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Mitigation Strategy for Duck Curve in High Photovoltaic Penetration Power System Using Concentrating Solar Power Station

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  • Qi Wang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Ping Chang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Runqing Bai

    (Electric Power Research Institute, State Grid Gansu Electric Power Company, Lanzhou 730070, China)

  • Wenfei Liu

    (Electric Power Research Institute, State Grid Gansu Electric Power Company, Lanzhou 730070, China)

  • Jianfeng Dai

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yi Tang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

Abstract

Concentrating solar power (CSP) station is counted as a promising flexible power supply when the net load power curve is duck-shaped in high photovoltaic (PV) penetration power system, which may lead to the serious phenomenon of PV curtailment and a large-capacity power shortage. This paper presents a mitigation strategy that replaces thermal power station with CSP station to participate in the optimal operation of power system for solving the duck-shaped net load power curve problem. The proposed strategy utilizes the dispatchability of thermal storage system (TSS) and the fast output regulation of unit in the CSP station. Simultaneously, considering the operation constraints of CSP station and network security constraints of the system, an optimization model is developed to minimize the overall cost including operation and penalty. The results obtained by nonlinear optimization function demonstrate that the replacement of concentrating solar power (CSP) station contributes to reducing the PV curtailment and lost load, while increasing the available equivalent slope for power balance. Thus, the proposed mitigation strategy can promote the penetration of PV generation and improve the flexibility of power system.

Suggested Citation

  • Qi Wang & Ping Chang & Runqing Bai & Wenfei Liu & Jianfeng Dai & Yi Tang, 2019. "Mitigation Strategy for Duck Curve in High Photovoltaic Penetration Power System Using Concentrating Solar Power Station," Energies, MDPI, vol. 12(18), pages 1-16, September.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3521-:d:266874
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    1. Alberto Bocca & Luca Bergamasco & Matteo Fasano & Lorenzo Bottaccioli & Eliodoro Chiavazzo & Alberto Macii & Pietro Asinari, 2018. "Multiple-Regression Method for Fast Estimation of Solar Irradiation and Photovoltaic Energy Potentials over Europe and Africa," Energies, MDPI, vol. 11(12), pages 1-17, December.
    2. Feng Qi & Fushuan Wen & Xunyuan Liu & Md. Abdus Salam, 2017. "A Residential Energy Hub Model with a Concentrating Solar Power Plant and Electric Vehicles," Energies, MDPI, vol. 10(8), pages 1-17, August.
    3. Jia Ning & Yi Tang & Qian Chen & Jianming Wang & Jianhua Zhou & Bingtuan Gao, 2017. "A Bi-Level Coordinated Optimization Strategy for Smart Appliances Considering Online Demand Response Potential," Energies, MDPI, vol. 10(4), pages 1-16, April.
    4. Zhao, Haoran & Wu, Qiuwei & Hu, Shuju & Xu, Honghua & Rasmussen, Claus Nygaard, 2015. "Review of energy storage system for wind power integration support," Applied Energy, Elsevier, vol. 137(C), pages 545-553.
    5. Nan Zhou & Nian Liu & Jianhua Zhang & Jinyong Lei, 2016. "Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response," Energies, MDPI, vol. 9(8), pages 1-24, July.
    6. Du, Ershun & Zhang, Ning & Hodge, Bri-Mathias & Kang, Chongqing & Kroposki, Benjamin & Xia, Qing, 2018. "Economic justification of concentrating solar power in high renewable energy penetrated power systems," Applied Energy, Elsevier, vol. 222(C), pages 649-661.
    7. Hernández, J.C. & Medina, A. & Jurado, F., 2007. "Optimal allocation and sizing for profitability and voltage enhancement of PV systems on feeders," Renewable Energy, Elsevier, vol. 32(10), pages 1768-1789.
    8. Domínguez, R. & Conejo, A.J. & Carrión, M., 2014. "Operation of a fully renewable electric energy system with CSP plants," Applied Energy, Elsevier, vol. 119(C), pages 417-430.
    9. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Von Bremen, L. & Tovar-Pescador, J., 2015. "Combining wind farms with concentrating solar plants to provide stable renewable power," Renewable Energy, Elsevier, vol. 76(C), pages 539-550.
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