Peak-Valley Time Period Partition of TOU Tariff Based on Fuzzy Equivalence Relation Clustering Algorithm

Time-of-Use (TOU) tariff is one of effective price-based demand response strategy, which can guide consumers to relieve the load peak pressure of power system and tap demand-side response potential. However, without considering the impact of pricing, improper peak-valley time period schemes may lead to a decrease in power supply reliability and an increase in operation costs of the power system. Therefore, this paper presents a peak-valley time period partition scheme of TOU tariff based on fuzzy equivalence relation clustering (FERC) algorithm. First, the solving steps and corresponding mathematical models of FERC algorithm are given, such as the characteristic indicator fuzzy set determined by the membership function and the fuzzy equivalence matrix. Secondly, the peak-valley characteristics of the load are first analyzed, and then a peak-valley period partition clustering based on FERC algorithm is proposed by combining semi-trapezoid membership functions and partition criterion constraints. Finally, the effectiveness of the proposed method is verified under a typical daily load in Hunan province. The results show that the proposed method can not only accurately reflect the peak valley characteristics of the load curve, but also effectively improve the calculation speed and convergence of peak-valley time period partition.