基于分布式计算技术的火电厂辅助调频储能系统容量及功率规划方法

随着大量新能源并网，传统火电机组调频响应时间长、爬坡速率慢等缺点带来的反向效果越来越明显。储能系统可以用来缓解调频压力，大量研究证明储能系统可以应用于发电厂中火电机组的辅助调频。文章提出了一种基于分布式计算技术的火电厂辅助调频储能系统容量和功率规划方法。首先基于电网的“2个细则”建立电厂的收益模型。其次基于全寿命周期理论，建立储能系统成本模型，最后以电厂在全寿命周期内的综合收益最大化为目标函数，基于大量历史运行数据，采用基于分布式计算技术的粒子群优化算法进行仿真寻优，得到准确性较高的储能系统最优配置容量和功率。最后通过算例说明了储能系统辅助调频的效果以及分布式计算技术应用的必要性。

Capacity and Power Planning Method Based on Distributed Computing for Energy Storage Assisted Frequency Modulation in Thermal Power Plants

With the interconnection of a large number of new energy sources， the impact caused by the shortcomings of long response time and low climbing speed of thermal power units in the frequency regulation control of traditional power systems are becoming more and more obvious. The increasing development of energy storage system can be used to alleviate the pressure of frequency modulation. A large number of studies have proved that energy storage system can be applied to auxiliary frequency modulation of thermal power units in power plants. In this paper， a capacity and power planning method for auxiliary frequency modulation energy storage system of thermal power plant on the basis of distributed computing technology is proposed. Firstly， the profit model of power plant is established on the basis of the two rules of power grid. Secondly， the cost model of energy storage system is established on the basis of the life cycle theory. Finally， the optimal capacity and power allocation of energy storage system is obtained by using the particle swarm optimization algorithm based on distributed computing technology and taking the maximum comprehensive profit of power plant as the objective function. An example is given to illustrate the effect of auxiliary frequency modulation of energy storage system and the necessity of application of distributed computing technology.