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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]

The deployment of battery energy storage systems (BESS) can provide numerous benefits including increased renewable energy penetration, improvements in power quality and reliability, reduction of demand peaks, and reduced greenhouse gas (GHG) emissions. During the implementation of BESS, one of the most crucial factors is to determine the optimal size of the BESS to permit the balance between the technical characteristics of the BESS and the additional overall cost including the economic operation of the microgrid (MG). Therefore, the optimal sizing of the BESS allows the storage of sufficient power during the change of dispatch from the distributed energy resources (DERs) or in critical events such as natural disasters. The proposed framework determines the optimal size of the BESS based on forecasting the natural disasters or the outage cases, to enhance the reliability and economic operation of the MG. In this study, two stages are proposed to determine the optimal size of BESS in the MG. The first stage is the forecasting stage, which predicts the location of the outage or the faults that may occur. In the second stage, obtain the optimal size of the BESS to minimize the total operation cost for an economic operation of the MG. The teaching‐learning‐based optimization (TLBO) combined with quadratic programming (QP) is applied to solve the proposed objective formulation proposed to minimize the total operation cost of the MG. This study has been investigated in a group of customers with a single type of MG using various fault scenarios. The obtained results are compared with the state of the art. The proposed technique yields very promising results and robust performance compared with the available methods in the literature. [ABSTRACT FROM AUTHOR]

In this study, a new control of grid-connected doubly-fed induction generators (DFIGs) is introduced to attain lowvoltage ride-through capability. The grid-side converter is proposed to be a multilevel converter (MLC) controlled by conventional DC-link voltage controller. The MLC is designed and integrated into the grid-connected DFIG. The rotor-side converter is considered a two-level conventional converter controlled by the proposed virtual voltage strategy. The virtual strategy is to use the designed input control signal rather than the actual measured one during system disturbance. The system disturbance in this study is the voltage dip. The proposed virtual controller is designed to use busbar voltage during normal operation, whereas it utilizes the designed virtual voltage during wide range conditions of low grid voltages. The energy conversion system currents are increased due to voltage dip disturbances. The use of designed virtual voltage values is proposed as inputs to the controller to limit these currents at the rating values. These virtual voltages are extracted using direct-quadrature machine representation and fixed machine currents at the rated values or lower. On the basis of the proposed control concerning the virtual voltage concept, the generator currents are limited to the rated values, thereby protecting the energy conversion system during low grid voltages. Simulation results prove the validity of the proposed control scheme during extreme low voltages. [ABSTRACT FROM AUTHOR]

Hybrid micro-grid systems (HMGS) are small scale power system where the energy sources are installed to supply local customers. These systems may be considered as promising energy solution to meet the increased in energy demand and traditional sources depletion. Cost of electricity, system reliability, and environmental impacts of the system are three design criteria that must be considered in obtaining the accurate parameters of hybrid renewable energy system components. In this paper, hybrid micro-grid renewable energy system includes photovoltaic system, (PV) wind energy system, (WES) battery bank, (BB) and conventional diesel generator (DG) are proposed to meet the energy requirements in remote area, located in Red Sea called city of Bernice, Egypt, at 23° 54′ 31″ N, 35° 28′ 21″ E. Optimization of Cost of Electricity (COE), Renewable Factor (RF), and Loss of Power Supply Probability (LPSP) are main objective of the designing process of the hybrid system considered as the objective functions. Then, Multi-objective multi-verse optimization (MOMVO) algorithm is used with considering two scenarios, the first one is renewable sources and the second is renewable/diesel energy source. All the possible HMGS configurations namely: PV/battery, wind/battery, PV/wind/battery and PV/battery/diesel, wind/battery/diesel, PV/wind/battery/diesel are studied and analyzed. Moreover, one year hourly meteorological weather data for case study are recorded. Reverse osmosis desalination (ROD) is considered in conjunction with the residential load. The proposed power management strategy is used to manage the system operation when supplying the load. A linear fuzzy membership function is used for purpose of decision making. The simulation results show that MOMVO produces appropriate components size and the PV/wind/battery/diesel is the optimum configuration with values of COE = 0.2720$/KWh, LPSP = 0.1397, and RF = 92.37% at w 1 = 0.5, w 2 = 0.3, and w 3 = 0.2. Sensitivity analysis is performed to show the effect of changing system parameters on the objective functions. It is also shown that the techno-economic feasibility of using HMGS for rural electrification systems and enhance energy access. [ABSTRACT FROM AUTHOR]