Biogeography-based optimization based on population competition strategy for solving the substation location problem. (1st May 2018)

• Record Type: Journal Article
• Authors: Li, Ling-Ling; Yang, Yan-Fang; Wang, Ching-Hsin; Lin, Kuo-Ping
• Is Part Of: Expert systems with applications. Volume 97(2018)
• Page Start: 290
• Page End: 302
• Publication Date: 2018-05-01
• Subjects: Substation location -- Biogeography-based optimization -- Population competition strategy; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2017.12.039
• Languages: English
• ISSNs: 0957-4174

Abstract

Highlight: We developed a biogeography-based optimization with population competition algorithm. The novel algorithm improves conventional biogeography-based optimization. Empirical results indicate that the proposed algorithm has superior performance. Abstract: Location planning of electrical substations is a power planning problem, in which expert knowledge is used to determine ideal substation locations. Using intelligent planning to help electric power experts to reasonably plan the location of a substation can not only ensure the reliability of power supply, but also save on cost to a great extent. In order to improve the economics of electric power planning, this study proposes a combined biogeography-based optimization with population competition algorithm (BBOPC) method. Competition strategy can enhance the search ability of the algorithm due to the dispersed populations involved. A comparative evaluation against the biogeography-based optimization (BBO), competitive strategy based on BBO (CBBO), modified mutation operator based on BBO (MBBO), and BBOPC methods is carried out in selecting the optimal position for a substation. The final results show that, (1) for a simple substation location problem, the minimum total investment cost achieved by BBOPC was less than that of CBBO, currently the most cost-effective method whose total investment cost is relatively better. (2) For a complex substation location problem, the minimum total investment cost achieved by BBOPC was less than that of MBBO. (3) BBOPC demonstrates better convergence characteristics and robustness compared to the other approaches. The proposed BBOPC method can help power experts develop reasonable power planning, which can help the power system effectively achieve operational reliability and economy.