Multi-Objective Invasive Weed Optimization – An application to optimal network reconfiguration in radial distribution systems

• Published in: International journal of electrical power & energy systems Vol. 73; pp. 932 - 942
• Main Authors: Sudha Rani, D., Subrahmanyam, N., Sydulu, M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2015
• Subjects: Invasive weeds; Load balancing; Minimal switching’s; Multi-objective; Network reconfiguration; Minimal switching’s; Multi-objective; Network reconfiguration; Load balancing; Invasive weeds
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2015.06.020

•A new Multi Objective Invasive Weed Optimization algorithm is proposed.•Four objectives are considered simultaneously to solve network reconfiguration.•Pareto front technique is used to solve multi-objective problem.•The proposed algorithm is implemented for both practical and IEEE test systems. Optimal Network Reconfiguration (ONR) is one of the technique utilized by distribution operators in normal and emergency condition for optimal operation of the distribution system. In this article, a Multi-Objective Invasive Weed Optimization (MOIWO) Algorithm is proposed to solve the Optimal Network Reconfiguration (ONR). While solving ONR of the radial distribution system, minimization of active power loss, maximum node voltage deviation, number of switching operations and the load balancing index are considered as the objectives simultaneously. For adopting Invasive Weed Optimization (IWO) Algorithm for solving this multi-objective problem, a non-dominated sorting technique and crowding distance are used to rank the weeds. To investigate the feasibility of the proposed algorithm, it is tested on standard IEEE 33-Bus Test Radial Distribution System and 84 Bus Taiwan Power Company (TPC) Practical Distribution Network. For an analysis of the load flows in a radial distribution system Backward/Forward sweep load flow algorithm is implemented. The performance of the proposed algorithm is compared with results available in recent literature and it is observed that the proposed method produces a high quality Pareto solution and finds a global optimum configuration.