Price-Maker Economic Bidding in Two-Settlement Pool-Based Markets: The Case of Time-Shiftable Loads

In this paper, a new scenario-based stochastic optimization framework is proposed for price-maker economic bidding in day-ahead and real-time markets. The presented methodology is general and can be applied to both demand and supply bids. That is, no restrictive assumptions are made on the characteristics of the pool and its agents. However, our focus is on the operation of time-shiftable loads with deadlines, because they play a central role in creating load flexibility and enhancing demand response and peak-load shaving programs. Both basic and complex time-shiftable load types are addressed, where the latter includes time-shiftable loads that are uninterruptible, have per-time-slot consumption limits or ramp constraints, or comprise several smaller time-shiftable subloads. Four innovative analytical steps are presented in order to transform the originally nonlinear and hard-to-solve price-maker economic bidding optimization problem into a tractable mixed-integer linear program. Accordingly, the global optimal solutions are found for the price and energy bids within a relatively short amount of computational time. A detailed illustrative case study along with multiple case studies based on the California energy market data are presented. It is observed that the proposed optimal price-maker economic bidding approach outperforms optimal price-maker self-scheduling as well as even-load-distribution.