Title: Renewable energy management in microgrid with demand response using adaptive particle swarm optimisation

Authors: Pothula Jagadeesh; Asapu Siva; Patil Mounica; Guthikonda Tejaswi; M. Mohamed Thameem Ansari; Md. Azahar Ahmed

Addresses: Department of EEE, SRKR Engineering College, Bhimavaram, India ' Department of EEE, Shri Vishnu Engineering College for Women, Bhimavaram, Andhra Pradesh, India ' Department of EEE, Vardhaman College of Engineering, Hyderabad, Telangana, India ' Department of EEE, Sri Vasavi Institute of Engineering and Technology, Nandamuru, Andhra Pradesh, India ' Department of Electrical Engineering, Annamalai University, Annamalai Nagar, India ' Department of EEE, SRKR Engineering College, Bhimavaram, India

Abstract: Effective energy management of renewable energy sources (RES) on microgrids (MGs) presents opportunities and problems. In this research, we offer an adaptive particle swarm optimisation (APSO)-based scheduling model for dynamic and stochastic renewable generation, load demands, and market energy prices. This suggested APSO model optimises battery storage, controlled load schedule, and energy balance at least operational cost. Compared to comprehensive evaluations, APSO excels at handling uncertainties, achieving rapid convergence, and remaining robust and reliable in various issue contexts. Comparing APSO to various metaheuristic optimisation methods shows its improved adaptability, efficiency, and efficacy. It tackles inadequacies in current microgrid operations practice by combining probabilistic modelling, demand response integration, and multi carrier energy systems to create a comprehensive framework for sustainable and economically optimal microgrid operation.

Keywords: microgrid; renewable energy systems; adaptive particle swarm optimisation; APSO; demand response; energy management; cost optimisation; probabilistic modelling.

DOI: 10.1504/IJPT.2026.154600

International Journal of Powertrains, 2026 Vol.15 No.2, pp.173 - 192

Received: 09 Oct 2025
Accepted: 07 Dec 2025
Published online: 07 Jul 2026 *

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