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Dynamic Economic Dispatch Model of Microgrid Containing Energy Storage Components Based on a Variant of NSGA-II Algorithm

Author

Listed:
  • Fei Zhao

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Jinsha Yuan

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

  • Ning Wang

    (School of Electrical and Electronic Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

With the development of microgrid, in order to improve the economy of the microgrid and intelligent service of electric power marketing, the proper management of the output of micro-source in microgrid and power exchange between grids is an urgent problem to be solved. Considering the interests of multiple stakeholders, such as users, power grids, renewable energy and battery, a dynamic economic dispatch model of microgrid is proposed in this paper based on time-of-use power price mechanism. Using a variant of Non-Dominated Sorting Genetic Algorithm (NSGA)-II algorithm, at the same time, an external penalty function is introduced to deal with the constraint conditions, which is convenient for solving multi-objective optimization models. Based on the data of load forecasting and renewable energy output in microgrid, the function of battery and time-of-use power price mechanism is considered to optimize the output of controllable micro-source in the system, in order to achieve the optimization of microgrid dispatch. The model established in this paper considers the overall economic optimization of multi-objective and multi-interest groups within the microgrid, and hence, can get a more comprehensive and reasonable scheduling scheme. It provides effective help for the operation of micro grid system, and realizes the electric power marketing for demand side, so as to provide help for improving the power marketing’s economy and intelligent service.

Suggested Citation

  • Fei Zhao & Jinsha Yuan & Ning Wang, 2019. "Dynamic Economic Dispatch Model of Microgrid Containing Energy Storage Components Based on a Variant of NSGA-II Algorithm," Energies, MDPI, vol. 12(5), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:871-:d:211361
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    References listed on IDEAS

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    1. Hawkes, A.D. & Leach, M.A., 2009. "Modelling high level system design and unit commitment for a microgrid," Applied Energy, Elsevier, vol. 86(7-8), pages 1253-1265, July.
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    Cited by:

    1. Kaiye Gao & Tianshi Wang & Chenjing Han & Jinhao Xie & Ye Ma & Rui Peng, 2021. "A Review of Optimization of Microgrid Operation," Energies, MDPI, vol. 14(10), pages 1-39, May.
    2. Hyung-Joon Kim & Mun-Kyeom Kim, 2019. "Multi-Objective Based Optimal Energy Management of Grid-Connected Microgrid Considering Advanced Demand Response," Energies, MDPI, vol. 12(21), pages 1-28, October.
    3. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    4. Senthilkumar Subramanian & Chandramohan Sankaralingam & Rajvikram Madurai Elavarasan & Raghavendra Rajan Vijayaraghavan & Kannadasan Raju & Lucian Mihet-Popa, 2021. "An Evaluation on Wind Energy Potential Using Multi-Objective Optimization Based Non-Dominated Sorting Genetic Algorithm III," Sustainability, MDPI, vol. 13(1), pages 1-29, January.
    5. Óscar Gonzales-Zurita & Jean-Michel Clairand & Elisa Peñalvo-López & Guillermo Escrivá-Escrivá, 2020. "Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids," Energies, MDPI, vol. 13(13), pages 1-29, July.
    6. Ahmed I. Omar & Ziad M. Ali & Mostafa Al-Gabalawy & Shady H. E. Abdel Aleem & Mujahed Al-Dhaifallah, 2020. "Multi-Objective Environmental Economic Dispatch of an Electricity System Considering Integrated Natural Gas Units and Variable Renewable Energy Sources," Mathematics, MDPI, vol. 8(7), pages 1-37, July.

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