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Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system

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  • Tanwar, Surender Singh
  • Khatod, D.K.

Abstract

This paper presents an approach for optimal placement and sizing of dispatchable and non-dispatchable renewable distributed generators (DG) units in a radial distribution network. In this work, wind and solar energy based DG units are considered as non-dispatchable DG, while biomass energy based DG units are considered as dispatchable. The formulated multi-objective problem comprises of technical performance indices for real power loss, maximum branch current capacity, voltage deviation, environment impact reduction index; and economic index. The appropriate weighting factors for different indices has been decided by Analytic Hierarchy Process (AHP). To solve the developed formulation, Particle Swarm Optimization (PSO) based approach has been used and applied on a 51-bus distribution networks. Also, in order to validate the use of AHP, the prioritization to different indices leads to formation of four scenarios and results are obtained in terms of the technical, economic and environmental parameters. The results obtained by the proposed method have been compared with other multi-objective problems considering different weighting factors to the indices and emerged as a simple and efficient approach.

Suggested Citation

  • Tanwar, Surender Singh & Khatod, D.K., 2017. "Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system," Energy, Elsevier, vol. 127(C), pages 52-67.
    • Handle: RePEc:eee:energy:v:127:y:2017:i:c:p:52-67
    DOI: 10.1016/j.energy.2017.02.172
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    References listed on IDEAS

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    Cited by:

    1. Syed Ali Abbas Kazmi & Usama Ameer Khan & Waleed Ahmad & Muhammad Hassan & Fahim Ahmed Ibupoto & Syed Basit Ali Bukhari & Sajid Ali & M. Mahad Malik & Dong Ryeol Shin, 2021. "Multiple (TEES)-Criteria-Based Sustainable Planning Approach for Mesh-Configured Distribution Mechanisms across Multiple Load Growth Horizons," Energies, MDPI, vol. 14(11), pages 1-44, May.
    2. Li, Rui & Wang, Wei & Wu, Xuezhi & Tang, Fen & Chen, Zhe, 2019. "Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis," Energy, Elsevier, vol. 168(C), pages 30-42.
    3. Jamal, Taskin & Urmee, Tania & Shafiullah, G.M., 2020. "Planning of off-grid power supply systems in remote areas using multi-criteria decision analysis," Energy, Elsevier, vol. 201(C).
    4. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).
    5. Salman Khodayifar & Mohammad A. Raayatpanah & Abbas Rabiee & Hamed Rahimian & Panos M. Pardalos, 2018. "Optimal Long-Term Distributed Generation Planning and Reconfiguration of Distribution Systems: An Accelerating Benders’ Decomposition Approach," Journal of Optimization Theory and Applications, Springer, vol. 179(1), pages 283-310, October.
    6. Muhammad Shahroz Sultan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Dong Ryeol Shin, 2023. "Multi-Objective Optimization-Based Approach for Optimal Allocation of Distributed Generation Considering Techno-Economic and Environmental Indices," Sustainability, MDPI, vol. 15(5), pages 1-30, February.
    7. Syed Ali Abbas Kazmi & Usama Ameer Khan & Hafiz Waleed Ahmad & Sajid Ali & Dong Ryeol Shin, 2020. "A Techno-Economic Centric Integrated Decision-Making Planning Approach for Optimal Assets Placement in Meshed Distribution Network Across the Load Growth," Energies, MDPI, vol. 13(6), pages 1-71, March.
    8. Xiang, Yue & Zhou, Lili & Su, Yunche & Liu, Jichun & Huang, Yuan & Liu, Junyong & Lei, Xia & Sun, Zhang & Xu, Weiting & Zhang, Wentao, 2018. "Coordinated DG-Tie planning in distribution networks based on temporal scenarios," Energy, Elsevier, vol. 159(C), pages 774-785.

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    Keywords

    PSO; AHP; Scenarios; Load variation;
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