Optimal Clean Energy Resource Allocation in Balanced and Unbalanced Operation of Sustainable Electrical Energy Distribution Networks

Abhinav Kumar, Sanjay Kumar, Umesh Kumar Sinha, Aashish Kumar Bohre and Akshay Kumar Saha ()
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Abhinav Kumar: Electrical Department, National Institute of Technology Jamshedpur, Jamshedpur 831014, India
Sanjay Kumar: Electrical Department, National Institute of Technology Jamshedpur, Jamshedpur 831014, India
Umesh Kumar Sinha: Electrical Department, National Institute of Technology Jamshedpur, Jamshedpur 831014, India
Aashish Kumar Bohre: Electrical Egg. Department, National Institute of Technology, Durgapur 713209, India
Akshay Kumar Saha: Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, Durban 4041, South Africa

Energies, 2024, vol. 17, issue 18, 1-52

Abstract: Electric power is crucial for economic growth and the overall development of any country. The efficient planning of distribution system is necessary because all the consumers mainly rely on the distribution network to access the power. This paper focuses on addressing distribution system challenges and meeting consumers’ fundamental needs, such as achieving an improved voltage profile and minimizing costs within an environmentally sustainable framework. This work addressed the gap in the existing research by analysing the performance of both balanced and unbalanced systems within the same framework, specifically using the IEEE 33-bus and IEEE 118-bus test systems. Unlike prior studies that focused solely on either balanced or unbalanced systems, this work redistributed balanced loads into three-phase unequal unbalanced loads to create a more challenging unbalanced distribution network. The primary objective is to compare the effects of balanced and unbalanced loads on system the performances and to identify strategies for mitigating unbalanced load issues in each phase. Six optimization methods (PSO, TLBO, JAYA, SCA, RAO, and HBO) were employed to minimize losses, voltage variations, and other multi-objective function factors. Additionally, the study compared the cost of energy loss (CEL), emission factors, costs associated with distributed clean energy resources (DCER), and active and reactive power losses. Phase angle distortions due to unbalanced loads were also analysed. The results showed that among the optimization techniques tested (PSO, TLBO, JAYA, SCA, RAO, and HBO), the HBO method proved to be the most effective for the optimal allocation of distributed clean energy resources, yielding the lowest PF MO values and favourable outcomes across the technical, economic, and environmental parameters.

Keywords: distributed clean energy resources; active power loss index; reactive power loss index; voltage index; balanced and unbalanced distribution systems; soft computing techniques (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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