Demand side flexibility for a Heat Booster Substation with ultra low temperature district heating

Ultra-low temperature district heating (ULTDH) systems improve the heat distribution efficiency by reducing thermal network losses and provide an easier access to Renewable Energy Sources (RES) by utilizing them as heat sources through Power-to-Heat solutions. In this study, Domestic Hot Water (DHW) preparation at a Heat Booster Substation (HBS) supplied with ULTDH is investigated for generating demand side flexibility. The main components of the HBS are a Hot Water Storage Tank (HWST) and an electric-driven heat pump. A genetic algorithm based control strategy is developed to optimally utilize the thermal energy storage capability of the HBS by intelligently scheduling the charging of the HWST based on time-varying electricity price signals. A multi-objective control strategy is designed to reduce energy costs while generating flexibility on the demand side. The components of the HBS are numerically modeled and experimentally validated to form a dynamic non-linear model of the HBS. Further, the data-driven seasonal ARIMA model, ARIMA(0, 1,1) x (0, 1, 1)168, is developed to forecast the DHW consumption based on a statistical analysis of the historic consumption profiles over a two-year period. The forecast RMSE of the DHW prediction model is less than 0.03 kg s-1 over the two-year test period, indicating that the prediction model is able to accurately forecast the DHW consumption of the residents. With the control-oriented HBS numerical model and the DHW prediction model serving as decision support tools, the developed control strategy is implemented at the HBS. Results show that in comparison to a rule-based control strategy, the developed control strategy demonstrates significant demand side flexibility while attaining energy cost savings of more than 91% and 84% at time resolutions of 15 and 30 min for the control interval respectively. With increased volatility in electrical prices due to higher penetration of RES, greater energy cost savings of more than 150% are observed.