基于改进免疫蚁群算法的风光水火蓄多源互补优化调度

A Study on the Multi-Source Complementary Optimized Scheduling of WindPhotovoltaic-Hydro-Thermal-Pumped Based on Improved Immune Ant Colony Algorithm

为提升风光水火蓄多源互补运行的经济性,计及不同类型电源的调峰特性,提出一种基于改进免疫蚁群算法的风光水火蓄多源互补优化调度策略。以火电机组的煤耗成本和启停成本、水电机组的发电成本、抽水蓄能的运行成本以及弃风弃光惩罚成本最低为优化目标,构建了风光水火蓄多源互补优化调度模型;提出改进的免疫蚁群算法对调度模型进行求解,改善了人工蚁群算法易陷入局部最优解的缺陷;通过夏、冬季典型日不同装机容量的抽水蓄能的算例仿真,表明所提模型可以充分利用抽水蓄能机组的“削峰填谷”以及能源之间的互补性,实现降低火电机组煤耗、新能源全额消纳、利用柔性电源调节的目的。

Considering the existing tariff mechanisms of different types of power sources and their peaking characteristics,in this paper we propose an optimized dispatching strategy for the multiple complementary sources of wind,water,and thermal energy storage based on an improved immune ant colony algorithm to improve the system economy.Firstly,an optimized dispatching model for the multiple complementary sources is constructed with the objectives of minimizing the coal consumption cost and start-up cost of thermal power units,the generation cost of hydro power units,the peaking cost of pumped hydro storage,and the penalty cost of wind and light abandonment.Secondly,the improved immune ant colony algorithm is used to solve the scheduling model,preventing the defect that the artificial ant colony algorithm is prone to falling into local optima.Finally,through the simulation of pumped storage units with different installed capacities on typical summer and winter days,it is shown that the proposed model can make full use of the"peak-shaving and valley-filling"of pumped storage units and the complementarity between energy sources to improve the operational efficiency of each power source,and achieve the objectives of reducing the fuel cost of thermal power,full consumption of new energy sources,and regulation with flexible power sources.