Utilization of demand side management for stability improvement in renewable energy resources in United Kingdom.

Sundas, Rida; Atalor, Daniel Osaroboh; Baig, Nauman Anwar; Yahya, Hira

Abstract

This research deals with the Particle Swarm Optimization (PSO) algorithm for a meagre load shifting in demand side management focusing on scheduling the residential, commercial, and industrial load in United Kingdom. Irregular and unscheduled load consumption causes sparsity in renewable energy sources, which on the other sides causes customers discomfort in their utility bills. Nash equilibrium, which smartly minimizes energy utility cost and peak-to-average ratio, is still an intense problem. Therefore, a bidirectional framework is developed to monitor both the demand and supply side and provide solutions to solve customer's problems. The PSO algorithm is employed to achieve super liner convergence rate and minimize to average ratio. The suitable selection for the inertia weight creates an equilibrium between global and local exploration abilities. The detailed analysis and results of the two cases of the PSO algorithm have been drawn to illustrate the reduction in peak-to-average ratio and utility cost.

Citation

SUNDAS, R., ATALOR, D.O., BAIG, N.A. and YAHYA, H. 2024. Utilization of demand side management for stability improvement in renewable energy resources in United Kingdom. In Proceedings of the 2024 Future technologies conference (FTC 2024), 14-15 November 2024, London, UK. Lecture notes in networks and systems, 1154. Cham: Springer [online], 1, pages 558-571. Available from: https://doi.org/10.1007/978-3-031-73110-5_37

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 Future technologies conference (FTC 2024)
• Start Date: Nov 14, 2024
• End Date: Nov 15, 2024
• Acceptance Date: Apr 15, 2024
• Online Publication Date: Nov 5, 2024
• Publication Date: Dec 31, 2024
• Deposit Date: Dec 2, 2024
• Publicly Available Date: Nov 6, 2025
• Print ISSN: 2367-3370
• Electronic ISSN: 2367-3389
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 1
• Pages: 558-571
• Series Title: Lecture notes in networks and systems
• Series Number: 1154
• Series ISSN: 2367-3370; 2367-3389
• ISBN: 9783031731099
• DOI: https://doi.org/10.1007/978-3-031-73110-5_37
• Keywords: Appliances scheduling; Demand side management (DSM); Load shifting; Particle swarm optimization (PSO) algorithm; Smart grids
• Public URL: https://rgu-repository.worktribe.com/output/2612941