白晶,张志坚,王卫,周运斌,张绍峰.新型电力系统中高压感应电机起动过程不同算法的对比研究[J].电测与仪表,2023,60(7):70-76. BAI Jing,ZHANG zhijian,WANG wei,ZHOU yunbin,ZHANG Shaofeng.Comparative study on different algorithms of starting process of high voltage induction motor in novel power system[J].Electrical Measurement & Instrumentation,2023,60(7):70-76.
新型电力系统中高压感应电机起动过程不同算法的对比研究
Comparative study on different algorithms of starting process of high voltage induction motor in novel power system
The carbon emission of the power industry is the main component of carbon emissions in China. To achieve the double carbon goal, it is an inevitable trend to build a novel low-carbon power system. However, a large number of new energy sources lead to low overload capacity of the power system. The starting of large induction motors may lead to equipment disconnection, which will adversely affect the stability of the system. Therefore, the efficient and accurate calculation of large motor starting process is particularly important for the transient time domain simulation of novel power system. In this paper, traditional explicit Euler, implicit Euler, implicit trapezoid and Runge Kutta algorithms are compared and studied from the aspects of accuracy, stability and simulation efficiency. The implicit trapezoid algorithm has the advantages of accuracy and efficiency, but it is easy to cause numerical oscillation with large time step. On this basis, an improved trapezoidal efficient stability algorithm is proposed, variable parameters are introduced into the traditional algorithm, and the optimal parameter interval for reliable convergence of the algorithm is determined. Compared with the traditional trapezoidal method, the algorithm can effectively solve the numerical oscillation problem without increasing the computational complexity. Taking a 600 kW motor starting as an example, it is verified that the improved algorithm has no numerical oscillation problem, which shows the effectiveness and feasibility of the improved trapezoidal method, and provides a reference for the selection of efficient simulation algorithms for novel low-carbon power system.