Distribution Network Pricing for Uncertain Load Growth Using Fuzzy Set Theory

Chenghong Gu, Wenjiang Yang, Yonghua Song, Furong Li

Research output: Contribution to journalArticle

12 Citations (Scopus)
137 Downloads (Pure)

Abstract

The decarbonization of transport and heating will introduce uncertain smart appliance growth in the power system, which fundamentally challenges traditional network pricing. In this paper, a new long-term distribution network charging is proposed to accommodate uncertain load growth. Instead of using fixed a load growth rate (LGR), it adopts a fuzzy model, developed based on a set of projected deterministic LGRs and confidence levels. This fuzzy model is incorporated into the pricing model through {\alpha } -cut intervals. In order to improve computational efficiency, an analytical pricing approach is introduced. The vertex extension approach is used to build charge membership functions. Thereafter, a common defuzzification approach, center of gravity, is employed to defuzzify membership functions in order to generate deterministic charges. The new approach is benchmarked with two existing standard charging methods on a practical U.K. high-voltage distribution system. Results show that it is effective in capturing the uncertainty in load growth.
Original languageEnglish
Pages (from-to)1932 - 1940
Number of pages9
JournalIEEE Transactions on Smart Grids
Volume7
Issue number4
DOIs
Publication statusPublished - 28 Jan 2016

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