Quantifying the Flexibility of Centralized Hot Water Systems at a University Campus by Considering Demand Response Participation Uncertainty

Centralized hot water systems in university dormitories can provide significant energy flexibility through demand response (DR). Thus far, however, existing studies have mainly focused on system-level optimization and have failed to provide a quantitative framework that accounts for individual users’ DR participation behavior and the associated uncertainty. In this paper, we develop a data-driven approach to evaluate demand-side flexibility and quantify the uncertainty that arises as a result of user participation. A clustering-based stochastic load prediction model is proposed and validated using real operational data, serving as the baseline for DR load shifting. Four DR strategies for students are designed based on time-of-use pricing and/or academic credit incentives. A survey of nearly 1000 students is used to calibrate participation probabilities, while a binomial distribution model characterizes the uncertainty of user participation, allowing us to derive the probability distribution and expected value of the system’s flexibility potential. Compared with the no-DR baseline, the combined price–credit incentive yields the highest flexibility, achieving a peak-shaving rate of 62.66% and thus significantly outperforming the price-only strategy. Notably, the academic credit incentive alone increases students’ willingness to participate more effectively than price signals. Furthermore, when the number of participating users exceeds 648, the fluctuation range of the estimated flexibility potential falls below 10.5%, enabling stable flexibility evaluation with a moderately large user sample.