基于改进差分进化算法的风电并网系统多目标动态经济调度

Multi-objective dynamic economic dispatch in wind power integrated system based on an improved differential evolution algorithm

大规模风电接入对传统经济调度提出了新的挑战。建立了综合考虑火电机组运行成本、污染气体排放成本、风电运行成本、备用成本的多目标动态经济调度模型,并引入正、负旋转备用约束来应对风电波动性对调度带来的影响。采用层次分析法将多目标优化模型转化成单目标优化模型。提出一种改进差分进化算法对模型进行求解,算法中引入正交初始化技术和控制参数自适应调整策略以提高种群的全局寻优能力。以IEEE30节点系统为例验证所提模型的合理性和算法的有效性。

Integrating large scale of wind power into power grid poses new challenges to the traditional economic dispatch （ED）. A multi-objective dynamic economic dispatch model considering the operating cost of fossil fired units and wind farms, the discharging cost of pollution, and the cost of reserve is formulated. The up spinning reserve and the down spinning reserve constraints are included to deal with the influence of wind power＇s waviness on ED. According to the analytic hierarchy process （AHP）, the multi-objective objective optimization model is transformed to a single objective optimization model. An improved differential evolution （DE） algorithm is developed to find the solution of the model. The algorithm embeds the orthogonal initialization technology and the adaptive adjustment strategy of controlling parameters to improve the global optimization ability of population. Taking the IEEE 30-bus system for instance, the rationality of the model and the effectiveness of the algorithm are verified.