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A Cyber Physical Model Based on a Hybrid System for Flexible Load Control in an Active Distribution Network

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  • Yun Wang

    (Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Dong Liu

    (Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Chen Sun

    (Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

To strengthen the integration of the primary and secondary systems, a concept of Cyber Physical Systems (CPS) is introduced to construct a CPS in Power Systems (Power CPS). The most basic work of the Power CPS is to build an integration model which combines both a continuous process and a discrete process. The advanced form of smart grid, the Active Distribution Network (ADN) is a typical example of Power CPS. After designing the Power CPS model architecture and its application in ADN, a Hybrid System based model and control method of Power CPS is proposed in this paper. As an application example, ADN flexible load is modeled and controlled with ADN feeder power control by a control strategy which includes the normal condition and the underpowered condition. In this model and strategy, some factors like load power consumption and load functional demand are considered and optimized. In order to make up some of the deficiencies of centralized control, a distributed control method is presented to reduce model complexity and improve calculation speed. The effectiveness of all the models and methods are demonstrated in the case study.

Suggested Citation

  • Yun Wang & Dong Liu & Chen Sun, 2017. "A Cyber Physical Model Based on a Hybrid System for Flexible Load Control in an Active Distribution Network," Energies, MDPI, vol. 10(3), pages 1-20, February.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:3:p:267-:d:91401
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    References listed on IDEAS

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    1. Zaman, Forhad & Elsayed, Saber M. & Ray, Tapabrata & Sarker, Ruhul A., 2016. "Evolutionary algorithms for power generation planning with uncertain renewable energy," Energy, Elsevier, vol. 112(C), pages 408-419.
    2. Wenpeng Yu & Dong Liu & Yuhui Huang, 2013. "Operation Optimization Based on the Power Supply and Storage Capacity of an Active Distribution Network," Energies, MDPI, vol. 6(12), pages 1-16, December.
    3. Khodr, H.M. & El Halabi, N. & García-Gracia, M., 2012. "Intelligent renewable microgrid scheduling controlled by a virtual power producer: A laboratory experience," Renewable Energy, Elsevier, vol. 48(C), pages 269-275.
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    Cited by:

    1. Chen Sun & Dong Liu & Yun Wang & Yi You, 2017. "Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network," Energies, MDPI, vol. 10(8), pages 1-24, July.

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