在双碳目标背景下,为实现电网调峰以消纳更多新能源以及传统火电的节能减排需求,该文建立配合储能系统及大规模风电并网的不同调峰深度下火电机组环境经济调度模型,分析火电机组的调峰能力以及不同调峰深度下机组的煤耗特性和CO2排污特性的变化;提出一种不同调峰深度下的惩罚因子,将多目标环境经济调度转化为单目标优化,并给出一种改进的灰狼算法以求解模型。与原始灰狼算法和粒子群算法相比,该文提出的算法具有更好的优化性能。算例结果表明：在RPR和DPR调峰阶段,系统煤耗成本和CO2排放量随调峰深度增加而减小;在DPRO调峰阶段,CO2排放量随调峰深度增加而增加。储能系统发挥了削峰填谷的作用,大幅减小弃风,降低了系统运行的总成本。
Abstract
Under the background of carbon neutrality and emission peak, in order to achieve the aim of peak-load regulation of power grid to satisfy the demands of more accommodation capacity to new energy and energy conservation and emission reduction of traditional thermal power, this paper puts forward an environmental economic dispatch model of thermal power units at different peak-load regulation depths in large-scale wind power connected to grid with energy-storage system, analyzes the peak-load regulation capacity of thermal power units and the changes of characteristics of coal consumption and CO2 emission at different peak-load regulation depths, proposes a penalty factor at different peak-load regulation depths to transform multi-objective environmental economic dispatch into single-objective optimization,and establishes an improved gray wolf optimization to solve the model. Compared with the original gray wolf optimization and the particle swarm optimization, the improved gray wolf optimization has better optimization performance. The results show that the cost of coal consumption and CO2 emission decline with the adding of peak-load regulation depth in RPR and DPR, and the CO2 emission increases with the adding of peak-load regulation depth in DPRO. Energy-storage system can play the role of decreasing peak load and increasing valley load, greatly reducing the rate of wind curtailment and the total cost of the system.
关键词
环境经济调度 /
二氧化碳 /
燃煤 /
调峰 /
负荷分配 /
改进灰狼算法
Key words
environmental economic dispatch /
carbon dioxide /
coal combustion /
peak-load regulation /
load distribution /
improved gray wolf optimization
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