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An Optimization Model and Modified Harmony Search Algorithm for Microgrid Planning with ESS

Author

Listed:
  • Yang Jiao
  • Jing Wu
  • Qing-kun Tan
  • Zhong-fu Tan
  • Guan Wang

Abstract

To solve problems such as the high cost of microgrids (MGs), balance between supply and demand, stability of system operation, and optimizing the MG planning model, the energy storage system (ESS) and harmony search algorithm (HSA) are proposed. First, the conventional MG planning optimization model is constructed and the constraint conditions are defined: the supply and demand balance and reserve requirements. Second, an ESS is integrated into the optimal model of MG planning. The model with an ESS can solve and identify parameters such as the optimal power, optimal capacity, and optimal installation year. Third, the convergence speed and robustness of the ESS are optimized and improved. A case study comprising three different cases concludes the paper. The results show that the modified HSA (MHSA) can effectively improve the stability and economy of MG operation with an ESS.

Suggested Citation

  • Yang Jiao & Jing Wu & Qing-kun Tan & Zhong-fu Tan & Guan Wang, 2017. "An Optimization Model and Modified Harmony Search Algorithm for Microgrid Planning with ESS," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-11, August.
    • Handle: RePEc:hin:jnddns:8425458
    DOI: 10.1155/2017/8425458
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    Cited by:

    1. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    2. Shouheng Tuo & Zong Woo Geem & Jin Hee Yoon, 2020. "A New Method for Analyzing the Performance of the Harmony Search Algorithm," Mathematics, MDPI, vol. 8(9), pages 1-17, August.
    3. Youssef, Heba & Kamel, Salah & Hassan, Mohamed H. & Nasrat, Loai, 2023. "Optimizing energy consumption patterns of smart home using a developed elite evolutionary strategy artificial ecosystem optimization algorithm," Energy, Elsevier, vol. 278(C).

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