Robust Investment for Demand Response in a Distribution Network considering Wind Power and Load Demand Uncertainties

Yi Yu, Jian Zhao, Zhao Xu, Jiayong Li, Xishan Wen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)


Due to the increasing penetration of wind power into the distribution network, preserving system security and reliability becomes a significant challenge for the system operator. In the smart grid environment, the demand side is required to take more responsibilities to accommodate the uncertainty of wind power generations, known as demand response (DR). To enable this feature in the utility grid, system-wide costs, which include metering, communication and load control system upgrade cost and incentive cost for customers, should be considered in assessing cost-effectiveness. This paper proposes a novel optimization model for demand response facility (DRF) investment to determine the DR sizing and siting. Robust optimization is adopted to maintain overall economic benefit and distribution network operation security. The problem is formulated as a bi-level mixed-integer program. A column-and-constraint generation algorithm (C&CG) combined with outer-approximation (OA) linearization method is employed to solve this problem. Numerical tests on a modified IEEE 33-bus distribution network illustrate the effectiveness and validation of the proposed model.

Original languageEnglish
Article number20180218
JournalInternational Journal of Emerging Electric Power Systems
Issue number2
Publication statusPublished - Feb 2019


  • active distribution network
  • demand response
  • robust optimization
  • uncertainty

ASJC Scopus subject areas

  • Energy Engineering and Power Technology


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