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In recent years, a sharp increase in integration of renewable energy sources (RESs) in power system network has been observed. High penetration of RES interfaced with power electronics converters-inverters with reduced or no inherent inertia compromises modern power system's overall stability. Due to low inertia, voltage and frequency deviations far off the allowable threshold occur. To overcome this challenge, an adaptive inertia control strategy based on optimization technique is proposed. The improved particle swarm optimization (PSO) and genetic algorithm (GA) optimization techniques-based PID controller has been used to generate the appropriate virtual inertia coefficient for effective emulation of inertia in the presence of energy storage system. The conventional PSO suffers local optima stagnation, resulting in premature convergence during searching process in order to achieve global and local position. To address this issue, the velocity update equation was modified on inertia weight (w) using an additional exponential term with linear decreasing inertia weight PSO (LDIW-PSO). In this paper, exponential power is taken strategically instead of squaring it in order to reduce the number of iterations for faster convergence. Finally, a microgrid based on wind and solar energy is simulated using MATLAB/Simulink where three cases, 2% disturbance, 3% disturbance, and 4% disturbance, have been considered. Here, the evaluation of proposed system is carried out based on four main performance indices (ITAE, IAE, ISE, and ITSE). Furthermore, validation was done through hardware prototype to get experimental results in real time. The results from MATLAB simulation and experimental setup are in sync. [ABSTRACT FROM AUTHOR]

The efficiency of on-site consumption of new energy and the economy of dispatching strategy for that in modern microgrids are increasingly concerning, which are closely related to the microgrid control model with source-load uncertainty. To this end, this paper proposes the multiagent hierarchical IQ (λ)-HDQC regulation strategy to realize the source-load-storage-charging collaborative control of the microgrid model with high-permeable new energy. The first layer adopts the IQ (λ) strategy, which avoids the overestimation and underestimation problems of traditional reinforcement learning by the coupled estimation method. The second layer adopts the HDQC allocation strategy, which solves the problem of low utilization of new energy in the proportional allocation method and improves the adaptability of the regulation strategy in the complex stochastic environment. The interaction of the two-layer strategies realizes the source-network-load-storage-charge global dynamic interactive regulation of microgrids. Indicators of energy efficiency are constructed in this paper to measure the simulation results. And the superiority of the proposed strategy is verified through the simulation results of the microgrid system. [ABSTRACT FROM AUTHOR]

The increasing integration of renewable energy sources into modern electric grids has led to a rise in uncertain factors that must be managed to maintain voltage security during reactive power optimization (RPO). Traditional deterministic RPO methods fail to account for these uncertainties, which can result in power grid security issues such as voltage violations. To address these challenges, this paper proposes a data-driven interval-based reactive power optimization method (IRPOM). The IRPOM represents the uncertainties associated with renewable power generation and load demands as intervals within the RPO problem formulation. The proposed method uses an improved particle swarm optimization algorithm to solve the RPO problem. In each iteration, the uncertain power flow is solved using the optimizing-scenarios method- (OSM-) based interval power flow (IPF) algorithm. This approach calculates the real power losses and checks whether state quantities, including voltage, power flow, and generator output, exceed their limits. Furthermore, a data-driven modeling approach is introduced to reduce the conservativeness of the IRPOM solutions. The effectiveness of the proposed method is demonstrated through detailed computational analysis on a modified IEEE 30-bus system. The results show that the proposed approach ensures economic efficiency while maintaining a low bus voltage threshold crossing probability close to zero. [ABSTRACT FROM AUTHOR]

The global demand of electrical power has increased enormously due to various reasons such as fast-changing and challenging technologies, climatic change, economic growth, and lifestyle of mankind. Due to global warming issues and the depletion of conventional sources of power generation, the utilization of renewable energy sources has drastically increased. So, many challenges exist in integrating the microgrid with AC grid and load. The alternative arm converter (AAC) is among the most innovative converter topologies used in high voltage direct current (HVDC) applications. This research work presents a new control strategy to generate pulses to trigger the switches in the AAC in a proper sequence to obtain a smooth output waveform. The AAC output is controlled by implementing various controllers such as the proportional-integral-derivative (PID) controller, fractional order PID (FOPID) controller, and FOPID controller tuned by metaheuristic algorithm-bacterial foraging optimization technique (BFOT). Also, a comparative analysis is performed based on the spectral analysis of the output voltage obtained. In comparison to other controllers, the FOPID controller optimized by the bacterial foraging optimization technique (BFOT) produced the least total harmonic distortion (THD) of the AAC output voltage. In addition, this paper also discusses about the performance and analysis on the design of an energy management system (EMS) to optimally utilize the energy sources such as PV system, wind system, and battery based on their availability which feed the AAC. The energy management system controls the entire integrated system in association with an integrated CUK-SEPIC converter to fulfil the load demand at the point of common coupling, either from the microgrid or the AC grid. A nine-level AAC model is designed integrating the microgrid, grid, and industrial loads with an energy management system using MATLAB/Simulink. The performance parameters of the entire model are analysed at every stage to provide stabilized output to meet the load demand. [ABSTRACT FROM AUTHOR]

Considering the increasing penetration of renewable energy sources (RESs) into power grids, adopting efficient energy management strategies is vital to mitigate the uncertainty issues resulting from the intermittent nature of their output power. This paper aims to resolve the energy management problem by presenting an adaptive robust optimization (ARO) model in which uncertainties associated with solar and wind powers, consumer demand, and electricity prices are considered. The proposed model comprises three stages, one master and two subproblems, using both linearized and convexified power flow equations. Meanwhile, a new optimization-based bound tightening (OBBT) method is also presented to strengthen the relaxation. The proposed solution method solves the microgrid (MG) operation management problem with high accuracy due to considering the convexification method in a reasonable computational time and reducing operational costs compared to conventional models. The numerical results indicate the benefits of the proposed ARO and solution approach over traditional methods. [ABSTRACT FROM AUTHOR]

In this paper, the optimal operation of microgrids (MGs) with thermal blocks, distributed generations (DGs), storage systems, and responsive loads is presented to achieve optimal scheduling of active, reactive, and thermal power of the mentioned elements in the day-ahead (DA) reactive power and energy market environment. The thermal block has a combined heat and power (CHP) system, a boiler, and thermally responsive loads. This scheme minimizes the difference between the total operating costs of the MG and power sources and the total revenue gained from the sale of energy and reactive power of the mentioned elements in the markets located in the MG. It is constrained by the AC power flow equations, network operation constraints, and the operating model of these elements. Furthermore, this scheme is subject to the uncertainties of energy price, load, and renewable power. In this paper, to access the optimal resistant solution against the maximum prediction error associated with the mentioned uncertainties, a robust model based on information gap decision theory (IGDT) is used. Finally, by implementing the proposed scheme on a 119-bus radial MG, the obtained numerical results confirm the ability of the scheme to simultaneously improve the economic and operational situation of the MG. The proposed scheme succeeded in improving energy cost, energy loss, voltage drop, and power factor of the distribution substation by roughly 101%, 44%, 41%, and 16% compared to power flow studies, even in the worst-case scenario caused by uncertainties. [ABSTRACT FROM AUTHOR]

Driven by the carbon peaking and carbon neutrality target, the large-scale grid-connected of renewable energy such as wind and solar has increased, and the volatility and randomness have posed new challenges to the stability of the power grid frequency. In this case, battery energy storage is a grid auxiliary resource with fast response and adjustable parameters, which can provide frequency support for the grid system in a short period. This paper studies the frequency regulation strategy of large-scale battery energy storage in the power grid system from the perspectives of battery energy storage, battery energy storage station, and battery energy storage system, respectively. First of all, the droop control based on logistic function and the virtual inertia control based on piecewise function are proposed for battery energy storage frequency regulation, which improves the performance of battery energy storage power output effectively. Second, the weighting factor is set according to the current battery charge to achieve the most optimal distribution of frequency regulation power for each battery pack in the battery energy storage station. In the end, a control framework for large-scale battery energy storage systems jointly with thermal power units to participate in system frequency regulation is constructed, and the proposed frequency regulation strategy is studied and analyzed in the EPRI-36 node model. The results of the study show that the proposed battery frequency regulation control strategies can quickly respond to system frequency changes at the beginning of grid system frequency fluctuations, which improves the stability of the new power system frequency including battery energy storage. In addition, this paper also provides a certain reference for the construction of the new power system dispatching that integrates "Generation-Grid-Load-Storage" in the future. [ABSTRACT FROM AUTHOR]

DC microgrids have been quite popular in recent times. The operational challenges like control and energy management of the renewable-driven standalone DC microgrids have been an interest of research. This paper presents a bidirectional quasi Z-source DC-DC converter (BQZSDC). This converter topology has been developed based on a conventional buck-boost type bidirectional converter, and it interfaces the storage system and the common DC bus. The challenge, however, lies in effectively managing the uncertain renewable energy sources and the storage system and catering for the loads simultaneously. An effective control strategy is needed for that energy management and to achieve various microgrid objectives. This paper deals with one such effective control strategy implemented for BQZSDC. That is, the fixed-frequency double-integral sliding mode control (FF-DISMC) controls the converter to regulate the DC bus voltage and battery current. A detailed analysis of the controller is conducted, and its performance is evaluated for both charging (buck) and discharging (boost) modes. Simulations have been performed in MATLAB, showing that the controller performs satisfactorily in achieving the objectives of voltage regulation and battery current regulation. Finally, the performance of the proposed controller is validated with the hardware setup. [ABSTRACT FROM AUTHOR]

In recent years, low-voltage direct current (LVDC) microgrids are becoming more attractive because they represent a solution to integrate renewable sources, storage, and electronic loads bringing some advantages in comparison with traditional AC grids. However, the protection of such a network involves many challenges, especially in the case of LVDC microgrids with more than one feeder and multiple energy sources. Indeed, the traditional protection breakers used for an AC grid cannot isolate the faults and protect the components of a DC grid, while the use of solid-state circuit breakers increases energy losses. This paper deals with the analysis and design of the protection schemes for LVDC microgrids through the combination of mechanical circuit breakers and hybrid circuit breakers. This solution has the advantage of energy loss reduction but introduces further issues due to the slow transition times of the mechanical circuit breakers. Thus, a completely decentralized control system capable of overcoming the fast fault-clearing time, cost-effectiveness, and selectivity issues is designed to protect from pole-to-pole faults. The proposed control strategy is compared with a centralized protection scheme available in the literature through numerical simulation. The two algorithms show similar performances, with a mean voltage dip duration of less than 30 ms and a maximum voltage dip duration of about 100 ms in the most severe fault condition, but the proposed solution is more reliable and flexible since it does not depend on the communication system. [ABSTRACT FROM AUTHOR]

The operation of power systems needs uninterrupted and precise wide-area real-time monitoring for secure and automated control of power networks, therefore, there is a requirement of robust state estimation (SE) by the smart control centre. An iterative free static state estimation (IFSSE) scheme is developed using the linear measurement model (LMM) in this paper for microgrids (MGs) integrating distributed generation energy resources (DGERs). The developed scheme of IFSSE utilizes M-estimator (ME) concept, which is combined with the linear static state estimation (SSE) approach in order to provide robust estimation. The developed IFSSE scheme is iteration-free due to the implementation LMM that is achieved from placing the microphasor measurement units (μPMUs) and separate bad data processing (BDP) is not required for this proposed scheme. The proposed scheme's performance has been verified by employing it on modified IEEE-14 bus test systems (BTS) integrating DGERs and modified IEEE 30 BTS integrating DGERs then comparison has been done by taking two cases, i.e., linear SSE without BDP and linear SSE with BDP. [ABSTRACT FROM AUTHOR]

Transformation of the distribution network, integrated with Distributed Energy Resources (DER), into a MicroGrid (MG) is an attractive approach in improving the reliability and resilience of the network. In this paper, by introducing the important and necessary aspects of the MG formation problem, an effective methodology for transformation of a distribution network into the MG is proposed. In the presented methodology, optimal allocation of DERs within MG is obtained by optimization of power losses and voltage stabilization along feeders. Moreover, the short-circuit constraints are also taken into account simultaneously while allocating DERs. The reason for the latter is that the integration of DERs alters the amplitude and direction of the short circuit current, which can cause the overall fault current to exceed the designed fault-level capability of the circuit breakers. This issue may put CBs at risk of failure and degrading MG resilience. In this regard, resilience-oriented evaluation of the MG formation, from the perspective of considering short circuit level and coordination of OCRs, is also performed. Another advantage of short circuit studies is devising complete and economic overcurrent-based protection plan for MG in both operating modes (grid-connected and islanded). It should be pointed out that adopting an appropriate control routine is a key element in the MG formation. Hence, a control strategy, based on Energy Storage System (ESS) utilization, is suggested in this paper. This feature, which is another contribution of the paper, will guarantee seamless transition to island mode and stable operation of the MG. The proposed formulation of the MG formation is solved using a modified multi-objective PSO and the Pareto-optimal set is obtained. However, since the optimal solutions are nondominated to each other, a Fuzzy Satisfaction Method (FSM) is utilized to find the optimal solution among the Pareto-set. Utilization of the proposed methodology leads to the successful transformation of the distribution network into a MG, which not only considers the load flow constraints but also preserves the optimal coordination of the protective relays and resilience of the MG. In addition, seamless transition and stable operation of the MG in island mode is achieved. [ABSTRACT FROM AUTHOR]

To improve the voltage and frequency stability and suppress the voltage harmonics of a microgrid, a virtual synchronous generator (VSG) control strategy based on the harmonic current bypass control is proposed in this paper. First, a robust voltage control link is added to the virtual excitation component of the traditional VSG control strategy to reduce the amplitude error of the inverter's driving voltage caused by the reactive power-voltage droop coefficient. A harmonic current bypass control link is then used to adjust the inverter's voltage signal to reduce the total harmonic distortion of the microgrid. Finally, a simulation model of the microgrid is established using the MATLAB/Simulink software, and its stability is analyzed. In addition, the proposed control strategy is also compared with the traditional droop control and traditional VSG control strategies, focusing on the frequency instability and harmonic suppression performance of the microgrid. The numerical simulation results verified the effectiveness and superiority of the improved VSG control strategy proposed in this paper. [ABSTRACT FROM AUTHOR]

In recent years, renewable resources have widely been used to provide necessary energy due to the increasing fossil fuel prices, environmental pollution concerns, and the necessity to meet the growth in energy demands. The output of renewable resources especially solar and wind energies is associated with meteorological parameters, so their reliability creates many challenges for the energy sector. The consumption peak of the gas network is taken into account to adjust the frequency of the microgrid (MG). Both gas network load and electric load distributions are adjusted at the same time. In a multicarrier network, the frequency is regulated in a nonlinear manner. Meanwhile, new necessary loads for production and electric vehicles have imposed new loads on the power network; if proper management is not performed to respond to these new loads, the increase of network frequency deviations may lead the network to fail and even break down. In this paper, a network of various sources including the wind turbine, solar panel, storage (battery and flywheel), electric vehicle (EV), diesel generator (DG) electric power generation, and multicarrier energy hub (MCEH) with combined heat and power (CHP) was designed to examine vehicle-to-grid (V2G) electric vehicles. The ANFIS adaptive fuzzy control method was used to provide a fine-tuning frequency of the network. A comparison between the suggested approach and a fuzzy controller system was carried out to examine the superiority of the introduced approach to the frequency control. The simulations were obtained using MATLAB/SIMULINK software. The simulation outcomes indicated that the SMART controller can achieve good efficiency in frequency regulation and reliable output power in the examined microgrid. Further comparison in terms of effective (RMS) values and maximum frequency deviation indicates the superior performance of the proposed method over the fuzzy method. [ABSTRACT FROM AUTHOR]

Due to the strong uncertainties of renewable energy and load demands, the new type of power systems is facing severe challenges in terms of generation control and load dispatch. Considering the uncertainties of the penetrated renewable energy and diversified load demands, this paper proposes a random fuzzy power flow analysis method (RFPF) to exactly depict the impact on the various flows of power systems. In the RFPF, the random fuzzy models of wind turbine generators, photovoltaic generators, and load demands are established utilizing the stochastic probability functions and fuzzy interval to reveal the uncertainties with high precision. Afterwards, the random fuzzy mean value is developed as an index of accuracy, and the fuzzy number of the output variables is extracted under the 95% confidence level. Furthermore, the proposed RFPF model is executed by applying a three-point estimate method (3PE) to figure out the corresponding power flow of the power system, costing less computation burden compared with the Monte Carlo simulation. Simulation studies conducted on the IEEE-33 system verifies the accuracy of the RFPF and the efficiency of the 3PE. [ABSTRACT FROM AUTHOR]

In a conventional AC distribution system, the conservation voltage reduction (CVR) strategy is widely employed to lower down the voltage of specific load to lower the power consumption. The wide applicability of demand side management (DSM) using CVR in a stand-alone microgrid through VSI-based energy sources is a thrust area, that is, not examined yet and needs to be explored. The fast dynamics and flexible control are the characteristics of the voltage-current droop method which further increases the inertia of the voltage source inverter. For utilizing these advantages of this droop method, it is required to determine the accurate droop gain to properly coordinate the distribution of power among DGs. In this paper, the voltage-current droop method is utilized to carry out the function of DSM, and a modified droop computation method for voltage-current droop is formulated to determine the impedance from initial of the DG point to the downstream end for multifeeder network. As most of the droop control techniques emulate the conventional power grid such as Q-V droop control which reduces voltage with the increase of reactive power, the research prospect is very high in devising the new droop computation method for voltage-current droop for accurate control of power. In addition to it, the work is extended to apply the benefits of voltage-current droop to execute DSM strategy in standalone MG. Moreover, the capability of the proposed estimation of droop parameter is implemented on a standalone 5-bus single-feeder multi-DGs network, and furthermore, the scheme is applied to IEEE-9 bus multifeeder multi-DGs network to show the applicability of the proposed scheme. The simulation results produced from MATLAB/Simulink are compared with the decentralized power-based droop method and conventional voltage-current droop technique to analyse the performance of the devised scheme. [ABSTRACT FROM AUTHOR]

In order to optimize the economy and environmental protection of microgrid, this paper establishes a demand response model based on comprehensive satisfaction, combines the advantages of the classical multiobjective particle swarm algorithm and multiobjective firefly algorithm, and proposes a hybrid particle swarm optimization and firefly algorithm (HPSOFA) to solve the joint economic and environmental dispatch problem of microgrid and improve the wind and light consumption capacity. The proposed improved algorithm introduces a random perturbation term and adaptive learning coefficients, and the algorithm is selected by the dominance relationship of individuals, which improves the diversity of populations and increases the possibility of the algorithm to solve the global optimum. The proposed algorithm is used to solve the test functions of different dimensions, and the results show that the Pareto front of HPSOFA has better distribution and accuracy, which verifies the effectiveness of the proposed algorithm. Simulation analysis is carried out using power data from a region of Liaoning Province, China, and experiments conclude that the operating cost and environmental cost of HPSOFA are significantly lower than other algorithms. [ABSTRACT FROM AUTHOR]

This paper develops a distributed fixed-time quadratic coordinated control strategy for isolated DC microgrids with time delays. The proposed control scheme based on the droop control strategy is intended to realize bus voltage recovery and current balance distribution under time delays. We first model the isolated DC microgrids as a single integrator system with input delays by the Artstein's transform. The current balance and voltage recovery are achieved by using fixed time control, which does not depend on the initial state of the system. Based on the Lyapunov functional method, the stability analysis criterion of the system is derived. In order to verify the effectiveness of the proposed control method, the DC microgrid system is simulated in Matlab/Simulink. [ABSTRACT FROM AUTHOR]

Isolated microgrids (MGs) face challenges in performance stability and active/reactive power sharing as a result of frequency/voltage deviations and mismatched line impedance issues. In this paper, a consensus-based multiagent system (MAS) is proposed as a solution to restore voltage/frequency deviations and enable true power sharing. The invention of an Intelligent Distributed Secondary Control Scheme (IDSCS) can efficiently achieve hoped-for outcomes. The proposed IDSCS features estimation and compensation sublayers. For the estimation sublayer, discrete dynamic consensus algorithm-based state estimators are presented to collect average information of frequency, voltage, and reactive power. Each DG is viewed as an agent sharing information with its immediate neighbors through a sparse cyber communication network. In the compensation sublayer, online tuned proportional integral (PI) controllers using artificial neural networks (ANNs) are proposed as an intelligent voltage and frequency compensators. This combination uses the simplicity of the PI controller mathematical formula and ANN's ability to deal with parameter variations and nonlinearity. Due to the global nature of the frequency parameter, the active power-sharing compensator is unnecessary. For compensating reactive power deviations, ANNs-based reactive power controllers are proposed. Furthermore, at the primary control level, the proposed strategy employs discrete-time proportional resonant (PR) controllers in a stationary reference frame, eliminating the need for any α β / d q or d q / α β transformations. Distributed implementation of the proposed method guarantees system scalability without MG topology or demand pattern expertise. The control scheme was validated using hypothetical MAS in MATLAB Simulink platform. The simulation findings indicate the proposed MG system can effectively distribute power among the DGs while maintaining voltage and frequency stable. [ABSTRACT FROM AUTHOR]

Microgrids are considered to be smart power grids that can integrate Distributed Energy Resources (DERs) in the main grid cleanly and reliably. Due to the random and unpredictable nature of Renewable Energy Sources (RESs) and electricity demand, designing a control system for microgrid energy management is a complex task. In addition, the policies of microgrid agents are changing over time to improve their expected profits. Therefore, the problem is stochastic and the policies of the agents are not stationary and deterministic. This paper proposes a fully decentralized multiagent Energy Management System (EMS) for microgrids using the reinforcement learning and stochastic game. The microgrid agents, comprising customers, and DERs are considered as intelligent and autonomous decision makers. The proposed method solves a distributed optimization problem for each self-interested decision maker. Interactions between the decision makers and the environment during the learning phase lead the system to converge to the optimal equilibrium point in which the benefits of all the agents are maximized. Simulation studies using a real dataset demonstrate the effectiveness of the proposed method for the hourly energy management of microgrids. [ABSTRACT FROM AUTHOR]

Rural and remote area electrification is of grave concern around the globe. Therefore, well-planned and cost-effective microgrids integrating renewable energy sources are emerging as effective solutions. However, the microgrid's stable operation and its future deployment is affected by the perturbations caused due to uncertainity in renewable sources, dependency on the battery state of charge, and load variation. So, considering the possible concerns affecting the planning and development of a microgrid for any given region, this paper proposes a comprehensive performance assessment of the hybrid residential microgrid based on a load model of Kibber village in Himachal Pradesh, India. The proposed approach is divided into three parts for the best planning of microgrids. Firstly, the MATLAB–Simulink software technically analyzes the system performance under perturbations considering the available renewable sources. Secondly, an economic analysis using HOMER Pro software is done to examine the cost-effectiveness of the proposed microgrid model through the simulation of electrical loads for Kibber village, considering the available renewable sources. Lastly, a real-time analysis of the proposed prototype of programmable logic controller-based hardware test bench has been developed, aiming for future regional microgrid deployment. System voltage, frequency, power shared, percentage of load met, energy cost, available renewable energy resource, etc. have been considered for validating the proposed controller. The proposed comprehensive assessment of the microgrid model is reproducible with necessary modifications for any geographical location. It will be helpful for its future deployment aiming at rural and remote electrification. [ABSTRACT FROM AUTHOR]

This paper presents a flexible-reliable operation strategy for clean microgrids (MGs) consisting of power sources, energy storage systems (ESSs), and responsive loads. The proposed strategy attempts to provide the minimum expected operating cost for the MG, power sources, predicted pollutant emission, and expected energy not-supplied (EENS) because of an N − 1 event considering different applications. The objective function of the problem is subject to several constraints including AC optimal power flow equations, flexibility and reliability boundaries, and model of power sources and active loads. The Pareto optimization based on the weighted sum method is then incorporated to obtain a single-objective model. Probabilistic programming is also used to model the uncertainties of load, renewable energy, electrical energy price, and MG equipment accessibility. The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. A standard MG is employed to test the proposed strategy and indicate its capability in enhancing technical and economic indicators of the MG while ensuring that the MG is clean. [ABSTRACT FROM AUTHOR]

Summary.Aiming at the problems of insufficient scalability and slow response speed of the traditional three-layer control structure based on the time scale, this study proposes a distributed two-layer control structure. The primary control uses traditional power-frequency droop control, and the second-level control adopts a consensus protocol to simultaneously achieve the goals of frequency synchronization, frequency non-difference, and power optimization in a distributed manner, which can effectively improve the performance of microgrid frequency adjustment and power optimization. The cyber layer of the AC microgrid cyber-physical system (CPS) is extremely vulnerable to denial-of-service (DoS) attacks, resulting in the inability to achieve control objectives. For this reason, this paper designs a consensus algorithm based on event-triggered and a predictive compensation control link that combines empirical mode decomposition (EMD) and extreme learning machine (ELM) on the basis of the two-layer control structure. Finally, a 4-node islanded microgrid simulation example is used to verify the effectiveness of the proposed strategy. The simulation results show that the two-layer control strategy can achieve microgrid frequency recovery and power optimization while effectively responding to different degrees of DoS attacks. [ABSTRACT FROM AUTHOR]

In this paper, virtual inertia control (VIC) is suggested to increase the frequency stability in islanded microgrid (MG) clusters. The aim of the suggested control method is to improve damping characteristic of MG clusters including different distributed generations (DGs). The optimal/robust values of the VIC parameters are tuned by a μ-synthesis robust control method. The proposed robust/optimal VIC-based control method is confirmed by various scenarios. Computer simulation and hardware-in-the-loop (HIL) tests are used to show the effectiveness of the suggested method in increasing the damping of the power system. Clearly, different characteristics of the dynamic responses and the results show the practicality of the suggested robust VIC. [ABSTRACT FROM AUTHOR]

Time delays are enforced into the LFC system of microgrid (MG) while transmitting the control signals from the central controller and also aggregating the controllable loads of Demand Side Response (DSR). Due to these delays, the system dynamic performance gets affected leading to system instability. The time delays may be fixed or time varying. In this paper, a cyber physical microgrid is modeled with Dynamic Demand Control (DDC) loop including time delays, and the stability of the proposed model is analyzed both for fixed and time varying delays. The impact of fixed time delays on the stability of the proposed microgrid is theoretically evaluated using Frequency Sweeping Technique (FST). To examine the delay dependent stability of the proposed system with time varying delays, including external load perturbations, a matrix stability criterion is formulated and analyzed. The novelty of the method lies in the modelling of LFC with structured load perturbations and also investigating its impact on the stability of LFC using frequency domain approach. Since the effect of load perturbations is considered for the analysis, a more realistic operating condition can be portrayed in a microgrid system. The inclusion of DDC load in LFC of the microgrid provides better transient response even with larger time delays. The accuracy of the proposed method is verified through simulation results. [ABSTRACT FROM AUTHOR]

Linking AC and DC microgrids via a bidirectional AC-DC interfacing converter has emerged the hybrid AC-DC microgrid. The DC bus is connected to the grid by a series converter to mitigate the grid voltage's power quality problems. To enhance the reliability and to increase transferring active and nonactive powers between DC and AC main buses, the AC-DC bidirectional interfacing converters are connected in parallel. In this paper, the optimal number (n) of parallel-connected bidirectional interfacing converters is obtained to minimize the annual cost of investment and the reliability cost. A two-step deciding algorithm is proposed to find n. First, active and nonactive powers between DC and AC buses are obtained with power quality and power flow considerations. Based on two types of powers, two reliability indices are calculated, including the expected energy shortage (EES) based on active power and the expected Volt-Amps shortage (EVAS) based on nonactive power. The sum of two reliability index costs is considered as the reliability cost. Next, a decision-making strategy is executed to determine the optimal n by making a trade-off between minimization of two objectives: the annual cost of investment and the reliability cost. The simulations of a grid-tied hybrid AC-DC microgrid are done with the experimental measurement data of DC and AC loads and distributed generations. Simulation results verify the performance of the represented approach. [ABSTRACT FROM AUTHOR]

Deployment of DC Electric Spring (DCES) technology is an innovative demand side management (DSM) program that helps to mitigate voltage interruptions. Conventional control strategy uses proportional-integral controllers to regulate DC spring parameters. As PI controllers have a trade-off between settling time and peak overshoot, they may not be able to achieve the desired dynamic performance under varying DC microgrid (DCMG) conditions. In this regard, this paper proposes an inverted zero compensator for the control of shunt DCES (ShDCES) in DCMG. This controller regulates the ShDCES current and terminal voltage under all operating conditions with reduced settling time and peak overshoot. A power management algorithm is also proposed to optimize the operation of ShDCES under the presence of varying PV generation and critical and noncritical loads. A detailed mathematical analysis of ShDCES and inverted zero compensator design are furthermore incorporated to validate the strategy. The simulation of the proposed method is performed in MATLAB/Simulink environment. The comparison analysis with the conventional controller proves the effectiveness of the new controller. The results are also validated using real-time simulator OP4510RTS. [ABSTRACT FROM AUTHOR]

Multiple DC subgrids in close proximity can be connected to form a DC microgrid. The interconnected DC subgrids enhance reliability and efficient utilization of resources. In this paper, a novel coordinated power management strategy is proposed for interconnected subgrids of a DC microgrid. Each DC subgrid has PV and battery units. The proposed strategy is implemented on interlinking bidirectional converters (IBCs). The strategy considers the state-of-charge (SoC) and charging/discharging current of the batteries for SoC balancing-based power sharing through IBCs. A fuzzy logic controller is implemented to decide the amount of power flow through the IBCs from SoC and the charging/discharging current of battery units. Moreover, with the coordinated strategy, a high SoC battery takes more loads compared to a lower SoC battery. The proposed strategy supports fast charging and fast discharging of batteries depending on the SoC level. In addition, the coordinated strategy can seamlessly transfer the control of IBC from the power regulating mode to the voltage regulating mode without any additional control scheme during an outage of the battery unit. The feasibility of the proposed strategy is validated through simulation in MATLAB/Simulink and OPAL-RT real-time digital simulator. [ABSTRACT FROM AUTHOR]

Small-scale islanded microgrid technology has the potential to utilize renewable sources for electrification in extreme areas where conventional transmission of power is difficult. But due to the absence of a utility grid in the islanded operation, voltage and frequency control becomes the major concern. Instead of using a centralized large battery storage system, electric vehicle- (EV-) based distributed energy storage may provide a dynamic and much cheaper energy storage solution for small-scale systems in the long run. The only issue is to effectively manage the dynamics of EV penetration for achieving the overall control in the islanded system. To address the same issue, this paper proposes a novel segregation-based inverter control structure for an islanded microgrid while employing EVs as an energy storage system, thus eliminating the need for centralized storage. The designed integrated control structure simultaneously attends to the voltage and frequency regulation need of the system, overcoming the issue of control lag, along with energy storage and management aspects in the microgrid operation for controlling the power flow under various practical scenarios. Extensive experimental studies are performed in MATLAB/SIMULINK environment, which indicates that the proposed integrated control structure gives a satisfactory performance under various scenarios encompassing load variation, renewable energy uncertainties, and EV dynamics in comparison with conventional control schemes employed in the islanded microgrid. [ABSTRACT FROM AUTHOR]

Recently, increasing the number and severity of the natural hazards requires the resilience assessment and enhancement of the power system, especially the microgrid system. The emergency distribution generations have great potential to enhance the resilience of microgrid against blackouts under the emergency environment. This paper investigates the resilience assessment of the microgrid system under natural hazard, where emergency distribution generations are firstly pre-positioned on system nodes and then reconfigured after system damage occurs. A new resilience metric index and an efficient approximation computation method are provided for the resilience assessment of the focused problem. A new pre-position strategy and a new reconfiguration strategy on emergency distribution generations are proposed for the microgrid system emergency restoration under natural hazard. Also, a framework of resilience assessment is provided for problem-solving. The results of extensive experiments on the modified IEEE 30-Bus system and modified IEEE 118-Bus system confirm the effectiveness of the resilience assessment methodology and the superiority of proposed restoration strategies. [ABSTRACT FROM AUTHOR]

In this paper, two (series and parallel versions) quasi Z source inverter (qZSI)-based multioutput series-parallel topologies capable of supplying multiple three-phase AC and single boost DC outputs simultaneously are presented. The proposed parallel version topology can supply n number of AC outputs along with one boost DC with constant voltage and variable current. Similarly, the series version topology can give n number of AC including one boost DC output with constant current and variable voltage. The outputs of the proposed topologies can feed directly to DC/AC microgrids and multiple residential loads simultaneously without using any extra adapter/regulator and thereby avoiding local power conversion to meet the load demand. A hybrid pulse width modulation technique with constant frequency is used to operate the proposed topologies. The performance of the proposed topologies is verified by developing the prototypes of 2.18 kW (for parallel version) and 2.02 kW (for series version) for two three-phase AC outputs and one boost DC output. The developed prototypes show measured efficiency of 90.01% for the parallel and 89.95% for the series version topology. [ABSTRACT FROM AUTHOR]

This paper proposes an iterative approach to adjust the control parameters of multiple power converters within a microgrid, which operates in grid-connected and grid-islanded modes. The adequate control parameters are determined using an optimisation-based strategy, local measurements, and results obtained in previous algorithm iterations. The proposed objective function is based on the integral time-weighted absolute error (ITAE), modified to improve the microgrid control performance. The proposed approach addresses the control tuning complexity by considering an incremental strategy, starting from adjusting basic microgrids, continuing to the setting of intermediate microgrids, and finalising when the target microgrid control is fine adjusted. The results obtained at the CIGRE LV benchmark microgrid validate the proposal, obtaining during faults, the maximum deviations from rated frequency around 2.2% and 0.3% in grid-islanded or grid-connected cases, respectively. Also, voltage and power references are adequately followed during steady-state regardless of the microgrid operation mode, where the steady voltage profile is below 10% variation. The obtained results demonstrate the proposed approach advantages, which straightforwardly adjust multiple converters integrated into a microgrid. The main contributions are as follows: (a) the microgrid model is not required, and (b) only measurements at the point of common coupling of the distributed energy resource are used; consequently, the proposed tuning approach is especially applicable to complex microgrids. Finally, finely adjusted microgrids are required for further operation or protection studies where complex system configurations are commonly required. [ABSTRACT FROM AUTHOR]

In this paper, two (series and parallel versions) quasi Z source inverter (qZSI)-based multioutput series-parallel topologies capable of supplying multiple three-phase AC and single boost DC outputs simultaneously are presented. The proposed parallel version topology can supply n number of AC outputs along with one boost DC with constant voltage and variable current. Similarly, the series version topology can give n number of AC including one boost DC output with constant current and variable voltage. The outputs of the proposed topologies can feed directly to DC/AC microgrids and multiple residential loads simultaneously without using any extra adapter/regulator and thereby avoiding local power conversion to meet the load demand. A hybrid pulse width modulation technique with constant frequency is used to operate the proposed topologies. The performance of the proposed topologies is verified by developing the prototypes of 2.18 kW (for parallel version) and 2.02 kW (for series version) for two three-phase AC outputs and one boost DC output. The developed prototypes show measured efficiency of 90.01% for the parallel and 89.95% for the series version topology. [ABSTRACT FROM AUTHOR]

The usage rate of electric vehicles (EVs) is gradually increasing. Recharging of EVs should be carried out repeatedly over time, and the energy needed for this is high and increasing. With the present infrastructure, we cannot supply the required energy, and therefore, we need to implement a model that expands the power grid to satisfy our energy requirements. This paper proposes a convolutional neural network-based dynamic capacity expansion (CNN-DCE) for EV charging. Flower pollination optimization algorithm (FPOA) was used to improve the hyperparameters of CNN during training. The main aim is to reduce the cost of installing additional capacity resources and to reduce the operational cost. To cope with the load growth, different capacity resources are installed at different years of the planning boundary. Five statistical indices, such as mean squared error, mean absolute error, correlation coefficient, and scatter index, are used to evaluate the performance of CNN. The capacity expansion plan in the microgrid is achieved by expanding the energy of battery energy storage systems, microturbines, and solar and wind energy systems. The queuing delay for the EVs waiting in a queue for recharging has been considered. The performance of the proposed CNN-DCE is studied and compared with three other state-of-the-art methods. The results show that the resources reduce the planning cost to 26% for the short-term planning horizon, the long-term plan has 150% of the expansion, and the wind energy system covers 48% of the expansion cost. [ABSTRACT FROM AUTHOR]

This paper presents a new control scheme that permits flexible power sharing between parallel inverters connected to microgrid operating in an island mode. The presented scheme processes the information of active and reactive output powers from all inverters in a central controller that calculates the set points for each inverter, based on the desired ratios of their output powers. These necessitate adjustment of the inverters' terminal voltages (phase and magnitude) relative to the voltage at the common AC bus. The proposed power-sharing scheme uses a robust low bandwidth-based sharing communication to achieve precision and fast dynamic response, minimum circulating current between parallel inverters, and adapting to changes in line impedance, even under information transfer delays. The presented power-sharing scheme has been validated using MATLAB/Simulink simulation and experimental results obtained from a prototype of three three-phase parallel inverters connected to a number of loads. The results emphasize the superiority of the proposed topology performance under different loads (25% to 100%), line impedances, grid conditions, and communication delay. [ABSTRACT FROM AUTHOR]

In this paper, two (series and parallel versions) quasi Z source inverter (qZSI)-based multioutput series-parallel topologies capable of supplying multiple three-phase AC and single boost DC outputs simultaneously are presented. The proposed parallel version topology can supply n number of AC outputs along with one boost DC with constant voltage and variable current. Similarly, the series version topology can give n number of AC including one boost DC output with constant current and variable voltage. The outputs of the proposed topologies can feed directly to DC/AC microgrids and multiple residential loads simultaneously without using any extra adapter/regulator and thereby avoiding local power conversion to meet the load demand. A hybrid pulse width modulation technique with constant frequency is used to operate the proposed topologies. The performance of the proposed topologies is verified by developing the prototypes of 2.18 kW (for parallel version) and 2.02 kW (for series version) for two three-phase AC outputs and one boost DC output. The developed prototypes show measured efficiency of 90.01% for the parallel and 89.95% for the series version topology. [ABSTRACT FROM AUTHOR]

In this paper, two (series and parallel versions) quasi Z source inverter (qZSI)-based multioutput series-parallel topologies capable of supplying multiple three-phase AC and single boost DC outputs simultaneously are presented. The proposed parallel version topology can supply n number of AC outputs along with one boost DC with constant voltage and variable current. Similarly, the series version topology can give n number of AC including one boost DC output with constant current and variable voltage. The outputs of the proposed topologies can feed directly to DC/AC microgrids and multiple residential loads simultaneously without using any extra adapter/regulator and thereby avoiding local power conversion to meet the load demand. A hybrid pulse width modulation technique with constant frequency is used to operate the proposed topologies. The performance of the proposed topologies is verified by developing the prototypes of 2.18 kW (for parallel version) and 2.02 kW (for series version) for two three-phase AC outputs and one boost DC output. The developed prototypes show measured efficiency of 90.01% for the parallel and 89.95% for the series version topology. [ABSTRACT FROM AUTHOR]

In this paper, two (series and parallel versions) quasi Z source inverter (qZSI)-based multioutput series-parallel topologies capable of supplying multiple three-phase AC and single boost DC outputs simultaneously are presented. The proposed parallel version topology can supply n number of AC outputs along with one boost DC with constant voltage and variable current. Similarly, the series version topology can give n number of AC including one boost DC output with constant current and variable voltage. The outputs of the proposed topologies can feed directly to DC/AC microgrids and multiple residential loads simultaneously without using any extra adapter/regulator and thereby avoiding local power conversion to meet the load demand. A hybrid pulse width modulation technique with constant frequency is used to operate the proposed topologies. The performance of the proposed topologies is verified by developing the prototypes of 2.18 kW (for parallel version) and 2.02 kW (for series version) for two three-phase AC outputs and one boost DC output. The developed prototypes show measured efficiency of 90.01% for the parallel and 89.95% for the series version topology. [ABSTRACT FROM AUTHOR]