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An optimal investment planning framework for multiple distributed generation units in industrial distribution systems

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  • Hung, Duong Quoc
  • Mithulananthan, N.
  • Bansal, R.C.

Abstract

This paper presents new analytical expressions to efficiently capture the optimal power factor of each Distributed Generation (DG) unit for reducing energy losses and enhancing voltage stability over a given planning horizon. These expressions are based on the derivation of a multi-objective index (IMO), which is formulated as a combination of active and reactive power loss indices. The decision for the optimal location, size and number of DG units is then obtained through a benefit–cost analysis. Here, the total benefit includes energy sales and additional benefits, namely energy loss reduction, network upgrade deferral and emission reduction. The total cost is a sum of capital, operation and maintenance costs. The methodology was applied to a 69-bus industrial distribution system. The results showed that the additional benefits are imperative. Inclusion of these in the analysis would yield faster DG investment recovery.

Suggested Citation

  • Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    • Handle: RePEc:eee:appene:v:124:y:2014:i:c:p:62-72
    DOI: 10.1016/j.apenergy.2014.03.005
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    Cited by:

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    5. Bayat, A. & Bagheri, A., 2019. "Optimal active and reactive power allocation in distribution networks using a novel heuristic approach," Applied Energy, Elsevier, vol. 233, pages 71-85.
    6. Mahesh Kumar & Perumal Nallagownden & Irraivan Elamvazuthi, 2017. "Optimal Placement and Sizing of Renewable Distributed Generations and Capacitor Banks into Radial Distribution Systems," Energies, MDPI, vol. 10(6), pages 1-25, June.
    7. Anh Viet Truong & Trieu Ngoc Ton & Thuan Thanh Nguyen & Thanh Long Duong, 2018. "Two States for Optimal Position and Capacity of Distributed Generators Considering Network Reconfiguration for Power Loss Minimization Based on Runner Root Algorithm," Energies, MDPI, vol. 12(1), pages 1-16, December.
    8. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    9. Qiu, Jing & Zhao, Junhua & Yang, Hongming & Wang, Dongxiao & Dong, Zhao Yang, 2018. "Planning of solar photovoltaics, battery energy storage system and gas micro turbine for coupled micro energy grids," Applied Energy, Elsevier, vol. 219(C), pages 361-369.
    10. Daniels, Laura & Coker, Phil & Gunn, Alice & Potter, Ben, 2016. "Using proxies to calculate the carbon impact of investment into electricity network assets," Applied Energy, Elsevier, vol. 162(C), pages 551-560.
    11. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    12. Mahesh Kumar & Amir Mahmood Soomro & Waqar Uddin & Laveet Kumar, 2022. "Optimal Multi-Objective Placement and Sizing of Distributed Generation in Distribution System: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-48, October.
    13. Karatepe, Engin & Ugranlı, Faruk & Hiyama, Takashi, 2015. "Comparison of single- and multiple-distributed generation concepts in terms of power loss, voltage profile, and line flows under uncertain scenarios," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 317-327.
    14. Mokgonyana, Lesiba & Zhang, Jiangfeng & Li, Hailong & Hu, Yihua, 2017. "Optimal location and capacity planning for distributed generation with independent power production and self-generation," Applied Energy, Elsevier, vol. 188(C), pages 140-150.
    15. Santos, Sérgio F. & Fitiwi, Desta Z. & Cruz, Marco R.M. & Cabrita, Carlos M.P. & Catalão, João P.S., 2017. "Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems," Applied Energy, Elsevier, vol. 185(P1), pages 44-55.
    16. 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.
    17. Vikas Singh Bhadoria & Nidhi Singh Pal & Vivek Shrivastava, 2019. "Artificial immune system based approach for size and location optimization of distributed generation in distribution system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(3), pages 339-349, June.
    18. Bruno Canizes & João Soares & Zita Vale & Juan M. Corchado, 2019. "Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City," Energies, MDPI, vol. 12(4), pages 1-40, February.
    19. Bucciarelli, Martina & Paoletti, Simone & Vicino, Antonio, 2018. "Optimal sizing of energy storage systems under uncertain demand and generation," Applied Energy, Elsevier, vol. 225(C), pages 611-621.
    20. Yaghoobi, Jalil & Islam, Monirul & Mithulananthan, Nadarajah, 2018. "Analytical approach to assess the loadability of unbalanced distribution grid with rooftop PV units," Applied Energy, Elsevier, vol. 211(C), pages 358-367.
    21. Abdulla Al Wahedi & Yusuf Bicer, 2020. "A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems," Energies, MDPI, vol. 13(19), pages 1-26, September.

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