Analytical adaptive distributed multi-objective optimization algorithm for optimal power flow problems. (1st February 2021)

• Record Type: Journal Article
• Authors: Yin, Linfei; Wang, Tao; Zheng, Baomin
• Is Part Of: Energy. Volume 216(2021)
• Publication Date: 2021-02-01
• Subjects: Adaptive interchange objective value method -- Distributed multi-objective optimization problems -- Optimal power flow; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.119245
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The convergence speed of analytic distributed multi-objective optimization algorithms should be higher when solving distributed multi-objective optimization algorithms. An adaptive operation is introduced into the only analytic distributed multi-objective optimization algorithm, which is an interchange objective value method. Therefore, an adaptive interchange objective value method is proposed for distributed multi-objective optimization problems. The proposed adaptive interchange objective value method updates the reward coefficients of a basic analytical distributed multi-objective optimization algorithm in the iteration process of solving distributed multi-objective optimization problems. The adaptive interchange objective value method obtains multiple satisfy optimal objectives for multiple subsidiary distributed multi-objective optimization problems security and quickly. To verify the feasibility and effectiveness of the adaptive interchange objective value method for the analytical distributed multi-objective optimization problems, the analytical distributed multi-objective optimal power flow problems under IEEE 118-bus, IEEE 300-bus power system and the medium part of the European system with 1472-bus test system are simulated. The numerical simulation results under these three cases show that the proposed adaptive interchange objective value method can obtain multiple distributed objectives for analytical distributed multi-objective optimal power flow problems security and quickly. Highlights: Convergence speed of distributed multi-objective optimization problems is considered. Adaptive operation is introduced into interchange objective value (IOV) method. Analytic adaptive interchange objective value (AIOV) method is proposed. The AIOV method can obtain higher convergence speed than the IOV method. Distributed multi-objective OPF problems are solved by AIOV security and quickly.