Headroom-Based Optimization for Placement of Distributed Generation in a Distribution Substation


  • Mr. John Nweke Department of Electrical Engineering Technology, Federal Polytechnic Kaura-Namoda, Nigeria
  • Ayodeji Olalekan Salau Department of Electrical/Electronics and Computer Engineering, Afe Babalola University, Ado-Ekiti, Nigeria http://orcid.org/0000-0002-6264-9783
  • Dr. Candidus U. Eya Department of Electrical Engineering University of Nigeria, Nsukka Enugu, Nigeria


This paper presents a headroom-based optimization for the placement of distributed generation (DG) in a distribution substation. The penetration limits of DGs into the existing distribution substations are often expressed as a function of the feeder hosting capacity (headroom). Therefore, it is important to estimate the reliability of the networks operation as well as that of the limits imposed by the power quality standards through the evaluation of the hosting capacity (headroom) of the existing distribution feeder substation. This study aimed at developing a novel algorithm for the location of permissible headroom in a power substation for maximum active power supply by using distributed generators in each system bus without causing voltage violations. The developed algorithm can be used by utility companies to select feeder substations that have permissible headroom capacity for DG installation. Modeling and optimization was carried out in Power System Software for Engineers (PSS/E) environment using the IEEE 14-bus test system to evaluate the efficacy of the novel algorithm. The results obtained from the case study show that only four (4) feeder substations out of twenty–one (21) have the permissible headroom capacity for DG connections.

Author Biography

Ayodeji Olalekan Salau, Department of Electrical/Electronics and Computer Engineering, Afe Babalola University, Ado-Ekiti, Nigeria

Ayodeji Olalekan Salau received the B.Eng. in Electrical/Computer Engineering from the Federal University of Technology, Minna, Nigeria. He received the M.Sc and Ph.D. degree from the Obafemi Awolowo University, Ile-Ife, Nigeria. His research interests include computer vision, image processing, signal processing, machine learning, power systems technology, and nuclear engineering. Dr. Salau serves as a Reviewer for several journals including IEEE Transactions on Vehicular Technology, IET Communications, Biomedical Signal Processing and Control, International Journal of Emerging Electric Power Systems, and Journal of Engineering, Design and Technology. His research has been published in many reputable international conferences, book chapters, and major international journals. He is a registered Engineer with the Council for the Regulation of Engineering in Nigeria (COREN), a member of the International Association of Engineers (IAENG), and a recipient of the Quarterly Franklin Membership with ID number CR32878 given by the Editorial Board of London Journals Press in 2020.