Multiobjective optimal power flow using interior search algorithm: A case study on a real‐time electrical network. (19th March 2020)

• Record Type: Journal Article
• Authors: Chandrasekaran, Shilaja
• Is Part Of: Computational intelligence. Volume 36:Number 3(2020)
• Page Start: 1078
• Page End: 1096
• Publication Date: 2020-03-19
• Subjects: interior search algorithm -- losses -- optimal power flow -- pollutant emission -- production cost -- voltage deviation and Tamil Nadu power system; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12312
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: Optimal power flow (OPF) is a vital concern in an electrical network. In consequence of the intricacy of the power systems, the conventional formulations are not adequate for current situation. Hence, in this study, the multiobjective OPF (MOOPF) problem has been modeled to diminish the production cost, environmental emission, and losses and to enhance the voltage stability and voltage profile simultaneously. This study proposes the application of interior search algorithm (ISA) for resolving MOOPF problem. The simulations have been carried out on three various test systems such as IEEE 30‐bus system, IEEE 57‐bus system, and Tamil Nadu Generation and Distribution Corporation Limited, as a real part of 62 bus Indian utility system (IUS) to infer the efficacy of ISA in solving the OPF problems. The simulation results have been compared with other techniques. The comparison shows that ISA is used in resolving MOOPF problems.