Expert systems for security trend analysis of transient-voltage-limited power systems

Abstract

In this dissertation, we apply expert system techniques and Transient Energy Function (TEF) method results for dynamic system security assessment (DSSA). The concept of power system vulnerability combines the effect of contingencies on the security level and its rate of change with the changing system conditions and/or parameters. Vulnerability of a power system can be computed using the results of the sensitivity analysis program of the TEF method. The computation of vulnerability requires a large amount of data obtained from the results of stability analysis programs and this data needs to be organized into a structured knowledge base for DSSA. Further, the power system operators combine the above stability results with their experience and understanding of the power system in deciding the necessary corrective actions. This decision making process, which is based on heuristic rules, can be better solved using expert system techniques than algorithmic techniques. This dissertation describes an implementation of an expert system for DSSA which uses data from the Northern States Power Company (NSP) in Minnesota under certain operating conditions. The NSP system is transient-voltage-limited, and the security index used by NSP is the Twin City Export Margin (TCEM). The TCEM is the difference in MW between the actual export of power from Twin Cities and its allowable limit computed from stability results. This security index is correlated to the normalized energy margin $\Delta V$ of the TEF method. The expert system finds the NSP loading trend and uses this trend to predict the trend of the security index, TCEM. The expert system also adjusts the trend of the controlling parameters so that the security index can be kept at a predefined safe and economic level. The expert system primarily uses a supervised learning scheme and has an interactive user interface with graphic output. The TEF method is used for calculating stability information and the sensitivities of the control parameters on the security index. The knowledge base of the expert system is updated using the results of the TEF method.