Multi-Period energy procurement policies for smart-grid communities with deferrable demand and supplementary uncertain power supplies

We analyze a multi-period energy procurement problem for an energy aggregator, which is responsible for the centralized control of energy procurement and consumption in a community with smart grid installed. The aggregator can delay time-adjustable demand in the community through the smart grid if necessary. Furthermore, the aggregator can supply renewable energy as a supplementary power source to traditional electricity markets with pre-announced day-ahead real-time prices. To determine the optimal procurement amount, the aggregator needs to make tradeoffs between two types of power supplies, namely, traditional energy with variable prices versus free renewable energy with uncertain supplies. We solve the aggregator’s problem using dynamic programming and show that the optimal procurement policy is to procure traditional energy only when the price is below a threshold, which depends on the statistics of the day-ahead real-time price, wind energy distribution and the time left until the end of horizon. Through numerical studies, we compare the optimal policy with two other commonly-used policies in the wind energy setting, procurement based on the estimated supplies of wind energy and procurement up to the arrived demand. The cost-savings of our optimal policy are remarkable if the day-ahead real-time price fluctuates considerably. We also examine the robustness of our optimal policy in the scenarios of using historical wind energy data.