基于多目标的含风电场动态环境经济调度

在倡导大力开发新能源的政策下,含风电场发展迅速。但其出力调度问题很复杂,需要综合经济和环境因素,针对风电功率预测误差大,在研究含风电场动态环境经济调度时,在发电成本中考虑了旋转备用成本,在约束条件中考虑风功率预测误差对旋转备用容量的需求,以发电总成本最小、污染物排放总量最小、购电总费用最小为目标,建立含风电场动态环境经济调度模型。采用非支配排序遗传算法III对模型求解,以获得多样的解集和良好的收敛性。在含有1个风电场的5机电力系统算例中的仿真研究验证了所提出的基于多目标含风电场动态环境经济调度方案的合理性。

Dynamic Environmental and Economic Dispatching of Wind Farm Based on Multi-objective

Wind farms are developing rapidly under the new policy on energy resources vigorously advocated by the state. Its output scheduling is very complex, and needs the integration of economic and environmental factors. Aiming at the large prediction error of wind power, in the dynamic environmental economic dispatch of wind farm, the cost of rotating reserve is taken into account within the generation cost, and the demand of wind power prediction error for rotating reserve capacity is taken into account within the constraint condition. Aiming at the minimum total cost of power generation, the minimum total pollutant emission and minimum total cost of electricity purchase, a dynamic environmental and economic dispatching model of wind farm is established. Non-dominated Sorting Genetic Algorithm-III is used to obtain diverse solution sets and good convergence. The simulation of a five-machine power system with a wind farm verifies the rationality of the proposed dynamic environmental economic scheduling scheme based on multi-objective wind farms.