Optimal multi-timescale demand side scheduling considering dynamic scenarios of electricity demand

Zhejing Bao, Wanrong Qiu, Lei Wu, Feng Zhai, Wenjing Xu, Baofeng Li, Zhijie Li

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

In this paper, an optimal multi-timescale demand side scheduling framework, i.e., the combination of week-ahead and day-ahead, for industrial customers is proposed. Different demand side management (DSM) techniques suitable for distinct week-ahead and day-ahead timescales cooperate for achieving the overall optimal demand scheduling in the entire multi-timescale frame. Specifically, in the week-ahead scheduling, a dynamic scenario generation method is proposed to accurately simulate uncertainties of customer electricity demand time-series during the scheduling horizon, which can represent not only the marginal distribution of possible customer loads at each time instant but also the joint distribution among multiple loads at different time instants. In addition, priorities of various DSM techniques accepted by DSM participants and their willingness are also considered, aiming at mitigating impacts on their normal manufacturing process. With actual historical load data of industrial customers from advanced metering infrastructure system, the dynamic scenario generation method is shown to be effective in preserving statistic features of load fluctuations, and the proposed optimal multi-timescale coordinated demand side scheduling model is demonstrated to be an effective DSM approach.

Original languageEnglish
Article number8269337
Pages (from-to)2428-2439
Number of pages12
JournalIEEE Transactions on Smart Grid
Volume10
Issue number3
DOIs
StatePublished - May 2019

Keywords

  • Demand side management (DSM)
  • optimization
  • scenarios
  • scheduling
  • uncertainty

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