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A Class of Control Strategies for Energy Internet Considering System Robustness and Operation Cost Optimization

Author

Listed:
  • Haochen Hua

    (Research Institute of Information Technology, Tsinghua University, Beijing 100084, China)

  • Chuantong Hao

    (Research Institute of Information Technology, Tsinghua University, Beijing 100084, China)

  • Yuchao Qin

    (Research Institute of Information Technology, Tsinghua University, Beijing 100084, China)

  • Junwei Cao

    (Research Institute of Information Technology, Tsinghua University, Beijing 100084, China)

Abstract

Aiming at restructuring the conventional energy delivery infrastructure, the concept of energy Internet (EI) has become popular in recent years. Outstanding benefits from an EI include openness, robustness and reliability. Most of the existing literatures focus on the conceptual design of EI and are lack of theoretical investigation on developing specific control strategies for the operation of EI. In this paper, a class of control strategies for EI considering system robustness and operation cost optimization is investigated. Focusing on the EI system robustness issue, system parameter uncertainty, external disturbance and tracking error are taken into consideration, and we formulate such robust control issue as a structure specified mixed H 2 / H ∞ control problem. When formulating the operation cost optimization problem, three aspects are considered: realizing the bottom-up energy management principle, reducing the cost involved by power delivery from power grid (PG) to microgrid (MG), and avoiding the situation of over-control. We highlight that this is the very first time that the above targets are considered simultaneously in the field of EI. The integrated control issue is considered in frequency domain and is solved by a particle swarm optimization (PSO) algorithm. Simulation results show that our proposed method achieves the targets.

Suggested Citation

  • Haochen Hua & Chuantong Hao & Yuchao Qin & Junwei Cao, 2018. "A Class of Control Strategies for Energy Internet Considering System Robustness and Operation Cost Optimization," Energies, MDPI, vol. 11(6), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1593-:d:153086
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    References listed on IDEAS

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    Cited by:

    1. Junwei Cao & Wanlu Zhang & Zeqing Xiao & Haochen Hua, 2019. "Reactive Power Optimization for Transient Voltage Stability in Energy Internet via Deep Reinforcement Learning Approach," Energies, MDPI, vol. 12(8), pages 1-17, April.
    2. Haochen Hua & Yuchao Qin & Jianye Geng & Chuantong Hao & Junwei Cao, 2019. "Robust Mixed H 2 / H ∞ Controller Design for Energy Routers in Energy Internet," Energies, MDPI, vol. 12(3), pages 1-16, January.
    3. Maximiliano Lainfiesta & Xuewei Zhang, 2020. "Frequency Stability and Economic Operation of Transactive Multi-Microgrid Systems with Variable Interconnection Configurations," Energies, MDPI, vol. 13(10), pages 1-20, May.
    4. Aleksander Jakimowicz, 2022. "The Energy Transition as a Super Wicked Problem: The Energy Sector in the Era of Prosumer Capitalism," Energies, MDPI, vol. 15(23), pages 1-31, December.

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