TY - JOUR
T1 - Reinforcement of the distribution grids to improve the hosting capacity of distributed generation
T2 - Multi-Objective Framework
AU - Ahmadi, Bahman
AU - Ceylan, Oguzhan
AU - Ozdemir, Aydogan
N1 - Funding Information:
This research funded as a part of “ 117E773 Advanced Evolutionary Computation for Smart Grid and Smart Community ” project under the framework of 1001 Project organized by “ The Scientific and Technological Research Council of Turkey TUBITAK ” and “ EU HORIZON 2020 – Sustainable and Integrated Energy Systems in Local Communities (SERENE) ”.
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
KW - Distributed Generation (DG)
KW - Hosting capacity
KW - Energy storage system
KW - Static var compensator
KW - Multi-objective optimization
KW - UT-Hybrid-D
U2 - 10.1016/j.epsr.2023.109120
DO - 10.1016/j.epsr.2023.109120
M3 - Article
SN - 0378-7796
VL - 217
JO - Electric power systems research
JF - Electric power systems research
M1 - 109120
ER -
