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Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach

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  • Ahmadigorji, Masoud
  • Amjady, Nima

Abstract

This paper presents a dynamic (i.e., time-based) model for distribution system expansion planning (DSEP) considering distributed generation. The proposed model optimizes both investment and operation costs of distribution system. It determines the optimal location and size of distributed generators as well as the reinforcement strategy for primary (i.e., medium voltage) distribution feeders along a specified planning horizon. Besides, the dynamic feature of this model enables it to determine the time of each investment. The investment costs consist of installation cost of distributed generators and reinforcement cost of primary distribution feeders. Similarly, the operation costs comprise the cost of energy losses, operation and maintenance cost of the equipment and cost of power purchased from upstream grid (i.e., sub-transmission or transmission grid). The introduced model is solved using a combination of two efficient heuristic methods of Modified Integer-coded Harmony Search (MIHS) to find the optimal expansion scheme and Enhanced Gravitational Search Algorithm (EGSA) to optimize the operation costs. Furthermore, the suggested solution approach also incorporates an efficient mechanism for coding the candidate solutions in MIHS algorithm. The effectiveness of the proposed method and coding mechanism is extensively demonstrated by testing on two radial distribution systems and comparing the obtained results with the results of several other solution techniques.

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  • Ahmadigorji, Masoud & Amjady, Nima, 2015. "Optimal dynamic expansion planning of distribution systems considering non-renewable distributed generation using a new heuristic double-stage optimization solution approach," Applied Energy, Elsevier, vol. 156(C), pages 655-665.
    • Handle: RePEc:eee:appene:v:156:y:2015:i:c:p:655-665
    DOI: 10.1016/j.apenergy.2015.07.042
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    1. Luo, Lizi & Gu, Wei & Zhang, Xiao-Ping & Cao, Ge & Wang, Weijun & Zhu, Gang & You, Dingjun & Wu, Zhi, 2018. "Optimal siting and sizing of distributed generation in distribution systems with PV solar farm utilized as STATCOM (PV-STATCOM)," Applied Energy, Elsevier, vol. 210(C), pages 1092-1100.
    2. El-Sharafy, M. Zaki & Farag, Hany E.Z., 2017. "Back-feed power restoration using distributed constraint optimization in smart distribution grids clustered into microgrids," Applied Energy, Elsevier, vol. 206(C), pages 1102-1117.
    3. Wu, Zhi & Liu, Pengxiang & Gu, Wei & Huang, He & Han, Jun, 2018. "A bi-level planning approach for hybrid AC-DC distribution system considering N-1 security criterion," Applied Energy, Elsevier, vol. 230(C), pages 417-428.
    4. Waite, Michael & Modi, Vijay, 2016. "Modeling wind power curtailment with increased capacity in a regional electricity grid supplying a dense urban demand," Applied Energy, Elsevier, vol. 183(C), pages 299-317.
    5. Ihsan, Abbas & Brear, Michael J. & Jeppesen, Matthew, 2021. "Impact of operating uncertainty on the performance of distributed, hybrid, renewable power plants," Applied Energy, Elsevier, vol. 282(PB).
    6. Xiangang Peng & Lixiang Lin & Weiqin Zheng & Yi Liu, 2015. "Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem," Energies, MDPI, vol. 8(12), pages 1-19, December.
    7. Mandhir Kumar Verma & Vivekananda Mukherjee & Vinod Kumar Yadav & Santosh Ghosh, 2020. "Constraints for effective distribution network expansion planning: an ample review," 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. 11(3), pages 531-546, June.
    8. Detroja, Ketan P., 2016. "Optimal autonomous microgrid operation: A holistic view," Applied Energy, Elsevier, vol. 173(C), pages 320-330.

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