Smart building real time pricing for offering load-side Regulation Service reserves

Provision of Regulation Service (RS) reserves to Power Markets by smart building demand response has attracted attention in recent literature. This paper develops tractable dynamic optimal pricing algorithms for distributed RS reserve provision. It shows monotonicity and convexity properties of the optimal pricing policies and the associated differential cost function. Then, it uses them to propose and implement a modified Least Squares Temporal Differences (LSTD) Actor-Critic algorithm with a bounded and continuous action space. This algorithm solves for the best policy within a pre-specified broad family. In addition, the paper develops a novel Approximate Policy Iteration (API) algorithm and uses it successfully to optimize the parameters of an analytic policy function. Numerical results are obtained to demonstrate and compare the Actor-Critic and Approximate Policy Iteration algorithms, demonstrating that the novel API algorithm outperforms the Bounded LSTD Actor-Critic algorithm in both computational effort and policy minimum cost.