Distribution Network Pricing for Uncertain Load Growth Using Fuzzy Set Theory

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.