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Flyback converters are widely used for photovoltaic (PV) application. However, the majority of research has been focusing on the control aspect of the converter where as stability, especially sensitivity of design parameters, has not been well studied. This paper presents the small-signal modeling of flyback converters in continuous conduction mode (CCM) using a moving average technique. MATLAB/Simulink is used to find the eigenvalues of the closed-loop system. The system stability is analyzed through the movement of eigenvalues due to changes in parameters of different components. The developed model demonstrates stability issues when certain parameters such as controller gains and passive components' values.

This paper presents a small-signal modeling of cascaded H-bridge converter connected to a solar photovoltaic (PV) system. By analyzing eigenvalues of state-space equations of the system, the closed-loop controller has been designed to control the DC-link voltage in each cell as well as the grid current. The sensitivity and stability margins of the system have been examined by changing the grid impedance, capacitors of DC-link, and parameters of the controller. Also, the dynamic response of the system was analyzed by applying a step change in the DC-link setpoints. To verify the performance and effectiveness of the controllers, simulation has been conducted in MATLAB/SIMULINK for a three-phase cascaded H-bridge with three cells in each phase.

This paper presents sub-synchronous resonance (SSR) mitigation of double-fed induction generator (DFIG)-based wind generation system. The system is series compensated by a capacitor in transmission model. A virtual generator control (VSG) is developed and supplemented to the grid side converter (GSC) of the DFIG to not only enhance the inertial response, but also to alleviate SSR. Two cases are designed to: 1) analyze the system stability under different compensation levels, and 2) test the sensitivity of parameters of VSG loop on system stability. The linearized small-signal model was developed on MATLAB/Simulink to validate the effectiveness of the proposed method. Sensitivity analysis is conducted to examine the impact of VSG gains on stability of series compensated DFIG-based system.

Massive integration of converter-based renewable energy sources into power systems through weak AC grid has become a dilemma in recent years. This paper investigates the design of a robust nonlinear multi-input-multi-output (MIMO) controller for voltage source converters (VSCs) connected to weak AC grids. Feedback linearization method is used to find the controller equations and design the inputs to regulate the active power and output voltage of the converter. With this approach, the controller is designed in a way that the grid impedance impact on the stability of the converter system is significantly reduced. The robustness of the proposed controller is evaluated using time-domain simulations of a grid-connected VSC enhanced with the nonlinear controller in various case studies. The results illustrate a significant improvement compared to existing approaches.

Pulse width modulation (PWM) is the most commonly used technology for switching power electronics-based power converters in smart grids. However, implementing PWM in actual hardware is not as straightforward as it sounds. This paper develops a step-by-step procedure to implement PWM for single-phase and three-phase silicon carbide (SiC) converters using popular digital signal processing (DSP) boards from Texas Instruments (TI). The proposed model classifies the PWM implementation into multiple cascaded loops so that it can be understood easily from the electrical engineering point of view. The proposed step-by-step solution is then implemented on a C2000 F28069M LaunchPad development kit for single-phase and three-phase applications. An experimental setup on a 3.5 kW three-phase Silicon-Carbide (Sic) inverter was developed to validate the three-phase PWM implementation.

Improving the reliability and efficiency of microgrids to handle diverse load types will lead to more dependable electrical grids in small communities, reduce costs for both consumers and suppliers, and reduce carbon emissions. Better demand side management (DSM) has been proposed as a solution for creating more efficient m icrogrids a swell as limiting the need for increases in power generation capacity and transmission. This paper proposes a hardware implementation of DSM in an actual microgrid system to support grid needs. An algorithm for achieving DSM through load-leveling at the micro-level is presented and implemented on a physical microgrid and evaluated in order to create a Load-Leveling Trainer. A simulated case study, based on the electrical load needs of small communities in Bangladesh, is reviewed to prove that the Load-Leveling Trainer can be used to better balance electrical load demands.

In smart distribution networks, an essential responsibility of system operators is to effectively respond to the detected cyberattacks in order to prevent any possible blackout. This paper proposes a reaction framework for the distribution system operator (DSO) to respond to decentralized cyberattacks implemented on several distributed generation (DG) retailers, electric vehicle (EV) retailers, and demand response (DR) retailers. Due to the false data injections on the clients of DG / EV / DR retailers, wrong aggregated data will be submitted to the DSO. If a proper response is not provided, system has to rely on the targeted market participants which can result in congestion / blackout. As a result, we propose a real-time smart distribution network reconfiguration (RSDNR) framework for DSO to result in a system topology such that 1) minimum reliance on attacked retailers is required for system operation and 2) convenience of market participants is minimally affected by the administrative reaction of DSO. The effectiveness of the proposed scheme is validated on a well-known 136-bus distribution system modified with DGs and flexible loads which can provide DR.

Smart girds security is raising a lot of concerns to governments, energy industries, and consumers. Due to the vulnerability of smart grids and their critical nature, they can be a prime target for cyberattacks. False data injections in targeted buses can manipulate the power system measurements in such a way that the power flow in the system’s lines are altered. If those attacks are not observed, the attacker is able to overflow some lines with minimal unobserved false data injections which might cause power outages and even system blackouts. This paper proposes a bi-level mixed integer linear programming (BMILP) optimization model for false data injection on targeted buses to cause an overflow in transmission lines of a power system. The upper level problem of the model finds the minimum false data injections in targeted buses that can bypass DC state estimation and cause an overflow in selected lines by the attacker. The lower level problem runs the optimal power flow problem taking into account the false data injections to find a new optimal solution that satisfies the optimal power flow constraints and prevent lines overflow. The paper validates the results of such an attack considering IEEE 30 bus test system with several possible cases for the attack.

Fuel cell-based energy generation has become more popular in distributed power generation systems in recent years due to their zero emissions, sustainability, and portability. This paper presents the small-signal model of a grid-connected polymer electrolyte membrane (PEM) fuel cell system. The state-space modeling technique is used to model the fuel cell stack, boost converter, three-phase inverter and ac filter dynamics. Partial pressure dynamics of hydrogen, oxygen and water are included in fuel cell dynamics. The stability of the overall system is tested through eigenvalue analysis in MATLAB. Different case studies are developed to investigate the sensitivity of boost converter parameters and phase-locked loop (PLL) on the stability of the overall system.

Cyber attacks on transmission lines are one of the main challenges in security of smart grids. These targeted attacks, if not detected, might cause cascading problems in power systems. This paper proposes a bi-level mixed integer linear programming (MILP) optimization model for false data injection on targeted buses in a power system to overflow targeted transmission lines. The upper level optimization problem outputs the optimized false data injections on targeted load buses to overflow a targeted transmission line without violating bad data detection constraints. The lower level problem integrates the false data injections into the optimal power flow problem without violating the optimal power flow constraints. A few case studies are designed to validate the proposed attack model on IEEE 118-bus power system.

The ongoing noticeable growth of energy demand in the world dramatically increases the thermally overloaded distribution lines, which can seriously threaten the security of distribution power systems. This paper proposes an electricity market framework in which renewable energy-based market participants are motivated to contribute to the “power system security” via congestion management. Moreover, the communications between market participants are supervised to manage the “data transmission traffic”. In addition, electric vehicles are customized to contribute to system security not only as flexible loads but also as virtual distributed generation (DG) units. Furthermore, administrative support of the distribution system operator is modeled in the introduced holistic scheme to take into account the scenarios in which market participants are unable to fully resolve congested distribution feeders in the system. The effectiveness of the proposed market mechanism is verified on a 136-bus “unbalanced” distribution network equipped with wind turbines and photovoltaic DGs.

Vector current control is the most commonly used approach for converters in renewable energy generation systems. Unfortunately, the conventional vector current control for the VSCs is unable to synchronize to the weak ac grid. This paper derives the impedance model of a vector controlled voltage source converter (VSC) enhanced with a virtual synchronous generator (VSG) loop for weak ac grid connections. The impedance modeling includes the dynamic models of the phase-locked loop (PLL), ac side filter, inner current loops, outer power loops, and the VSG loop. Eigen loci of the impedance is used to analyze the stability of the control under different grid strengths. In addition, sensitivity of PLL gains, virtual inertia gains, and dc-link capacitor value on overall system stability is evaluated using frequency-domain analysis.

Different types of power grids have different characteristics which require proper control methods to be implemented. Typically, droop control schemes are utilized at the primary control level due to their simplicity and quick response. Nevertheless, those droop methods can be varied depending on the power grid impedance, and hence, various secondary control protocols might be needed. This research proposes a distributed design approach for distributed battery energy storage systems (BESSs) at the higher control level corresponding to three different droop schemes implemented at the lower control level for various grid conditions. The designed controllers use multi-agent system and consensus theory to regulate the voltage/frequency and synchronize the energy level as well as active and reactive power sharing among BESSs. A modified IEEE 57-bus power system is used in the simulation for validation purpose.

Standalone battery energy storage systems (BESS) have widely been integrated to wind turbines recently to enhance the power quality and reliability of wind generation systems. This research analyzes the stability of a doubly fed induction generator (DFIG)-type wind turbines with stand alone battery storage using small-signal analysis. For the wind turbine, the induction generator model, grid side converter (GSC) controller, AC dynamics, and rotor side converter (RSC) controller are considered. For the BESS, the AC filters, and BESS controller are considered in the modeling. Eigenvalue analysis is performed to study the sensitivity of parameters of the system and control parameters on the stability of the combined wind turbine+BESS system. MATLAB/Simulink is used to analyze the system and validate the design.

This paper proposes a novel application of a modular multi-level converter (MMC) for photovoltaic (PV) generation system to maximize the efficiency in partial shading conditions. A DC/DC boost converter is placed between each sub-module (SM) of the MMC and the PV array to extract the maximum PV power. Furthermore, the proposed topology is enhanced with an independent active/reactive power control strategy for demand response purposes. The effect of circulating currents is also minimized using a proportional resonance (PR) controller. The proposed system is validated using time-domain simulations via MATLAB/Simscape power system toolbox on a 10 MW three-phase grid-connected MMC system.

The paper proposes the stability analysis of an offshore wind power plant connected to an onshore AC grid through high voltage AC (HVAC) and multi-terminal high voltage DC (MTDC) transmission systems. Dynamic phasor (DP) technique is used to derive the small-signal model of the entire system and to analyze the system with sufficient accuracy and relatively lower computation cost. The DP modeling accounts for the voltage source converter (VSC) models, inner current controller, outer voltage controller, and droop controllers. The impact of the variation of the frequency droop gain, voltage droop gain and line inductance values on the system stability is studied by performing an eigenvalue analysis of the combined system. Simulations in MATLAB/Simulink are used to validate the DP-based analysis of VSC-HVDC systems for offshore wind farm applications.

In a deregulated electricity market, power system operator should systematically identify the optimal schedule of renewable distributed generation (DG) units to not only optimize the market profits but also improve the network conditions. This paper proposes a parallel computation-based methodology using fuzzy logic designed in the structure of a genetic algorithm (GA). Due to the efficient communication among the processors during the optimization, the proposed fuzzy-based parallel computation GA (FPCGA) addresses the shortcoming of the classic GA in convergence speed and quality of results. The proposed optimization algorithm is utilized in this paper to identify the optimal daily schedule for the system operator including the energy purchased from 1) the power grid, 2) each wind turbine DG, and 3) each photovoltaic DG. The efficiency of the proposed method is verified by its implementation on a 136-bus distribution system and its effectiveness is compared with similar methods.

This research designs a new approach for the reactive power sharing of distributed battery energy storage systems (BESSs) in smart grids. Droop control is the most commonly used approach in sharing the active/reactive powers between BESSs. However, this strategy never considers the operating power factor of BESSs, which might introduce high losses and equipment cost. The proposed control methodology in this paper attempts to remedy the unbalanced reactive load distribution problem for batteries and is aimed at driving the power factors of all the batteries connected in parallel to operate around the same point, close to unity power factor. A controller is designed based on the modified power factor strategy to synchronize the power factors of energy storage devices. The effectiveness of the proposed methodology is verified using simulation results comparing the reactive load before and after the deployment of the proposed control method on a microgrid with three BESSs using MATLAB/Simscape power system toolbox.

This research studies the stability of a grid-connected battery energy storage system (BESS) with a voltage source converter (VSC) and a filter. The VSC is a grid supporting controlled converter, which is enhanced with a primary and secondary frequency/voltage droop controllers, to enable grid connected and islanded mode operation without changing the controller structure. The linearized small signal model of the entire system is derived considering the inner current controller, the outer power loop, the primary and secondary frequency/voltage controllers, the LCL filter, and the phase-locked loop (PLL). The eigen values of the linearized system are obtained using state space modeling. To analyze the effects of certain parameters on the system stability, different case studies are performed.

This paper proposes a sub-synchronous resonance (SSR) mitigation controller for battery energy storage system (BESS). It is a fact that series compensated long transmission lines may interact with the generator shaft and cause SSR oscillations. With the high penetration of BESS in smart grids, auxiliary damping controllers can be designed in order to contribute to the SSR mitigation in wind farms or synchronous generators. This paper designs a damping controller for a grid connected BESS using the wide area measurement system (WAMS) data. The designed damping controller will be supplemented to the active power control of the BESS. Fast Fourier transform (FFT) analysis is conducted to analyze the performance of the designed damping controller. Time domain simulations with MATLAB/Simpscape toolbox on the modified IEEE second benchmark model (SBM) are performed to support the claims.

This paper proposes a distributed control architecture for battery energy storage systems (BESSs) based on multi-agent system (MAS) framework. The active/reactive power sharing, the frequency/voltage, and the energy of BESSs are synchronized by exchanging local information with a few other neighboring BESSs. Two consensus algorithms namely leaderless and leader-follower are proposed. The proposed control architecture offers unique features. Firstly, the heterogeneous nature of BESSs is explicitly taken into account in BESS models and consensus designs, while it is usually ignored in the literature. Secondly, the proposed designs bring the plug-and-play capability to the smart grid system by operating in both islanded and grid-connected modes. Next, the nominal frequencies and nominal voltage magnitudes of BESSs are used in the consensus design instead of their frequencies and voltage magnitudes. This makes the proposed structure much easier to be implemented in the real power grids. Lastly, an additional control input is designed to synchronize the energy levels of BESSs directly, whereas the energy levels of BESSs are synchronized indirectly through their powers in other existing research. Time-domain simulations on a modified IEEE 57-bus power system are then carried out to validate the proposed control structure and the consensus designs.

This paper investigates a distributed consensus control design for heterogeneous energy storage devices in smart grids. Using communications between energy storage devices in the system, primary and secondary voltage/frequency control are achieved. The primary voltage and frequency synchronization is achieved by equally sharing the active and reactive powers among energy storage devices. The secondary voltage and frequency restoration is achieved by selecting one energy storage as a virtual leader, and other energy storage devices will act as followers to follow the leader energy storage system. The uniqueness of the proposed consensus design is the use of nominal values of grid voltage and frequency instead of their measured values. The proposed design is validated using modified IEEE 14-bus system in MATLAB.

In this paper, consensus integral control is applied for energy storage in microgrids to synchronize the state-of charge (SoC) and power levels of batteries with limited information exchange. Both local information (SoC and power level) and neighbors' information (SoC and power level) will be fed into an integral control installed at every battery converter. The design is based on consensus control and takes into consideration of realworld battery coordination requirements, e.g., all batteries should work in the same charging or discharging mode. Compared with the consensus control in the existing literature for voltage consensus or battery SoC/power consensus, this paper offers a simple design. The major assumption of the paper is that each converter should possess an integral control. This assumption is valid since indeed integral controls exist if converters are equipped with secondary frequency control. The designed consensus control is validated by simulations on 14-bus microgrid and IEEE 57-bus power system. Simulation results demonstrate the effectiveness of the consensus integral control for variety modes of operation: charging, discharging, and load variation.

This paper investigates the application of sweeping method in initializing the state variables of an unbalanced radial distribution system for small signal analysis. The unbalance is caused by a single-phase PV system. The system is composed of a three-phase induction machine (IM), a single-phase PV, a load, and a power factor correction (PFC) unit. The IM is modeled in positive-, negative-, and zero- sequence dynamic phasors and then converted into in a abc dynamic phasors frame. The PV, load and PFC and radial network are all modeled in phase-based dynamic phasors. The sweeping method along with embedded Newton-Raphson iterations is implemented to find the equilibrium point for initialization. The iterative procedures are illustrated and demonstrated by case studies. A dynamic simulation case study is also presented.

In this paper, a real time model of the microgrid with an energy storage system has been implemented in RT-Lab. Coordinated control of the battery storage system with a PV system is simulated. To be more realistic, hardware-in-the-loop (HIL) testbed has been implemented with a real battery cell (3.2-V, 40-Ahr) connected to the real-time simulation model of the microgrid. A programmable current source (Magna) and programmable load (Bk 8500) have been used to create charging and discharging paths between the energy storage unit and the RT-LAB.

This paper employs impedance-model-based frequency domain analysis to detect subsynchronous resonances (SSR) in Type 3 wind farms with Thyristor Controlled Series Capacitor (TCSC). The contributions of this paper are (i) the derivation of dynamic phasor based TCSC impedance model and (ii) the application of such impedance model in Type 3 wind energy systems for SSR analysis. Impedance models for TCSC with constant firing angle control and impedance control are derived in this paper. With the derived impedance models, Nyquist-stability-criterion is applied to compare SSR stability in Type 3 wind farm with TCSC or with fixed capacitor compensation. This paper employs analytical models to demonstrate TCSC's capability in avoiding SSR in Type 3 wind generator interconnection systems. The analytical results obtained through impedance models are validated by detail model-based (with thyristor switch modeled) time-domain simulation in Matlab/SimPowerSystems.

In this paper, the real-time simulation model of a single-phase single-stage Photovoltaic (PV) has been developed in RT-LAB. The model is composed of a detailed model of a PV with Maximum Power Point Tracking (MPPT), a Phase Locked Loop (PLL), a proportional resonance (PR) controller, and a full bridge inverter. As the RT-LAB works in discrete time domain, modifications have been applied to the MPPT and the PR controller. The paper presents the control structures in discrete domain. Two categories of case studies have been carried out. In the first case, an irradiance signal composed of a ramp and a step change was applied. In the second case, the irradiance was generated by a Chroma controllable voltage source to emulate the random irradiance and it has been sent to the RT-LAB as an input signal. Outputs from the RT-lab were captured in oscilloscopes. The paper demonstrates the use of the developed PV model for real-time digital simulation and for hardware integration.