基于多时间尺度随机优化的年度调峰辅助服务需求评估模型

In order to calculate the annual peak regulation demand of power system, this paper constructed an annual peak regulation auxiliary service demand assessment model based on multi-time scale stochastic optimization. This optimization model includes three stages: mid-and-long term, short term and peak regulation service stage. In the mid-and-long term stage, the model considers the randomness and balance of daily electricity quantity, maximum load and minimum load to optimize the unit maintenance, cross-day start-stop and reservoir water level plan. In the short-term stage, the model considers the power balance of source-load and its fluctuation to optimize units output and abandonment load expectation based on the mid-and-long term plan. In the peak regulation stage, the model simulates the start-stop conditions of auxiliary services by analyzing the daily peak regulation capacity and abandoned water. Besides, this stage considers the deep peak regulation and start-stop peak regulation capacity of thermal power units. The simulation results based on the actual data of a provincial power grid in China show that the model can effectively simulate the randomness of multi-time scale power, and realize the annual peak regulation demand assessment.