基于电网考核指标的火电机组一次调频仿真与优化

Simulation and Optimization of Primary Frequency Modulation of Thermal Power Unit Based on Grid Assessment Index

通过分析内蒙古电网火电机组一次调频考核指标的定义、公式以及实际考核结果,在特定情景下针对15 s出力响应指数和30 s出力响应指数的考核计算公式提出了更为合理的修改建议;利用极限学习机算法搭建的神经网络模型在一次调频考核指标与一次调频性能的影响因素之间建立良好的非线性映射,并在此基础上根据特征变量的变异方向和程度,分析一次调频性能考核指标不合格的原因,提出改进和提升策略,优化机组运行。

The primary frequency modulation performance of thermal power generating units is critical to the power quality and safe and stable operation of the power grid. Based on the primary frequency modulation assessment indicators, it is urgent to improve the primary frequency modulation performance of thermal power generating units in the west Inner Mongolia power grid. Through the analysis of the definitions, formulas and actual assessment results of a frequency modulation assessment index, the assessment calculation formulas for 15 s output response index and 30 s output response index are proposed to provide more reasonable modification suggestions under specific scenarios. By using extreme learning algorithm, this paper builds the neural network model, establishes a satisfactory non-linear mapping between the primary frequency modulation assessment index and the influencing factors affecting the primary frequency modulation performance.On this basis, according to the variation direction and degree of the characteristic variable, this paper carries out reverse analysis to analyze the reason for the failure of the primary frequency modulation performance assessment index, and then propose targeted improvement and promotion strategies, which can directly guide the optimizing work.