Improvement optimal power flow solution under loading margin stability using new partitioning whale algorithm. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Mahdad, Belkacem
• Is Part Of: International journal of management science and engineering management. Volume 14:Issue 1(2019)
• Page Start: 64
• Page End: 77
• Publication Date: 2019-01-02
• Subjects: Power system planning -- OPF -- Whale optimization algorithm -- partitioning strategy -- boundary handling -- loading margin stability -- SVC; Management science -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Management; Management science; Periodicals; 658.005
• DOI: 10.1080/17509653.2018.1488225
• Languages: English
• ISSNs: 1750-9661

Abstract

ABSTRACT: This paper focuses on the solution of the optimal power flow (OPF) problem considering load growth using a novel metaheuristic optimization algorithm called Whale Optimization Algorithm (WOA). An interactive partitioning procedure is proposed to achieve a better solution and to improve search space diversity. In this study the new variant named partitioning WOA is applied to improve the security optimal power flow (SOPF) by minimization the total production cost with different complexities and constraints such as valve point effect and prohibited zones, total power loss and total voltage deviation considering critical load growth. The efficiency of the proposed algorithm has been validated on the IEEE 30-Bus, the Algerian 59-bus power system and to the large test system IEEE 118-Bus for various standard objective functions. For the test system IEEE-30 Bus, a competitive optimized quadratic cost (798.9225 $) is achieved compared to many recent techniques; also significant amounts of power loss and voltage deviation have been reduced for all test systems without affecting security constraints in particular for the IEEE 118-Bus, the total loss being reduced from 132.86 MW at base case (without optimization) to a competitive value 8.6099 MW. The proposed strategy proves its remarkable ability in solving the practical security constrained OPF for modern large power systems.