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Grid‐forming inverters are used for voltage regulation and frequency control in autonomous hybrid microgrids and multi‐microgrid systems by imitating synchronous generators. However, in microgrids with weak grids including low inertia levels and small X/R ratios, these inverters interact with each other, and as a result low‐frequency oscillations (LFO) arise. LFO impacts the frequency stability of multi‐microgrid systems. Nevertheless, LFO can be mitigated by the load‐frequency control system, which serves as a secondary control mechanism. However, the presence of wind turbines and photovoltaic systems in hybrid microgrids adds complexity to the operation of the load‐frequency control due to the uncertainty associated with these renewable energy resources, and various controllers have been employed. This paper proposes a novel approach to enhance the performance of the load‐frequency control system and suppress LFO. The presented technique reduces the complexity of the hybrid microgrid structure by reducing the number of controllers. The model predictive control (MPC) technique is utilized for load‐frequency control and the weight parameters of the MPC are determined using the rain optimization algorithm. The proposed method demonstrates improved dynamic response, reduced overshoot and undershoot responses, decreased controller complexity, and effective LFO suppression. The simulation results verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Modern (micro) grids host inverter-based generation units for utilizing renewable and sustainable energy resources. Due to the lack of physical inertia and, thus, the low inertia level of inverter-interfaced energy resources, the frequency dynamic is adversely affected, which critically impacts the stability of autonomous microgrids. The idea of virtual inertia control (VIC), assisted by battery energy storage systems (BESSs), has been presented to improve the frequency dynamic in islanded microgrids. This study presents the PD-FOPID cascaded controller for the BESS, a unique method for enhancing the performance of VIC in islanded microgrids. Using the firefly algorithm (FA), the settings of this controller are optimally tuned. This approach is robust to disruptions due to uncertainties in islanded microgrids. In several scenarios, the performance of the suggested approach is compared with those of other control techniques, such as VIC based on an MPC controller, VIC based on a robust H-infinite controller, adaptive VIC, and VIC based on an optimized PI controller. The simulation results in MATLAB show that the suggested methodology in the area of VIC is better than previous methods. [ABSTRACT FROM AUTHOR]

The influence of distributed generation sources in the Islanded microgrid has adverse effects on frequency stability because of the absence of inertia. Accordingly, the concept of a virtual synchronous generator (VSG) has been proposed, which follows the behavior of conventional synchronous generators. The virtual inertia control can be implemented on energy storage systems (ESSs) as a part of a virtual synchronous generator. Virtual inertial control does not perform optimally against the uncertainty of islanded microgrid parameters and disturbances. Therefore, virtual inertial control requires a supplementary controller in its structure that is resistant to these effects. In this paper, a new robust output feedback control method was used to control the virtual inertia in a two-area microgrid, which is based on the linear matrix inequality. The proposed control method does not need to measure all modes and only uses the output feedback. We compared the results of the proposed controller for controlling the virtual inertia in multiple different scenarios by considering the uncertainty of the two-area microgrid parameters as well as disturbances applied to the microgrid with the virtual inertia control based on optimized PI controllers (genetic algorithm), no controller (virtual inertia), and without considering virtual inertia (conventional methods). Accordingly, the effectiveness of the proposed method was demonstrated in terms of response speed, reduction of the frequency deviations and tie-line power deviations, robustness against parameters' uncertainty, and disturbances occurring to the two-area microgrid. [ABSTRACT FROM AUTHOR]

With the presence of distributed energy resources in the microgrid, the problem of load-frequency control (LFC) becomes one of the most important concerns. With changing the parameters of the microgrid components as well as the disturbances forced to the grid, designing a suitable LFC becomes more difficult. In this paper, the design of a Robust model predictive controller (RMPC) based on the linear matrix inequality as a secondary controller LFC system is discussed for controlling a microgrid on the shipboard. The main purpose of the proposed method is to improve the frequency stability of the microgrid in the presence of disturbances and the uncertainty of its parameters. The proposed controller simulation results, in several different scenarios, considering the uncertainty of the microgrid parameters as well as the input disturbances are compared. The main controllers are the fuzzy proportional-integral type1 and 2, and multi-objective multi-purpose functions optimized with the MOFPI (MBBHA), MOIT2FPI (MBHA) algorithm. The effectiveness of the proposed method in terms of the response speed and reduction of fluctuations and overcome uncertainties of the parameters, as well as robustness to disturbances, are discussed. Simulation is implemented in MATLAB software. The proposed method reduces the frequency oscillations caused by disturbances on the microgrid by 68% (68% improvement over other methods used in this field). Also, using this method, the damping speed of microgrid frequency fluctuations is increased by 53% (performance improvement). [ABSTRACT FROM AUTHOR]

The time delay between distributed generation sources puts the frequency stability at risk. Moreover, increasing the number of distributed generation sources in islanded microgrids due to the lack of inertia has undesirable effects on frequency stability. In this article, the notion of a virtual synchronous generator which follows the characteristics of a conventional synchronous generator is introduced. Virtual inertia control can be implemented on sources of energy storage. In this article, the problem of designing a Virtual Inertia Control method is based on Robust Model Predictive Controller (RMPC), considering the time delays in microgrids is addressed. To model the uncertainty of the system, employed the polytopic model and the Sedumi solver to solve the Linear Matrix Inequalities (LMI), in a shorter time. Compared the results of the proposed controller under several different scenarios with virtual inertial control schemes based on the optimized-PI-controller (Genetic algorithm), the H-infinity controller, and the control free procedure, considering uncertainties in microgrid parameters, time delays and input disturbances. The efficiency of the RMPC method has been indicated via the simulations performed in MATLAB. [ABSTRACT FROM AUTHOR]

This paper presents an economical approach for reliability improvement, harmonic mitigation and loss reduction in microgrids and active distribution networks that include of the distributed generations (DGs) considering technical constraints. The proposed method is a stochastic approach based on the calculation of the locational marginal price (LMP) in each DG bus. The problem is as a game-theoretic that each DG is taken as a single player considering its contributions on the aforementioned objectives. In this regard, each player gets a financial incentive as incremental price, based on a fair method using cooperative game-theoretic sharing strategy. In other words, each DG that aligns its generation with the aforementioned objectives will increase the price of selling energy. This increase in prices will lead to higher profits. Therefore, DGs are interested in volunteering to accomplish network goals. As a tool for system management, the proposed method can control the impact of the pricing in the form of incentives to satisfy each objective depending on its decision in the incentive allocation procedure. To obtain a more realistic framework, demands are considered as the uncertainty parameters. To validate the proposed method, it is evaluated on the real Taiwan Power Company (TPC) network. The promising results indicate that the total loss is decreased by 54.5%, harmonics are mitigated by 12.3% and the reliability is improved by 12.6%. [ABSTRACT FROM AUTHOR]

The interaction of droop controllers through power network is high in networked microgrids (NMGs) due to the low X/R ratio of the power lines impedance and lack of inertia in converter-based NMGs, which has raised stability concerns. On the other hand, inaccurate reactive power sharing and poor power quality due to the voltage and frequency deviations still remain as noticeable issues in NMGs. In this paper, a novel fuzzy consensus protocol is proposed to improve the droop controller performance in power sharing by incorporating the X/R ratio of the power lines impedance into droop loops. Power quality is also enhanced by restoring the average voltage profile based on a new consensus protocol, which is designed to be in coordination with reactive power sharing. In order to guarantee stability of the closed-loop system, linear matrix inequality method is adopted to determine the consensus signal coefficients as structured static output feedback gains. To this end, a novel small-signal model is proposed for NMGs to be adopted in the design process, by which the cross-coupling as well as interaction of droop controllers through the power network is properly realized. The numerical results in MATLAB/SIMULINK prove the effectiveness and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Microgrid (MG) concept is considered as the best solution for future power systems, which are expected to receive a considerable amount of power through renewable energy resources and distributed generation units. Droop control systems are widely adopted in conventional power systems and recently in MGs for power sharing among generation units. However, droop control causes frequency fluctuations, which leads to poor power quality. This paper deals with frequency fluctuation and stability concerns of  f-P droop control loop in MGs. Inspired from conventional synchronous generators, virtual damping is proposed to diminish frequency fluctuation in MGs. Then, it is demonstrated that the conventional frequency restoration method inserts an offset to the phase angle, which is in conflict with accurate power sharing. To this end, a novel control method, based on phase angle feedback, is proposed for frequency restoration in conjunction with a novel method for adaptively tuning the feedback gains to preserve precise active power sharing. Nonlinear stability analysis is conducted by drawing the phase variations of the nonlinear second-order equation of the δ-P droop loop and it is proved that the proposed method improves the stability margin of  f-P control loop. Simulation results demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• Capacitor placement problem in a radial distribution system. • Demand response program execution. • Compensating reactive power and minimizing real power losses and the total voltage deviation. • Optimal operation of isolated microgrids (MGs). • Harmony search algorithm (HSA). Reactive power compensation is one of the important problems during the operation of power systems. By the way, capacitor allocation is one of the efficient and affordable tools in order to reactive power compensation of power systems, which is used frequently in conversional networks. This paper presents an efficient approach for optimal placement and sizing of shunt capacitors in islanded microgrids to improve the voltage profile and mitigate the power loss considering demand response based on harmony search algorithm (HSA). To validate the efficiency of the proposed approach, a 69-node islanded microgrid is being studied. Also, the obtained results from HSA are compared with the particle swarm optimization (PSO) algorithm. The results of the proposed approach show the efficiency of optimal capacitor allocation in the islanded microgrid, which can be considered as an effective idea in reactive power compensation. [ABSTRACT FROM AUTHOR]

Locating the source of voltage sags in order to identify the events causing the problem and improving mitigation strategies is a major issue. When two utilities manage interconnected networks or manage a micro grid and an upstream grid, an occurred fault in one area may cause voltage sags that affect sensitive customers/critical loads in another area. From this viewpoint, this paper first reviews and analyses with detail different methods for voltage sag source location. Then eleven generalized method are introduced. A comparative analysis is performed between some of the discussed methods by applying extensive numerical simulations in a Brazilian regional utility by using PSCAD/EMTDC and MATLAB. The location of each monitor represents a difference kind of system topology (radial, interconnected, one source, two sources and interconnected microgrids). In the following, the effectiveness of methods was obtained and comprised for each monitor location and for the whole system.. The results obtained show that the effectiveness of methods based on instantaneous positive sequence components and Clarke's components is equal in many methods except distance relay and resistance sign methods, and that the effectiveness is lower, higher or equal than methods based on positive sequence phasors. The phasor based methods had less effectiveness. The generalized methods based on reactive power using instantaneous positive sequence components and Clarke's components gave the right location in 88% of total simulated cases. The results also provided a comprehensive background to propose future works and to select the best method especially at interconnection point of a micro grid with the presence of renewable distributed energy sources. [ABSTRACT FROM AUTHOR]

In an islanded Micro-Grid (MG), the use of conventional power flow analysis is not effective as the voltage of slack bus and the frequency of the MG are assumed to be constant. Such assumption fails to consider the real characteristics of the islanded MG as all DGs are involved in providing the demand of active and reactive power as well as maintaining the frequency of the MG. In this paper, a review of power flow methods in power system is shown. Furthermore a novel algorithm, named GPSO-GM (Guaranteed convergence Particle Swarm Optimization with Gaussian Mutation), for the power flow analysis problem in an islanded MG is proposed. The problem is modeled without any slack bus by considering steady state frequency as one of the power flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an islanded MG, a new formula for power flow equations is developed. PSO is adopted to minimize the mismatch of total active and reactive power. Two operators, mutation and guaranteed convergence, are added to PSO in order to help in finding an optimal solution and to assist in increasing the speed of the proposed algorithm as well as the accuracy of the results. [ABSTRACT FROM AUTHOR]

The islanding capability of Microgrids (MGs), when a fault happens in the grid, is seen as one major driver in enhancing the reliable of MGs. However, the use of power electronic interfaces based-MGs faces some difficulties in maintaining stability in an islanding mode due to the low capacity of installed DGs as well as the low speed response of MGs to any load changes. In fact, the lack of availability of spinning reserves makes fast response to load changes, as well as balancing between power generation and load demand difficult. This leads to deviation in voltage and frequency from their (pre-determined) permitted values. In this paper, a new MG’s topology along with a novel control strategy is proposed for stabilizing MGs in different operation modes. Battery storage is used to address the slow response problem of micro sources (MSs) to load changes, and to balance load demands and power generation in the islanding mode of MGs. A droop control idea is adopted in the lowest level of a hierarchy controller to enhance cooperation between power electronic inverters, and to improve load dispatch and voltage regulation. The voltage variation of the MG’s main bus is considered as a load change criterion, instead of the output power of converters, to increase the response speed of the control system. The effectiveness of the proposed control strategy is assessed using MATLA/SIMULINK. It is shown that the proposed control strategy improves the operation of MGs in grid connected and islanding modes where soft transient between these two modes are achieved. [ABSTRACT FROM AUTHOR]

The energy management system is executed in microgrids for optimal integration of distributed energy resources (DERs) into the power distribution grids. To this end, various strategies have been more focused on cost reduction, whereas effectively both economic and technical indices/factors have to be considered simultaneously. Therefore, in this paper, a two-layer optimization model is proposed to minimize the operation costs, voltage fluctuations, and power losses of smart microgrids. In the outer-layer, the size and capacity of DERs including renewable energy sources (RES), electric vehicles (EV) charging stations and energy storage systems (ESS), are obtained simultaneously. The inner-layer corresponds to the scheduled operation of EVs and ESSs using an integrated coordination model (ICM). The ICM is a fuzzy interface that has been adopted to address the multi-objectivity of the cost function developed based on hourly demand response, state of charges of EVs and ESS, and electricity price. Demand response is implemented in the ICM to investigate the effect of time-of-use electricity prices on optimal energy management. To solve the optimization problem and load-flow equations, hybrid genetic algorithm (GA)-particle swarm optimization (PSO) and backward-forward sweep algorithms are deployed, respectively. One-day simulation results confirm that the proposed model can reduce the power loss, voltage fluctuations and electricity supply cost by 51%, 40.77%, and 55.21%, respectively, which can considerably improve power system stability and energy efficiency. [ABSTRACT FROM AUTHOR]

• Proposing dynamic-scale conservation voltage reduction (DCVR) to solve technical issues of autonomous microgrids (AMGs). • AI-based deep reinforcement learning (DRL) technique is proposed for implementing DCVR. • Multi-agent DRL structure has been designed, and the agents are trained to realize decentralized DCVR. • Accurate Q-sharing is preserved while implementing the DCVR. • DCVR addresses the dynamic instabilities of AMGs by improving the primary frequency response. Conservation voltage reduction (CVR) is implemented in power systems to mitigate power consumption in steady-state time scales. We propose dynamic-scale CVR (DCVR) as a potent solution to provide cost-effective frequency support in inverter-interfaced (micro) grids. The proposed DCVR reduces the voltage profile in dynamics and consequently power reduction helps to maintain instant production-consumption balance for dynamic frequency support. However, DCVR implementation in autonomous MGs (AMGs) faces critical control and stability problems. DCVR is implemented by controlling the voltage, which is a local variable, and makes it difficult to be realized through a decentralized structure. Besides, preserving accurate reactive power sharing (Q-sharing) through conventional droop controllers while employing the DCVR is another critical concern. In this light, this paper proposes a novel artificial intelligence (AI)-based decentralized control structure to implement the DCVR in AMGs for tackling the existing issues. The multi-agent deep reinforcement learning (DRL) model, with a deep Q-network (DQN) algorithm, is adopted to address the grid instabilities and inaccurate Q-sharing issues that arise due to incorporating the DCVR. The proposed method is able to handle the nonlinearity and complexity of the system while maintaining proper dynamic performance and AMG stability. Simulation results in MATLAB/Simulink prove the effectiveness of the proposed control method. [ABSTRACT FROM AUTHOR]