Energy Scheduling of Isolated Microgrid with Battery Degradation Cost using Hybrid Particle Swarm Optimization with Sine Cosine Acceleration Coefficients

Abstract

The implementation of renewable generators together with a battery storage into an isolated Microgrid (MG) has become essential to minimise fuel utilization and contribute to maintain continuous supply of electricity. This paper studies the optimal set point of isolated MG units containing renewable generators, diesel generators and battery storage. The optimal energy dispatch of MG’s units is determined to supply the required load demand for a 48h horizon time. As the battery device has an important contribution in the MG, this paper proposes to implement battery degradation cost in the optimization model in addition to the fuel cost function. For this purpose, the Rainflow algorithm is used to count charging-discharging cycles and quantify the battery degradation. In addition, a Hybrid Particle Swarm Optimization with Sine Cosine Acceleration Coefficients (H-PSO-SCAC) algorithm is used to solve the defined objective function for an optimal energy management system of the isolated MG. A Weight Factor (WF) is proposed in the objective function. For the simulation tests, different values of WF are considered. The impact of WF is analysed on the algorithm behaviour, on the status of the State Of Charge (SOC) of the battery and its influence on the optimized MG cost function. The results demonstrate that the selection of an appropriate value of WF allows to the H-PSO-SCAC algorithm to achieve the best solution. In addition, with WF equals to 0.5, the charge/discharge cycles are reduced and the battery SOC is more stable.