Hybrid microgrids (HMGs) have shown great potential for the efficient integration of distributed energy resources and supporting reliable, flexible operation in standalone scenarios. In such systems, the secondary control is essential for restoring voltage and frequency deviations and ensuring accurate power sharing among distributed generators (DGs). While centralized control enables simple and cost-effective coordination, its vulnerability to controller or communication link failures can compromise global power sharing and system stability. This paper presents a resilient centralized secondary control architecture for standalone HMGs that preserves one-way broadcast coordination in normal operation while providing communication-free fault operation through locally deployed, online-trained artificial neural networks (ANNs). The ANNs are deployed at the DGs and the bidirectional interlinking converter (BIC) to predict point-of-common-coupling voltages using local measurements. These predicted values enable local controllers to emulate the behavior of the central secondary controller during system faults. This maintains accurate global power sharing during full centralized system failure and frequency/voltage regulation during isolated BIC operation, without introducing peer-to-peer coordination or additional distributed messaging. Furthermore, the ANNs are trained online during normal operation, allowing continuous adaptation to system changes. Real-time validation is carried out using a high-fidelity field-programmable gate array (FPGA)-based simulation platform with detailed power switching models. Results confirm the effectiveness of the proposed method in both seen and unseen scenarios, demonstrating improved resilience while retaining the low-overhead communication structure of centralized secondary control.

The increasing demand for efficient and resilient renewable-based energy systems is driving research towards hybrid ac/dc microgrids (HMG), offering a practical pathway to future dc-dominant grids by directly integrating a wide range of dc-operated resources. This paper proposes a model-free real-time control strategy for coordinating distributed generators (DGs) to achieve dynamic global power sharing in an islanded HMG. Conventional model-based controllers are replaced with a deep reinforcement learning agent based on the deep deterministic policy gradient (DDPG) algorithm. Unlike most existing studies that rely on offline training through computer simulations, the proposed agent is trained online during normal operation, without requiring predefined system models or manual controller tuning. The effectiveness of the method is validated through hardware-in-the-loop (HIL) experiments under different load variation scenarios, demonstrating robust dynamic response and accurate global power sharing.

This paper presents a buck-boost DC-DC converter design featuring a wider voltage gain capability. The proposed topology offers advantages such as continuous input current and a common ground connection shared by the input and output ports. The proposed converter's low input current ripple makes it particularly suitable for renewable energy applications, such as photovoltaic (PV) systems. In contrast to conventional buck-boost converters, which typically invert the output voltage polarity, this design delivers a positive output voltage. Additionally, the converter employs only a single main switch, which also benefits from reduced voltage stress, enhancing both reliability and operational efficiency. The converter's operation is grounded in detailed mathematical modeling, with simulation and experimental validation confirming consistency between theoretical predictions and practical performance.

The unsustainable use of resources (water, gas, and electricity) contributes to the intensification of global warming. On the other hand, the indiscriminate use of electrical resources poses serious problems to the sustainability and operability of the power grid. One of the solutions to mitigate this problem refers to responsible use of resources by the domestic user, creating new habits, without giving up their lifestyle and comfort. The creation of a game supported by a web application, which allows the use of group game techniques, can promote the increase of efficient consumption by the users. This work presents the development of a game which aimed at the consumption awareness of the participants. The competition between users was stimulated by the attribution of points, using the weekly consumption comparison of groups formed by the participants. Other functionalities, allowing users to obtain extra points, were designed to keep a high level of engagement.

DC-DC converters play a crucial role in providing power conversion for the integration of renewable energy sources into the electric power grid or as standalone power sources. However, achieving proper integration of applications like photovoltaic generators often requires DC-DC converters with an enhanced voltage range due to conditions such as PV shadowing. This is a feature that is lacking in standard DC-DC converters. Addressing this need, this paper presents a novel transformerless buck-boost converter with a wide conversion voltage ratio. The proposed converter has only one active switch, simplifying the gate driver and control system implementation. The wide conversion voltage ratio is ensured by its quadratic voltage gain. Operates in both step-up and step-down modes, unlike most existing quadratic topologies, which are limited to either step-up or step-down operation, and shares a common ground between the input and output terminals. The operational modes of the proposed converter and its steady-state performance are thoroughly analyzed. Simulation and experimental tests were conducted to evaluate its performance.

DC-DC converters are widely used to provide power conversion in electrical/electronic appliances and portable electronic devices. Over the last few decades, they also have been played a key role in the integration of renewable energy sources into the electric power grid or as standalone power sources. However, to achieve proper integration of certain electric/electronic devices/drives or photovoltaic power in shadowing conditions, it is frequently imperative to employ DC-DC converters that possess enhanced voltage amplification, a capability that standard DC-DC converters lack. According to this need, this paper proposes a new DC-DC Buck-Boost converter using a single power semiconductor switch. The proposed topology provides wide conversion voltage ratio, reduced voltage stress in the power semiconductor and reduced ripple of the input current. The operation principle of the proposed converter and the static gain will be discussed through a theoretical analysis. The performance of this power converter will be tested through simulations and experiments.

Due to the new paradigm in which AC grids must coexist with DC microgrids, new solutions to interlink those networks are required. In this context, a new interlink hybrid converter is presented in this paper. This solution is designed to interlink AC grids and bipolar DC microgrids or two DC microgrids. The simplest solution allows linking a three-phase AC grid using only two single-phase inverters. However, it can be extended with the purpose to make a multilevel converter. The solution allows to transfer the energy in a way that supports the attenuation of the voltage unbalance that can appear in the DC microgrid(s). This support is done by an independent transference of energy to the microgrid poles or microgrids. This concept and behavior of the interlink hybrid converter will be tested through simulation studies. The results obtained in these studies show the capability of the proposed solution.

While the past 50 years have been dominated by the so-called communication revolution, today, we are at the dawn of the energy revolution. The entire economy is energy driven, being electricity its most important energy vector. By the end of 2040, electricity is expected to contribute up to 40% of the increase in final energy consumption, and concepts, such as smart grid or internet of energy, are now commonplaces in our lexicon. The Paris UN climate change conference agreement has imposed three major changes into the electrical grid paradigm: the need to reduce carbon emissions; the need to decentralize electrical energy production, and the need to increase transport electrification.

In this paper, a robustness evaluation of Unscented Kalman Filter (UKF) in comparison with the Extended Kalman Filter (EKF) for State of Charge (SOC) estimation of a lithium-ion battery based on capacity degradation model is investigated. To more comprehensively evaluate the performance of EKF and UKF, A first-order RC equivalent circuit model was used to characterize the dynamic behavior of a 30Ah lithium-ion battery. Based on the relationship between the Arrhenius formula, battery capacity, temperature and charge-discharge current accelerated stress, a fitting formula is obtained to predict the battery capacity degradation rate. The simulation results show that UKF outperforms EKF in terms of estimation accuracy and convergence rate against temperature effects, current and voltage noises.

Reliability has become a mandatory feature in many safety critical applications, where major accidents, equipment damage or expensive downtimes must be prevented. One of the major qualities of the switched reluctance motor (SRM) is its high fault tolerance features. Although this motor can be able to continue operating even with some of its phases disabled, in this situation it appears an important torque ripple that could affect its proper functioning in some applications. This paper presents a novel low cost spilt-winding fault-tolerant approach, together with the correspondent power converter, that enables the motor to continue normal operation in the case of a winding open circuit. The obtained results show that the proposed solution, and its inherent fault tolerance behavior does not present a huge impact on the overall motor efficiency.

In this work it is proposed a switched reluctance machine (SRM) drive supplied by a renewable source (PV array) to operate a water pumping system. To improve the speed of the commutation between phases it is proposed the use of a multilevel converter for the SRM drive. This converter was designed to reduce the number of controlled power semiconductors, reducing the cost of the system. To obtain the maximum power extraction of the PV system is proposed the use of an algorithm based on the product of the time derivative of power with the time derivative of voltage. A control system to ensure the balance between the power generated by the renewable source and the water pumping system is also proposed. The operation and characteristics of the system will be verified by several numerical tests.

This paper presents an intelligent energy storage system for NZEB buildings integrated in a smart grid context. The proposed methodology is suitable for NZEB buildings that include integrated renewable generation and storage capabilities, aiming at high load matching and low grid interaction, acting as a prosumer. The considered energy storage system is electrochemical storage (batteries) and the renewable production is based on PV panels. The energy storage management is based on a genetic algorithm approach that aims to increase the energy storage system return of investment by, at the same time, minimizing the grid energy consumption, on higher DSO tariff periods, and reducing the number of battery operating cycles. In this way the management system will increase the life time of the energy storage system and reduce the amount of money that the prosumer has to pay to the DSO operator.

This paper presents a quasi-Z-source (qZS) converter that allows to supply multilevel voltages for the switched reluctance machine (SRM) drive. The use of qZS converter in SRM drives allows obtaining better high speed operation characteristics since higher voltages can be achieved. The proposed drive uses a qZS converter but designed in order to be possible to apply, to the SRM, different voltage levels on the magnetizing and demagnetizing stages. The presented converter also allows to regulate the output voltages and the difference between the voltage levels. Thus, it is possible to improve the efficiency of the drive, by reducing the switching frequency, as well as having better characteristics for high-speed operation. Different configurations of the converter are presented and the modulator associated to the SRM drive is described. In order to verify the features of the proposed system several results are also presented and discussed.

This work presents an energy management strategy based on scheduling battery operation in prosumer systems, according to forecast data available 24 hours in advance. The proposed method seeks to reach a beneficial compromise between prosumers and distribution grid operators, independently of specific economic context or technical regulations. An improvement to deal with forecast inaccuracy is carried out. Results demonstrate that it offers good properties regarding energy management, with a stored energy reserve estimation, battery lifetime preservation and self-consumption and self-sufficiency enhancement.

This paper studies and analyses the impacts introduced on Distribution Transformer (DT) overload due to the integration of nearly Zero-Energy Buildings (NZEBS) into existing distribution Low Voltage Grids (LVG). The negative impacts on the DT are studied and explained. For high nZEB integration levels, this study reveals that the subsequent reverse power flows can achieve higher values, especially around noon, than the DT rated (and overload limit) power thus accelerating its aging. A power electronics based Energy Storage System (ESS) is considered to mitigate these negative effects. The paper also analysis the mitigation of the negative DTs impact by considering this ESS solution. The established control laws prevent the transformer to be exposed to excessive reverse power flow levels.

This paper presents a four wire dual-buck inverter integrated in a photovoltaic system with grid support capabilities. In the context of smart-grids this kind of systems can play an important role. In this particular case the system will supply the ancillary services for unbalanced loads and reactive power compensation. A dual-buck inverter is adopted in order to ensure a higher reliability. This kind of inverter is characterized by the non-existence of shoot-through problems and by the possibility of the using power MOSFETs as active switches. The control system for the dual-buck inverter with the ancillary service functions is also presented. In order to verify the performance of this system several simulation results are presented and discussed.

The study and assessment of Power Quality issues is nowadays a very important subject, particularly regarding Cyber-physical and Industrial Agents based systems, which are extremely sensitive to Power Quality disturbances. Giving students or engineers practical experience in this field requires a large investment from teaching institutions. This paper presents a laboratory device that emulates Power Quality disturbances in order to provide the required experimental expertize in the subject. It addresses limiting aspects such as harmonic distortion, flicker, sags, swells and transients. The developed system presents a good opportunity for technicians, even without deep knowledge on the field of power quality, to learn basic principles and be able to identify Power Quality events. Since the system is based on real data, represents a valuable approach giving trainees practical knowledge on the field.

Demand Response programs influence the end-user electricity usage by changing its cost along the time. In this scenario, to better manage the building's energy demand and consequently the electricity related costs, the user needs to estimate the energy demand and on-site production of the building in function of the electrical devices that are present on the building boundary. This paper presents an agent-based electrical simulator that has been built with the main objective of providing those tools to the consumer. The proposed simulator uses a hybrid "bottom-up" approach, with both statistical and physical models. The referred software is capable of estimating the energy demand and on-site generation with a 1-min time resolution for the period of 24h and calculates the energy price for each scenario. Therefore more control over the demand side is given to the end-user, allowing an easy response to changes in the electricity costs along the day. Such techniques could help the user to maximize the usage of renewable energy and to lower the electricity costs. On the other hand it is also beneficial for the energy provider since it is more likely to reduce the demand at peak hours.

The perspective of Smart Grid developments brings a picture with active distribution networks having many distributed resources such as PV connected to the grid through inverters. The challenge for this future is so complex that the Smart Grid Coordination Group (SG-CG) is already considering for standardization in the new Use-Case cluster "Connect and active actor to the grid", the high level use case "Managing generation connection to the grid". This is considered as emerging necessary functionality of the "Distribution management system", to be subject of CEN/CENELEC standardization. This paper presents enabling solutions for these requests and proposes solutions for Automated Remote Grid Acceptance and Energy Services Tests using new concepts for the Smart Meter and for the inverters design. Results to sustain the proposals are also sustained by a case of simulation for a Grid Acceptance test - Fault Ride Through with reactive power and for an Energy Services Test proving interphase simetrization service.

In this paper a wireless home automation system is presented The proposed system allows controlling devices in a home environment by using a simple Bluetooth equipped mobile phone. The mobile phone communicates with a main Bluetooth/ZigBee module that communicates with the different ZigBee modules acting as the coordinator of the ZigBee network established between all nodes where electrical devices are connected The identification of each device is made through DomoML strings by using the KNX home automation standard protocol.

Smart grid structure could be very complex. Active power electronic transformers (APETs), composing an important part of the smart grid, could have many roles in that stochastic and variable system. Modular structure is the key to flexibility, reduced costs and losses. We propose a base module of the APET consisting of modular building blocks, also known as power electronics building blocks (PEBBs). PEBBs have plug-and-play functionality and can be connected together in various ways. Therefore, it is easy to adapt the APET to any kind of voltage level and type. To guarantee power quality, the base module has the functionality of power factor correction and active power injection. The performance of the base module was verified by computer-aided simulations.

In this paper a low-power wind generation grid-connected system for domestic consumers with two control modes (Maximum Power Point Tracking (MPPT) and Power Control (PC)), will be presented. The MPPT mode will be active when the home's load is higher than the wind generator's maximum available power and the PC mode will be active when the home's load is lower than the wind generator's maximum available power. These two techniques will be adopted to both optimize the wind system performance and to prevent power injection into the electrical grid. Hence, the PC mode will be a particularly important part of this system. It will also be crucial to assure that the controller decides correctly on which control mode should be active, given the current grid supplying power.

One of the most used power converters is the three-phase voltage source power inverter. This is one of the reasons why it is so important to assure a continuous and safety operation of this power converter. This paper considers the application of the S-Transform to detect and identify faulty power switches in voltage source inverters. The S-Transform is applied to the inverter output currents in order to get a specific pattern that allows the identification of the fault. This results in a fast and reliable fault detection methodology. The applicability of the proposed technique is confirmed through simulation and experimental results.

One of the most used power converters is the three-phase voltage source power inverter. This is one of the reasons why it is so important to assure a continuous and safety operation of this power converter. This paper considers the application of PCA and average value computation to detect and identify faulty power switches in voltage source inverters. The PCA is applied to the inverter output currents in order to get a specific pattern that allows the identification of the fault. This results in a fast and reliable fault detection methodology. The applicability of the proposed technique is confirmed through simulation and experimental results.

The idea of power electronic transformer is known already over 20 years. There are numerous papers written about power electronic transformers. In the literature one can find tens on different topologies, control methods, standards, requirements etc. It is easy to loose insight what topology to use and where. In this paper a general overview of the power electronic transformer technology in terms of smart grids is presented. The information collected from the literature is classified and organized. In conclusion some generalizations are made and development trends are shown.

This paper presents Hermes, a new modular platform that can be used in a variety of scenarios, including the role of body area network coordinator, enabling temperature, movement and heartbeat sensing, local and remote communication, and indoor and outdoor localization. Hermes is based on two main modules that can operate as a single system in a coordinated fashion or individually, depending on the application scenario. One of the modules uses a Telos-inspired architecture, with new processing, communication, sensing, storage and energy subsystems, and executing TinyOS. The other module is designed around a PIC 24F MCU, also supporting communication, sensing, storage, and executing a custom operating system. Both modules have expansion capabilities. The main innovative aspects of the implemented platform are its modularity and its capability to provide device abstraction, which considerably eases application development. The paper addresses the platform motivation, requirements, hardware architecture, implementation details, and performance evaluation.

This paper proposes a translation methodology to emulate PLC control program in the Matlab/Simulink environment. The translation package automatically translates the PLC control program into Matlab/Simulink software language. The PLC control program is translated into a Matlab function block, within the Matlab/Simulink environment, that will control the model of the industrial process as long as the simulation runs. The translation package inputs are: the type of PLC, the PLC's number of inputs and outputs and the PLC control program file. The translation package output will be a Matlab/Simulink compatible m-file with the correspondent PLC control program translation. Universidade de E¿vora students are successfully using this package, so that they can test their PLC control programs together with Matlab/Simulink process models.

A correspondence is established between the basic elements of logic reasoning systems (knowledge bases, rules, inference and queries) and the structure and dynamical evolution laws of neural networks. The correspondence is pictured as a translation dictionary which might allow to go back and forth between symbolic and network formulations, a desirable step in learning-oriented systems and multicomputer networks. In the framework of Horn clause logics, it is found that atomic propositions with n arguments correspond to nodes with nth order synapses, rules to synaptic intensity constraints, forward chaining to synaptic dynamics and queries either to simple node activation or to a query tensor dynamics.

Drive systems today determine the productivity and quality of industrial processes. However, they exhibit considerable complexities related with their behavior as large uncertainties at a structure and parameter levels, multidimensionality, and strong mutual interactions. This paper aims to analyze common features, and the potential, but also the drawbacks that fuzzy logic and formal language theories show when used for recognition of patterns in experimental drives. Two prototype systems are used: an electrohydraulic drive and an induction motor drive. We underline the similarities and various aspects of the recognition methodologies, despite their use on different systems. A set of experimental learning situations with critical effects on their performance are presented and discussed.

Formal language techniques have been used in the past to study autonomous dynamical systems. However, for controlled systems, new features are needed to distinguish between information generated by the system and input control. We show how the modeling framework for controlled dynamical systems leads naturally to a formulation in terms of context-dependent grammars. A learning algorithm is proposed for online generation of the grammar productions, this formulation then being used for modeling, control and anomaly detection. Practical applications are described for electromechanical drives. Grammatical interpolation techniques yield accurate results, and the pattern detection capabilities of the language-based formulation makes it a promising technique for the early detection of anomalies or faulty behavior.