Emerging heuristic optimization algorithms for expansion planning and flexibility optimization in sustainable electrical power systems

Sarda, Jigar, Pandya, Kartik and Shah, Margi ORCID: https://orcid.org/0000-0003-2222-8412 2019. Emerging heuristic optimization algorithms for expansion planning and flexibility optimization in sustainable electrical power systems. Presented at: International Conference on Power, Control and Communication Infrastructure, Institute of Infrastructure Technology Research and Management, Ahmedabad, India, 4-5 July 2019. Published in: Mehta, Axaykumar, Rawat, Abhishek and Chauhan, Priyesh eds. Advances in Control Systems and its Infrastructure. Proceedings of ICPCCI 2019. Lecture Notes in Electrical Engineering. , vol.604 Singapore: Springer Science Business Media, pp. 191-200. 10.1007/978-981-15-0226-2_15

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Abstract

The expansion planning and flexibility optimization of sustainable electrical power systems are facing higher complexity introduced by massive integration of variable renewable generation, the increasing need of facts and HVDC devices for flexibility in highly interactive energy markets, responsive demand and multienergy sector coupling. Therefore, the expansion and flexibility management problems involved in investments decision-making and operational planning need consideration of more accurate models such as non-linear models, probabilistic models and a large number of decision variables. As the problem is difficult to tackle using classical optimisation tools, metaheuristic methods are depicted to solve it. The paper is based on three benchmark systems to evaluate the feasibility and effectiveness of optimization algorithms in systems of different characteristics and size. Also, the paper presents the results and statistical comparative evaluation of the performance of different emerging heuristic optimization algorithms.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	Springer Science Business Media
ISBN:	978-981-15-0225-5
ISSN:	1876-1100
Last Modified:	13 Dec 2022 17:15
URI:	https://orca.cardiff.ac.uk/id/eprint/154834

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