Impact of reverse power flow on the optimal distributed generation placement problem

• Published in: IET generation, transmission & distribution Vol. 11; no. 18; pp. 4626 - 4632
• Main Authors: Sgouras, Kallisthenis I, Bouhouras, Aggelos S, Gkaidatzis, Paschalis A, Doukas, Dimitrios I, Labridis, Dimitris P
• Format: Journal Article
• Language: English
• Published: The Institution of Engineering and Technology 21.12.2017
• Subjects: distributed energy resources; distributed power generation; IEEE 30‐bus test systems; IEEE 33‐bus test systems; load flow; loss minimisation; ODGP; optimal DG placement; optimal distributed generation placement problem; particle swarm optimisation; particle swarm optimisation algorithm; Research Article; reverse power flow; RPF; IEEE 33-bus test systems; particle swarm optimisation algorithm; particle swarm optimisation; optimal distributed generation placement problem; distributed energy resources; IEEE 30-bus test systems; RPF; distributed power generation; optimal DG placement; loss minimisation; reverse power flow; ODGP; load flow
• ISSN: 1751-8687; 1751-8695; 1751-8695
• DOI: 10.1049/iet-gtd.2016.1791

Integration of distributed generation (DG) in existing distribution networks has been studied thoroughly during the past years as a measure of reducing grid's power losses. However, the optimal DG placement, known as ODGP, toward loss minimisation, has not been studied in depth by considering the possible impact of the reverse power flow (RPF) caused by extended penetration of distributed energy resources. This study uses a constriction factor embedded local particle swarm optimisation algorithm along with the appropriate particle formulation that solves the ODGP problem by taking into account the impact of possible RPF. In this study, the idea of RPF modelling is introduced by providing extended versions of IEEE test systems. Modified versions of the IEEE 30-bus and IEEE 33-bus test systems are modelled and results are presented in order to highlight the impact of RPF on the ODGP problem solution. The mathematical formulation is given, results and analysis for both extended systems are presented, while the importance of RPF for different conditions is assessed.