Multi-objective evolutionary programming for solving economic dispatch problem

• Main Authors: Adnan, N.A (Author), Jelani, S. (Author), Kamil, K. (Author), Khader, P.S.A (Author), Mansor, M.H (Author), Musirin, I. (Author), Roslan, N. (Author), Zuhdi, A.W.M (Author)
• Format: Article
• Language: English
• Published: World Academy of Research in Science and Engineering 2019
• Subjects: Economic dispatch; Evolutionary programming; Multi-objective optimisation; Weighted-sum method
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 22783091 (ISSN)
• ISSN: 22783091 (ISSN)
• DOI: 10.30534/ijatcse/2019/4481.62019

Economic dispatch (ED) is an optimisation strategy to ensure power systems operate in an economic manner. This paper proposes a multi-objective optimisation method to minimise the total generation cost and total system loss simultaneously and find the best adjustment for this economic dispatch problem. This study focused on solving the multi-objective economic dispatch problem using a Heuristic Optimisation (HO) method, namely Multi-Objective Evolutionary Programming (MOEP). The Weighted Sum Method (WSM) is integrated with EP to find a trade-off solution between two objectives: total generation cost minimisation and total system loss minimisation. The practicable proposed method was tested on the IEEE 30-Bus Reliability Test System (RTS) for three different scenarios. MATLAB programming language was used to run the designated algorithm of MOEP. The performance of MOEP to solve the multi-objective ED problem was then compared with another method; the Multi-Objective Artificial Immune System (MOAIS). The experimental results show that MOEP dominates in all cases that have been tested, proving that MOEP is superior than MOAIS in providing high-quality solution to economic dispatch problem with multiple objectives in terms of cheap total generation cost and low total system loss. © 2019, World Academy of Research in Science and Engineering. All rights reserved.