Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Author:

Mahfoud Rabea Jamil12ORCID,Alkayem Nizar Faisal13ORCID,Fernandez-Rodriguez Emmanuel4ORCID,Zheng Yuan12,Sun Yonghui2,Zhang Shida5,Zhang Yuquan12ORCID

Affiliation:

1. College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China

2. College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China

3. College of Civil and Transportation Engineering, Hohai University, Nanjing 210098, China

4. Technological Institute of Merida, Technological Avenue, Merida 97118, Mexico

5. Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Nankai District, Tianjin 300072, China

Abstract

Distribution companies (DISCOs) aim to maximize their annual profits by performing the optimal planning of distributed generators (DGs) or energy storage systems (ESSs) in the deregulated electricity markets. Some previous studies have focused on the simultaneous planning of DGs and ESSs for DISCO profit maximization but have rarely considered the reactive powers of DGs and ESSs. In addition, the optimization methods used for solving this problem are either traditional or outdated, which may not yield superior results. To address these issues, this paper simultaneously performs the optimal planning of DGs and ESSs in distribution networks for DISCO profit maximization. The utilized model not only takes into account the revenues of trading active and reactive powers but also addresses the active and reactive powers of DGs and ESSs. To solve the optimization problem, a new hybrid evolutionary algorithm (EA) called the oppositional social engineering differential evolution with Lévy flights (OSEDE/LFs) is proposed. The OSEDE/LFs is applied to optimize the planning model using the 30-Bus and IEEE 69-Bus networks as test systems. The results of the two case studies are compared with several other EAs. The results confirm the significance of the planning model in achieving higher profits and demonstrate the effectiveness of the proposed approach when compared with other EAs.

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

National Natural Science Foundation of China for Young International Scientists

2022 National Young Foreign Talents Program of China

Publisher

MDPI AG

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