Abstract
Optimization of Thermal Storage Operation and Selection of Heat Source are reported. Thermal storage system is the most difficult subsystem to operate and control in accordance with the design philosophy, while this subsystem governs energy conservation and effective use of energy source. Temperature profiles are the most convenient and meaningful measures to design and control the thermal storage. Thus, temperature profiles are used to predict the state of storage, and they are predicted via the prediction of heat load. Heat load is to be estimated and predicted using Kalman filter on day-base as well as time-base, which is quite useful to apply for instationary and nonergodic systems. Results are shown with actual data to evaluate the effectiveness of this optimization methodology. Co-relation between heat load and outside-air-temperature and/or solar insolation are also described.
