Fundamental Research on Integrated Security Monitoring and Control Systems

本课题的研究目的是通过对主要功能的算法开发，完成对电力系统运行具有重要意义的综合安全监控系统。研究结果如下：1.在线事故分析功能：开发了一种基于P-Q解耦线性化模型的快速现实方法来进行事故分析。母线电压幅值和相角可以在快速解耦潮流计算时间的三分之一内计算。电压幅值的平均误差小于1%，电压相角的平均误差小于1 °.预防控制策略的确定：通过以下程序确定全球预防控制策略。首先，违反状态变量，即，计算了输电元件的真实的潮流和母线电压幅值。然后考虑真实的功率部分（P部分）的运行成本和无功功率部分（Q部分）的传输损耗，使这些违规最小化。采用非线性优化技术对该问题进行求解.紧急控制策略的确定：考虑控制变量的特性，即，控制周期在P-部分最小化，并且要调整的控制变量的数目在Q-部分最小化。通过对这两个子问题的连续优化，确定紧急控制策略.在线数据采集功能：通过对状态估计理论的优化和评价，证明动态状态估计的精度是静态状态估计的3倍。通过引入状态估计和数据采集系统的不良数据可检测性、可辨识性和可观测性的思想，为电力系统状态估计的测量优化配置奠定了基础。

The purpose of this research is to complete the integrated security monitoring and control system, which will play an important role in the operation of power systems, by developing the algorithm of main functions. The results may be summarized as follows:1. On-line contingency analysis function: A fast realistic method based on a P-Q decoupled linearized model was developed for the contingency analysis. Bus voltage magnitudes and phase angles could be calculated within one third of the computation time of the fast decoupled load flow calculation. Mean errors of voltage magnitudes were less than one per cent and those of voltage phase angles were less than one degree.2. Determination of preventive control strategy: The global preventive control strategy was determined by the following procedures. At first, violations of state variables, i.e., real power flows in transmission elements and voltage magnitudes of buses, were calculated. Then these violations were minimized considering the operating cost in the real power part (P-part) and the transmission losses in the reactive power part (Q-part). The nonlinear optimization technique was used to solve the problem.3. Determination of emergency control strategy: The problem was formulated considering the characteristics of control variables; i.e., the control period was minimized at P-part and the number of control variables to be adjusted were minimized at Q-part. The emergency control strategy was determined by optimizing these two subproblems successively.4. On-line data acquisition function: It could be proved that the accuracy of the dynamic state estimation was three times that of the static state estimation by optimization and evaluation of staste estimation theories. The basis of optimal allocation of measurements for power system state estimation was established by introducting the idea of bad data detectability and identifiability as well as observability of state estimation and data acquisition system.