Optimal Sizing of Hybrid Micro-Grid System for Rural Communities in Kaduna State Using Improved Grey Wolf Algorithm

Adunnola F. O., Airoboman A. E., Doma R. A.

Abstract


The growing interest in microgrid design, operation, and optimization has led to a significant focus on optimal sizing of microgrid components. A microgrid is a localized, small-scale power system that integrates different energy sources (renewable and/or conventional), energy storage, and loads within a defined area. It can operate in grid-connected mode or islanded(off-grid) mode. The primary goals of microgrid optimal sizing include enhancing energy efficiency, system reliability, cost-effectiveness, and sustainability. To address this, researchers have developed an improved grey wolf optimization algorithm (IGWOA) for optimal sizing of off-grid hybrid microgrid systems consisting of photovoltaic (PV), wind turbine (WT), and battery energy storage (BES). This research utilized atmospheric weather data from the Nigerian Meteorological Agency and load demand data from the Kaduna electricity distribution center to demonstrate the effectiveness of the proposed approach. The microgrid optimal sizing problem was formulated as a constrained single objective optimization problem, considering constraints such as loss of power supply probability (LPSP), power balance, generation limits, and battery state of charge (SOC) limits. Three scenarios were considered in this research. Firstly, the target allowable maximum LPSP was fixed at 25% and the optimal sizing of the hybrid microgrid components and minimizing of the cost to #112,356.4   means #170,159,791.32) per year was obtained by the algorithm. Secondly, the impact of the target allowable maximum LPSP variation was again examined, and it was discovered increase in LPSP decreases the total installed capacity of the distributed energy resources (DERs), hence minimizing the total cost. Hence, the individual installed capacities of PV, WT, and BES varies arbitrarily with increase in LPSP. Furthermore, Lastly, in order to validate the proposed strategy, a comparative analysis between the IGWOA and other four algorithms viz, Particle Swarm Optimizer (PSO); Differential Evolution (DE); Water Cycle Algorithm (WCA); and the conventional Grey Wolf Optimizer (GWO) was carried out, and the result showed the applicability of the proposed algorithm. The study provides a long-lasting solution for optimal sizing of PV, WT, and BESS hybrid microgrid design, with simulations conducted in the MATLAB Software environment. 


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