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Optimizing distributed generation parameters through economic feasibility assessment

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  • Muttaqi, K.M.
  • Le, An D.T.
  • Aghaei, J.
  • Mahboubi-Moghaddam, E.
  • Negnevitsky, M.
  • Ledwich, G.

Abstract

To meet the fast growth of electricity demand, the traditional network solution tends to expand existing substations, build more new substations, and build transmission lines. Distributed Generation (DG) is posed as an alternative method for the network providers not only to accommodate the load increase and relieve network overload, but also to offer other additional technical and economic benefits. This paper addresses the issue of DG planning and has proposed a technique for optimizing the DG size and location to minimize the overall investment and operational cost of the system. The proposed optimization methodology assesses the compatibility of different generation schemes in terms of their cost factors that can be significantly contributed by a DG. The direct and indirect costs of power supply quality, reliability, energy loss, total power operation, and DG investment are used as key cost components of the DG siting and sizing strategy. The Particle Swarm Optimization (PSO) method is applied to obtain the optimal DG planning solutions. Finally, the proposed approach is tested on a distribution feeder of an Australian power network. Simulation results are presented to illustrate the feasibility and effectiveness of the proposed method.

Suggested Citation

  • Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
    • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:893-903
    DOI: 10.1016/j.apenergy.2016.01.006
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    4. 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.
    5. Xie, Shiwei & Hu, Zhijian & Wang, Jueying, 2020. "Two-stage robust optimization for expansion planning of active distribution systems coupled with urban transportation networks," Applied Energy, Elsevier, vol. 261(C).
    6. Nojavan, Sayyad & Majidi, Majid & Esfetanaj, Naser Nourani, 2017. "An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management," Energy, Elsevier, vol. 139(C), pages 89-97.
    7. 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.
    8. Senthil Kumar, J. & Charles Raja, S. & Jeslin Drusila Nesamalar, J. & Venkatesh, P., 2018. "Optimizing renewable based generations in AC/DC microgrid system using hybrid Nelder-Mead – Cuckoo Search algorithm," Energy, Elsevier, vol. 158(C), pages 204-215.
    9. Kumar, Jitendra & Suryakiran, B.V. & Verma, Ashu & Bhatti, T.S., 2019. "Analysis of techno-economic viability with demand response strategy of a grid-connected microgrid model for enhanced rural electrification in Uttar Pradesh state, India," Energy, Elsevier, vol. 178(C), pages 176-185.
    10. Xi, Lei & Yu, Tao & Yang, Bo & Zhang, Xiaoshun & Qiu, Xuanyu, 2016. "A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid," Applied Energy, Elsevier, vol. 178(C), pages 198-211.
    11. Singh, A.K. & Parida, S.K., 2018. "A review on distributed generation allocation and planning in deregulated electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4132-4141.
    12. Calvillo, C.F. & Sánchez-Miralles, A. & Villar, J. & Martín, F., 2016. "Optimal planning and operation of aggregated distributed energy resources with market participation," Applied Energy, Elsevier, vol. 182(C), pages 340-357.
    13. Hee-Kwan Shin & Jae-Min Cho & Eul-Bum Lee, 2019. "Electrical Power Characteristics and Economic Analysis of Distributed Generation System Using Renewable Energy: Applied to Iron and Steel Plants," Sustainability, MDPI, vol. 11(22), pages 1-27, November.
    14. Yu-Cheol Jeong & Eul-Bum Lee & Douglas Alleman, 2019. "Reducing Voltage Volatility with Step Voltage Regulators: A Life-Cycle Cost Analysis of Korean Solar Photovoltaic Distributed Generation," Energies, MDPI, vol. 12(4), pages 1-16, February.

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