Research on Novel Whale Algorithm for Multi-objective Optimal Power Flow Problem. Issue 1 (February 2021)

• Record Type: Journal Article
• Authors: Zhao, Xilai; Chen, Gonggui; Qin, Qilin
• Is Part Of: Journal of physics. Volume 1754:Issue 1(2021)
• Publication Date: 2021-02
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1754/1/012192
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: To solve the non-differentiable optimal power flow (OPF) problems while satisfying various operational constrains, a multi-objective novel whale optimization algorithm (MONWOA) is proposed. MONWOA algorithm can overcome the premature-convergence of standard whale optimization algorithm. A Pareto-dominant approach with constrains (PDA) is employed to guarantee no violations of various inequality constraints on state variables. MONWOA algorithm is applied to optimize fuel cost, emission, active power loss and fuel cost (with value-point loadings). The bi-objective and tri-objective trials are implemented on IEEE30-bus system and the IEEE57-bus system. A large number of experimental results obtained by MONWOA and MOPSO algorithms, demonstrate that MONWOA has the definite competitive advantages to obtain uniform distribution Pareto front set (PFs), high-quality Pareto optimal solution (POS) and search for the best compromise solution (BCS) in solving MOOPF problem.