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Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion

Author

Listed:
  • Jing Qiu

    (Energy Flagship, The Commonwealth Scientific and Industrial Research Organization (CSIRO), Mayfield West, NSW 2304, Australia)

  • Junhua Zhao

    (School of Science and Engineering, Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China)

  • Dongxiao Wang

    (Center for Intelligent Electricity Networks, The University of Newcastle, Callaghan, NSW 2308, Australia)

Abstract

This paper presents a multi-objective transmission expansion planning (TEP) framework. Rather than using the conventional deterministic reliability criterion, a risk component based on the probabilistic reliability criterion is incorporated into the TEP objectives. This risk component can capture the stochastic nature of power systems, such as load and wind power output variations, component availability, and incentive-based demand response (IBDR) costs. Specifically, the formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to conduct risk analysis. Thus, a final expansion plan can be selected according to individual risk preferences. Moreover, the economic value of IBDR is modeled and integrated into the cost objective. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and risk are provided. The proposed approach is numerically verified on the Garver’s six-bus, IEEE 24-bus RTS and Polish 2383-bus systems. Case study results demonstrate that the proposed approach can effectively reduce cost and hedge risk in relation to increasing wind power integration.

Suggested Citation

  • Jing Qiu & Junhua Zhao & Dongxiao Wang, 2017. "Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion," Energies, MDPI, vol. 10(7), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1036-:d:105399
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    Citations

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    Cited by:

    1. Faezeh Akhavizadegan & Lizhi Wang & James McCalley, 2020. "Scenario Selection for Iterative Stochastic Transmission Expansion Planning," Energies, MDPI, vol. 13(5), pages 1-18, March.
    2. Yuhong Wang & Lei Chen & Hong Zhou & Xu Zhou & Zongsheng Zheng & Qi Zeng & Li Jiang & Liang Lu, 2021. "Flexible Transmission Network Expansion Planning Based on DQN Algorithm," Energies, MDPI, vol. 14(7), pages 1-21, April.
    3. Zipeng Liang & Haoyong Chen & Xiaojuan Wang & Idris Ibn Idris & Bifei Tan & Cong Zhang, 2018. "An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty," Energies, MDPI, vol. 11(8), pages 1-22, August.

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