Strategic Bidding Model for Load Service Entities Considering Priced-Based and Incentive-Based Demand Response

Due to the volatility of energy purchase prices caused by the randomness of new energy generation, load serving entities (LSEs) as electricity retailers are at risk of lost profits. Demand response has the potential to help smooth price volatility by alleviating energy shortages. However, it is difficult for LSEs to formulate an optimal bidding strategy because of the demand response uncertainty. Therefore, to maximize the profits of LSEs, this paper proposes a bi-level strategic bidding model for LSEs considering priced-based and incentive-based demand response. Based on the survey dataset, the upper bound of reliable aggregate capacity is determined with chance constraints. The upper and lower level problems are decoupled by the Karush-Kuhn-Tucher conditions, and the objective function is linearized by the strong duality theory. Finally, the bi-level model is transformed into a mathematical problem with equilibrium constraints. With this method, LSEs can determine optimal incentive prices and bidding capacities to avoid extreme energy prices for maximum profit. The effectiveness of the proposed method is verified in a modified IEEE 39 bus system.