Electrothermal Flexibility for Demand Response Using Inverse Simulation

This paper provides a hierarchical optimization algorithm based on the inverse simulation for the exploitation of the flexibility of electrothermal heating systems in office buildings in a demand response schema led by an aggregator. Inverse simulation, based on the approximate differentiation method, is applied on local building level to turn the customer's comfort specifications, i.e., indoor temperature comfort zone, into the technical power and flexibility specifications and, hence, acceptable power schedules. The aggregator then optimizes for a global system level objective. We prove that the inverse simulation yields the same result as the forward simulation approach, whereas it protects the privacy and thermal comfort of the customer. Moreover, via a general use case, we provide an insight on how to optimally balance demand and supply on the system level.