Stochastic control and real options valuation of thermal storage-enabled demand response from flexible district energy systems

Highlights: • We calculate the real option value of flexibility from CHP-thermal storage. • Stochastic optimal feedback control problem is solved under uncertain market prices. • Efficient real-time numerical solutions combine simulation, regression and recursion. • Clear, interpretable feedback control maps are produced for each hour of the day. • We give a realistic UK case study using projected market gas and electricity prices. - Abstract: In district energy systems powered by Combined Heat and Power (CHP) plants, thermal storage can significantly increase CHP flexibility to respond to real time market signals and therefore improve the business case of such demand response schemes in a Smart Grid environment. However, main challenges remain as to what is the optimal way to control inter-temporal storage operation in the presence of uncertain market prices, and then how to value the investment into storage as flexibility enabler. In this outlook, the aim of this paper is to propose a model for optimal and dynamic control and long term valuation of CHP-thermal storage in the presence of uncertain market prices. The proposed model is formulated as a stochastic control problem and numerically solved through Least Squares Monte Carlo regression analysis, with integrated investment and operational timescale analysis equivalent to real options valuation models encountered in finance. Outputs are represented by clear and interpretable feedback control strategy maps for each hour of the day, thus suitable for real time demand response under uncertainty. Numerical applications to a realistic UK case study with projected market gas and electricity prices exemplify the proposed approach and quantify the robustness of the selected storage solutions