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Aggregating Large-Scale Generalized Energy Storages to Participate in the Energy and Regulation Market

Author

Listed:
  • Yao Yao

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

  • Peichao Zhang

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

  • Sijie Chen

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

Abstract

This paper proposes a concept of generalized energy storage (GES) to facilitate the integration of large-scale heterogeneous flexible resources with electric/thermal energy storage capacity, in order to participate in multiple markets. First, a general state variable, referred to as the degree of satisfaction (DoS), is defined, and dynamic models with a unified form are derived for different types of GESs. Then, a real-time market-based coordination framework is proposed to facilitate control, as well as to ensure user privacy and device security. Demand curves of different GESs are then developed, based on DoS, to express their demand urgencies as well as flexibilities. Furthermore, a low-dimensional aggregate dynamic model of a GES cluster is derived, thanks to the DoS-equality control feature provided by the design of the demand curve. Finally, an optimization model for large-scale GESs to participate in both the energy market and regulation market is established, based on the aggregate model. Simulation results demonstrate that the optimization algorithm could effectively reduce the total cost of an aggregator. Additionally, the proposed coordination method has a high tracking accuracy and could well satisfy a diversified power demand.

Suggested Citation

  • Yao Yao & Peichao Zhang & Sijie Chen, 2019. "Aggregating Large-Scale Generalized Energy Storages to Participate in the Energy and Regulation Market," Energies, MDPI, vol. 12(6), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:1024-:d:214354
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    References listed on IDEAS

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    Cited by:

    1. Qitian Mu & Yajing Gao & Yongchun Yang & Haifeng Liang, 2019. "Design of Power Supply Package for Electricity Sales Companies Considering User Side Energy Storage Configuration," Energies, MDPI, vol. 12(17), pages 1-16, August.
    2. Ricardo Faia & Pedro Faria & Zita Vale & João Spinola, 2019. "Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House," Energies, MDPI, vol. 12(9), pages 1-18, April.
    3. Yizhi Cheng & Peichao Zhang & Xuezhi Liu, 2019. "Collaborative Autonomous Optimization of Interconnected Multi-Energy Systems with Two-Stage Transactive Control Framework," Energies, MDPI, vol. 13(1), pages 1-21, December.
    4. Fernando Lezama & Ricardo Faia & Pedro Faria & Zita Vale, 2020. "Demand Response of Residential Houses Equipped with PV-Battery Systems: An Application Study Using Evolutionary Algorithms," Energies, MDPI, vol. 13(10), pages 1-18, May.

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