考虑风电随机模糊不确定性的电力系统多目标优化调度计划研究

Multi-objective dispatch planning of power system considering the stochastic and fuzzy wind power

提出了一种考虑风电随机模糊多重不确定性的电力系统多目标调度计划新模型和相应的算法。首先,依据风电并网后的电力系统不确定环境实际提出以随机模糊变量描述风电功率,以区间形式表述负荷预测的不确定性。其次,以燃煤机组的购电费用和污染气体排放量最小为目标函数,构建考虑风电和负荷预测值不确定性的电力系统随机模糊多目标交易计划模型。然后,提出利用负荷的不等式区间约束将遗传算法的初始寻优种群模糊化,提出采用概率密度分布描述解的随机模糊分布特征,从而可获得兼顾多重不确定特征多目标交易计划解集。最后,以含10台燃煤机组和一个大型等值风电场的某省级系统为例进行模型和算法的求解验证,结果表明了提出模型和算法的合理性和有效性。

This paper presents a novel dispatch planning of the power system considering the stochastic and fuzzy characteristics and multiple uncertainties of large-scale wind power. Firstly, based on the actual uncertainty of power system integrating wind power, wind speed is modeled as random fuzzy variable, and the fluctuation of the load forecast uncertainty is expressed by the interval. Secondly, considering the multi-attribute uncertainty of wind power and load, a novel multi-objective unit commitment model which minimizes both the power purchase cost and emission of atmospheric pollutants of thermal generators is proposed. Then the initial optimization populations of genetic algorithm are fuzzed by inequality interval constraint of load. The probability density distribution is used to describe the stochastic and fuzzy characteristics of the solution. Therefore, the solution set of multi-objective considering multiple uncertain characteristics can be achieved. Finally, the proposed generation dispatch method is tested on a provincial grid containing ten thermal generators and a large wind farm. The results show the effectiveness of the proposed model and the approach.