Flexible and efficient microgrid energy management: a sigmoid-based optimization strategy

Abstract This paper introduces a sigmoid-based optimization for an energy management system designed for microgrids (MGs) aimed at minimizing operational costs and enhancing efficiency under real-time pricing conditions. The MG integrates renewable energy sources and battery energy storage system units, proposing an alternative approach to the droop control technique, improving the traditional methodology, and providing additional flexibility in terms of control techniques and management. Therefore, the proposed methodology involves the use of a modified hierarchical control, when the optimal power flow (OPF) incorporates the sigmoid function (SF) during real-time pricing analysis for a more efficient and adaptable management. In this context, the limitations of traditional droop control are overcome by the SF, providing a more flexible, robust, and efficient system, allowing a faster response when load demands and generation capacities are modified instantly. Finally, experimental validation and comparative analysis between the SF and traditional droop control are presented considering the optimization under real-time pricing, demonstrating the practical effectiveness of the proposed solution.