(203ai) Optimal Design of Building Thermal Energy Storage Systems

Energy consumption by Heating Ventilation and Air Conditioning (HVAC) systems is usually heaviest when electricity prices are at their highest. One approach to reducing energy costs is to employ Building Thermal Energy Storage (BTES) to time-shift power consumption away from periods of high power demand to periods of low power cost. In previous work, the method of Economic Model Predictive Control (EMPC) was shown to be effective at minimizing energy expenditures. Furthermore, the method Infinite Horizon EMPC (IH-EMPC) was proposed to significantly reduce computational effort while maintaining economic performance.

Clearly, an economic analysis of a BTES system must weigh the operational cost savings against the capital cost investments. Ideally, one would implement an optimal BTES design scheme with the objective of maximizing Net Present Value (NPV). In a previous effort, the an estimate of this optimal design was determined through use of a surrogate controller, known as Economic Linear Optimal Control (ELOC) which enforces constraints statistically, and assumed a Gaussian distribution for electricity prices. If one were to remove these assumptions, then a simulation based gradient search algorithm will be required. In this work, we illustrate have such an algorithm can be constructed, why a barrier approach must be used to enforce feasibility constraints and how IH-EMPC can be used to significantly improve computational efficiency.