Scheduling and real-time control of flexible loads and storage in electricity markets under uncertainty

In many countries, groups of producers and consumers are organized into virtual entities to participate in electricity markets. These entities are called balance groups (BGs), or are given similar names, because they are responsible for maintaining an energy balance for the group, and experience costs in case of imbalances. With large shares of uncertain renewable energy sources (RES), BGs are exposed to the risk of high balancing costs. In this paper, we propose a day-ahead (DA) scheduling and a real-time (RT) control scheme to minimize the spot market and balancing costs of a BG using flexible loads and storage resources. In the DA scheduling problem, we account for RES and price uncertainties by formulating a two-stage stochastic optimization problem with recourse. The RT control problem is formulated as a stochastic model predictive control (MPC) problem that uses short-term RES forecasts. We demonstrate the performance of the proposed scheme considering a BG with a wind farm, an industrial load, and a pumped-storage plant. The results show that the proposed scheme reduces the BG costs, but the cost savings vary and are case dependent.