Distributionally robust heat-and-electricity pricing for energy hub with uncertain demands

摘要

? 2022 Elsevier B.V.In this work, we investigate the energy market pricing problem of an energy hub (EH) under endogenous uncertain demands. While traditional pricing problems consider exogenous energy demands, in multi-energy scenarios, the difference between power and heat prices could affect the compliance of residents to use certain energy, and therefore affect the realization of stochastic demand. Moreover, the probability distribution of such endogenous uncertainty and how it is influenced by energy prices may not be known exactly. This article proposes a bilevel optimization framework based on the game theory containing an upper-level EH dispatch with energy pricing and a series of lower-level household energy management problems. This framework seeks for optimal heat-and-electricity market prices for both EH and users to minimize their expected costs. To address uncertain probability distributions in decision-making processes, a modified distributionally robust chance-constrained programming approach is employed. The results demonstrate that the proposed framework could provide an effective pricing scheme for EH.