Distributed Opportunistic Scheduling in Power Systems an Optimal Stopping Approach

Demand response plays a key role in saving energy expenditure for future smart grid systems. For a system with multiple users which have different energy consumption and real-time requirements, the scheduling problem is quite challenging. In this work, we propose a novel distributed opportunistic scheduling scheme based on the optimal stopping rule approach. Our objective is to minimize the total energy cost while satisfying the energy and timing requirements of each user. We show that the optimal scheduling scheme is a pure threshold policy, i.e., each user need to be turned on when the electricity price is lower than a certain value; otherwise, remains idle. Our simulation results show that the proposed low-complexity distributed scheduling scheme can dramatically reduce the cost. A heuristic peak avoid approach is also proposed to bypass the peak peak price, which is a often a priori. Our result can also be implemented to the problem of maximizing profit with a fixed amount of energy, which is, in fact, the dual of the energy minimization problem.