Optimal control of a bio-based phase change material thermal energy storage for demand response

In this study, the design and development of an optimal control strategy for the operation of an innovative bio-wax phase change material based pillow plate thermal energy storage unit delivering space heating to a four-storey-high research building is presented. The hydronic heating system in the ZEB-laboratory comprises an electric driven heat pump, the thermal storage unit and hydronic radiators. Numerical control-oriented dynamic models to simulate the phase-change dynamics of the thermal system are developed and validated. To predict the hourly heating load of the building reliably and accurately, a 14-node Resistance-Capacitance thermal network model is developed to be employed as a decision support tool. An optimal model-based predictive control strategy based on the validated system models is developed for application in real-time operation of the thermal storage unit. The control strategy is designed to optimally utilize the energy storage capability of the thermal energy storage unit to generate demand flexibility in response to time-varying electricity price signals. In comparison to a rule based control, the developed optimal control demonstrates a high degree of flexibility - as quantified by values of flexibility factor close to 1 being obtained - indicating a system operating with maximum flexibility, during one month of operation. Further, results demonstrate the availability of storage capacity of 100 kW h-200 kWh per day on average, indicating the capability of the optimized operation of the thermal energy storage unit to provide grid ancillary services. In addition to being demand flexible, the optimal charging schedule reduces the energy consumption and cost by about 40% - 50% on average. Thus, the developed optimal control strategy demonstrates a significant capability to generate and maximize demand flexibility to shift loads intelligently, provide grid services, and reduce energy cost and consumption.