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Microgrid (MG) is not only undergoing rapid upsurge and an effective combination of distributed generations (DGs)-based renewable energy sources, but it also fulfills a significant function in upgrading grid infrastructure. It is necessary for DGs, during and after any disturbances in the voltage, to stay connected in order to enhance the voltage, most importantly guaranteeing the stability of the power system. In this present context, the behavior of the distributed generations control systems has a significant impact on the MG performance. This paper investigates the effect of different control schemes of the inverter-based DG unit on the stable operation of MG after the occurrence of faults that lead to islanding events. In this paper, an appropriate control strategy is proposed to enhance the fault ride-through of MG. Within the scope of the study, the MG consists of a conventional diesel generator and an inverter-based DG unit. The MG also contains several load types; RLC load as a static load and induction motor as a dynamic load. The MATLAB Simulink is used to model the MG and its inverter control schemes. In order to assure MG stability, the variations of the voltage and frequency are possessed as key references. Results indicate that the control strategies of the inverter have a strong influence on the stability of MG. Moreover, the MG configuration with the proposed FRT resists fault effects for longer durations and this enhances the stability. [ABSTRACT FROM AUTHOR]

Distributed generations (DGs) have been utilized in some electric power networks. Power loss reductions, voltage improvement, increasing reliability, postponement of system upgrading and environmental friendliness are some advantages of DG-unit applications. This paper presents a new optimization approach that employs a flower pollination algorithm (FPA) to determine the optimal DG-unit’s size and location in order to minimize the total system real power loss and improve the system buses voltage. The FPA is a new metaheuristic optimization technique and it is inspired by the reproduction strategy of the flow pollination process of flowering plants. To reveal the validity of the FPA algorithm, IEEE 33-bus, 69-bus and 136-bus radial distribution test systems are examined with different test cases of the objective function using the MATLAB. Furthermore, the results obtained by the proposed FPA algorithm are compared with other metaheuristic optimization techniques such as backtracking search optimization algorithm, artificial bee colony, and selection algorithm. The outcomes verify that the FPA algorithm is efficient, robust, and capable of handling mixed integer nonlinear optimization problems. [ABSTRACT FROM AUTHOR]

In this study, a probabilistic planning approach is proposed for optimally allocating different types of distributed generator (DG) (i.e. wind‐based DG, solar DG and non‐renewable DG) into a harmonic polluted distribution system so as to minimise the annual energy losses and reduce the harmonic distortions. The proposed planning methodology takes into consideration the intermittent nature of the renewable resources, load profile and the technical constraints of the system. The objective function is the total system annual power loss. The constraints include voltage limits at different buses (slack and load buses) of the system, feeder capacity, total harmonic distortion (THD) limits and maximum penetration limit of DG units. The optimisation process is achieved using the genetic algorithm optimisation method. This proposed approach has been applied to a typical rural distribution system with different scenarios including all possible combinations of distributed energy resources. The simulation results using Matlab programming environment show that significant reductions in the energy losses and THD are achieved for all the proposed scenarios. Also simulation results depict that the proposed method is robust and computationally efficient. [ABSTRACT FROM AUTHOR]