Simultaneous Distributed Generation Allocation and Network Reconfiguration: A Review of Computational Intelligence.

Abstract

Progressive load growth and variation on the distribution network prevents the network from optimally delivering safe and reliable power to the end users of electricity due to power loss and voltage deviations. Network reconfiguration (NR) and distributed generation (DG) allocation are two techniques that can improve the distribution network performance. To reduce the challenges on the distribution system in the presence of load growth, distribution Network Reconfiguration (DNR) and Distributed Generation (DG) are simultaneously employed using various Computational Intelligent Techniques (CITs). This review paper focuses on the role of CITs in addressing the optimisation challenge of simultaneous deployment of NR and DG. Fifty-two (52) articles were surveyed, where two (2) of which are review papers, the remaining fifty (50) were reviewed for over five (5) years from google scholar for various algorithms and techniques used in implementing NR and DG to reduce the distribution network challenges. Four (4) metrics were considered in the review which include: Case Scenarios, Fitness/Objectives, Test network and the Implementation platform. Each technique's strengths and weaknesses in handling the multi-objective nature of the problem and ensuring efficient convergence are analysed. Findings from the review indicate that the review for achieving single objective using NR only and DG only was 80% (40) and 54% (27) respectively while the review for various multiple objectives was 56% (28) and 8% (4) used the multi-objective variants of the CITs with only one (1) considering the conflicting objective of maximising load growth while minimising power loss or voltage deviations. This indicates that with the increasing penetration of DG into the distribution networks with increasing load, more work needs to be done in the simultaneous NR and DG planning.