Demand-side management program planning using stochastic load forecasting with extreme value theory

Young Min Wi, Seongbae Kong, Jaehee Lee, Sung Kwan Joo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Demand-side management (DSM) is easy to apply to reduce system peak load by a utility and it can be a convenient way to control and change amount of electric usage by end-use customers. Planning and operating techniques for a DSM program are required to efficiently manage and operate the program. This paper is focused on planning technique for an incentive-based DSM program. This paper describes a stochastic model that can estimate the operating days, hours, and total capacity for efficiently planning a DSM program. A temperature stochastic process, from weather derivatives, is used in the proposed method. Temperature sensitivity is proposed to improve load forecasting accuracy. The generalized extreme value distribution is also proposed for estimating stochastic results. The results of case studies are presented to show the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)1093-1099
Number of pages7
JournalJournal of Electrical Engineering and Technology
Issue number5
Publication statusPublished - 2016 Sept

Bibliographical note

Funding Information:
This research was supported by Korea Electric Power Corporation through Korea Electrical Engineering & Science Research Institute. (No. R15XA03-45) This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIP) (No. 2015R1C1A1A01051928)

Publisher Copyright:
© The Korean Institute of Electrical Engineers.


  • Demand-side management program
  • Generalized extreme value distribution
  • Load forecasting
  • Temperature stochastic process

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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