration, the pulse interval time, and the pulse number has been simultaneously tested and analyzed. The DC bus voltage drop during the pulsed load operation has been taken as the index in the simulation. Key findings in the study have been summarized in detail, which leads to the final conclusions.

In order to emulate the frequency support characteristics of conventional synchronous generators (SGs), control algorithms based on the virtual synchronous generator (VSG) have been extensively applied to grid-tied converters. However, in the case that a large inertia is used in VSGs, active power oscillations can be introduced in the transients, due to the lack of enough damping effects. To avoid this phenomena, various solutions with additional damping terms have been proposed. This paper analyzes and compares six relevant fixed- parameter active-power-oscillation damping solutions in detail, where responses under set point and phase angle changes, the parameter sensitivity, and capabilities of limiting the rate of change of frequency (RoCoF) and attenuating power ripples are included. The results show the advantages and drawbacks of each solution, leading to the conclusion that extra damping terms may significantly degrade the inertial response of VSGs and have high dependency on the parameter estimation accuracy.

Wind turbine converters (WTCs) with grid forming (GFM) control can contribute to voltage and frequency support in the power system, by emulating synchronous machine (SM) dynamics, provided that there are sufficient buffers. Over the past few years, several control algorithms have been developed for the GFM operation of WTCs. This article investigates the state-of-the-art in the field of GFM control algorithms for WTCs, where the principle of each control algorithm is discussed in detail, and corresponding characteristics are summarized. Comparison results with respect to voltage build-up strategies, the synchronization of GFM WTCs, the interaction attenuation, the virtual inertia realization and the complexity of individual GFM algorithm are given in a table, which leads to the conclusion that mitigation of oscillations among WTCs, appropriate inertia emulation, and coordination with energy storage systems need to be further investigated in the future GFM WTCs.

Multi-functional grid-tied inverters (MFGTIs) have been investigated recently for improving the power quality (PQ) of microgrids (MGs) by exploiting the residual capacity (RC) of distributed generators. Several centralized and decentralized methods have been proposed to coordinate the MFGTIs. However, with the increasing number of the MFGTIs, it demands a method with improved reliability and flexibility, which are characteristics of distributed framework that has not been introduced into the PQ improvement (PQI) field before. In this paper, we propose a distributed consensus method to undertake the PQI task. The task is proportionally shared among the MFGTIs according to their instant RCs. Besides, most of the existing methods assume that the RCs of the MFGTIs are sufficient for tackling the PQ problem (PQP), which is not always true. In the case of insufficient RC, the active power output of each MFGTI is scaled down by the same factor determined by a proposed leader-follower protocol to make room for the task. In summary, the PQP is dealt with in both cases of sufficient and insufficient RC under the distributed control framework. Finally, simulations and hardware-in-the-loop experiments of an MG consisting of three 10kVA MFGTIs are presented to verify the effectiveness of the proposed methods.

The deployment of electric vehicle charging stations degrades the quality of power in the distribution grid. This article proposes an interval type-2 fuzzy logic controlled shunt converter coupled novel high-quality charging scheme for electric vehicles. This system includes three-phase bidirectional front-end ac-dc pulsewidth modulation (PWM) converter, backend dc-dc PWM converter and three-phase three-wire distribution static compensator. The bidirectional converters help to perform both grid to vehicle and vehicle to grid mode of operations. The combination of dc-link voltage with decoupled current control technique is exploited for ac-dc converter. A multistep constant current control technique is proposed for the dc-dc converter to charge and discharge the battery. A fuzzy logic controller based instantaneous reactive power theory control method is proposed for shunt converter. The performance of type-1, interval type-2, and real coded genetic algorithm optimized fuzzy logic controllers are evaluated by the shunt converter dc-link voltage and the total harmonic distortion of the source current. Lithium-ion batteries are utilized as an energy storage device for electric vehicles in the proposed system. The entire system is modeled and evaluated in the MATLAB/Simulink environment. An interval type-2 and real coded genetic algorithm optimized fuzzy logic controller affords the better performance during V2G and G2V operations, respectively.

The increase of green house gases (GHGs) emissions and depletion in fossil fuels have urged an extensive use of renewable energy resources (RESs) and energy storage systems (ESSs) in short route ferries and yachts. In current times, most of the smaller seaports are not equipped with the cold ironing facility, hence, when fossil fuel based SMGs are berthed at the port their auxiliary engines are kept on, which pollutes the seaport. In order to address this issue, RES and ESS equipped SMGs can be interconnected via DC bus to formulate a sea port microgrid. The Dc bus interfaced sea port microgrid can be used for providing mobile cold ironing facility to the nearby ships that are integrated with fossil fuels to minimize the emissions, vibrations, and noise pollution. Generally, power sharing among several mcicrogrids is achieved through a communication based control strategies that adds up complexity and the cost. This study, alternatively, proposes an adaptive droop based control algorithm, which is applied to DC SMGs for communication less power-sharing among hybrid energy resources (Battery, Photovoltaic and Fuel Cell). The proposed scheme further helps to charge the battery banks that are below the threshold limits by using the RES integrated in several SMGs.

This article addresses the security of distributed secondary control of inverter-based distributed energy resources (DERs) in microgrids. The proposed cybersecure scheme utilizes the weighted mean subsequence reduced algorithm at each DER to discard the corrupted information received from neighboring DERs. This algorithm requires the connectivity of underlying communication graph to be above a specific threshold. To cope with this requirement, a methodology is proposed such that each DER is able to virtually change the quality of communication links connected to that DER to enhance the connectivity of communication graph. Two islanded microgrid test systems are simulated to validate the effectiveness of proposed cybersecure secondary control.

Powering small islands with reliable, affordable and green electricity is a big challenge due to their dispersed geographical location with limited number of consumers and the heavy dependence on fossil fuels. This paper aims to address this challenge of reducing dependency on fossil fuel generators by providing an easy and feasible solution using available and accessible energy resources. The proposed method utilizes the bidirectional energy transfer mechanism available in electric boats (EBs) to support the consumers' power demand. It proposes a new real-time load-support (RTLS) system with a coordinated control using EBs, community generators, and battery energy storage systems. It analyzes the management of the intermittent source-dependent small-scale grid in real time, under various weather, load, and battery state-of-charge conditions. The RTLS system coordinates the customers' load demand with the available EBs, photovoltaics, and battery storage to provide efficient load support and to regulate the bus voltage and frequency. The efficacy of the proposed system is validated both computationally in a real network and in a laboratory setup. It is found that this novel system can substantially reduce the grid load demand and maintain the power quality under various load/source uncertainties and fault conditions. The system robustness is also evaluated considering undesirable conditions, such as severe three-phase faults and sudden EB disconnections. The performance of the proposed method is compared with that of the day-ahead load management approach to validate its effectiveness under various scenarios.

A VICINITY platform-based load scheduling method by considering the smart parking and household smart appliances for renewable energy resources integrated residential microgrids is proposed in this paper. The proposed method can shift the local loads and publish the vacant number of parking slot with a real-time electric vehicle charging price to VICINITY platform according to the renewable energy generation and the usage of the parking spaces to reduce energy cost and increase resident's revenue. The experimental platform-based real-life cross domain lab testing verifies the effectiveness of the proposed control approach.

Grid-connected inverters with LCL filter work stable using active damping methods. However, stability can be threatened easily by grid impedance variation. Particularly, delay in digitally controlled systems has a negative effect on the stable region of grid-connected inverters and shrinks this region. Therefore, by variation of grid impedance, it is very probable that resonance frequency located in the unstable region. To address this problem, a delay compensation method based on converter-side current feedback is proposed in this paper, which tackles the negative impact of the delay. The proposed method expands the stable region using passivity-based stability and guarantees the stable operation of inverter against grid impedance variation. Also, it does not need any extra sensors for active damping, which reduces the cost and increases the reliability. It is shown that the proposed method is effective in case of multi-paralleled inverters whiles normally coupling effect among inverters makes the stability condition worse. The effectiveness of the proposed method is verified through various case studies.

This paper proposes the utilization of a bidirectional DC-DC converter with sliding mode control in a wind distributed system employing the switched reluctance generator (SRG). The SRG wind system is connected to a three-phase AC utility grid by means of a voltage source converter. The presented proposal employes the DC-DC converter to regulate the optimum excitation voltage at the SRG side, while the VSC is responsible to maintain the DC bus voltage in a fixed value to allow the DC-AC conversion with the required voltage level and frequency. To face the problem of wide voltage variations, sliding mode control is applied to ensure the desired PWM duty cycle to the bidirectional DC-DC converter. SRG control is implemented through direct power control by current hysteresis, for low speeds, and by voltage single pulse control, for high speeds of operation. A careful examination about the behavior of the system considering the whole SRG operating speed range is carried out. Simulation results show that the proposal system is applicable and the applied sliding mode controller has rapid an robust behavior, as desired.

Prosumers concept has evolved with the technology advancements in renewable energy sources and intelligent responsive load devices. Digitalization paves the way for prosumers participation in energy market with the help of big data and distributed ledger technologies. Hence, power system is becoming more decentralized at distributed level, which consists of prosumers, consumers, and distributed energy resources-based microgrid systems. These microgrid participants require a transactive energy system for energy price signals-based smooth energy transactions among themselves. In this regard, this paper proposes a microgrid transactive energy system design and its functional layers. Blockchain-based transactive energy systems are also discussed. Finally, the peer-to-peer and community-based energy markets are presented.

The papers in this special section offer a collection of new and original papers that cover different aspects from architecture, scheme design, control strategy, optimization, application and deployment of energy Internet systems.

Medium-voltage dc (MVdc) distribution system is considered as the promising power architecture of future shipboard power system. Fault-tolerance ability is of great importance for power system on ships. In this paper, zonal dc-dc conversion system based on modular multilevel converter (MMC) and three-phase bridge rectifier are proposed with its hierarchical fault-tolerant scheme. The topology configurations of the front-end MMC with multiwinding medium frequency transformer under normal and postfault circumstances are presented. The reconfiguration scheme and fault-tolerant control strategy are also proposed to ride-through submodule (SM) level fault, phase level fault and bus level fault. Based on the hierarchical fault-tolerant scheme, redundant configuration of the MMC SM is further analyzed with the hierarchical reliability modeling. The effectiveness of the proposed control strategy is verified by the experimental results.

Hardware-in-the-loop (HIL) simulation is a technique that is being used increasingly in the development and test of complex systems. Real-world testing of an intricate system in a field-like power plant can be challenging, time-consuming, expensive, and hazardous. HIL emulators allow engineers to test devices thoroughly and efficiently in a virtual environment with high reliability and minimum risk of defect. In this paper, the complete electric power system (including generator, turbine-governor, excitation system, transmission lines, transformer, external grid and related loads) is implemented in a MATLAB/Simulink environment. Different virtual instrument pages are modeled in the graphical programming language of LabVIEW which enable fast and reliable measurement functions such as data acquisition, archiving, real-time graphical display and processing. The interaction between MATLAB and LabVIEW is accomplished by generating a Pharlap ETS Targets*.dll file which enables the two software to exchange real-time data. Also, a real 1518-kW excitation system is considered as a test case for the introduced HIL system. This equipment is connected to LabVIEW software through a National Instrument PXI technology. Different scenarios (electrical frequency/active power change, voltage step response, etc.) are simulated in the designed power system emulator (PSE). The validity of the implemented model for the excitation system is verified by finding good matching between MATLAB and HIL simulation results.

This paper proposes a new protection structure to locate any type of faults in a meshed micro grid based on only measuring the current and voltage of the Distributed Generator (DG) that communicates with its neighboring DGs. In the first step, following a wavelet transform, a set of features are selected and fed to a Multiclass Support Vector Machine (MSVM) to detect occurrence and type of fault. Then, faulted zone-the area between two DGs that fault occurs between them- is determined thanks to two facts. First, one of the DG in two sides of the faulted zone endures the lowest voltage. Second, regarding fundamental frequency of 50 Hz, if this DG injects a harmonic of 300 Hz, the DG with the lowest voltage at 300 Hz is the next closest DG. Finally, based on the optimum features and these two DGs, a SVM is used to locate the faulted line. Simulation results show the effectiveness of the proposed method in a meshed micro grid.

A hybrid modular multilevel converter (MMC), consisting of full-bridge sub-modules (FBSMs) and half-bridge sub-modules (HBSMs), is an efficient and DC-fault tolerant topology, which can be used in overhead-line HVDC transmission application. Additionally, it can work under over-modulation condition (i.e., arm submodule clusters may generate negative voltage during a fundamental cycle) to improve the utilization of submodules (SMs). Regarding the over-modulation issue, this paper proposes a reduced-switching-frequency modulation method, considering the different dynamics of FBSMs and HBSMs, for hybrid MMCs. Moreover, an improved wave-distributing approach which can reduce losses and make the operating time and losses of the two types of SMs more even than the conventional method is presented. Finally, the effectiveness of the proposed method is verified by an over-modulation hybrid MMC simulation model built based on PSCAD/EMTDC platform.

Distributed cooperative control methods attract more and more attention in microgrid secondary control because they are more reliable and flexible. However, the traditional methods rely on the periodic communication, which is neither economic nor efficient due to its large communication burden. In this paper, an event-triggered-approach-based distributed control strategy is used to deal with the secondary frequency and voltage control in the islanded microgrid. By using the outputs of estimators, which are reset to the actual values only at the event-triggered time, to replace the actual values in the feedback control laws, the proposed control strategies just require the communication between distributed secondary controllers at some particular instants while having frequency and voltage restoration function and accurate active power sharing. The stability and interevent interval are also analyzed in this paper. An islanded microgrid test system is built in PSCAD/EMTDC to validate the proposed control strategies. It shows that the proposed secondary control strategies based on the event-triggered approach can highly reduce the interagent communication.

Maritime applications have found in the integration of the electric power system a way to further improve efficiency and reduce the weight of new electric ships. This movement has led scientists to integrate smart management systems to optimize the overall behavior of the grid. In this context, power electronics play a key role in linking the different elements of the power architecture. Moreover, the transition toward a dc distribution, which has already been established in other applications, is being regarded as a promising alternative to ease the integration of renewable sources, batteries, and the ever increasing number of dc loads. In this paper, blackbox models are proposed as a tool to foresee the effect of these complex interactions, overcoming the lack of detailed information about the power converters. Large-signal strategies are proposed in order to consider nonlinearities in the static and dynamic behavior of the converters. An accurate model of the physical layer is essential to allow intelligent systems to take the most out of the system performance. This approach offers the opportunity to study the dynamic response of complex interconnected systems, tune the system-level controllers, design protections, or assess the compliance of the system dynamics with the standards. Experimental results are included in order to validate the proposed method.

The use of integrated shipboard power system (SPS) has greatly contributed to the next-generation vessels development. In this sense, how to realize the reasonable power distribution between hybrid zones in SPS is becoming one of the key problems to ensure system robustness and reliability. In this paper, a flexible power control strategy is proposed for the coordinated operation of the hybrid ac/dc zones in SPS. First, the interactive relationship of the ac/dc interface is analyzed, and the virtual inertia and capacitance are defined to reveal the interactive influence of the ac and the dc subgrids, which leads to a new V-f droop principle. Then, the flexible control strategy is designed based on the droop principle as well as the characteristics of the analogous virtual synchronous generator, and the key parameters' determination are discussed in detail, which can realize a proper assignment of cross-zone supportive power and improve the system dynamic response. In addition, the coordinated control loops are designed with the distributed energy storages and interlinking converters for the implementation of the strategy. Finally, the proposed strategy is validated by the simulation, which shows that the strategy can enhance the power quality and dynamics of the hybrid zones and contribute to the robustness of the whole SPS.

DC distribution is now becoming the major trend of future mobile power systems, such as more-electric aircrafts and ships. As dc distribution has different nature to the conventional ac system, a new design of well-structured control and management methods will be mandatory. In this paper, a shipboard power system with dc distribution and energy storage system (ESS) is picked as the study case. To meet the requirement of control and management of such a large-scale mobile power system, a hierarchical control design is proposed in this paper. In order to fully exploit the benefit of the ESS, as well as to overcome the limitation in controllability, a novel inverse-droop control method is proposed, in which the power sharing is according to the source characteristic, instead of their power rating. A frequency-division method is also proposed as an extension to the inverse-droop method for enabling a hybrid ESS and its autonomous operation. On the basis of the proposed methods, the control methods for management and voltage restoration levels are also proposed to establish a comprehensive control solution. Real-time simulations are carried out to validate the performance of the proposed control design under different operating conditions. When compared to more conventional droop-based approaches, the new proposal shows enhancement in efficiency.

This paper proposes a distributed hierarchical cooperative control strategy for a cluster of islanded microgrids (MGs) with intermittent communication, which can regulate the frequency/voltage of all distributed generators (DGs) within each MG as well as ensure the active/reactive power sharing among MGs. A droop-based distributed secondary control scheme and a distributed tertiary control scheme are presented based on the iterative learning mechanics, by which the control inputs are merely updated at the end of each round of iteration, and thus, each DG only needs to share information with its neighbors intermittently in a low-bandwidth communication manner. A two-layer sparse communication network is modeled by pinning one or some DGs (pinned DGs) from the lower network of each MG to constitute an upper network. Under this control framework, the tertiary level generates the frequency/voltage references based on the active/reactive power mismatch among MGs while the pinned DGs propagate these references to their neighbors in the secondary level, and the frequency/voltage nominal set points for each DG in the primary level can be finally adjusted based on the frequency/voltage errors. Stability analysis of the two-layer control system is given, and sufficient conditions on the upper bound of the sampling period ratio of the tertiary layer to the secondary layer are also derived. The proposed controllers are distributed, and thus, allow different numbers of heterogeneous DGs in each MG. The effectiveness of the proposed control methodology is verified by the simulation of an ac MG cluster in Simulink/SimPower Systems.

The triangle carrier based pulse width modulation (TCB-PWM) can be functionally equivalent to space vector base PWM (SVB-PWM). For multi-level inverter, it is very difficult to realize the SVB-PWM because its vector space is very complex. In this paper, a unified TCB-PWM strategy for three-phase N-level diode clamped inverter, including continuous PWM (CPWM) and discontinuous PWM (DPWM), is proposed. With the proposed strategy, the final modulation signals can be easily obtained by twice common mode voltage (CMV) injections. The PWM driver signals are generated by comparing the final modulation signals and phase deposition triangle carriers. Especially, the procedures to realize different types of PWM method are demonstrated in this paper. The proposed method can be directly implemented in digital processers.

Fault current limiters (FCLs) are one class of solutions to cope with the upcoming challenges in microgrid protection. Considering high penetration of distributed generations (DGs) in microgrids, the necessity of designing cheap and effective FCL is getting higher. This paper attempts to fill this gap by proposing an embedded FCL operating based on modifying the secondary control of DGs. As this method is designed for four-wire system, besides cost-effectiveness, it has independency and flexibility to only limit the fault current of DG. In order to validate the proposed method, different types of faults are examined through an extensive simulation study.

The paper proposes a hybrid droop control strategy to enhance the stability and increase maximum constant power loads (CPLs) capability of DC microgrids in a realistic scenario. By capturing the detailed model of inner control loops and hybrid droop control and general dc MG topology, a thorough comparative study is conducted between traditional droop control and hybrid droop control. Enhanced control bandwidth and system stability margin are shown to illustrate the advantages of the proposal. CPL penetration is one of the critical consideration of this paper. The hybrid droop control can increase the maximum CPL power capability of the system. Simulation studies are conducted to verify the analysis results and the effectiveness of the method.

This paper proposes a robust optimization framework for energy hub management. It is well known that the operation of energy systems can be negatively affected by uncertain parameters, such as stochastic load demand or generation. In this regard, it is of high significance to propose efficient tools in order to deal with uncertainties and to provide reliable operating conditions. On a broader scale, an energy hub includes diverse energy sources for supplying both electrical load and heating/cooling demands with stochastic behaviors. Therefore, this paper utilizes the Information Gap Decision Theory (IGDT) to tackle this uncertainty as an efficient robust optimization tool with low complexity to ensure the optimal operation of the system according to the priorities of the decision maker entity. The proposed optimization framework is also implemented on a benchmark energy hub which includes different energy sources and evaluated under different working conditions.

DC distribution technology has become the new choice and the trending technology of shipboard power systems for its advancement over its AC counterpart. In DC shipboard power systems, the bus voltage stability is a critical issue. The presence of tightly controlled high-power constant power load can induce system-level voltage instability. To mitigate such a problem, a novel compensation method based on model-derived specially designed negative virtual inductance loop is proposed in this paper. The mechanism of the proposed method is presented in detail. In addition to that, the proposed compensation method is compliable with both voltage-controlled and droop-controlled converters. Simulations are carried out to validate the proposed method, and the results show enhanced stability margin and capability when feeding constant power loads.

Recently, DC distribution has been more and more considered in shipbuilding industry as an emerging solution due to its potential to enhance the system performance in terms of fuel economy, reliability, volume and weight. Moreover, there is a growing trend to integrate alternative power sources (APSs) and energy storage systems (ESSs) into next-generation ships, and thus reducing cost and emission. In this context, the future shipboard power systems (SPSs) are expected to be compatible with various generation methods and complex onboard power consumers, which can be naturally identified as islanding microgrids (MGs). In this paper, specialized hierarchical control strategy is proposed to coordinate the system operation and meet the requirement of shipboard applications. Several advantageous functions are achieved by proposed control strategy. A study case of DC SPS is modeled and simulations are carried out to verify the proposed control strategy.

In this paper a new method is presented to achieve economic exploitation and proper usage of network capacity by exerting controlling actions over flexible loads and energy storage (ES) equipment. Multi-objective planning for demand response programs (DRP) and battery management policies is carried out by considering energy not supplied (ENS). In order to achieve an optimal scheduling, charge/discharge control for batteries, demand response programs and dispatch of controllable distributed generations (DGs) are also considered. Then, the balanced cost and benefits of participants are evaluated. As a whole, the main objective of this paper is to manage the load and energy storage options in a smart grid to reduce ENS, to minimize overall operation cost and to maximize DG operators' (DGOs) profit. These goals are obtained by considering ENS cost in a multi-objective optimization problem. Distribution company (DisCo) modifies energy cost as a signal for DGO in order to coordinate with each other. So, behavior of DGO is based on modified energy price applied by upstream system considering ENS price.

In this paper, an improved grid voltage modulated control (GVM) with power compensation is proposed for grid-connected voltage inverters when the grid voltage is unbalanced. The objective of the proposed control is to remove the power ripple and to improve current quality. Three power compensation objectives are selected to eliminate the negative sequence components of currents. The modified GVM method is designed to obtain two separate second-order systems for not only the fast convergence rate of the instantaneous active and reactive powers but also the robust performance. In addition, this method converts the system into a linear invariant system though designing a new voltage input. Simulation results are presented to verify the correctness and validity of the proposed control strategy and power compensation method.

Voltage and frequency transient variations are the most common power quality issues in a ship microgrid system. In this paper, the impacts of the voltage dips induced by the sudden-load of ballast pump are analyzed in detail for the ship power systems. Several relevant ship power quality standards and potential solutions are introduced and discussed properly. The experimental tests from a real ship are presented to show the impact of moderate voltage dips on the selected working generator and bow thruster.

In this paper, first, the existing frequency and voltage amplitude restoration control strategies are reviewed. Moreover, the proposed second order washout filter control strategy is proposed to enhance the dynamic response under load disturbance. The physical parameter of the proposed method is derived, and system stability for the system parameter is discussed. Finally, extensive simulation results are provided to verify the effectiveness of the proposed method for UPS system.

Microgrids rely on energy management levels to optimally schedule their components. Conventionally, the research in this field has been focused on the optimal formulation of the generation or the demand side management separately without considering real case scenarios and validated only by simulation. This paper presents the power scheduling of a real site microgrid under a price-based demand response program defined in Shanghai, China managing generation and demand simultaneously. The proposed optimization problem aims to minimize operating cost by managing renewable energy sources as well as shiftable loads considering the preferred time of use. The proposal has been tested experimentally in a laboratory prototype.

Shunt active power filters (S-APF) are highly popular ways for harmonic compensation due to the high performance and simplicity of installation. S-APF is commonly controlled in current control mode with load harmonic current detection, which is not quite suitable for the distributed power generation system (DPGS) where the nonlinear loads are highly dispersed. Local harmonic voltage detection based Resistive-APF (R-APF) seems more suitable to be applied in the DPGS, however, R-APF suffers from poor compensation performance and difficulty of parameter tuning. In this paper, a direct harmonic voltage control strategy for the S-APF is proposed with local point of common coupling (PCC) voltage detection only. The control strategy design procedure is given in detail. Simulation is conducted in Matlab/Simulink to compare the performance between the R-APF and the proposed method. The results validate superiority of the proposed method.

Strict regulation on emissions of air pollutants imposed by the maritime authorities has led to the introduction of hybrid microgrids to the shipboard power systems (SPSs) which acts toward energy efficient ships with less pollution. A hybrid energy system can include different means of generation such as renewables (e.g., solar PV, wind power) and conventionals (e.g., diesel engines) as well as energy storage systems (ESSs) such as batteries, fuel cells and flywheels. To optimally manage different energy sources in a shipboard microgrid while meeting different technical/environmental constraints, it is necessary to set up an energy management system. This paper provides an overview of hybrid shipboard microgrids and discusses different methods of power and energy management in such systems which are essential for control, monitoring and optimizing the overall system performance in various mission profiles.

The external droop control loop of I-V droop control is designed as a voltage loop with embedded virtual impedance, so the internal current loop plays a major role in the system bandwidth. Thus, in this paper, the influence of internal current loop on transient response performance of I-V droop controlled paralleled dc-dc converters is analyzed, which is guided and significant for its industry application. The model which is used for dynamic analysis is built, and the root locus method is used based on the model to analyze the dynamic response of the system by shifting different control parameters. Analysis results show that any converter's inner current loop can influence all converters' dynamic responses in the system and the one with larger Virtual Resistance (VR) has greater effect. Increasing the proportional terms can decrease the fluctuations of current and voltage, and key parts of errors can be reduced more rapidly during dynamical process, but adverse effect on completely eliminating errors can be caused; increasing integral terms can enlarge current fluctuations during dynamical process, but the errors can be eliminated more rapidly. The experiments are performed to verify the analysis.

An average power sharing control strategy for parallel operation of voltage source inverter (VSI) based modular Uninterruptible Power Systems (UPSs) is proposed in this paper. The presented method is based on a modified droop control. The proposed method conquers the drawback of conventional droop plus virtual impedance control, and at the same time some challenges in the real applications have been considered. Such as the mismatch of output impedance of the parallel modules, the different calibration accuracy of the sample circuit, and the offset of the voltage reference from the control unit. Simulation has been presented in order to verify the effectiveness of the proposed control methodology under these three different conditions. The simulation results demonstrate that a better power sharing performance is obtained and successfully prevent of negative power which can protect the DC bus.

In this paper, the hierarchical control strategy of a photovoltaic/battery based dc microgrid is presented for electric vehicle (EV) wireless charging. Considering irradiance variations, battery charging/discharging requirements, wireless power transmission characteristics, and onboard battery charging power change and other factors, the possible operation states are obtained. A hierarchical control strategy is established, which includes central and local controllers. The central controller is responsible for the selection and transfer of operation states and the management of the local controllers. Local controllers implement these functions, which include PV maximum power point tracking (MPPT) algorithm, battery charging/discharging control, voltage control of DC bus for high-frequency inverter, and onboard battery charging control. By optimizing and matching parameters of transmitting coils, receiving coils and compensation capacitors, the wireless power transmission system is designed to be resonant when it is operating at the rated power, with the aim to achieve the optimum transmission system efficiency. Simulation and experimental results of the hierarchical control of the microgrid with electric vehicle wireless charging are established, showing the effectiveness of the proposed approach.

This paper develops a supervisory control and data acquisition (SCADA) system to monitor an islanded DC microgrid including wind turbine, photovoltaics, and battery units. The SCADA system is based on KingView 6.55, and establishes data communication between the host and the slave computers through intelligent modules and different communication techniques. The developed SCADA system can monitor real-time parameters such as voltages, currents, or powers, and can store the important parameters into the database. Users can get historical data realistically and effectively through SQL access. When some values in the system exceed or fall below the predetermine limits, the SCADA system can pop up the alarm screen, give an alert and send a text message or call an specified person via an SMS module. The host not only can monitor the operation status of the system, but also give orders to control the action of the slaves. This way, it implements the combination of required monitoring and control functions. The SCADA system includes an energy management system (EMS), monitoring of state of charge (SOC) of the battery management system (BMS), and black start operation. The system is in operation in a DC microgrid system in Tianjin, China.

A multiple time-scale optimization scheduling including day ahead and short time for an islanded microgrid is presented. In this paper, the microgrid under study includes photovoltaics (PV), wind turbine (WT), diesel generator (DG), batteries, and shiftable loads. The study considers the maximum efficiency operation area for the diesel engine and the cost of the battery charge/discharge cycle losses. The day-ahead generation scheduling takes into account the minimum operational cost and the maximum load satisfaction as the objective function. Short-term optimal dispatch is based on minimizing the adjustment of the day-ahead scheduling and giving priority to the use of renewable energy. According to the forecast of the critical and noncritical load, the wind speed, and the solar irradiation, mixed integer linear programming (MILP) optimization method is used to solve the multi-objective optimization functions. Simulation results shown that the proposed multiple time-scale optimization scheduling approach minimizes the battery usage and maximize the use of renewable energies.

With the increase of wind generation penetration, power fluctuations and weak inertia may attempt to the power system frequency stability. In this paper, in order to solve this problem, a hierarchical control strategy is proposed for permanent magnet synchronous generator (PMSG) based wind turbine (WT) and battery unit (BU). A central controller forecasts wind speed and determines system operation states to be sent to the local controllers. These local controllers include MPPT, virtual inertia, and pitch control for the WT; and power control loops for the BU. The proposed approach achieve at the same time both output power smoothing and frequency participation. Simulation results confirm the effectiveness of the proposed control strategy in different scenarios.

Because of the low power losses and moderate cost, the magnetic powder cores are popular in producing the filtering inductors for the high efficient and cost-effective power converters. However, the soft magnetic property of the powder cores leads to the wide variation of inductance along with the changing of the inductor current in one cycle of the grid, which challenges the system stability and power quality. In this paper, the current-dependent small-signal model of a three-phase LCL-filtered inverter is derived for designing the corresponding controller. Based on the developed small-signal model, a capacitor current feedback based active damping loop and a fractional order repetitive control based compound current control loop are designed to stabilize the system and enhance the control accuracy in steady-state, respectively. The controller design procedure is given in detail. Finally, all-digital simulation has been conducted on a 3.7 kVA inverter system to verify the theoretical expectations.

This paper proposes multiagent system-based event-triggered hybrid controls for guaranteeing energy supply of a hybrid energy generation system with high security. First, a multiagent system is constituted by an upper level central coordinated control agent combined with several lower level unit agents. Each lower level unit agent is responsible for dealing with internal switching control and distributed dynamic regulation for its unit system. The upper level agent implements coordinated switching control to guarantee the power supply of overall system with high security. The internal switching control, distributed dynamic regulation, and coordinated switching control are designed fully dependent on the hybrid behaviors of all distributed energy resources and the logical relationships between them, and interact with each other by means of the multiagent system to form hierarchical hybrid controls. Finally, the validity of the proposed hybrid controls is demonstrated by means of simulation results in different scenarios.

In this Special Section on Systems of Power Converters: Design, Modeling, Control, and Implementation, we have 11 high-quality papers approved for publication that cover the following three topics. 1) Converter Design and Operation. 2) Subsystem-Level Applications. 3) System-Level Applications. These topics and the corresponding papers are summarized.

This paper presents a robust distributed secondary control (DSC) scheme for inverter-based microgrids (MGs) in a distribution sparse network with uncertain communication links. By using the iterative learning mechanics, two discrete-time DSC controllers are designed, which enable all the distributed energy resources (DERs) in an MG to achieve the voltage/frequency restoration and active power sharing accuracy, respectively. In special, the secondary control inputs are merely updated at the end of each round of iteration, and thus, each DER only needs to share information with its neighbors intermittently in a low-bandwidth communication manner. This way, the communication costs are greatly reduced, and some sufficient conditions on the system stability and robustness to the uncertainties are also derived by using the tools of Lyapunov stability theory, algebraic graph theory, and matrix inequality theory. The proposed controllers are implemented on local DERs, and thus, no central controller is required. Moreover, the desired control objective can also be guaranteed even if all DERs are subject to internal uncertainties and external noises including initial voltage and/or frequency resetting errors and measurement disturbances, which then improves the system reliability and robustness. The effectiveness of the proposed DSC scheme is verified by the simulation of an islanded MG in MATLAB/SimPowerSystems.

In order to suppress the zero sequence circulating currents (ZSCCs) between parallel operating three level voltage source inverters with common AC and DC buses, a common mode voltage reduction PWM (CMVR-PWM) technique and neural point potentials (NPPs) control based method is proposed in this paper. An equivalent model of ZSCC is developed, and two excitation sources of ZSCC, differences of common mode voltages (CMVs) and NPPs between paralleled inverters, are analyzed. A CMVR-PWM method is investigated to reduce the CMV, and a simple electric circuit is adopted to control the NPPs. With this two strategies, ZSCCs between parallel inverters can be eliminated effectively. This strategy has the advantage of without carrier synchronization and can be utilized to parallel operating inverters with different types of filter. Simulation result validate the proposed ZSCC elimination schemes.

Next generation power management at all scales is highly relying on the efficient scheduling and operation of different energy sources to maximize efficiency and utility. The ability to schedule and modulate the energy storage options within energy systems can also lead to more efficient use of the generating units. This optimal planning and operation management strategy becomes increasingly important for off-grid systems that operate independently of the main utility, such as microgrids or power systems on marine vessels. This work extends the principles of optimal planning and economic dispatch problems to shipboard systems where some means of generation and storage are also schedulable. First, the question of whether or how much energy storage to include into the system is addressed. Both the storage power rating in MW and the capacity in MWh are optimized. Then, optimal operating strategy for the proposed plan is derived based on the solution from a mixed-integer nonlinear programming (MINLP) problem. Simulation results showed that including well-sized energy storage options together with optimal operation management of generating units can improve the economic operation of the test system while meeting the system's constraints.

During the past few years, microgrids (MGs) have been becoming more attractive as effective means to integrate different distributed energy resources (DERs). To coordinate active and reactive power sharing among DERs, conventional droop control method is widely used as a decentralized control scheme. However, sharing powers among the sources based on the units' rated capacities is not an optimal solution in terms of economy and efficiency. In this paper, a new adaptive droop-based control strategy is proposed for AC MGs to optimally share MG load between corresponding units. The mentioned control strategy is developed in two levels. The upper control level is a mixed-objective optimization algorithm that provides optimal set-points for power generations considering system's constraints and goals, while the lower control level is responsible for tracking the reference signals coming from the upper level. To demonstrate the effectiveness of the proposed control strategy under different operating scenarios, simulation results in a benchmark MG are also presented.

In this paper we propose a new decentralized control strategy applied to a DC Microgrid in order to manage the power delivery of storage devices into a common DC-link, avoiding high-bandwidth communication (HBC) between the storage devices (SD) and alternative sources. Batteries and Ultracapacitors (UC) are used as SD and the common DC-link is fed by alternative sources such as photovoltaic panels, wind turbines and fuel cells as well. The batteries are used to supply/absorb extra power in steady-state regime while the UC absorbs the power transients caused by variations on the power production or load connections. The proposed strategy uses as input for the batteries control only the DC-link voltage and state of charge (SOC), while for the UC only the DC-link voltage and UC terminal voltage are used to achieve the power sharing among the storage devices, equalization of the batteries and voltage restoration of the UC without HBC. The DC-link voltage is not restored in order to work as the sharing signal between storage devices. Additionally, the DC Microgrid is connected to the AC grid in order to deliver the extra power to the distributed system; however, the voltage variation on the DC-link does not affect the power quality of the produced energy. Simulated and experimental results are presented to demonstrate the feasibility of the proposed approach.

The performance of current and voltage regulators during transients and steady-state is of primary concern for power converters intended for stand-alone applications. Dynamics performance and command tracking capability are enhanced by actively decoupling the controlled states variables. To further widen the current loop bandwidth while still preserving a well-damped system a lead compensator structure on the forward loop is proposed. A 3 kHz bandwidth with 0.707 damping factor is achieved for the inner current controller. Accordingly, also the voltage regulator bandwidth can be widen, thus requiring even more a proper anti-wind up scheme to avoid saturation of the integral term during demanding transients. Lab-tests are performed in accordance with standards imposed to uninterruptible power supplies, verifying the theoretical analysis.

The paper presents a detailed analysis of second order harmonic ripple in a DC microgrid. A boost converter feeding PWM inverter load is considered and equivalent circuit is proposed. The effect of the size of input capacitor, output capacitor and inductor of boost converter, on this ripple has been investigated. The proposed model has been validated through experimentation and simulation.

Based on the hierarchical control structure in islanded Micro-Grid (MG) systems, the coupling/tradeoff effects in different levels are analyzed in details. In the primary level, analyses of the coupling effects among droop control gains, line impedance differences, output reactive power and voltage magnitudes are provided specifically. In the secondary level, the tradeoffs between accurate reactive power sharing and voltage magnitudes regulation are further detailed. The analysis results can provide a guideline for the design of MG structure and its control parameters. In addition, novel containment-based controller is proposed to control the voltage into a reasonable range which is the first time to apply this algorithm in MG. Furthermore, dynamic-consensus-based controller is used to guarantee accurate reactive power sharing. The combination of controllers offers a coordinated distributed operation and enhanced system performance. Finally, experimental results are shown to validate the effectiveness of the proposed method.

Random fluctuation of PV power is becoming a more and more serious problem affecting the power quality and stability of grid as the PV penetration keeps increasing recent years. Aiming at this problem, this paper proposed a control strategy of energy storage system based on Model Predictive Control (MPC). By the continuous optimizing of MPC, we can obtain the system parameters accurately, and then calculate the energy storage power. At the same time, this control took state of charge (SOC) and other parameters into account to ensure the health and stability of the energy storage units. Finally, simulation results proved the proposed control strategy had good performance and robustness.

Droop control framework with an adjustable virtual impedance loop is proposed in this paper, which is based on the cloud model theory. The proposed virtual impedance loop includes two terms: a negative virtual resistor and an adjustable virtual inductance. The negative virtual resistor term not only can avoid the active/reactive power coupling, but also it may reduce the output voltage drop of the PCC voltage. The proposed adjustable complex virtual impedance loop is putted into the conventional P/Q droop control to overcome the difficulty of getting the line impedance, which may change sometimes. The cloud model theory is applied to get online the changing line impedance value, which relies on the relevance of the reactive power responding the changing line impedance. The verification of the proposed control strategy is done according to the simulation in a low voltage microgrid in Matlab.

Microgrid is regarded as a new form to integrate the increasing penetration of distributed generation units (DGs) in the extensive distribution systems. This paper proposes an adaptive overcurrent protection strategy for a microgrid network. The protection coordination of the overcurrent relays is treated as a linear programming problem for the different operation states. In the control center, an artificial neural network (ANN) model is trained with real-time measurements to identify the states whether there is a fault on the line segment. Fault location is estimated further with the same measurements in another neural network model. Reconfigurations can be performed to modify the settings of the on-field relays to enhance the reliable operation for the different operational situations. The test results show that the adaptive overcurrent protection scheme with the assistance of estimation model can modify the protective settings for the new operation state accurately and intelligently.

Grid background harmonics may be amplified, propagate through a long distribution feeder and even lead to power system instability. In this paper, harmonic propagation issue is investigated and mitigation of the harmonics is analyzed by using transmission line theory which has already been applied in power systems. It is demonstrated that a specific harmonic will not be amplified if the feeder's length is less than one quarter of the harmonic wavelength meanwhile the terminal impedance is less than characteristic impedance. Besides, three scenarios will be considered in accordance with the relationship between the feeder's length and harmonic wavelength. Harmonic suppression control strategies will be respectively designed considering 5thand 7thharmonics coexisting in the distribution line. Finally, a simulation study has been performed to verify the theoretical analysis and demonstrate the effectiveness of the proposed strategy.

This paper presents a linear active disturbance rejection control (LADRC) for grid-connected converter with LCL filter. The high rejection performance for external disturbance, internal decoupling, parameter variation is achieved by adopting extended state observer(ESO) and designing controller with direct pole placement. Robustness of parameter uncertainty and sensitivity of input disturbance are analyzed in frequency domain to demonstrate the superior characteristic in disturbance rejection. The theoretical analysis is verified in Matlab/Simulink. The simulation results show the excellent capability of rejection in grid voltage disturbance.

With penetration of plug-in electrical vehicles (PEV), fast charging stations (FCS) are expected to constitute be a considerable portion of total energy consumptions. This paper proposes a hybrid power coordinating control strategy implemented in a fast charging station equipped with flywheel energy storage system, in order to provide a comfortable charging circumstance for PEV as well as some ancillary services (active power and reactive power support) for grid by four-quadrate bidirectional operation. The distributed bus signaling (DBS) method is employed for coordinating the control between grid converter and flywheel converter to avoid the highly dependent on communication. Finally, the experimental results based on dSPACE1006 are presented to show the effectiveness of the proposed control structure.

In this paper, a novel control method was proposed for current source inverters under the grid-connected working mode. The control scheme is based on a modified droop control method, with an additional current reference signal that will be generated instead of the voltage reference. Hence, there is only a current control loop with droop control in the whole control scheme without voltage control loop. So it is very suitable for grid-connected current source inverter which will simplify the design of the control scheme and combine the advantage of droop control. The parallel configuration is widely used to acquire high power demand, but the circulating current problem is a key issue that should be considered. In this paper, a simulation based on parallel current source inverters using the proposed control scheme is provided. Simulation results showed that a good circulating current suppression capability of the proposed control scheme is obtained with a proper controller design.

The possibility of increasing penetration level of grid-interactive microgrids (MGs) has gained a great interest over the past decade. Thus, it is critical to investigate the performance of the MGs under voltage sags, since it may induce instability to the power grid. Negative sequence droop control based voltage support strategy has been proposed to aid MGs riding through three phase asymmetrical voltage sags. However, since the line impedance from each converter to the point of common coupling (PCC) is not identical, both positive sequence and negative sequence output current of the converters cannot be equally shared if no extra current balancing loop is added. Accordingly, a dynamic consensus algorithm (DCA) based negative/positive sequence current sharing scheme is proposed in this paper. Finally, a lab-scale AC microgrid was designed and tested in the lab to validate the feasibility of the proposed control method.

Synchronization techniques can be broadly classified into two major categories-closed-loop and open-loop methods. The open-loop synchronization (OLS) techniques, contrary to the closed-loop ones, are unconditionally stable and benefit from a fast dynamic response. Their performance, however, tends to worsen in the presence of frequency drifts. To deal with this problem, two approaches are often recommended in the literature-adapting OLS techniques to the grid frequency variations by feeding back the frequency estimated by them or using the frequency estimated by a secondary frequency detector in a parallel manner. In the presence of the frequency feedback loop, nevertheless, the OLS technique may not be truly open-loop, which makes a deep stability analysis necessary. Using the secondary frequency detector, on the other hand, increases the computational effort and implementation complexity. Another drawback of most of the available OLS techniques is that their implementation involves the computation of sine and cosine functions, which is undesirable from the computational standpoint, particularly when the implementation with low-cost digital signal processors is intended. The aim of this paper is to develop a true OLS (and therefore, unconditionally stable) technique without any need for the calculation of sine and cosine functions. The effectiveness of the proposed synchronization technique is confirmed through the simulation and experimental results.

In this paper, an intelligent energy management system based on energy saving and user's comfort is introduced and applied to a residential smart home as a case study. The proposed multi-objective mixed-integer nonlinear programming (MINLP)-based architecture takes the advantages of several key modeling aspects such as load shifting capability and domestic energy micro-generation characteristics. To demonstrate the efficiency and robustness of the proposed model, several computer simulations are carried out under different operating scenarios with real data and different system constraints. Moreover, the superior performance of the proposed energy management system is shown in comparison with the conventional models. The numerical results also indicate that through wise management of demand and generation sides, there is a possibility to reduce domestic energy use and improve the user's satisfaction degree.

This paper presents a new family of fuzzy phase locked loop (FPLL)-fuzzy double decouple synchronous reference frame phase locked loop (FDDSRF-PLL)-that incorporated DDSRF-PLL into FPLL. FDDSRF-PLL enjoys both advantageous of DDSRF-PLL and fuzzy system to detect the fundamental-frequency positive-sequence component of the utility voltage under unbalanced and distorted conditions as well as fast and smooth tracking of phase jump. Furthermore, to achieve the best possible performance, a fuzzy adaptive particle swarm optimization (FAPSO) algorithm is considered to optimize parameters of the fuzzy system and DDSRF-PLL's filters. The results show that, in comparison with DDSRF-PLL and FPLL, FDDSRF-PLL has better performance in tracking of the positive-sequence voltages of the three-phase system under unbalanced condition, phase and jump simultaneously.

In future, distributed energy resources (RESs) will be utilized at consumption points. As a consequence, power flow and fault current would be bidirectional and topology-dependent; and hence the conventional protection strategies would be inefficient. This paper categorizes the main challenges in AC and DC microgrids, and then investigates the existing and promising solutions for the corresponding challenges. To the authors' knowledge, three parts of smart grids are required to be developed to facilitate implementation of protection scheme in microgrids. The main requirements and open issues of these three parts are discussed at the end of this paper.

Voltage and current control loops play an important role in the performance of microgrids employing power electronics voltage source inverters. Correct design of feedback loops is essential for the proper operation of these systems. This paper analyzes the influence of state feedback cross-coupling in the design of resonant regulators for inner current loops in power converters operating in standalone microgrids. It is also demonstrated that the effect of state feedback cross-coupling degrades the performance of the control loops by increasing the steady-state error. Different resonant regulators structures are analyzed and compared, performing experimental tests to validate the results of the theoretical analysis.

This paper presents a centralized strategy for equalizing the state of charge of distributed energy storage systems in an islanded ac microgrid. The strategy is based on a simple algorithm denoted as equalization algorithm, which modifies the charge or discharge ratio on the time, for distributed energy storage systems, within a determined period of time in order to equalize the state of charge. The proposed approach has been tested in a MATLAB/Simulink model of the microgrid where the performance of the proposed strategy was verified.

In this paper, an optimal power flow problem is formulated in order to minimize the total operation cost by considering real-time pricing in DC microgrids. Each generation resource in the system, including the utility grid, is modeled in terms of operation cost, which combines the cost-efficiency of the system with the demand response requirements of the utility. By considering the primary (local) control of the grid-forming converters of a microgrid, optimal parameters can be directly applied to the control of this level, thus achieving higher control accuracy and faster response. The optimization problem is solved in a heuristic way by using genetic algorithms. In order to test the proposed algorithm, a six-bus droop-controlled DC microgrid is used as a case-study. The obtained simulation results show that under variable renewable generation, load, and electricity prices, the proposed method can successfully dispatch the resources in the microgrid with lower total operation costs.

In this paper, a multiagent based distributed control is proposed for DC microgrid to minimize the operation cost. The power of each distributed generator (DG) is dispatched in a distributed manner in a multiagent system by means of voltage scheduling. Every DG unit is taken as an agent, and they share the load corresponding to the operation cost of all the units in the system with only communication with direct neighbors through incremental cost consensus. The power regulation according to the power reference generated by consensus is implemented through voltage scheduling in local primary controllers. Simulation verification shows that total operation cost of the DC microgrid is successfully reduced though the proposed method.

Due to the increasing penetration of distributed generation resources, more and more microgrids can be found in distribution systems. This paper proposes a phasor measurement unit based distance protection strategy for microgrids in distribution system. At the same time, transfer tripping scheme is adopted to accelerate the tripping speed of the relays on the weak lines. The protection methodology is tested on a mid-voltage microgrid network in Aalborg, Denmark. The results show that the adaptive distance protection methodology has good selectivity and sensitivity. What is more, this system also has a good capability on monitoring and control of the network.

Owing to the increasing penetration of distributed generation, there are some challenges for the conventional protection in distribution system. Bidirectional power flow and variable fault current because of the various operation modes may lead to the selectivity and sensitivity of the overcurrent protection decreased. This paper adopts distance protection for one mid-voltage level microgrid in Aalborg, Denmark. Different operation modes of the network are analyzed and tested in the paper. The simulation results show that the variations of the fault currents seen by the forward relays are much larger than the backward relays. Meanwhile, the fault currents change little with the randomness of renewable energy except the intermittence. Finally, it shows that the designed distance protection has satisfactory performance to clear the various faults.

Smart meters are the cornerstone in the new conception of the electrical network or Smart Grid (SG), providing detailed information about users' energy consumption and allowing the suppliers to remotely collect data for billing. Nevertheless, their features are not only useful for the energy suppliers, but they can also play a big role in the control of the Microgrid since the recorded power and energy profiles can be integrated in energy management systems (EMS). In addition, basic power quality (PQ) disturbances can be detected and reported by some advanced metering systems. Thus, this paper will expose an example of Smart Meters integration in a Microgrid scenario, which is the Intelligent Microgrid Lab of Aalborg Univeristy (AAU). To do this, first the installation available in the Microgrid Lab will be introduced. Then, three different test scenarios and their respective results will be presented, regarding the capabilities of this system and the advantages of integrating the Smart Meters information in the Microgrid control.

With the increasing penetration of renewable energy, microgrids (MGs) have gained a great attention over the past decade. However, a sudden cut out of the MGs due to grid fault may lead to adverse effects to the grid. As a consequence, reactive power injection provided by MGs is preferred since it can make the MG a contributor in smooth ride through the faults. In this paper, a reactive power support strategy using droop controlled converters is proposed to aid MG riding through three phase symmetrical voltage sags. In such a case, the MGs should inject reactive power to the grid to boost the voltage in all phases at AC common bus. However, since the line admittances from each converter to point of common coupling (PCC) are not identical, the injected reactive power may not be equally shared. In order to achieve low voltage ride through (LVRT) capability along with a good power sharing accuracy, a hierarchical control strategy is proposed in this paper. Droop control and virtual impedance is applied in primary control loop while secondary control loop is based on dynamic consensus algorithm (DCA). Experiments are conducted to verify the effectiveness of the proposed control strategy.

In an autonomous microgrid without connection to the interconnected grid to support the frequency and voltage, it is more complex to control and manage. Thus in order to investigate the dynamic stability of the medium-voltage (MV) microgrid in Dongao Island, a detailed small-signal state-space model of the autonomous MV mixed-source microgrid containing diesel generator set (DGS), grid-supporting battery energy storage system (BESS), squirrel cage induction generator (SCIG) wind turbine and network is developed. Sensitivity analysis is carried out to reveal the dynamic stability margin of the MV microgrid and identify the permissible variations range of the droop coefficients. Finally, the theoretical analysis is verified with time-domain simulation and experimental results.

This document analyses the large-signal stability for an inverter-based generator such as photovoltaic and wind power sources. The objective of this study is to determine the stability region taking into account the electrical and control signal of the generator. The generator uses the concept of the electrostatic machine for the model of the generator. Finally, the applied procedure to find the Lyapunov's function is the Popov method, which not only permits to generate a valid function but also to determine the stability region of the system.

In this paper, a distributed multiagent based algorithm is proposed to achieve SoC balance for DES in the DC microgrid by means of voltage scheduling. Reference voltage given is adjusted instead of droop gain. Dynamic average consensus algorithm is explored in each agent to get the required information for scheduling voltage autonomously. State-space analysis on a single energy storage unit and simulation verification shows that the proposed method has two advantages. Firstly, modifying the reference voltage given has less impact on system stability compared to gain scheduling. Secondly, by adopting multiagent methodology, the proposed distributed control has less communication dependence and more reliable during communication topology changes.

This paper presents consensus-based distributed control strategies for voltage regulation and power flow control of dc microgrid (MG) clusters. In the proposed strategy, primary level of control is used to regulate the common bus voltage inside each MG locally. An SOC-based adaptive droop method is introduced for this level which determines droop coefficient automatically, thus equalizing SOC of batteries inside each MG. In the secondary level, a distributed consensus based voltage control strategy is proposed to eliminate the average voltage deviation while guaranteeing proper regulation of power flow among the MGs. Using the consensus protocol, the global information can be accurately shared in a distributed way. This allows the power flow control to be achieved at the same time as it can be accomplished only at the cost of having the voltage differences inside the system. Similarly, a consensus-based cooperative algorithm is employed at this stage to define appropriate reference for power flow between MGs according to their local SOCs. The effectiveness of proposed control scheme is verified through detailed hardware-in-the-loop (HIL) simulations.

This paper proposes a distributed control strategy for voltage and reactive power regulation in ac Microgrids. First, the control module introduces a voltage regulator that maintains the average voltage of the system on the rated value, keeping all bus voltages within an acceptable range. Dynamic consensus protocol is used to estimate the average voltage across the Microgrid. This estimation is further utilized by the voltage regulator to elevate/lower the voltage-reactive power (Q-E) droop characteristic, compensating the drop caused by the droop mechanism. The second module, the reactive power regulator, dynamically fine-tunes the Q-E coefficients to handle the proportional reactive power sharing. Accordingly, locally supplied reactive power of any source is compared with neighbor sources and the local droop coefficient is adjusted to mitigate and, ultimately, eliminate the load mismatch. The proposed controllers are fully distributed; i.e., each source requires information exchange with only a few other sources, those in direct contact through the communication infrastructure. A Microgrid test bench is used to verify the proposed control methodology, where different test scenarios such as load change, link failure, and inverter outage are carried out.

This paper is focused on an advanced control for autonomous microgrids. In order to improve the performance regarding security and stability, a hierarchical decentralized coordinated control scheme is proposed based on multi-agents structure. Moreover, corresponding to the multi-mode and the hybrid characteristics of microgrids, an event-triggered hybrid control, including three kinds of switching controls, is designed to intelligently reconstruct operation mode when the security stability assessment indexes or the constraint conditions are violated. The validity of proposed control scheme is demonstrated by means of simulation results.

This paper explores a control strategy for parallel uninterruptible power systems (UPS). The control technique used in that work was based on the droop control method. This method is usually applied to achieve good active and reactive power sharing when communication between the inverters is difficult due to its physical location. This paper has considered that the UPS systems there were no communication between their controls. A detailed mathematical model about the explored system is shown in that work and simulation results are presented in order to prove the theory presented.

Paralleled dc converter systems are widely used in distribution systems and uninterruptable power supplies. This paper implements a hierarchical control in a droop-controlled dc-dc conversion system with special focus on improving system efficiency which is dealt within the tertiary regulation. As the efficiency of each converter changes with output power, virtual resistances (VRs) are set as decision variables for adjusting power sharing proportion among converters. It is noteworthy that apart from restoring the voltage deviation, secondary control plays an important role to stabilize dc bus voltage when implementing tertiary regulation. Moreover, system dynamic is affected when shifting VRs. Therefore, the stability is considered in optimization by constraining the eigenvalues arising from dynamic state space model of the system. Genetic algorithm is used in searching for global efficiency optimum while keeping stable operation. Simulation results are shown to demonstrate the effectiveness of the method.

Parallel inverters having LCL output filters cause voltage distortions at the point of common coupling (PCC) in islanded microgrids when non-linear loads are present. A capacitive virtual impedance loop could be used to provide selective harmonic compensation in islanded microgrids, instead of introducing additional active or passive filters into the system that could compromise the stability of the microgrid. However, the performance of these compensation loops becomes degraded when a virtual resistance is introduced with the aim to improve the overall stability of the parallel inverters. With the capacitive virtual impedance, there is effectively a compromise between the additional stability provided by the virtual resistance and the harmonic compensation due to the virtual capacitance. This paper focuses on overcoming this limitation of the capacitive virtual impedance with additional virtual resistance for selective harmonic compensation in islanded microgrids. Simulation results were given to show the suitability of the proposed algorithms in reducing the voltage harmonics at the PCC.

In this paper, a distributed coordinated control scheme based on frequency-bus-signaling (FBS) method for a low-voltage AC three phase microgrid is proposed. The control scheme is composed by two levels. Firstly a primary local control which is different for the DGs and the ESS is proposed. The ESS adopts FBS control which is based on changing slightly the bus frequency in the microgrid when the state-of-charge is near to the limit. This way, the DG controller when detecting that the frequency is increasing, will reduce the injected power by using a virtual inertia control loop. Then secondary control is implemented to restore the frequency deviation produced by the primary ESS controller while preserving the coordinated control performance. Real-time simulation results show the feasibility of the proposed approach by showing the operation of the microgrid in different scenarios.

Parallel operation of distributed generation is an important topic for microgrids, which can provide a highly reliable electric supply service and good power quality to end customers when the utility is unavailable. However, there is a well-known limitation: the power sharing accuracy between distributed generators in a parallel operation. Frequency and voltage droop is a well-established control method for improving power sharing performance. In this method, the active and reactive power calculations are used to adjust the frequency and amplitude of the output voltage. This paper describes the digital implementation of a droop method, and analyzes the influence of power calculation on droop method performance. According to the analysis, the performance of droop control in a digital control system is limited by the accuracy and speed of the power calculation method. We propose an improved power calculation method based on p-q theory to improve the performance of the droop control method, and we compare our new method with two traditional power calculation methods. Finally, simulation results and experimental results from a three single-phase 1-kW-inverter system are presented, which validate the performance of our proposed method.

In a microgrid system, distributed energy storage units are commonly employed as the energy buffers. In this paper, a dynamic power sharing method based on the state-of-charge (SoC) of each energy storage unit is proposed. Droop control is employed as the basic control strategy for the distributed energy storage units. By using the proposed method, the coefficients in the conventional droop method are adjusted according to the SoC of each energy storage module. The modules with higher SoC delivers more active power, while those with lower SoC delivers less. Meanwhile, the reactive power is equally shared in the energy storage system. The relationship between the droop coefficient and SoC are studied deeply and the small signal model is developed to verify the stability of the control system. It is found that the active power sharing speed becomes faster with higher exponent of SoC. At the same time, in order to restore the AC-bus voltage, secondary control is employed to eliminate the deviations of the voltage frequency and amplitude caused by the droop control, with the droop coefficients adjusting according to the SoCs. The model of the secondary control scheme for SoC-based droop method is developed and its stability is discussed. The theoretical analysis is demonstrated by both simulation and experimental results.

This paper focuses on the islanded operation of microgrids. In this mode of operation, the microsources are required to cooperate autonomously to regulate the local grid voltage and frequency. Droop control is typically used to achieve this autonomous voltage and frequency regulation. Inverters having LCL output filters would cause voltage distortion to be present at the PCC of the local load when non-linear current is supplied to the load due to the voltage drop across the grid side inductor. Techniques to reduce the output voltage distortion typically consist of installing either passive or active filters to selectively compensate harmonic frequencies. However, by adding suitable control strategies to the inverters connected to the microgrid, the power quality of the microgrid can be improved without the installation of any additional equipment. In this paper, a capacitive virtual impedance loop, implemented in each of the microsource inverters, is proposed so as to dampen the voltage harmonics at the PCC of the local load. Simulation results are presented showing the suitability of the proposed algorithm in dampening the PCC voltage harmonics.

This paper presents a novel approach to conceive the secondary control in droop-controlled MicroGrids. The conventional approach is based on restoring the frequency and amplitude deviations produced by the local droop controllers by using a MicroGrid Central Controller. A distributed networked control system is used in order to implement a distributed secondary control thus avoiding the use of a MicroGrid Central Control. The proposed approach is not only able to restore frequency and voltage of the MicroGrid but also ensures reactive power sharing. The distributed secondary control do not relies on a central control, so that the failure of a single unit will not produce the fail down of the whole system. Experimental results are presented to show the feasibility of the distributed control. The time latency limits of the communication systems are studied as well.

This paper proposes the practical realization of a fuzzy variable structure control applied to a PWM inverter. Variable structure Control (VSC) is a robust control method for handling nonlinear systems where occur parameter variations and external disturbances. However, control input chattering round sliding surface exists, and may deteriorate the system performance. To reduce the chattering, a fuzzy logic for VSC is applied to overcome the problem. By composing the advantages of both VSC and fuzzy logic (FL), the PWM Inverter system can be designed and produces low total harmonic distortion (THD) output voltage and fast dynamic response under different types of load. Experimental results on a single-phase PWM inverter laboratory prototype controlled by a dSPACE-based DSP controller are presented to illustrate the improved performance, particularly under severe rectifier load. Moreover, for comparison purposes, a conventional variable structure controlled single-phase PWM inverter is also tested on the same experimental system.