Multi-Objective Optimal Performance of a Hybrid CPSD-SE/HWT System for Microgrid Power Generation

Shboul, Bashar; Al-Arfi, Ismail; Michailos, Stavros; Ingham, Derek; Udeh, Godfrey T.; Ma, Lin; Hughes, Kevin; Pourkashanian, Mohamed

Abstract

A new integrated hybrid solar thermal and wind-based microgrid power system is proposed. It consists of a concentrated parabolic solar dish Stirling engine, a wind turbine, and a battery bank. The electrical power curtailment is diminished, and the levelised cost of energy is significantly reduced. To achieve these goals, the present study conducts a dynamic performance analysis over one year of operation. Further, a multi-objective optimisation model based on a genetic algorithm is implemented to optimise the techno-economic performance. The MATLAB/Simulink® software was used to model the system, study the performance under various operating conditions, and optimise the proposed hybrid system. Finally, the model has been implemented for a specific case study in Mafraq, Jordan. The system satisfies a net power output of 1500 kWe. The developed model has been validated using published results. In conclusion, the obtained results reveal that the optimised model of the microgrid can substantially improve the overall efficiency and reduce the levelised cost of electricity.

Citation

Shboul, B., Al-Arfi, I., Michailos, S., Ingham, D., Udeh, G. T., Ma, L., Hughes, K., & Pourkashanian, M. (2022). Multi-Objective Optimal Performance of a Hybrid CPSD-SE/HWT System for Microgrid Power Generation. In M. A. Mellal (Ed.), Applications of Nature-Inspired Computing in Renewable Energy Systems (166-210). IGI Global. https://doi.org/10.4018/978-1-7998-8561-0.ch009

• Publication Date: 2022
• Deposit Date: Dec 5, 2022
• Publicly Available Date: Apr 24, 2025
• Publisher: IGI Global
• Pages: 166-210
• Series Title: Advances in Environmental Engineering and Green Technologies
• Book Title: Applications of Nature-Inspired Computing in Renewable Energy Systems
• Chapter Number: 9
• ISBN: 9781799885610 ; 9781799885627
• DOI: https://doi.org/10.4018/978-1-7998-8561-0.ch009
• Public URL: https://hull-repository.worktribe.com/output/4131080