Optimal power flow for a deregulated power system using adaptive real coded biogeography-based optimization. (December 2015)

• Record Type: Journal Article
• Authors: Ramesh Kumar, A.; Premalatha, L.
• Is Part Of: International journal of electrical power & energy systems. Volume 73(2015:Dec.)
• Page Start: 393
• Page End: 399
• Publication Date: 2015-12
• Subjects: Adaptive mutation -- Biogeography-based optimization -- Optimal power flow -- Fuel cost minimization -- Voltage profile improvement -- Voltage stability enhancement; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2015.05.011
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Determine the optimal settings of control variables for optimal power flow problem. ARCBBO algorithm was incorporated with objective function of OPF problem. Hence, expose accuracy and robustness of results. Using of adaptive Gaussian mutation, obtained smooth convergence characteristics. Abstract: The optimization is an important role in the wide geographical distribution of electrical power market, finding the optimum solution for the operation and design of power systems has become a necessity with the increasing cost of raw materials, depleting energy resources and the ever growing demand for electrical energy. Using adaptive real coded biogeography-based optimization (ARCBBO), we present the optimization of various objective functions of an optimal power flow (OPF) problem in a power system. We aimed to determine the optimal settings of control variables for an OPF problem. The proposed approach was tested on a standard IEEE 30-bus system and an IEEE 57-bus system with different objective functions. Simulation results reveal that the proposed ARCBBO approach is effective, robust and more accurate than current methods of power flow optimization in literature.