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Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF)

Author

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  • Abdurrahman Shuaibu Hassan

    (Department of Electrical and Electronics Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa)

  • Yanxia Sun

    (Department of Electrical and Electronics Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa)

  • Zenghui Wang

    (Department of Electrical and Mining Engineering, University of South Africa, Roodepoort 1710, South Africa)

Abstract

Distributed generation (DG) plays a vital role in electrical power networks. However, power loss reduction, voltage profile improvement, friendly environment, and reliability are all benefits of DG units. In this research work, a worthwhile methodology is recommended for optimal allocation of traditional (gas turbine) and renewable energy sources that are based on distributed generators which include solar and wind in the distribution system. The major objective of the research paper is the minimization of real, reactive power losses and emissions produced during the application of these conventional sources. Originally, the best locations to place this DG are identified using the concept of water, energy, and food algorithm (WEFA). The number and sizes of these renewable energy sources selected (wind and solar) are determined by applying the concepts of the Dragonfly Algorithm. The Weibull and beta distribution functions are modeled to extract the exact position to fix our DGs to minimize losses within the distribution network. To assess the performance of WEF five different cases scenario considered are DG capacity, Location of Bus, voltage profile, maximum power loss as well as utilization rate. The proposed WEF Algorithm is tested on the IEEE standard 33-bus system. The simulated results were compared with others found in literature and found to be better in terms of power loss reductions.

Suggested Citation

  • Abdurrahman Shuaibu Hassan & Yanxia Sun & Zenghui Wang, 2022. "Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF)," Energies, MDPI, vol. 15(6), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:6:p:2242-:d:774724
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    References listed on IDEAS

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    1. Li, Yang & Feng, Bo & Li, Guoqing & Qi, Junjian & Zhao, Dongbo & Mu, Yunfei, 2018. "Optimal distributed generation planning in active distribution networks considering integration of energy storage," Applied Energy, Elsevier, vol. 210(C), pages 1073-1081.
    2. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
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    Cited by:

    1. Nagaraju Dharavat & Suresh Kumar Sudabattula & Suresh Velamuri & Sachin Mishra & Naveen Kumar Sharma & Mohit Bajaj & Elmazeg Elgamli & Mokhtar Shouran & Salah Kamel, 2022. "Optimal Allocation of Renewable Distributed Generators and Electric Vehicles in a Distribution System Using the Political Optimization Algorithm," Energies, MDPI, vol. 15(18), pages 1-25, September.
    2. Elseify, Mohamed A. & Hashim, Fatma A. & Hussien, Abdelazim G. & Kamel, Salah, 2024. "Single and multi-objectives based on an improved golden jackal optimization algorithm for simultaneous integration of multiple capacitors and multi-type DGs in distribution systems," Applied Energy, Elsevier, vol. 353(PA).

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