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Microgrid Spinning Reserve Optimization with Improved Information Gap Decision Theory

Author

Listed:
  • Hong Zhang

    (Department of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
    Beijing Key Laboratory of Demand Side Multi-Energy Carriers Optimization and Interaction Technique, Beijing 100192, China)

  • Hao Sun

    (Department of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Qian Zhang

    (Department of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

  • Guanxun Kong

    (Department of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China)

Abstract

Distributed generation (DG) is an important method of energy generation that accelerates the decentralization process of centralized systems, and has been widely deployed in modern society due to its economical, sustainable, and environmentally friendly characteristics. However, with the tremendous development of DG, system reliability operations are facing increasingly severe challenges because of the fluctuations of the renewable generation. In this paper, a novel spinning reserve optimization method is proposed to maximize the maximum allowance of system uncertainty (MAoSU) under the premise of satisfying the preset system operational cost. Then, the success rate of DG off-grid operation is calculated by comparing the magnitude of optimal spinning reserve capacity with the power exchange between the main grid and the distributed grid. The simulation results show that decision-makers need to increase the operational cost to compensate for system uncertainty, and the percentage increase of the operational cost is in proportional to the MAoSU and system renewable energy penetration rate. Additionally, with the increase of the MAoSU, the system needs to prepare more spinning reserve capacity to maintain system reliability operations. Finally, with the decrease of the MAoSU, the success rate of system off-grid operation decreases sharply, especially when the MAoSU is less than 0.5.

Suggested Citation

  • Hong Zhang & Hao Sun & Qian Zhang & Guanxun Kong, 2018. "Microgrid Spinning Reserve Optimization with Improved Information Gap Decision Theory," Energies, MDPI, vol. 11(9), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2347-:d:168034
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    References listed on IDEAS

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