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Summary: Microgrid is a new era in the power system and it has more scope of investigation on research. Due to an increase in demand and future expansion of the power system, analyzing the complexities of the network becomes a challenging task. Artificial intelligence plays a vital role in resolving such issues in a microgrid in various aspects. Owing to the rapid growth of periodical update in computational cost reduction, enhanced data analysis‐based algorithm artificial intelligence enters into new epoch Artificial Intelligence AI 2.0. Based on such approach, machine learning has been evolved as AI 2.0 initially. Now, it develops branches like deep learning, reinforcement learning, and a combination of both deep reinforcement learning algorithms. These algorithms are precise to attain higher priority in decision‐making under a complex network. This paper deals with numerous challenges of the above algorithm to state the significance of AI 2.0 and summarization of their application toward microgrid is useful to analyze the power system. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces a unique simulation framework for testing and validating multiple operation issues of grid connected microgrids. The framework is widely adjustable and enables various control actions, for example, load shedding, demand response, power curtailment, and integration of battery energy storage systems (BESS). The microgrid operation framework runs several algorithms, providing data for the optimization of the actors at different time scales. In the first part of the paper, the framework, three predictor algorithms, and the network topology used for the tests are presented in detail. Balancing power requirements of microgrids are dominantly determined by uncertainties of intermittent renewable energy‐based generation and changes in consumption. Beyond the environment development, the aim of the present research is to quantify the temporal change of balancing needs between certain confidence intervals. Accordingly, in the second part of the paper, possible approaches to determine the balancing power needs are presented, including the stochastic approach of the new System Operation Guideline (SO GL). The last part of the paper presents error characteristics of the predictor algorithms and balancing power needs are calculated in the context of the European balancing market terminology. Daily and seasonal temporality of errors is examined. The authors recognized that in transition to a more flexible distribution grid operation, the importance of possible microgrid market value propositions is increasingly appreciated. Future research perspectives include physical demonstration and validation of possible ancillary service strategy planning for microgrids. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a control scheme to reduce the circulating current in parallel inverters of autonomous microgrid. The proposed scheme is based on adaptive modulation index, which is generated by a controller operating along with conventional voltage‐current‐droop controller. Three‐phase inverters are connected in parallel for increased power capability and reliability. These paralleled inverters share common load in a desired ratio with the help of droop controller. One of the operational challenges in paralleled inverter system is that of circulating current which causes power loss, decreased efficiency, current distortion and reduced life. In order to reduce the circulating current, the reference modulation index is adjusted adaptively through an independent controller. The original modulation index is revised by making proportional adjustment toward voltage and current drop errors. This way, the proposed controller works independently and does not affect the performance of conventional droop controller. The design procedure for the proposed controller based on system modeling is also presented in the paper. The effectiveness of proposed controller is verified through simulation and experimental validation. A comparison of performance with a recently published PID‐based coordinated controller is also presented. The results establish the superiority of proposed scheme for balanced, unbalanced and nonlinear load conditions. [ABSTRACT FROM AUTHOR]

Summary: Arguably, the most important challenge nowadays in the energy industry is the utilization of intermittent renewable energy sources. On the one hand, renewable sources are the future in terms of sustainability. While on the other hand, several questions remain unanswered in connection with their day‐to‐day operation and system integration. Creating microgrids with local control of the distributed energy resources seems to offer solutions but there is a lack of practical experience. Especially in Europe, where a microgrid with islanding capability is connected to a widespread, synchronously operating grid, it is a complicated task, owing to the control methods. In this paper, the technical possibilities are presented, which are necessary to allow island mode operation of a microgrid. The case study discusses a "living lab" in which several energy generation technologies have been deployed thus it is a good representation of future renewable‐based microgrids. To support the island operation, numerical calculations and simulations are used to determine power and energy needs of necessary flexibility measures. Basis of the calculations is the year‐long data measured on‐site. Sizing and operation modes for energy storage and demand‐side resources and an architectural scheme are presented. Net present value for all technological options are compared to aid the selection of the best option. A sensitivity analysis is also performed to assess how potential change in various parameters of the economical calculation affect the results. It is shown that provision of uninterruptible power supply and thus island operation of the site can be provided within reasonable techno‐economical limits. [ABSTRACT FROM AUTHOR]

Summary: The installation of an energy storage system (ESS) is vital for the Micrgorid (MG) islanded operation to ensure the maintenance of demand–supply balance. Lithium‐ion batteries (LIBs) are among the most commonly used ESS technologies for grid‐based applications, which is used in this paper to constantly maintain the demand–supply balance in a residential MG. For this purpose, a novel frequency‐based energy management scheme is proposed. It uses an LIB ESS to handle the primary frequency control and energy management during peak‐load period, while the dispatchable distributed generators like microturbine and fuel cell supply the base load. The air‐conditioning TCLs consume a significant part of the residential load profile, especially during mid‐summer. Unlike TCLs that instantaneously use their generated cooling thermal energy to control indoor temperatures, the thermal energy storage systems (TESSs) can also store the thermal energy and use it later. In this paper, the TESSs are used instead of TCLs to reduce the power consumption of a residential Microgrid (MG) in islanded mode. By doing this, the required LIBESSs capacity is decreased 70% considerably than the case the TCLs are used for controlling the indoor temperatures. Also, replacing the ACs and EHPs with TESSs results in a 63.7% reduction in the total cost of electrical and thermal storage. [ABSTRACT FROM AUTHOR]

This paper endeavours a control scheme for optimal control of voltage and frequency of power inverter which relied upon distributed generation in cognitive microgrid using soft computational methods. It gives sound direction on how to control the active power flow, voltage‐frequency regulation, and sharing of power among various components of MG. The classical voltage–frequency control strategy in parallel with the modern control method is well excavated in the present paper. Moreover, modulation techniques, variants of reference frames, power quality indices are covered blatantly. Thus, the paper gives fast insight and understanding to the engineers working in this niche area. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a prediction‐based optimization strategy (POS) for the Energy Management System to balance the use of diesel generator (DG) and emergency battery (EB) in the microgrid. The POS is developed by combing two operating strategies, the "predictive analysis" and "optimal operation" in each scheduling period for the microgrid. Based on the predicted microgrid state and energy demand, a multi‐objective mixed‐integer nonlinear programming model (MOMINP) is constructed to minimize the fuel consumption and the regularization of battery charge/discharge subject to the practical constraints in the microgrid. This paper proposes a detailed scheme to deal with the multiple objectives and nonlinear constraints in the MOMINP, then the MOMINP is successfully converted into a mixed‐integer linear programming model (MILP). And an adjustment strategy is designed to obtain the near‐optimal solution of the MOMINP based on the optimal solution of the MILP solved by using the CPLEX Optimizer. Experimental results show that in a basic scheduling period, the working time of DG in the POS‐softmax regression strategy is shorter than the current operation, and the fuel consumption reduction ratio is about 15.3% with the same battery SoC value at the end of the scheduling. At the same time, the fuel consumption in the POS‐accurate prediction strategy can be reduced by up to 54.9% compared with the POS‐softmax regression strategy and can be reduced by 61.8% compared to the current operation. Based on the comparative analysis of the actual case data of a micro‐grid in 6 months, it can be seen that on average the POS works better than the current operation, with an approximately 23.6% decrease in the objective function and an additional 16.2% decrease with an accurate prediction. [ABSTRACT FROM AUTHOR]

A number of recent or novel metaheuristic algorithms have been explored in the subject of optimization; although now not all of these algorithms are as efficient as their creators claim, a few have been confirmed to be a pretty efficient and useful tool for addressing complex optimization problems. On the other aspect, LINGO is a software tool used for linear, nonlinear, optimization problems. This paper's objective is to study how well the LINGO optimizer performs as contrasted to metaheuristic optimization strategies for over current relay coordination. The operation of directional over current relay is demonstrated with the applicability of LINGO optimizer and metaheuristic strategies. In this study, two distinct case studies, which include a mixed overhead line‐underground cable and a DER primarily based IEC microgrid benchmark, are tested for comparative evaluation among the LINGO optimizer and metaheuristic strategies. During the first stage of case study I, the crow search algorithm (CSA), a novel metaheuristic technique, was proposed, and its results are contrasted with the most popular conventional techniques: Particle swarm optimization (PSO) and water cycle algorithm (WCA). It reveals that implementing the proposed CSA algorithms improved over all time setting concerning the most common traditional techniques such as PSO and WCA. And, after implementing the LINGO optimizer, it is proven that compared with other metaheuristic optimization techniques, the second one proposed LINGO optimizer provides advanced consequences. In a similar manner, both proposed methods were applied and determined their performances in case study II and once more LINGO proved its strength over the metaheuristic approach. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces an optimal voltage control (OVC) framework for islanded microgrids (MGs) as a unified hierarchical control scheme, started from bus voltage set‐points optimization at tertiary level, then effectively followed by secondary control, which controls the distributed energy resources via their primary level controllers. The distributed control structure is proposed here for both tertiary and secondary levels to benefit from higher reliability, avoidance of a single point of failure, and a relatively simple communication system. At the tertiary level, a new distributed voltage protocol, based on the Lyapunov theory, is proposed to optimize power losses and voltage profile deviations in the MG. The obtained optimal voltage references are passed to the secondary level, in which a modified distributed protocol (MDP) is utilized to ensure the OVC and dynamic stability. In addition, the proposed MDP can maintain the critical bus voltage against load changes until the next optimal set‐point updates. The performance of the MDP is examined for different scenarios such as load changes and DGs plug and play operation in the MATLAB/Simulink environment. [ABSTRACT FROM AUTHOR]

Summary: This paper is concerned with the two‐stage hierarchical control of microgrids (MG) that can operate in both grid‐connected and off‐grid modes. The procedure consists in the segmentation of the control scheme in the primary and secondary levels, thus enabling the application of faster and slower dynamics according to the process. A decentralized droop control‐based method is used in the primary level, while a distributed multi‐agent coordination scheme is applied in the secondary one. The multi‐agent system is run on Python Agent DEvelopment (PADE) environment, a FIPA‐compliant agent framework. The key contributions this paper provides are the control strategies of reactive power output of non‐dispatchable sources, dynamic sharing of energy storage systems, and the management of loads of microgrids, all of them based on multi‐agent system. Co‐simulations using PSCADTM and PADE are performed considering several operating scenarios of the MG resources under different load conditions. Simulation results validate the accurate performance of the proposed control strategies. [ABSTRACT FROM AUTHOR]

Summary: The supercapacitors (SCs) are suitable for short‐term fast power regulations, while the batteries are suitable for long‐term slow energy management of microgrid (MG). As SCs and batteries complement each other's deficiencies, the SC‐battery hybrid energy storage systems (SBHESS) have been commonly used for mixed applications of fast transient and slow long‐term power regulations. The SC reduces the stress of fast power variations on the battery, which prolongs its lifetime. However, it increases the cost of the energy storage in comparison to the case that battery is just used. Therefore, the drawback of SBHESS is its increased cost. The sizes of SC and its converter, which directly determine their costs, should be enough to handle primary frequency control (PFC) in the worst cases of shortage and surplus power generation that the MG ever experiences. In this paper, the potentials of Photovoltaic (PV) systems, smart LED lighting loads (SLEDLLs), and thermostatically controlled loads (TCLs) in PFC is used to decrease the participation share of SC in the PFC and hence decrease the sizes and costs of SC, and its converter. The simulation results show that with the coordination of SBHESS, SLEDLLs, PVs, and TCLs, the required sizes of SC and its converter are decreased by 64% and 50%, respectively. Also, for a 10‐year period operation, the total cost of SC and its converter is decreased by 51.5%. [ABSTRACT FROM AUTHOR]

Summary: In battery swapping station (BSS), the battery swapping of electric vehicle (EV) is not synchronous with the centralized charging of BSS. Based on new energy electricity generation and battery swapping demand information of EVs, how to formulate charging–discharging strategies of centralized charging stations is essential in BSS energy management system. Different from traditional BSS scheduling issues, considering that the supply–demand balance of power in isolated microgrid (IMG) could be regulated by the discharging of backup batteries, a service model of EV BSS is proposed with strong constraints, coupling relationships and randomness. Because the microgrid‐BSS capacity configuration optimization issue is nonlinear and multivariable, if traditional optimization algorithms are utilized, it would take a long time and the optimal solution may not be obtained. Moreover, there is no guarantee of complete convergence even with the standard particle swarm optimization (PSO) algorithm. In this paper, the quantum behavior particle swarm optimization (QPSO) algorithm is used to handle operation control issues of BSS. As shown in case results, with the QPSO algorithm proposed, both the reliability of battery swapping service and the maximum profit of BSSs could be implemented. [ABSTRACT FROM AUTHOR]

Summary: The low voltage ride through (LVRT) capability is an important aspect of the microgrid system, dominated by renewable energy sources (RES). Earlier studies investigate the LVRT capabilities of microgrids but ignore their frequency stability during and after the fault scenario. This paper fills this gap by investigating the frequency fault ride through (FFRT) capability of photovoltaic (PV) based microgrid model and suggests a novel PI‐based virtual damping (PIVD) controller for enhancing the dynamic performance. This controller tracks the frequency error and de‐loads the solar power in the same proportion. This de‐loading creates useful virtual inertia reserve (VIR), which replaces the role of battery storage by stabilizing the grid during the contingency period. To validate the effectiveness, a microgrid assisted with the PIVD controller is simulated in MATLAB and its frequency performance is compared with pre‐existing conventional and ESS models. The comparative results confirm that the proposed model is capable of riding through the severe fault scenario, with the least possible frequency deviation. [ABSTRACT FROM AUTHOR]

Summary: Microgrids are considered a reliable option for its ability to work autonomously during the event of faults. With widespread blackout, microgrid itself may experience blackout and hence, fails to support the customers. For system operators, the selection of an appropriate black start unit and procedure is of utmost importance. A fast and reliable black start unit will reduce vulnerability in grid operation. This paper proposes a novel black start methodology for a microgrid where the appropriate Distributed Energy Resource (DER) is utilized as black start unit for the recovery at the planning phase. In order to validate the findings, the proposed methodology is implemented on an industrial microgrid. Results show that bottom‐up restoration with solar photovoltaic systems having Battery Energy Storage System (BESS) can offer fast and faithful restoration in comparison to other DER units. [ABSTRACT FROM AUTHOR]

Summary: Nowadays, microgrids are emerging as an invaluable framework for the integration of renewable energy sources and demand response programs. In such systems, energy storage facilities are also frequently deployed to properly manage surplus energy from renewable sources on pursuing more efficient management of the system. Hybrid storage systems in which various storage facilities are combined may result in a more effective solution than only considering one storage technology. This way, the good features of the different technologies may be jointly exploited while their drawbacks are minimized. Due to the large‐scale integration of renewable energies in this kind of grid, coping with uncertainties becomes a critical issue. Moreover, the operation of microgrids frequently deals with other kinds of uncertainties related to energy pricing from the upscale grid (in the case of grid‐connected mode) or local demand. This way, proper modeling of uncertainties is essential for adequately operating these systems. This paper contributes to this pool by developing a novel interval‐based formulation, for optimal scheduling of microgrids considering battery and pumped‐hydro storage systems. To achieve this goal, the optimal scheduling of a microgrid with pumped‐hydro and battery energy storage considering demand response is modeled, firstly. Then, the new interval‐based formulation is used to cope with the uncertainties. Finally, the suggested model is verified using simulations in various cases, and the results confirm the effectiveness of the novel interval‐based formulation for the optimal scheduling of microgrid with pumped‐hydro and battery energy storage under uncertainty. [ABSTRACT FROM AUTHOR]

Summary: For proper performance of protection and control systems in microgrids, an islanding event must be detected as soon as possible. In this paper, a novel algorithm is proposed to detect the microgrid operation mode using only the voltage and current samples at the relay location. This approach can be used in all microgrids with any type of source such as synchronous or inverter‐based distributed generators. An optimal method is proposed to determine the input parameters of a classification method by using local information. The goal of the optimization is to minimize the time and maximize the accuracy of microgrid connection state detection. Moreover, in the classification method, three states, that is, islanding, reconnection to the utility grid and other events are considered. The objective function of this problem is defined as the summation of the weighted time factor and detection error. The inputs of the islanding detection problem can be a large number of network parameters, such as frequency, voltage, current, power, their sequence components or rates of changes. Consequently, the variables of the classification problem are the number and the type of input parameters of the classification problem. The optimization problem is solved by using a genetic algorithm‐based, and a support vector machine is used for the classification process. In order to evaluate the validity of the proposed method, different situations are considered for the operation of the grid, and in each case, different events are simulated. The results are compared with similar methods, and the advantage of the proposed method is shown. [ABSTRACT FROM AUTHOR]

Summary: The distributed generations (DGs) of an islanded microgrids (MGs) comprises of interconnecting primary and secondary control layers. The interactions among these controllers may yield new oscillatory modes with low damping, which decrease the stability margins. As the distribution network is dynamic in nature, the maintenance of system stability is of great concern, mainly while operating in autonomous mode. This paper proposes the optimal internal model control (IMC)‐based droop control scheme to improve the small‐signal stability and transient‐response of an inverter‐based MGs (IMGs) under different operating conditions. The proposed optimal scheme is achieved with the following approach: (a) first, comprehensive small signal model is prepared for the study system, and the interaction of the control parameters which influence the system stability are investigated through eigenvalue analysis, (b) the critical values of the significant parameters of the IMC and droop controllers are sorted out, and their corresponding stability domain is formulated, (c) based on the stability domain, PSO optimization technique is employed to generate optimal values, which delivers effective coordination among the crucial control parameters to improve the stability, (d) the developed optimal control scheme is cross‐validated by comparing with the existing methods from the literature. The effectiveness of the proposed optimal scheme is subsequently assessed quantitatively with the help of time‐domain specifications. [ABSTRACT FROM AUTHOR]

Summary: "Electric vehicles (EVs) are one of the most promising technologies to green the transportation systems. However, high penetration of EVs brings heavy electricity demand to the power grid." Due to the intermittent character of renewable energy sources (RESs), it turns out to be very challenging to manage EV charging with other renewable generation and grid load. This paper aims to introduce a dispatch strategy assisted with the optimization concept for enhancing the economy of the microgrid system. The major objective is to minimize the cost of system operation and environmental control when meeting system load requirements. The output constraints related to the distributed power supply, such as power limits, are subjected to optimization. To solve this optimization issue, a new "Fitness Sorted Moth Search algorithm (FS‐MSA)" is introduced. Finally, the proposed work is compared and validated with other existing works with respect to various measures. The enhanced outcomes prove the efficacy of the implemented FS‐MSA model. This work concentrates on EV adoption integrated with RES for sustainable mobility. On observing the result, it can be noticed that the adopted scheme was 81.97%, 82.03%, 82%, and 81.97%, better than existing genetic algorithm, particle swarm optimization (PSO), moth search algorithm, and lagrange multiplier optimization (LMO) models for mean case scenario. [ABSTRACT FROM AUTHOR]

Summary: The Energy Management System (EMS) is a strong need for achieving cost‐effective, reliable, and pollution‐free operation of microgrids operating in isolated areas. Commonly, the EMS approaches use optimization and rolling‐horizon predictions. However, the inclusion of very short‐term predictions increases the complexity of the optimization, compromising its ability and reliability to operate online. In response to this problem, this paper proposes a rule‐based EMS (RB‐EMS) which uses neither optimization nor prediction horizons. Instead, the RB‐EMS evaluates historical data, and very short‐term predictions to calculate the setpoints of distributed energy resources, and schedulable loads in a cost‐effective, reliable, and sustainable manner. As a form of self‐regulation, the RB‐EMS introduces the Reliability Index to calculate the maximum state of charge of the energy storage system. Given the speed imposed by the very short‐term predictions, the RB‐EMS also introduces a start‐up manager for diesel units that present a dead time in their enlistment. The isolated ESUSCON‐HUATACONDO microgrid was used as a testbed for performance validation. The work shows a first scenario comparing the RB‐EMS against a rolling horizon EMS based on MILP optimization. A second scenario shows the energy management performance with 1 minute predictions. The better results obtained, and the computational simplicity of the RB‐EMS allows propose it to achieve faster and more reliable energy management in other isolated microgrids. [ABSTRACT FROM AUTHOR]

This paper presents a novel multi-objective energy management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads. The fluctuation of the grid tie-line power flow is regarded as one of the optimal objectives in order to decrease the power exchange between the microgrid and the main grid caused by intermittent and variable renewable resources. The uncertainty of renewable energy and loads is also considered in this paper. Stochastic optimization method is implemented for the output of renewable resources and controllable loads. Using the ε-constrained and weighted sum method, the multi-objective operation optimization problem, which includes the minimum microgrid operation costs, fluctuations of the grid tie-line power, and the risk management, is converted to a single-objective mixed-integer linear optimization problem. The scheduling is achieved for controllable units such as diesel generators, batteries, controllable loads, and grid tie-line power under various weights. The main contribution of the study is to achieve the energy management for a microgrid with regulation of the grid tie-line power fluctuations and peak shaving. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of three typical microgrid operation modes. First is the analysis of the grid-connected mode, in which the main goal is to optimize the microgrid operation (in terms of economics, carbon emissions and/or reliability) when it is connected with the main grid. Second is the analysis of the planned island mode, in which the main goal is to provide a stable and smooth transition from grid-connected to island mode while keeping both the frequency and the voltages within the required limits. Finally, the paper presents the analysis of the emergency island mode, which occurs after sudden islanding, in which the main goal is to maintain the energization of critical customers. The objectives and the operation strategies of microgrid management are different in each operation mode. This paper proposes a novel, centralized, multi-agent-based, microgrid controller architecture, which provides the coordination of all three operation modes and enables the easy configuration/combination of optimization goals that are subject to a given set of operational constraints. The microgrid controller consists of a real-time agent (responsible for closed loop control and maintenance of the system's frequency), an operation planning agent [responsible for near-term (15 minutes up to 24 hours) and short-term (1 to 7 days) optimization] and a state agent (responsible for overall monitoring, management and coordination of the other two agents). A microgrid controller with the aforementioned agents has been developed and tested. The simulation results are presented for a typical microgrid test example. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An effective hybrid strategy‐based protection scheme to differentiate between inverter faults and symmetric/unsymmetric faults on distribution line, in addition to detect and identify that faulty section in a microgrid. The proposed hybrid strategy is combined execution of principal component analysis (PCA) and nomadic people optimizer (NPO) learning process‐based gradient boosting decision tree (GBDT). Hence it is commonly named as PCA‐NPOGBDT strategy. Here, three stages are occupied using fault analysis on microgrid to differentiate among inverter faults on microgrid and symmetric/unsymmetric faults on distribution line, in addition to detect/classify that faults and recognize that faulty section. They are: data set generation, feature removal and training process. In this paper, the first procedure of the proposed strategy is the microgrid parameters such as voltage and current signals at usual and unusual condition data set preparation with PCA technique. The data set based on PCA preparation process has feature removal of the power flow parameters and describes that characteristics nature of the various signals happened with microgrid system. The removed data set is evaluated with the NPO‐based GBDT system to classify that sort of fault happened at microgrid system. The proposed model is performed at MATLAB/Simulink working stage and compared with various existing techniques. Computation time of fault detection using proposed and existing system is analyzed and likened to other existing systems like RF, DT, SVM and DBN under 100, 150, 200, 250, and 500 trails. The computation time under 100, 150, 200, 250 and 500 trails of proposed technique is 48.1740, 51.2133, 71.0483, 60.00126, and 57.80132. [ABSTRACT FROM AUTHOR]

The interruption in the power system has a substantial social and economic effect, especially during natural disasters and faults causing a massive outage. Therefore, the appropriate and fast diagnosis of the fault locations and service restoration should be conducted quickly to restore power to as many undamaged sections as possible. In this context, self‐healing service restoration can restore power systems and enhance distribution networks' resilience. This paper proposes a novel self‐healing topology to maintain the power system's balance while prioritizing the critical loads in a micro‐grid system. The micro‐grid system is operated in two different modes, which are the normal mode and self‐healing mode. In the normal mode, the energy management system (EMS) solves the economic power dispatch function to minimize the cost while satisfying the load demand. The self‐healing mode is triggered once a fault occurred in any of the distributed energy resources (DERs). This mode aims to maximize the undamaged DERs power generation to meet the total prioritized critical loads. The metaheuristic binary teaching‐learning‐based optimization (BTLBO) technique is utilized to obtain the service restoration problem's optimal switching action sequence and avoid tuning the parameters to handle the problem of premature convergence. The micro‐grid model is based on the IEEE 37 bus, where several disturbance scenarios have been simulated to evaluate the proposed self‐healing topology's performance. The results show the proposed technique outperforms traditional self‐healing methods. [ABSTRACT FROM AUTHOR]

Summary: Distributed generation is considered as a key component of the emerging microgrid (MG) concept, enabling the integration of renewable sources in a distributed network. The MG has been accepted globally as a new approach that provides a flexible, reliable, sustainable, and economical solution for green and clean power generation. Microgrid is constituted by distributed energy resources (DERs) and is a combination of parallel connection equipped with suitable control and protection scheme for the operation in both islanded and utility grid‐connected mode. Microgrid structure with various hierarchy control techniques is categorized into three layers such as primary control, secondary control, and tertiary control techniques. A comprehensive literature review of these control techniques in AC microgrid is presented. In addition, the technical challenges of existing MGs affect real‐time applications around the globe. For the development and execution of various MG topologies, suitable power strategies are adopted to integrate distributed generation (IDG), energy storage system (ESS), and consumer loads for an improved energy management system (EMS). This paper presents a state‐of‐the‐art review of recent control techniques of AC microgrids with DERs having various important aspects; hierarchical control techniques, management strategies, technical challenges, and their future trends in the system. Moreover, a comparative performance analysis of our proposed review with existing surveys of AC control techniques with their individual merits and demerits have been presented. Furthermore, this investigation of different power control techniques applied in MG is compared and classified in terms of various important features, highlighting potential advantages, and different applications. [ABSTRACT FROM AUTHOR]

Economic load dispatch (ELD) is a key issue for the economic and eco-friendly operation of smart grids. With the increasing prevalence of renewable energy generation (REG), the stochastic properties of REG are drawing increased attention in the field of microgrid ELD. In this paper, the microgrid ELD problem considering uncertain REG, namely stochastic ELD (SELD), is formulated based on the wait-and-see approach. SELD is an optimization problem constrained by stochastic variables, and the optimal solutions are also random. The model incorporates many important factors, such as the detailed generation cost characteristics of microsources that make it difficult to obtain closed-form solutions. Therefore, the efficient two-point estimate method is applied to determine means and standard deviations of optimal solutions. To solve the cost-minimization subproblem of microgrid SELD, an improved particle swarm optimization (IPSO) is also proposed. The simulation results show that the new mechanism in IPSO contributes to the optimization ability. Results also show that combined heat and power-based microsources and the electricity tariff between the upstream grid and the microgrid have a significant influence on the expected total cost. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: The vanadium redox flow battery (VRFB) has the advantages of flexible design, high safety, no cross‐contamination, long service life, environmental friendliness, and good performance. VRFB has become the best choice for large‐scale electrochemical energy storage. Renewable energy has severely restricted the development and use due to its discontinuous, unstable, and uncontrollable output power. The microgrid (MG) composed of VRFB, wind energy, and photovoltaic renewable energy is an effective solution to the random and intermittent nature of renewable energy. The work analyses the development status and existing problems of renewable energy power generation, VRFB energy storage technology, and microgrid. Without involving the development of the key components of the VRFB, research how to improve the performance of the VRFB to make it in the best operating state in the microgrid. The main contribution of this paper are to combine the application background of the microgrid to improve the overall performance of the battery from the aspects of VRFB modeling, battery structure design optimization, flow field and flow optimization, stack design, thermal treatment, and temperature characteristic distribution. Finally, this review offers insights for improving the performance of VRFBs in microgrids. Highlights: Analysis of renewable energy, energy storage technology, and microgrid framework.Systematic analysis of the problems of vanadium flow battery in microgrid.Researched how to improve the overall performance of the vanadium flow battery without developing new component materials. [ABSTRACT FROM AUTHOR]

A MicroGrid (MG) can be operated in two main situations: grid-connected mode and autonomous mode. Power electronics (PE) are required to interface the DG units with the MG. This paper presents an optimal operating strategy and cost minimization scheme for an electronically weak-coupled MG. The major objective of the paper is to minimize the overall cost considering both the power system and the power electronics constraints in the two modes of operation. The paper presents steady-state models of power electronic converter/inverter systems for coupling distributed generation (DG) units to the grid based on Newton-Raphson method. A Matlab program is developed to represent the proposed algorithm. The program is tested in various network conditions and verified by applying it to an MG with three different DG units. The main contribution of the study is to ensure that the converter constraints are satisfied for both types using DC/AC inverter and AC/AC matrix converter. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Microgrids (MGs) are known as suitable options to accommodatethe high penetration of renewable energies, like solar and wind. MGs have provided the requirements of controlling and adjusting these sources. In addition, batteries are becoming indispensable components of MGs because of their capabilities in addressing the renewable energies' power output intermittency. In MGs, the problem of smart energymanagement along with battery sizing has been introduced as the necessity to ensure the efficient use of renewable sources and decrease traditional fossil‐fuel‐based generation technology penetration level in power systems. Accordingly, a novel method is presented in this paper to effectively address the above‐mentioned requirements, utilizing the modified shuffled frog leaping algorithm (MSFLA), applied to different case studies. The results, obtained from the numerical simulation, are compared to several well‐established optimization approaches to verify the performance of MSFLA. In terms of computational efficiency and quality of the obtained solution, the MSFLA has demonstrated promising outcomes, together with superior performance in comparison with other algorithms. The results show that the presented framework, including the battery sizing, would be very beneficial to minimize the operating cost of MGs. [ABSTRACT FROM AUTHOR]

Imbalance between generation and consumption in each instant can result in frequency instability. A storage device that responds quickly to changes and is capable of energy injection or consumption in a microgrid (MG) can improve frequency stability. The Flywheel Energy Storage System (FESS) has this characteristic. In this paper, a detailed model of the FESS is presented, and its control strategies for frequency regulation are proposed and discussed. The field oriented control is used for machine-side convertor control of FESS. Two MG islanding scenarios and the performance of the proposed control strategy are studied by MATLAB/Simulink. The simulation results show good FESS performance with regard to frequency changes in the MG. [ABSTRACT FROM AUTHOR]

Objective: In microgrid (MG), besides the load perturbation, volatile nature in renewable output power along with energy storage system and inertia uncertainties cause large frequency deviations which may weaken the MG and could lead to complete blackout. Therefore, MG requires an intelligent, efficient and robust control method. Methods: In response to this challenge, this paper proposes a novel fuzzy logic approach (FLA) tuned multistage PID controller for frequency control of an islanded MG in the presence of high renewable penetration. The proposed controller is intended for principal parameter tuning of multistage PID controller under critical operating conditions as mentioned in the objective. Results: The real‐time MG test system is considered to present the simulation results. The test system is modelled in Matlab/Simulink. The results are carried out under different operating scenarios and the performances of the proposed technique are compared with various existing techniques in the literature. Conclusions: The simulation outcomes divulge that the proposed controller is more superior in improving the frequency dynamics of the MG (in terms of settling time, overshoot and error reduction) under various disturbance conditions. Furthermore, the proposed controller is more robust to renewable and energy storage system uncertainties in MG and less sensitive to MG parametric variations as compared to other controllers in literature. [ABSTRACT FROM AUTHOR]

Summary: Microgrids (MGs) can operate in two modes: grid‐connected and islanded. Islanding can be scheduled or unintentional. MG should be able to maintain its stability in case of unintentional islanding. Therefore, it is necessary to provide the required spinning reserve for stable islanding. In this paper, a two‐stage scheduling strategy is proposed to determine the required reserve for stable islanding by considering uncertainties of load and renewable generations. The proposed strategy uses advantages of the load as a reserve provider to compensate the deficiency of DGs and batteries in providing the required reserve. A novel objective function is proposed to determine the optimal amount of demand which considered as reserve. The objective function minimizes the sum of reserve preparation costs, expected cost of calling load reserve, and expected cost of emergency load curtailment. Another significant feature of the proposed model is its modularity that enables the model to be integrated with any other scheduling model. The effectiveness of the proposed model is evaluated by mathematical analysis and numerical simulations. [ABSTRACT FROM AUTHOR]

If sensitive loads are connected to the point of common coupling (PCC), compensation should be carried out in order to reduce PCC voltage harmonics. In this case, compensation is performed by the interface converters of distributed generation (DG) units. In this paper, a novel method is proposed for voltage harmonics compensation in islanded microgrids. The proposed method is capable of adjusting compensation percentage in proportion to the existing level of distortion at PCC. Also, this controller provides a proper sharing of compensation workload, considering the nominal capacity of DGs, which will improve the sharing of nonlinear load. Also, to decrease the asymmetry among phase impedances of microgrid, a novel structure is proposed to generate virtual impedance. At fundamental frequency, the proposed structure for the virtual impedance improves the control of the fundamental component of the power, and at harmonic frequencies, it acts to adaptively improve nonlinear load sharing among DG units. In the structures of the proposed harmonics compensator and the proposed virtual impedance, a self-tuning filter is used for separating the fundamental component from the harmonic components. This self-tuning filter decreases the number of the phase-locked loops. The simulation results in MATLAB/SIMULINK environment show the efficiency of the proposed approach in improving load sharing and decreasing voltage harmonics. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, two-level decentralized optimization power dispatch control strategies are proposed in an islanded microgrid without communication network to ensure frequency security and economic benefit. First, the secondary-level decentralized optimization control strategy is designed only by using local measurement regarding frequency deviation. It is able to implement the optimal power dispatch for all dispatchable distributed generation units in a coordinated way in order to completely restore the system frequency with minimum operation cost. Then, the first-level decentralized droop compensation control strategy is designed to implement real-time optimal power sharing among all energy storage units in order to quickly compensate large supply-demand imbalance and ensure frequency security. Moreover, the proposed control strategies are proved to be able to meet the requirements of the 'plug and play' operation in the absence of communication network. Simulation results verify the validity of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: The inflation of clean, efficient, sustainable, effective, secure, and reliable electricity demand have been triggered much interest for Microgrid (MG) at a miraculous and quickened pace. The necessity of reliability enhancement, diversity of fuel, cutback of greenhouse gases, severe weather fluctuation etc. has stimulated the inclusion of MG concept not only in utility level but also in customer and community level. Incorporation of solar photovoltaic (SPV) and thermoelectric (TE), termed as Solar photovoltaic‐thermoelectric (SPV‐TE) hybrid system is found be a very promising technique to broadening the utilization of solar spectrum and enhancing the power output effectively‐cum‐efficiently. This hybrid architecture caters electrical energy with additional thermal energy that signifies upon harnessing of solar insolation in an exceptional way. But in order to retain the voltage profile in the permissible level, MG needs storage mechanism for smoothening of renewable based power inconstancy, catering high active power significantly and dodging the long term reactive power rising. This paper illustrates the comparative analysis of three systems such as Conventional MG;TE coupled Conventional MG, and only TE coupled solar PV based MG defining the necessity of employment of energy storage system (ESS). The superiority of third system has been outlined in terms of lesser complexity in source integration, mitigating the detriment of Wind energy system (WES) and Fuel Cell Systems (FCT) integration in real life application, delivery of higher active power, and lesser reactive power absorbance over the two other systems. The studied system is modeled in MATLAB/Simulink environment and the results are presented to support, verify, and validate the analysis. [ABSTRACT FROM AUTHOR]

Multiple strategy‐based microgrid systems, consisting of several renewable energy sources (RES) with distributed storages are becoming well accepted in the context of smart grid framework. While such kind of microgrid seems to be pivotal in future energy structure, they impose numerous setbacks in the power network due to stochastic variability of distributed generations and uncertainties in load. In this paper, it has been emphasized on major challenges of microgrid for secure, automated, and competent operation. To deal with such kind of encounters, the smart modeling of microgrid assets refer to propose an efficient stochastic scaffold of using Petri nets (PNs). PNs are comprehensively used to demonstrate and investigate industrial systems activities under both discrete and continuous‐time occurrence. Hence, time‐based PNs develop more reliable option for grid penetration strategies in the realm of uncertain function for loads and RES‐integrated microgrid. This work intends to uphold such microgrid model that features unpredictability in distributed energy resources and load. The proposed model using PNs produces effective results that are described as in the category of parallel computing. With the awareness of economic green energy platform, a two‐stage microgrid model has been designed using generalized stochastic PNs (GSPN). In the first phase, scenario generations have been configured for each uncertain variable, and then modified real‐coded genetic algorithm (MRCGA) is utilized to resolve each deterministic dilemma populated from first phase. In order to replicate deliverable attributes of microgrid, reachability graph is stimulated also by useful marking to examine the complete system. [ABSTRACT FROM AUTHOR]

This paper proposes a low voltage (400 Vdc) distributed renewable energy fed DC microgrid structure for a residential system, which uses DC voltage for the electronic appliances. The distributed energy sources—solar photovoltaic (PV) and wind energy are considered as input sources. The output power from these sources is stochastic in nature. An efficient energy management and switching circuit is designed to control the power flow from the sources with a high gain DC‐DC converter as the main component. The output power regulation is achieved by means of controlling duty ratios of the switches in the proposed high gain converter through PI controller. The control algorithm effectively converts the unregulated DC power from the solar PV and wind into regulated DC for driving a DC load connected in DC‐microgrid. The energy management and switching circuits account for seamless operation of the DC microgrid under various modes when one or all the sources and loads are connected directly at the DC grid link. The designed energy management and switching circuit also ensures the power balancing in the proposed system. The proposed DC microgrid structure is simulated using MATLAB Simulink. The performance of the proposed high gain converter for the DC grid link voltage regulation is analyzed under source power variation and dynamic changes in load for various operating conditions. The proposed DC microgrid structure is validated using simulation results. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid algorithm consisting of particle swarm optimization and pattern search algorithm is proposed to evaluate and optimize the design and operation of microgrids (MGs) in combined gas and power networks. Key performance indicators (KPIs) are modeled and proposed to evaluate and assess MGs. The paper begins by proposing a comprehensive study to define KPIs, which are used to evaluate the following MG parameters: economical efficiency, reliability, environmental conservation, and power quality. Multi-objective evaluation functions are then developed by building a relationship matrix of MG and KPI components. The results are then displayed as optimized power generation percentages for each technology with values for four KPI categories: cost, quality, reliability and environmental friendliness. Two case studies are examined in this paper; both the province of Ontario and Toronto regional zone under all system parameters with varying percentage of generation via gas technology. Results indicated that the optimal scenario for both Ontario and Toronto was achieved at hybrid PSO-patern search percentage generation via gas technology with improved cost KPI and other KPIs remaining approximately constant. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In a microgrid, the islanding condition occurs when the utility circuit breaker (CB) is opened. In this case, the microgrid is disconnected from the main grid. Therefore, the islanding condition can be detected by monitoring the variables that caused the utility CB to open. In this paper, the utility CB current is measured at the grid side, and the islanding condition is detected based on a feature extracted from the measured signal before the utility CB opening. Discrete wavelet transform is used to extract the features of the measured current, and then, the artificial neural network is trained in order to detect the islanding conditions based on the extracted features. Since the disturbances of distributed generation (DG) units or fault occurrence have no effect on the measured current, the proposed method is an effective one for islanding detection in distribution networks with high penetration of DGs. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: The integration of intermittent renewable energy sources coupled with the increasing demand of electric vehicles (EVs) poses new challenges to the electrical grid. To address this, many solutions based on demand response have been presented. These solutions are typically tested only in software‐based simulations. In this paper, we present the application in hardware‐in‐the‐loop (HIL) of a recently proposed algorithm for decentralised EV charging, prediction‐based multi‐agent reinforcement learning (P‐MARL), to the problem of optimal EV residential charging under intermittent wind power and variable household baseload demands. P‐MARL is an approach that can address EV charging objectives in a demand response aware manner, to avoid peak power usage while maximising the exploitation of renewable energy sources. We first train and test our algorithm in a residential neighbourhood scenario using GridLAB‐D, a software power network simulator. Once agents learn optimal behaviour for EV charging while avoiding peak power demand in the software simulator, we port our solution to HIL while emulating the same scenario, in order to decrease the effects of agent learning on power networks. Experimental results carried out in a laboratory microgrid show that our approach makes full use of the available wind power, and smooths grid demand while charging EVs for their next day's trip, achieving a peak‐to‐average ration of 1.67, down from 2.24 in the baseline case. We also provide an analysis of the additional demand response effects observed in HIL, such as voltage drops and transients, which can impact the grid and are not observable in the GridLAB‐D software simulation. [ABSTRACT FROM AUTHOR]

In order to achieve stable operation of the microgrid under different modes, a multiple-loop feedback controller is designed in this paper using the inverter output voltage, the capacitor voltage, and the capacitor current as the feedback variable for the outer, middle, and inner loop, respectively. Control parameters are calculated by the combined method of Routh-Hurwitz criterion and pole assignment principle. The resulting external characteristic of distributed generation is that the output impedance is inductive in low frequencies and resistive in high frequencies, thus droop control among multiple inverter units in a microgrid can be achieved by means of wireless communication. The designed multiple controller can improve system stability and guarantee high quality output as well as fast dynamic response when microgrid operates in grid-connected mode. It is capable of keeping load voltage and frequency stable and facilitating power sharing among different inverter units when the microgrid operates in islanded mode. Furthermore, smooth switching between different control strategies for different operating modes is convenient with the designed controller. With a simple design, the multiple-loop controller is practical and easy to implement. Simulation results verify the reasonableness and effectiveness of this design. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper presents new design methodology and performance comparison of two hybrid fault-tolerant control (FTC) schemes applied to the regulation of the frequency and voltage amplitude of a diesel engine generator installed in a microgrid. Both of them are based on a unique combination of a model reference adaptive control (MRAC) with a proportional-integral-derivative (PID) controller and artificial intelligence techniques, i.e. artificial neural networks (ANN) and genetic algorithms (GA). Since in an islanded microgrid, the frequency of the system is determined by the shaft speed of the diesel engine (DE), while the voltage amplitude is set by the synchronous generator (SG) field voltage, therefore, two FTC systems for frequency and voltage regulation have been implemented in each proposed control scheme. The first scheme consists of an MRAC system with a PID controller tuned by a GA for controlling the speed of the DE and a classic MRAC system for controlling the voltage amplitude of the SG. In the second scheme, an MRAC system with a GA-tuned PID controller is used for the DE, and a hybrid controller in which the MRAC is combined with an ANN and a PID controller tuned by a GA is designed for the SG. The dynamic models of the microgrid components are presented in detail, and the proposed microgrid and its FTC systems are implemented and tested in the Simpower Systems of MATLAB/Simulink® simulation environment. All results indicate high effectiveness and robustness of the MRAC-based FTC schemes in both normal and emergency/faulty operations of the microgrid in comparison with a benchmark baseline controller, IEEE Type 1 AVR for the SG and a PID controlled governor for the DE. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An essential part of the smart grid development is to connect the main transmission grid with microgrids that consist of distributed generation resources. The integration of microgrids and the transmission grid not only can improve the reliability of the power system operation but also can increase the competition of the electricity market. The effective trading between microgrid agents and a distribution company (DisCo) is consistent with the direction of smart grid development. Developing effective strategy to optimally schedule energy trading between microgrid agents and the DisCo will bring benefits to all parties and promote further development of distributed clean energy. By analyzing the operation characteristics of the electricity market with the addition of microgrid agents as new market participants, this paper presents a bi-level optimization model that aims to maximize the benefits of microgrid agents and a DisCo while considering transmission loss factors from various generators, duality role of the microgrid agents who can either buy electricity from the wholesale market at volatile prices or sell electricity into the market or to its local consumers. The model presented in this paper jointly optimizes the energy schedules of the microgrid agents and the DisCo and determines the bid/offer price at which the microgrid agent buys and sells electricity from/to the DisCo. At last, simulation results are provided to demonstrate the feasibility and application of the proposed two-level optimization model. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Simulation of the power grid including numerous microgrids (MGs) with complex and detailed model (DM) is very time‐consuming. Nevertheless, these kinds of simulations are vital for power engineers and utilities to analyze the impact of dynamic interconnections among MGs and the power grid. In this paper, an electrical equivalent model (EM) including electrical components, such as an equivalent solid oxide fuel cell (SOFC) model, voltage source converter (VSC), and static load, is proposed for a fuel cell‐based MG. The parameters of the EM are estimated to behave similar to the DM of the MG in different scenarios and operating points. The parameter estimation procedure is conducted using genetic algorithm. The IEEE 9‐Bus transmission system is considered as the main grid, while the IEEE 33‐Bus distribution system is considered as the grid‐connected MG. Three SOFCs of different size and dynamic parameters are connected through VSCs to the MG. Different scenarios of active and reactive power changes are simulated, and results of the EM and DM are compared, to demonstrate the accuracy of the determined EM. [ABSTRACT FROM AUTHOR]

Summary: In most today's power systems, microgrids are connected to the network through a grid‐interface converter. In these converters, the phase‐locked loop (PLL) is the most popular technique for network synchronization. This paper investigates the dynamic performance and the stability of synchronous reference frame PLL influenced by various factors. These factors include the network‐side and microgrid‐side parameters. Similar to the effect of network‐side factors, the effect of microgrid components also plays an important role in the stability of the PLL. Given that the stability of PLL affected by microgrid‐side parameters have not been studied yet, so in this article, after a detailed analytical modeling of microgrid components (including the production power fluctuations, energy storage system, microgrid‐side loads, and controller parameters), the stability of PLL affected by different microgrid‐side parameters has been evaluated. In addition, with the aim of achieving a criterion for the assessment of PLL stability, also, based on the proposed criterion, the rate of exchanged output power is determined for the grid‐interface converter with the aim of guaranteeing the stability of PLL. [ABSTRACT FROM AUTHOR]

Summary: In recent scenario, there is abundant availability of renewable energy resources to satisfy the significant increase in residential, industrial, and commercial demand. This paper presents a novel framework to determine the preeminent size of renewable distributed generators (RDGs) by optimizing the system components such as area required for solar‐photovoltaic modules, swept area occupied by wind turbine blades, and area used by fuel cell. A microgrid with hybrid RDG (h‐RDG) is integrated in distribution system to minimize the distribution loss, substation energy requirement, and improve the voltage level of the load. The power loss minimization is formulated as a nonlinear problem and optimized by the proposed Hybrid Nelder Mead‐Particle Swarm Optimization algorithm. The microgrid location is identified by voltage stability index to improve the stability of system. Further, the system is analyzed for energy flow in different seasonal loading conditions with mixture of residential, industrial, and commercial load. The effective performance of the proposed technique is applied to standard 12‐bus, 69‐bus, and a practical Tamil Nadu (TN) 84‐bus radial distribution system (RDS) for different hybrid combinations of h‐RDG in microgrid. The result proves that the proposed method provides a simple and efficient tool for optimal and flexible use of h‐RDG in microgrid under different climatic changes by simultaneously reducing distribution energy loss and improving voltage profile. [ABSTRACT FROM AUTHOR]

Because of the growing usage of wind energy systems worldwide, more challenges in power quality and microgrid stabilization domains have emerged. In this paper, a new distributed FACTS-based green plug-switched filter capacitor (GP-SFC) filter is presented for efficient utilization of microgrid-connected wind energy systems. The primary goals are improving the energy use, stabilizing voltage dynamically, enhancing power quality, and improving the power factor at the common interface AC buses of the microgrid-connected wind system. The proposed GP-SFC topology is modelled and simulated using MATLAB/Simulink software. A dynamic multiloop error-driven controller is proposed for adjusting the pulse switching pattern of the variable speed wind turbine system. In addition to the low cost of the proposed GP-SFC filter, the results show that it can promote the use of wind energy system under load changes and temporary fault conditions. Besides, the proposed GP-SFC guarantees high-speed controllability while maintaining its capability for power factor correction and voltage support using its switched shunt capacitor. Also, the system performance with the proposed filter is compared with the system with a conventional D-STATCOM compensator. The results validate the effectiveness and robustness of the GP-SFC topology. [ABSTRACT FROM AUTHOR]

Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2-step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional-Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy-logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy-logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real-time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network. [ABSTRACT FROM AUTHOR]

This paper presents a new stochastic operation scheduling model for microgrid in day-ahead electricity market considering the forecast uncertainties of wind generations, microgrid's load, and locational marginal price of the point of common coupling, as well as the uncertainties pertaining to availability of generation units of the microgrid. The financial risk caused by these uncertainties is modeled by conditional value-at-risk criterion. The proposed approach is formulated as a risk-minimizing two-stage stochastic model based on mixed-integer linear programming framework. This model minimizes the expected scheduling cost together with the cost of financial risk. The impacts of different uncertainty sources on the model's results in both grid-connected and islanded operation modes are extensively studied. Additionally, higher effectiveness of the proposed stochastic model compared with common deterministic approach, regarding total operation cost and convergence behavior, is illustrated through an out-of-sample analysis. [ABSTRACT FROM AUTHOR]

This paper proposes a novel simulator of energy consumption patterns that allows designing demand side management (DSM) strategies without economic incentives. The simulator emulates consumers' patterns with and without installed DSM interfaces, based on both actual consumption measurements and surveys applied to the inhabitants of an existing isolated microgrid (Huatacondo, Chile) that has a particular DSM strategy without economic incentives. The simulator uses Markov chains to generate data characterizing consumption patterns without DSM and Bayesian networks for cases in which the users respond to the DSM strategy. Data obtained from the simulator are used to derive a response model of the consumers to the DSM interface, which can be included for the energy management system design. Results show that the implemented strategy can be effective and can generate savings up to 4.45% in diesel consumption for an ideal case where all the dwellings have the interface installed. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes the new concept of preplanned microgrid islanding (PMI) in the smart distribution system. PMI is a special form of controlled islanding that can be used to provide demand-side service for electrical users under the scheduled distribution operation, especially for the preventive maintenance. A simulation-based multi-objective optimization framework is developed to decide the starting time and duration of PMI. The optimization objectives include the minimization of load curtailment, operating cost, and pollutant emission. On one hand, the stochastic short-term simulation method is developed to assess the performance of candidate PMI schemes considering multiple uncertainties and optimal scheduling of microgrid operation. On the other hand, the weighted-sum approach is used to compromise the conflicting objectives according to the decision preferences of users. Furthermore, the response surface methodology is adopted to improve the efficiency of scheme selection with the help of experimental design technique and regression analysis. Finally, the effectiveness and high efficiency of the proposed method is verified in case studies. Sensitivity analysis is also performed to investigate the impact of decision preference, season scenario, and sizing alternative on optimization result. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]