Utilizing Particle Swarm Optimization Algorithm for Energy Management Application

Submission Deadline: 01 January 2023 (closed)

Guest Editors

Wali Khan Mashwani, Kohat University of Science & Technology (KUST), Pakistan. Email: walikhan@ieee.org
Atila Goktas, Muğla Sıtkı Koçman Üniversitesi,Turkey. Email: gatilla@mu.edu.tr
Zakia Hammouch, Moulay Ismail University, Morocco. Email: zakia.hammouch@fste.umi.ac.ma


Swarm optimization is a new, popular and helpful approach for solving complex energy management application problems. The introduction of various parameters used in non-renewable energy sources and renewable energy sources is included in this work. The work also consists of the optimization techniques for both types of energy sources utilized in a wireless sensor network. The algorithm can ensure an appropriate energy consumption by demand response with sequence-dependent switching costs. The benefits are as follows: Saving energy; Reducing carbon dioxide emissions; Improving distribution efficiency; Improving customer satisfaction, and supporting other sustainable technologies. The main challenge associated with this algorithm is the need for exhaustive calculation done by every particle in the swarm. This implies that computation speed is limited and makes it unsuitable for large-scale applications in the power system environment.


Swarm Optimization, energy sources, electricity, renewable energy, PSO, WSN, challenges

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