Optimal management of microgrid energy by considering demand side management plan and maintenance cost with developed particle swarm algorithm

Abstract

This paper introduces a pioneering approach to power system optimization by integrating microgrids and demand-side management, with a focus on its novel contributions. Emphasizing cost reduction, the study targets effective demand management through load shifting. A unique microgrid energy management system is proposed for peak-shaving, leveraging the cost advantages of lower controllable unit expenses. The system actively involves microgrid units in responsive load management, reducing peak consumption during high-demand periods. Evaluation of various demand-side management techniques, especially peak-time rebate programs, is conducted through presented indices measuring the energy management solution's effectiveness. To address the complexity, a particle swarm-based algorithm is introduced for computational efficiency. Validation of the proposed method and model in diverse scenarios showcases significant cost reduction, demonstrating the practicality and innovation of the integrated microgrid and demand-side management strategy. The study highlights a substantial reduction in peak load through load response program participation. At a 20 % participation rate with a 10-cent incentive, there's a significant decrease in peak load during specific hours. With increasing participation and incentives, peak load reduction intensifies, reaching optimal results at a 40 % participation rate and a 20-cent incentive.