Improved meta-heuristic techniques for simultaneous capacitor and DG allocation in radial distribution networks. (December 2015)

• Record Type: Journal Article
• Authors: Kanwar, Neeraj; Gupta, Nikhil; Niazi, K.R.; Swarnkar, Anil
• Is Part Of: International journal of electrical power & energy systems. Volume 73(2015:Dec.)
• Page Start: 653
• Page End: 664
• Publication Date: 2015-12
• Subjects: Cat swarm optimization -- Distributed resources -- Improved meta-heuristic techniques -- Intelligent search -- Network reconfiguration -- Smart distribution systems; 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.2015.05.049
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Simultaneous allocation of shunt capacitors and DGs in distribution networks. Piece-wise multi-level load profile is considered to evaluate annual energy loss. Penalty factor approach is proposed to check maximum node voltage deviations. Improved variants of GA, PSO and CSO are proposed as optimizing tools. Intelligent search is proposed to enhance the performance of solution techniques. Abstract: The active and reactive power flow in distribution networks can be effectively controlled by optimally placing Shunt Capacitors (SCs) and Distributed Generators (DGs). This paper presents improved versions of three evolutionary or swarm-based search algorithms, namely, Improved Genetic Algorithm (IGA), Improved Particle Swarm Optimization (IPSO) and Improved Cat Swarm Optimization (ICSO) to efficiently handle the problem of simultaneous allocation of SCs and DGs in radial distribution networks while considering variable load scenario. The benefit of network reconfiguration has also been taken into account after optimal allocation of these devices. Several algorithm specific modifications are suggested in the standard forms of GA, PSO and CSO to overcome their inherent drawbacks. In addition, an intelligent search approach is proposed to enhance overall performance of proposed algorithms. The proposed methods are investigated on IEEE 33-bus and 69-bus test distribution systems showing promising results when compared with other recently established methods. Application results also show a marked improvement in the performance of these algorithms while compared with their respective standard counterparts.