A Joint Optimization Algorithm for Renewable Energy System

Khan, Imran; Muhammad-Sukki, Firdaus; Ardila-Rey, Jorge Alfredo; Mas'ud, Abdullahi Abubakar; Alshammari, Saud Jazaa; Madsen, Dag Øivind

Abstract

Energy sustainability is a hot topic in both scientific and political circles. To date, two alternative approaches to this issue are being taken. Some people believe that increasing power consumption is necessary for countries' economic and social progress, while others are more concerned with maintaining carbon consumption under set limitations. To establish a secure, sustainable, and economical energy system while mitigating the consequences of climate change, most governments are currently pushing renewable growth policies. Energy markets are meant to provide consumers with dependable electricity at the lowest possible cost. A profit-maximization optimal decision model is created in the electric power market with the combined wind, solar units, loads, and energy storage systems , based on the bidding mechanism in the electricity market and operational principles. This model utterly considers the technological limits of new energy units and storages, as well as the involvement of new energy and electric vehicles in market bidding through power generation strategy and the output arrangement of the virtual power plant's coordinated operation. The accuracy and validity of the optimal decision-making model of combined wind, solar units, loads, and energy storage systems are validated using numerical examples. Under multi-operating scenarios, the effects of renewable energy output changes on joint system bidding techniques are compared.

Citation

Khan, I., Muhammad-Sukki, F., Ardila-Rey, J. A., Mas'ud, A. A., Alshammari, S. J., & Madsen, D. Ø. (2023). A Joint Optimization Algorithm for Renewable Energy System. Intelligent Automation and Soft Computing, 36(2), 1979-1989. https://doi.org/10.32604/iasc.2023.034106

• Journal Article Type: Article
• Acceptance Date: Aug 8, 2022
• Online Publication Date: Jan 5, 2023
• Publication Date: 2023
• Deposit Date: Dec 1, 2022
• Publicly Available Date: Jan 5, 2023
• Print ISSN: 1079-8587
• Publisher: Tech Science Press
• Peer Reviewed: Peer Reviewed
• Volume: 36
• Issue: 2
• Pages: 1979-1989
• DOI: https://doi.org/10.32604/iasc.2023.034106
• Keywords: Renewable energy; optimization algorithm; electricity market; decision-making
• Public URL: http://researchrepository.napier.ac.uk/Output/2968739