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An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment

Author

Listed:
  • Whei-Min Lin

    (Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan)

  • Chung-Yuen Yang

    (Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 807, Taiwan)

  • Chia-Sheng Tu

    (College of Intelligence Robot, Fuzhou Polytechnic, Fuzhou 350108, China)

  • Ming-Tang Tsai

    (Department of Electrical Engineering, Cheng-Shiu University, Kaohsiung 833, Taiwan)

Abstract

This paper presents the scheduling dispatch of a microgrid (MG), while considering renewable energy, battery storage systems, and time-of-use price. For the risk evaluation of an MG, the Value-at-Risk (VAR) is calculated by using the Historical Simulation Method (HSM). By considering the various confidence levels of the VAR, a scheduling dispatch model of the MG is formulated to achieve a reasonable trade-off between the risk and cost. An Improved Bee Swarm Optimization (IBSO) is proposed to solve the scheduling dispatch model of the MG. In the IBSO procedure, the Sin-wave Weight Factor (SWF) and Forward-Backward Control Factor (FBCF) are embedded in the bee swarm of the BSO to improve the movement behaviors of each bee, specifically, its search efficiency and accuracy. The effectiveness of the IBSO is demonstrated via a real MG case and the results are compared with other methods. In either a grid-connected scenario or a stand-alone scenario, an optimal scheduling dispatch of MGs is carried out, herein, at various confidence levels of risk. The simulation results provide more information for handling uncertain environments when analyzing the VAR of MGs.

Suggested Citation

  • Whei-Min Lin & Chung-Yuen Yang & Chia-Sheng Tu & Ming-Tang Tsai, 2018. "An Optimal Scheduling Dispatch of a Microgrid under Risk Assessment," Energies, MDPI, vol. 11(6), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1423-:d:150339
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    References listed on IDEAS

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    Cited by:

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    2. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward blockchain-based renewable energy microgrid design considering default risk and demand uncertainty," Renewable Energy, Elsevier, vol. 163(C), pages 870-881.
    3. Wu, Zhongqun & Yang, Chan & Zheng, Ruijin, 2022. "Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid," Energy, Elsevier, vol. 245(C).
    4. Qi Wang & Dasong Sun & Jianxiong Hu & Yi Wu & Ji Zhou & Yi Tang, 2019. "Risk Assessment Method for Integrated Transmission–Distribution System Considering the Reactive Power Regulation Capability of DGs," Energies, MDPI, vol. 12(16), pages 1-14, August.
    5. Xiuyun Wang & Shaoxin Chen & Yibing Zhou & Jian Wang & Yang Cui, 2018. "Optimal Dispatch of Microgrid with Combined Heat and Power System Considering Environmental Cost," Energies, MDPI, vol. 11(10), pages 1-23, September.
    6. Mimica, Marko & Giménez de Urtasun, Laura & Krajačić, Goran, 2022. "A robust risk assessment method for energy planning scenarios on smart islands under the demand uncertainty," Energy, Elsevier, vol. 240(C).

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