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Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network

Author

Listed:
  • Yi Yu

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China
    Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Xishan Wen

    (School of Electrical Engineering, Wuhan University, Wuhan 430072, China)

  • Jian Zhao

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
    Department of Electrical Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Zhao Xu

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

  • Jiayong Li

    (Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China)

Abstract

The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN) daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.

Suggested Citation

  • Yi Yu & Xishan Wen & Jian Zhao & Zhao Xu & Jiayong Li, 2018. "Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network," Energies, MDPI, vol. 11(2), pages 1-18, February.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:2:p:354-:d:130041
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    References listed on IDEAS

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    1. Faruqui, Ahmad & Harris, Dan & Hledik, Ryan, 2010. "Unlocking the [euro]53 billion savings from smart meters in the EU: How increasing the adoption of dynamic tariffs could make or break the EU's smart grid investment," Energy Policy, Elsevier, vol. 38(10), pages 6222-6231, October.
    2. Pepermans, G. & Driesen, J. & Haeseldonckx, D. & Belmans, R. & D'haeseleer, W., 2005. "Distributed generation: definition, benefits and issues," Energy Policy, Elsevier, vol. 33(6), pages 787-798, April.
    3. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    4. Afgan, Naim H. & Carvalho, Maria G. & Hovanov, Nikolai V., 2000. "Energy system assessment with sustainability indicators," Energy Policy, Elsevier, vol. 28(9), pages 603-612, July.
    5. Bradley, Peter & Leach, Matthew & Torriti, Jacopo, 2013. "A review of the costs and benefits of demand response for electricity in the UK," Energy Policy, Elsevier, vol. 52(C), pages 312-327.
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    Cited by:

    1. Kuihua Wu & Kun Li & Rong Liang & Runze Ma & Yuxuan Zhao & Jian Wang & Lujie Qi & Shengyuan Liu & Chang Han & Li Yang & Minxiang Huang, 2018. "A Joint Planning Method for Substations and Lines in Distribution Systems Based on the Parallel Bird Swarm Algorithm," Energies, MDPI, vol. 11(10), pages 1-14, October.
    2. Yongli Wang & Yujing Huang & Yudong Wang & Haiyang Yu & Ruiwen Li & Shanshan Song, 2018. "Energy Management for Smart Multi-Energy Complementary Micro-Grid in the Presence of Demand Response," Energies, MDPI, vol. 11(4), pages 1-19, April.
    3. Fei Wang & Kangping Li & Xinkang Wang & Lihui Jiang & Jianguo Ren & Zengqiang Mi & Miadreza Shafie-khah & João P. S. Catalão, 2018. "A Distributed PV System Capacity Estimation Approach Based on Support Vector Machine with Customer Net Load Curve Features," Energies, MDPI, vol. 11(7), pages 1-19, July.
    4. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.

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