Optimal Bi-Level Stochastic Energy Scheduling of Integrated Community Energy System

Abstract

In this paper, an optimal bi-level stochastic scheduling model based on multi-scenario stochastic programming for power demand of building consumers in integrated community energy systems (ICES) is proposed. As the upper level, the ICES operator optimizes the energy purchase scheduling and electricity prices to lower level consumers in order to maximize its revenue. On the premise of ensuring comfortable temperature, the buildings' consumers in lower level whose heating zone modeled by thermal dynamics adjust the flow rate of air-condition to minimize the expenditure according to electricity prices. Moreover, multi-scenario stochastic program is used to decrease the impact of wind power prediction errors on dispatch scheduling. The bi-level optimization problem is solved by the Karush-Kuhn-Tucker conditions and strong duality theorem. At last, a case of 33-node electric network and 9-node gas network is simulated to verify feasibility and validity of the proposed optimal bi-level buildings scheduling model.