Community microgrid scheduling considering building thermal dynamics

Abstract

This paper proposes a scheduling model for community microgrids considering the building thermal dynamics and customer comfort preference. The proposed optimization framework minimizes the total cost of operating the community microgrid, including fuel cost, purchasing cost, battery degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation from the set point. The heating, ventilation and air-conditioning (HVAC) systems are scheduled intelligently to reduce the electricity cost while maintaining the indoor temperature in the comfort range set by customers. Numerical simulation results show significant saving in electricity cost by the proposed model.