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Summary: Energy management of the grid connected microgrid (MG) systems with low cost using a novel hybrid algorithm is implemented in this paper. The novel proposed hybrid technique is the combined performance of both the Random Forest (RF) and Coral Reefs Optimization (CRO) algorithm and in this way it is named as RFCRO. Optimum operation of micro‐sources for decreasing the electricity production cost by hourly day‐ahead and real‐time scheduling is the main objective of the paper. The proposed hybrid technique is to manage the power flows between the energy sources and the grid. To achieve this point, demand response and minimum cost of energy are determined. This technique is involved with the mathematical optimization problems that necessitate more than one fitness function to be optimized simultaneously. By using the inputs of MG‐like wind turbine, photovoltaic array, battery, and fuel cell with corresponding cost functions, the RF is employed to predict the load demand. CRO clarifies the squirrel in optimizing the configuration of MG based on the load demand. The proposed hybrid technique is implemented in MATLAB/Simulink working platform and compared with other solution techniques like BFOANN, ALO, GOAPSNN, and RBFNN‐SSA technique. The comparison result reveals that the superiority of the proposed technique confirms its ability to solve the problem. [ABSTRACT FROM AUTHOR]

Summary: A hybrid AC/DC microgrid takes advantages of both DC and AC microgrids with distributed generation (DG) units in both the respective grids connected through a bidirectional interlinking converter (BIC). Control of hybrid AC/DC microgrid presents a significant research and engineering challenge and hence needs increased research efforts. Existing control algorithms restrict individual controllers to control only designated parameters. This paper proposes MPC‐based distributed control algorithm that will analyze grid conditions, and it would designate BIC to regulate the highest deviated parameter (AC/DC voltage or current) in all nonlinear conditions by performing multivariable optimization using variable control scheme in MPC. Other parameters would be controlled by individual controllers as per their capability. MPC being a nonlinear control technique having an excellent dynamic response and constraint inclusion feature has advantage as compared to other linear and nonlinear techniques. The performance of the proposed algorithm has been compared against other techniques and proved in MATLAB/SIMULINK simulation. [ABSTRACT FROM AUTHOR]

Summary: Provisional microgrids create by the connection of two beside microgrids to achieve economic benefits. So far, there have been many reviews on AC microgrids. However, due to the many advantages of DC microgrids, they cannot be ignored. To achieve the advantages of both AC and DC microgrids, hybrid structures were considered. The subject of controlling hybrid microgrids is relatively more complex. Due to the variable nature of the distributed generation resources, this complexity in islanding conditions is even greater than normal conditions. This paper proposes a robust frequency control for islanding provisional microgrid including hybrid AC/DC part as a master microgrid and AC conventional part as a slave microgrid. As authors are aware, there are no scientific reports for frequency control of the proposed microgrid. One of the issues affecting the performance of this controller is the choice of weighting functions. To achieve optimal controller, an algorithm is used to determine the best weighting functions according to the way the controller works, and by examining the sensitivity functions. Finally, simulations were performed to investigate the performance of the controller and the results of using this controller for this microgrid were examined. [ABSTRACT FROM AUTHOR]

Background: Positive feedback (PFB) based anti‐islanding schemes have gained wide popularity in islanding detection. However, the disturbance injected by the PFB methods can easily cause the destabilization of the grid‐connected distributed generation (DG) system. Therefore, how to effectively balance the normal operation of the grid‐connected system and the effectiveness of the islanding detection is essential. Purpose: In this study, the trade‐off design of the PFB control gain is given, where the requirements of grid‐tied control and islanding detection are simultaneously considered. Design/Method: Firstly, the small‐signal models are established to investigate the stability of a DG system in both islanded and grid‐connected mode. Meanwhile, the minimum and maximum PFB gains are obtained by root loci method, thus, the PFB gain can be accurately determined without trial and error. Additionally, the Sensitivity analysis is conducted for the DG system. Factors such as grid impedance, phase‐locked loop (PLL) bandwidth, proportional‐integral (PI) controller gains, inverter output current rating, and load quality factor are thoroughly taken in account, which provides the guideline of the PFB gain design. Finally, simulations and experiment tests are performed to confirm the theoretical analysis. Results: This paper presents a trade‐off design of the PFB control gain for a DG system from the essence of the PFB algorithm. The essence of PFB as well as the cause of the interconnected system instability are revealed. In addition, the minimum and maximum PFB gains are obtained by the stability analysis. Conclusions: A high PFB gain will contribute to the islanding detection but deteriorate the grid‐connected system stability. Further, it is found that 1) the maximum PFB gain decreases with the grid impedance increasing, 2) the increase in PLL bandwidth and the integral gain in current loop lead to a decrease in the maximum PFB gain, 3) the minimum PFB gain which reflects the islanding detection capability of the VPF scheme is not affected by the load quality factor, 4) when the inverter output current is large, a reasonable PFB gain may not be found as the islanding detection and the normal operation of the grid‐connected system cannot be balanced. [ABSTRACT FROM AUTHOR]

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 presents a comprehensive analytical study of conventional proportional‐integral‐derivative (PID) controller and fuzzy logic controller in a hybrid micro‐grid system (HMGS) for frequency stabilization. Conventional PID and fuzzy logic controllers are tuned by the competition over resources (COR) algorithm. The performance of proposed COR based fuzzy tilt‐integral‐derivative with filter (FTIDF) method is demonstrated on an interconnected HMGS. HMGS completes with variety of energy storage systems and different renewable generation sources. The system analysis is performed under number of scenarios. The scenarios include load fluctuations, variations in wind speed, and sun irradiance. The supremacy of FTIDF controller is established by comparing the results with CRO tuned conventional PID with filter (PIDF), fuzzy PIDF and fuzzy TIDF controllers. The effectiveness of the proposed system is investigated using simulation studies, which are performed using MATLAB/SIMULINK software. [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]

The recent trends toward enhancing distribution system automation and the development of microgrids are making the perspective of applying intraday reconfigurations more and more appealing. This paper formulates and applies a comprehensive rule-based approach to determine the configuration with minimum losses during time for a distribution system with time-varying load and local generation patterns. The results of the optimization carried out for successive periods are used to develop an original procedure for determining the timings of the intraday reconfiguration by taking into account the ranking of the best configurations and the persistence in time of these configurations. The objective function used depends on a parameter called cost ratio, that is, the ratio between the cost of the energy losses kilowatthour and the cost of performing a switching operation. A specific indicator (called objective assessment ratio) is introduced in order to quantify the convenience of performing intraday reconfiguration with respect to maintaining during the day the same configuration leading to the lowest daily energy losses. The results obtained on two classical test systems and on a real distribution network are included, comparing the outcomes of the proposed approach with the results obtained from other methods. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an energy management strategy of direct current (DC) microgrids (MGs) is presented. The proposed MG consists of fuel cells, batteries, and supercapacitors, along with associated DC/DC and DC/AC converters. Coordination between different sources of MG is implemented using a multi‐agent system. Multi‐agent algorithm is implemented using an open source agent building toolkit, Java Agent Development framework (JADE). The energy source components are modeled and implemented using MatLab/Simulink (power system library). The proposed energy management strategy is designed using proportional‐integral (PI) controllers, which is implemented using the JADE. Interface between MatLab/Simulink and multi‐agent system (JADE) is done with the help of MACSimJX. The proposed multi‐agent framework is presented and the interface between the JADE and MatLab/Simulink is described in details. Then, the design and implementation steps of the PI controller using JADE are presented. Simulation work is carried out, and the results show that the proposed multi‐agent‐based controller effectively coordinated with variable loads in MG. [ABSTRACT FROM AUTHOR]