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

Authors :
Ahmadi, Bahman
Ceylan, Oguzhan
Ozdemir, Aydogan
Source :
Electric Power Systems Research. Apr2023, Vol. 217, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

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. • Maximization of the hosting capacity while minimizing the energy losses. • Maximization of the energy transferred to the off-peak hours through intelligent control. • Multi-Objective Advanced GWO algorithm to determine the Pareto front solutions. • Singular and collaborative impacts of the reinforcement units on the objectives. • High-quality Pareto solutions and high computational efficiency of MOAGWO. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03787796
Volume :
217
Database :
Academic Search Index
Journal :
Electric Power Systems Research
Publication Type :
Academic Journal
Accession number :
161792506
Full Text :
https://doi.org/10.1016/j.epsr.2023.109120