已有文献分析了传统的离散时间调度模型,并指出这类调度模型存在备用容量上、下限不可达的问题。该文进一步指出这类调度模型中存在备用容量上、下限约束过; 于严格、限制机组的深度变负荷能力的不足。以连续时间调度模型为基础,建立了充分发挥机组深度变负荷能力的风火电联合随机调度模型。仿真实验结果表明,这; 种含风电场的电力系统动态经济调度模型能有效应对风电出力的随机波动性特征,充分发挥机组深度变负荷能力,在保证系统可靠性的前提下能节省更多的成本。Some researchers analyzed the traditional discrete-time scheduling; model, and pointed out that the upper and lower bounds of spinning; reserve offered by thermal units are unreachable. We further find that; the upper and lower bounds of spinning reserve modeled in the; discrete-time scheduling model are too strict in some situation. In; order to solve this problem, we analyzed the thermal units supply; responses based on the continuous time scheduling. And then a stochastic; scheduling model of wind & thermal power joint operation was established; in consideration of the thermal units supply responses. Simulation; results show the new model can effectively cope with random fluctuation; characteristics of wind power output, take full advantage of the supply; responses of thermal units, and save more cost while guaranteeing the; system reliability.国家自然科学基金项目; 福建省自然科学基金项
