考虑多种污染物时空分布的电力系统高维多目标优化调度策略

Many-objective optimization dispatching strategy for power system considering the temporal and spatial distribution of different pollutants

提出了一种全新的考虑多种污染物时空分布的电力系统高维多目标优化调度策略.首先,构建出一种真正适用于电力调度的火电厂污染物时空分布模型,首次将大气边界层的日变化考虑在内,充分体现了火电厂的污染物扩散特征,提升了结果的准确性;然后,结合各类污染物的时空分布特点及环境容量,建立同时减少发电成本、碳排放及PM_(2.5),SO_2,NO_2空气质量影响的高维多目标优化调度模型;最后,借助具有代表性的高维多目标优化算法获得近似的帕累托最优解集,并提出一种考虑目标特征与环境容量的多目标决策方法筛选折中解.采用自建的模拟城市案例以及广东省案例进行仿真,结果表明:所述调度方法不仅可以有效改善空气质量,还可根据环境容量的时空变化做出相应的调整,真正意义上实现经济、环保的电力调度.

A novel many-objective optimization dispatching strategy for power system considering the temporal and spatial distribution of different pollutants is proposed in this paper. Firstly, a thermal power plant pollutant temporal and spatial distribution model is constructed which is truly suitable for power dispatching. The diurnal variation of atmospheric boundary layer is taken into account for the first time, reflecting the pollutant dispersion characteristics of power plants and improving the accuracy. Then, combined with the temporal and spatial distribution characteristics of various pollutants and environmental capacity, a many-objective power dispatching model is constructed to reduce the generation cost, carbon emissions and the effects on air quality by PM_（2.5）, SO_2 and NO_2.The approximate Pareto optimal set is obtained by representative algorithms and a multi-objective decision method considering the features of different objectives and environmental capacity is proposed. The simulation results of the simulated city and Guangdong shows that the dispatching method can not only effectively improve air quality, but also be adjusted according to the environmental capacity, realizing the economic and environmental power dispatching in real sense.