Distribution Network Pricing for Uncertain Load Growth Using Fuzzy Set Theory

Chenghong Gu, Wenjiang Yang, Yonghua Song, Furong Li

Research output: Contribution to journalArticlepeer-review

25 Citations (SciVal)
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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
Issue number4
Publication statusPublished - 28 Jan 2016


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