直流输电控制保护定值智能校核关键技术研究

Key technology research on intelligent verification of DC transmission control and protection calibration values

针对当前直流输电系统中控制保护校核存在精度与自动化水平均较低的问题,设计了一种基于改进多目标量子粒子群算法的智能校核技术方案。该方案在选取相关指标参数并根据其特性建立耦合波动参数解析模型的基础上,将模型的求解转化为多目标优化问题。采用经差分进化算子改进的多目标QPSO算法实现了问题的求解进而完成校核。对直流输电控制系统中保护参数样本集进行测试,结果表明,所提算法能够实现对直流输电系统控制保护参数的准确、高效校核,且协方差最低值小于0.07,具有良好的自动化水平,有助于系统的安全、稳定运行。

In response to the low accuracy and automation level of control and protection verification in current DC transmission systems,an intelligent calibration technology scheme based on improved multi⁃objective Quantum Particle Swarm Optimization algorithm is proposed.On the basis of selecting relevant indicator parameters and establishing a coupled fluctuation parameter analysis model based on their characteristics,this scheme transforms the solution of the model into a multi⁃objective optimization problem.The multi⁃objective QPSO algorithm improved by differential evolution operator was used to solve the problem and complete the verification.The results of testing the sample set of protection parameters in the DC transmission control system show that the proposed algorithm can achieve accurate and efficient verification of control and protection parameters in the DC transmission system,and the minimum covariance value is less than 0.07.It has a good level of automation and contributes to the safe and stable operation of the system.