Static VAR Generators (SVGs) are power electronics devices used to compensate unbalanced currents and correct power factor. SVGs can be used in networks with neutral connection if they use a four-wire topology. The main topologies for two-level three-phase converters are the four-leg four-wire (4L4W) converter and the three-leg converter with split capacitor, a.k.a. three-leg four-wire (3L4W) converter. The selection of the topology and sizing of the dc capacitor are crucial aspects in the SVG design. However, in the literature the dc capacitor is usually sized by numeric simulations that limits the comprehension of its sizing. In this paper, a methodology for the sizing of the dc capacitor of four-wire SVGs is proposed. This methodology is based on the calculation of the ripple of the dc-link voltage using analytic expressions, when the SVG compensates negative-and zero-sequence currents. The proposal simplifies the sizing of the power stack, and helps to select the most adequate topology depending on the application. The contributions have been validated by using numeric simulations in MATLAB/Simulink to design a 15 kvar SVG.

The rapid growth in electricity generation from renewable energy sources represents a major challenge to maintaining the stability of power systems. In this scenario, virtual power plants (VPPs) represent a suitable solution for providing ancillary services to the grid. However, to achieve this goal, renewable energy sources and storage units must be adequately coordinated. In this article, a secondary controller for VPPs that allows the provision of frequency response services is proposed. This controller takes into account the resource availability of the VPP elements (wind, sun irradiance, energy stored, etc.) to calculate the power references for each unit. The effectiveness of the proposed control strategy is tested using a simplified scenario in which a VPP is connected to the transmission network. The VPP consists of two wind power plants, a solar photovoltaic power plant, an energy storage system, and local loads. Four case studies are analysed that include sudden changes of the VPP load, impact of external network, and variations of the power generated by the VPP using realistic generation profiles. Numerical simulation results obtained in Matlab/Simulink are used for validation purposes. In all the cases, the frequency is restored to its nominal value while the VPP power exchange converges to the reference set-point.

In recent years, power electronic converters have been increasingly used for integration of different generation technologies to electricity networks. However, due to their fast control loops and non-ideal grid conditions, these devices are prone to interact with each other. This can lead to an unstable grid operation with possible catastrophic results. In order to study such interactions between devices before commissioning of new power plants, power hardware in the loop (PHIL) techniques have been increasingly used. However, emulation of complex grid scenarios is not straightforward and requires in-depth knowledge of the emulated grids and dedicated hardware and software. In this paper, the emulation of complex grid scenarios in a PHIL platform is presented. The proposed methodology can be used to emulate not only the dynamics of power devices but also the primary, secondary and tertiary control levels. Four complex scenarios are described and their implementation discussed, with special emphasis on practical details that are commonly not explained in the literature. Results show that the low-frequency dynamics of diesel generators, microgrids, electrical systems and local-power networks can be effectively emulated in the PHIL platform. All the scenarios are validated experimentally.

This paper presents a simple multi-vector model predictive power control (MV-MPPC) strategy for the rotor side converter (RSC) of a doubly fed induction generator (DFIG). In this strategy, the stator active and reactive power derivatives for the three vectors are estimated for the upcoming period and the duration time of these vectors is predicted according to a cost function. The objective of the cost function is to decrease the stator power errors. The proposed model predictive control is validated in Matlab/Simulink environment and in the laboratory for a 5 KW DFIG prototype. The simulation and experimental results showed that the proposed method has a fast dynamic response to the power and rotor speed changes and it has a constant switching frequency.

Most electronic devices are connected to the grid by using power electronics converters and, in order to reduce the filter size and cost, novel filter topologies are being proposed in the literature. For high-power applications, LTCL filters are an attractive solution since the size of inductors can be reduced while maintaining a low switching frequency. However, this type of filter requires additional passive damping elements unless an active damping strategy is included in its control system. In this paper, the hardware and control system design of a VSC connected to the grid via a LTCL filter is addressed, with emphasis on the damping problem. It is shown that adequate damping can be provided by applying two different strategies. The first one is by changing the hardware of the converter (without additional passive elements), while the second one is by adding a compensator in series with the current controller. The proposed design methodology and control system improvements were tested in a simulation of a 15 kW VSC connected to the grid via a LTCL filter.

Two different methods for implementing inertial damping on a Virtual Synchronous Machine (VSM) and their potential for attenuating power system oscillations when utilized in a VSC HVDC terminal are investigated in this paper. As a reference case, the VSM is considered with only a frequency droop providing damping in the virtual swing equation. Then, the effect of damping based on high-pass filtering of the virtual speed is compared to damping based on high-pass filtering of the measured grid frequency. A simplified model of a power system with two equivalent generators and a VSC HVDC terminal is introduced as a case study. Analysis of the small-signal dynamics indicates that damping based on the VSM speed has limited influence on the power system oscillations, while improved attenuation can be obtained by introducing damping based on the locally measured grid frequency. The presented analysis and the operation of the proposed VSM-based damping strategy is validated by numerical simulation of a 150 MVA VSM controlled VSC HVDC terminal connected to a dynamic model of the assumed grid configuration.

An increased deployment of distributed generation in recent years has contributed to creation of meshed power networks usually seen as a way to improve power flow management capability. Also, power electronics converters have been commonly used to interface distributed resources to the grid, yet their impact on the network stability has not been sufficiently explored. In this paper the stability of meshed weak power networks with high penetration of power electronics converters is studied. For that purpose a small-signal state-space model of the complete power network has been developed by introducing linearized state-space models for each system component including power converters and their control systems, lines, loads and the grid connection. Both eigenvalue and maximum singular value analyses have been then used for the stability assessment. The variation of three typical parameters was studied and their impact on the stability evaluated: 1) PLLs bandwidth, 2) radial grid line inductance value and 3) cross-feeder line inductance value. The principal findings include a positive impact on the stability from the increase of the PLLs bandwidth and a potential compromise of the system safe operation from the increase of the grid inductances.

The emulation of synchronous machines is an attractive solution to improve the integration of distributed energy resources in weak grids. In this sense, synchronverters have been widely analysed in the literature, but their digital implementation has been seldom studied. This paper presents the discrete-time implementation of the control algorithms for a battery-supported synchronverter in a weak grid. First of all, the formulation is described in a synchronous reference frame and a simple method to adjust the parameters is described. Some modifications are proposed to the classical synchronverter that will be implemented in its incremental form. By using this implementation method the control system a) becomes easier to implement, b) wind-up problems are avoided, and c) command signals are easier to saturate. Since the control system is non-linear, these features are of a particular relevance. All the control developments are tested experimentally in a 15 kVA converter with a 47.5 kWh Li-ion battery connected to a weak grid.

A novel modelling method and a stability analysis procedure for weak power networks with high penetration of power electronics converters are proposed in this paper. The modeling approach can be applied to any network topology and in order to model of the complete network it introduces small-signal state-space models for each network component including power lines, loads, power converters and their control algorithms. The proposed linearized model was validated by comparing its response with the response of the non-linear model. In order to identify the critical network and control parameters of the weak grid in presence of disturbances the developed small-signal model was then used in the stability analysis based on the frequency response of singular values. Finally, the existence of the identified resonance modes was confirmed by using the original non-linear model of the network.

The SmartHG project goal is to develop a suite of integrated software services (the SmartHG Platform) aiming at steering residential users energy demand in order to: keep operating conditions of the electrical grid within given healthy bounds, minimize energy costs, and minimize CO2 emissions. This is achieved by exploiting knowledge (demand awareness) of electrical energy prosumption of residential users as gained from SmartHG sensing and communication infrastructure. This paper describes such an infrastructure along with user demand patterns emerging from the data gathered from ~600 sensors installed in ~40 homes participating in SmartHG test-beds.

In order to optimally manage a modern electricity distribution network, peaks in residential users demand should be avoided, as this can reduce energy and network asset management costs. Furthermore, this must be done without compressing residential users demand. To this aim, in a demand response setting, residential users are given a price policy, which economically motivates them to shift their loads in order to achieve this goal. However, if the price policy for all users is similar, this demand response may result in simply shifting the demand peaks (peak rebound), leaving the problem unsolved. In this paper we propose a novel methodology which i) for each network substation s, automatically computes the desired power profile to be kept in order to optimally manage the network itself, ii) for each network substation s, automatically synthesizes individualized price policies for residential users connected to s, so that s is kept at the desired profile. Note that price policies individualization avoids the peak rebound problem, as different users have different low tariff areas. Furthermore, our methodology measures the flexibility of a residential user as the capacity needed by a home energy storage system (e.g., a battery) to always follow the given price policy, thus mitigating residential users discomfort. We show the feasibility of our approach on a realistic scenario taken from an existing medium voltage Danish distribution network.

Increasing global interest in clean and distributed energy systems emphasizes the importance of power electronics technologies in grid integration of renewable energy resources. High penetration of renewables such as wind turbines introduces new challenges for the grid stability seeking appropriate solutions. From a technical and economic point of view any application and testing of new management schemes in real power networks is risky. To overcome these obstacles, hardware-in-the-loop (HIL) technologies appear as a suitable and logical option, because they make equipment or control algorithm evaluation easier, faster and more economical. This paper addresses the hardware-in-the-loop discrete time modeling of a permanent magnet synchronous machine (PMSM) wind turbine (WT). The discrete time modeling has been considered and used so that the developed models can be executed in real-time on an industrial computer. In addition, some features of the Smart Energy Integration Lab (SEIL) - a purposely build lab environment for implementation of grid scenarios and the HIL system used for the implementation are presented. Finally, the paper experimentally validates the design methodology for real-time emulation of wind turbines.