Optimal power flow analysis using Lévy flight spider monkey optimisation algorithm. (2016)

• Record Type: Journal Article
• Authors: Sharma, Ajay; Sharma, Harish; Bhargava, Annapurna; Sharma, Nirmala; Bansal, Jagdish Chand
• Is Part Of: International journal of artificial intelligence and soft computing. Volume 5:Number 4(2016)
• Page Start: 320
• Page End: 352
• Publication Date: 2016
• Subjects: spider monkey optimisation -- SMO -- swarm intelligence -- Levy flight -- local search -- LFLS -- optimal power flow -- OPF -- IEEE 30-bus -- exploitation; Artificial intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4950

Abstract

Optimal power flow (OPF) is the most requisite tool in the power system analysis. The OPF is relatively a difficult constrained optimisation problem and broadly solved by conventional as well as modern intelligent methods. In this paper the authors proposed a Lévy flight spider monkey optimisation (LFSMO) algorithm to solve the standard OPF problem for IEEE 30-bus system, which is proposed to improve the exploitation capability of spider monkey optimisation (SMO) algorithm. The performance of LFSMO is evaluated by testing it over 25 benchmark functions.