中文摘要：

为应对风电并网给电力经济调度带来的影响,构建了含风电场的多目标动态环境经济调度模型。该模型能同时兼顾燃料费用目标及污染排放目标,并计及阀点效应、网络损耗以及由风电不确定性引起的旋转备用需求。为求解该模型,达到为决策者提供最优调度方案集的目的,将基于分解的多目标进化算法（multi-objective evolutionary algorithm based on decomposition,MOEA/D）应用于动态调度领域。针对模型的复杂约束,在算法中加入对机组出力的实时调整及对约束违反量的适当惩罚,并利用归一化操作,避免算法向某一目标过度进化。经过对算例的仿真及对不同调度方案的对比分析,验证了所提调度模型的合理性以及改进MOEA/D算法解决此类问题的有效性。

英文摘要：

To cope with the impacts of grid-connected wind farm on power system economic dispatching, a multi-objective dynamic economic dispatching model, which can consider both fuel cost objective and pollution emission objective simultaneously as well take valve point effect, network loss and the demand on spinning reserve due to the uncertainty of wind power, is constructed. To solve the constructed model and achieve the aim of providing decision-maker the optimal dispatching scheme, the multi-objective evolutionary algorithm based on decomposition （MOEA/D） is applied in the field of dynamic dispatching. In allusion to complex constraints in the model, the real-time regulation of unit output and adequate penalty on violating extent of constraints are added into the algorithm, and the normalized operation is utilized to avoid excessive evolution of the algorithm towards a certain objective. Through simulation of a 10-machine system and contrastive analysis on different dispatching schemes, the reasonableness of the proposed dispatching model as well as the effectiveness of using the improved MOEA/D algorithm to solve such a kind of problem are validated.