An Efficient Technique-Based Distributed Energy Management for Hybrid MG System: A Hybrid SBLA-CGO Technique
Abstract This manuscript presents an optimal energy management on microgrid (MG) connected to the grid that chooses the energy scheduling based on the proposed method. The present method is the joint implementation of the Side-Blotched Lizard Algorithm (SBLA) and the Chaos Game Optimization Algorithm (CGO) and hence it is named as SBLA-CGO method. Here, the MG system contains a photovoltaic system (PV), wind turbine (WT), battery storage (BS) and fuel cell (FC). Constantly, the necessary load demand of MG system connected to the grid is measured with SBLA method. The CGO increases the perfect match of MG with the expected load requirement. Moreover, renewable energy forecasting errors are evaluated twice by MG energy management for minimizing the control. Through the operation of MG schedule of several RES to decrease the electricity cost using the first method. Balancing the energy flow and minimize the effects of prediction errors according to the rule presented as planned power reference is second method. The main aim of the present method is evaluated with connection of fuel cost, the variation of energy per hour of the electrical grid, the cost of operation and maintenance of MG system connected to the network. According to RES, the energy demand and SOC of the storage elements are the conditions. Renewable energy system units use batteries as energy sources to allow them to operate continuously on stable and sustainable power generation. The analysis of the present method is analyzed by comparing with the other systems. The results of the comparison assess the strength of the present system and confirm their potential for solving the issues.