Optimized Scheduling for Improving Wind Power Accommodation Ability Based on Controllable Load

Aiming at the problem of high heat load and low power load during the winter heating period in the Three North region, the combined heating and power dispatching model is built with the heat storage electric boiler equipped in multi-region thermal power plants as controllable load. The improved particle swarm optimization algorithm is applied to iteratively find the solution. The problems of heating up by curtailed wind power, wind power local consuming, and wind power accommodation ability are studied in this paper. A bi-level scheduling optimization model is established that takes into account the influence of wind power curtailment and controllable loads. The upper-level optimization is to minimize electricity purchase cost of controllable load by scheduling it. The lower-level model is to minimize power generation cost by scheduling the units and provide the spot electricity price to the upper-level model. The case study is carried out, in which the bi-level optimization model is transformed into a single-level optimization model with equilibrium constraints by KKT condition and then solved by Matlab. The optimization results show that the heat storage during the wind power curtailment period and the coordinated heat supply between the regions can effectively utilize the heat storage capacity of the heat storage tank, improve the wind power acceptance and optimize the unit generation cost.