Combination of Side‐Blotched Lizard and Chaos Game Optimization based distributed energy management for microgrid system

Abstract

In the last decade, numerous energy management techniques have been presented. All of them have common objectives of minimizing the cost, PAR, and carbon emissions. In this manuscript, an optimal energy management (EM) on grid connected micro grid (MG) choosing energy scheduling with low emission and cost using hybrid technique is proposed. The proposed system is combination of Side-Blotched Lizard Algorithm (SBLA) and Chaos Game Optimization (CGO) Algorithm; thus it is called SBLA-CGO technique. The micro grid system consists of Photo-Voltaic (PV) system, Wind Turbine (WT), Battery Storage (BS), and Fuel cell (FC). The needed load demand of the grid connected MG system is continuously measured by SBLA method. Perfect combination of MG is increased via CGO along forecasted load demand circumstance. Moreover, the renewable energy (RE) predicting errors are assessed twice by micro grid EM to diminish the control. Several renewable energy source (RES) are considered by MG scheduling process to reduce the cost of electricity utilizing first method. The second method consists of balancing the power flow (PF) and reducing the effects of forecast errors according to rule given as programmed power reference. The major purpose of proposed method is assessed through the incorporation of FC, variation of hourly power of electrical network, cost of operation through preservation of system of microgrid linked to the network. According to RES, the power requirement and SOC of storage elements are the conditions. Batteries are used from source of energy to maintain and allow the units of renewable energy system to continue to operate at constant and stable power output. The proposed method is compared with other existing methods. The fitness of the proposed technique with the existing one is evaluated and the adequacy of proposed technique is 3.069. With this output results can know the advantage of proposed method and verify its effectiveness in solving the complexity.