Optimization of Solar-Wind-Battery Energy Storage Systems in a Large Scale Networked Microgrids for the Minimization of Overall Grid Cost Using Improved Butterfly Optimizer
Raja Dhanavath, Satish Kumar Injeti and Busi Rambabu
In order to maximise energy extraction, it is essential to incorporate nontraditional energy sources into the power grid. The implementation of wind turbines, Solar Photo Voltaic (PV) systems, micro-turbines (MT), storage systems, and associated technologies will revolutionise the provision of energy. This study estimates the total grid cost of the electricity system on an hourly basis over the course of one year, considering the variations in electricity demand, solar and wind energy generation, and grid prices. This paper presents an optimal method for designing and organising photovoltaic (PV), wind turbine (WT), and battery energy storage systems (BESS) in a networked environment. The Butterfly Optimisation algorithm (BOA) and Chaotic Velocity Bidirectional Butterfly Optimisation Algorithm with Adaptive Control Strategy (CVBBOA-ACS) algorithms are efficient optimisation techniques employed to minimise total cost of the grid when operating in networked mode. The proposed methodology is validated by conducting experiments on a benchmark test system consisting of four separate Microgrids (MGs) that are interconnected. The load flow analysis is performed using the MATPOWER/MATLAB framework. The study offers a thorough examination of the acquired data and the simulation results demonstrate that the CVBBOA-ACS algorithm is exceptionally efficient in minimising the overall cost of the grid.
Keywords: networked microgrids, Battery Energy Storage Systems (BESS); Butterfly Optimization algorithm (BOA); Distributed Energy Resources (DERs); Chaotic Velocity Bidirectional Butterfly Optimization Algorithm (CVBBOA); Distributed Energy Resources (DER)