Reinforcement of the distribution grids to improve the hosting capacity of distributed generation: Multi-objective framework

Ahmadi B., CEYLAN O., Özdemir A.

Electric Power Systems Research, vol.217, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 217
  • Publication Date: 2023
  • Doi Number: 10.1016/j.epsr.2023.109120
  • Journal Name: Electric Power Systems Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Environment Index, INSPEC
  • Keywords: Distributed generation, Energy storage systems, Hosting capacity, Multi-objective optimization, Static var compensator
  • Istanbul Technical University Affiliated: Yes


© 2023 The Author(s)Excessive penetration of renewable energy resources into the distribution grid without additional preventive measures has led to several operational problems. However, most strategies developed to accommodate more renewable energy units suffered from other operational problems. Therefore, further efforts are needed to address the other key vulnerabilities of the grid in addition to maximizing the hosting capacity. In this regard, this study is devoted to a new multi-objective formulation to maximize the hosting capacity and minimize the total energy losses while satisfying the operational constraints and maximizing the energy transferred to off-peak hours. The Multi-Objective Advanced Gray Wolf Optimization (MOAGWO) algorithm is used as a solution tool. The proposed formulation and solution algorithm are tested on IEEE-33-bus and 69-bus medium voltage test systems. The impacts of energy storage systems, voltage regulators, and static var compensators on the hosting capacity and the objective functions are identified using several scenarios. The results showed that the optimal device type and locations depend on the level of DG penetration. Finally, a comparison according to two popular multi-objective performance indices showed that the quality of the Pareto front distribution obtained by MOAGWO was better than the ones obtained with the two other popular heuristic methods.