LAUSR

Abstract Rising penetrations of renewable distributed generations (RDG) units at the demand side in residential power markets imply a reduction in the revenue of a power plant. In addition, the intermittent nature of RDG units requires the power plant to maintain the generation capacity to meet the demand during the intermittent periods. This paper derived two resilient three-part tariff (TPT) pricing policies based on either the time-of-use (ToU) pricing or the increasing-block pricing (IBP) schemes. The proposed pricing policies aim to maximize the power plant profit and the social welfare of users (consumers and prosumers) and recover the losses related to the uncertainties in energy supply and demand. To handle hybrid uncertainties in demand and capacity, a novel mixed type-2 fuzzy stochastic approach based on the integration of a type-2 fuzzy set and scenario-based stochastic programming is proposed. The application of the proposed model was examined using an empirical case study. Our results indicated that the resilient TPT with ToU could help power plants improve their profits by approximately 41.14% compared to those earned through the traditional two-part tariff. Furthermore, a decision matrix is proposed to allow the power plant to visualize an appropriate tariff plan amongst various options accurately.