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Analysis of protective device operation (identify problems) Analysis of energy use Correlation of power quality levels or energy use with important parameters (eg, voltage sag performance versus lightning flash density) Equipment performance as a function of power quality levels (equipment sensitivity reports)
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1142 On-line power quality data assessment
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On-line power quality data assessment analyzes data as they are captured The analysis results are available immediately for rapid dissemination Complexity in the software design requirement for on-line assessment is usually higher than that of off-line Most features available in off-line analysis software can also be made available in an online system One of the primary advantages of on-line data analysis is that it can provide instant message delivery to notify users of specific events of interest Users can then take immediate actions upon receiving the notifications Figure 1128 illustrates a simple message delivered to a user reporting that a capacitor bank located upstream from a data acquisition node called DataNode H09_5530 was energized at 05-15-2002 at 04:56:11 AM The message also details the transient characteristics such as the magnitude, frequency, and duration along with the relative location of the capacitor bank from the data acquisition node Figure 1129 shows another example of the on-line power quality assessment It shows the time trend of a fifth-harmonic current magnitude along with its statistical distribution The data and its analysis are displayed on a standard Web browser Here a user can analyze data up to the current time This on-line system has the capability of performing a full range of transient, harmonic, and steady-state characterization along with their statistical distribution analysis comparable to that in off-line assessment analysis 115 Application of Intelligent Systems Many advanced power quality monitoring systems are equipped with either off-line or on-line intelligent systems to evaluate disturbances and system conditions so as to make conclusions about the cause of the problem or even predict problems before they occur The applications of intelligent systems or autonomous expert systems in monitoring instruments help engineers determine the system condition rapidly
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Downloaded from Digital Engineering Library @ McGraw-Hill (wwwdigitalengineeringlibrarycom) Copyright 2004 The McGraw-Hill Companies All rights reserved Any use is subject to the Terms of Use as given at the website
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Figure 1128 On-line data analysis can send e-mail notifications to users about the occur-
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This is especially important when restoring service following major disturbances The implementation of intelligent systems within a monitoring instrument can significantly increase the value of a monitoring application since it can generate information rather than just collect data11 The intelligent systems are packaged as individual autonomous expert system modules, where each module performs specific functions Examples include an expert system module that analyzes capacitorswitching transients and determines the relative location of the capacitor bank, and an expert system module to determine the relative location of the fault causing a voltage sag Sections 1151 and 1152 describe the approach in designing an autonomous expert system for power quality data assessment, and give application examples
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1151 Basic design of an expert system for monitoring applications
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The development of an autonomous expert system calls for many approaches such as signal processing and rule-based techniques along with the knowledge-discovery approach commonly known as data mining Before the expert system module is designed, the functionalities or objectives of the module must be clearly defined In other words, the designers or developers of the expert system module must have a clear understanding about what knowledge they are trying to discover from volumes of raw measurement data This is very important since they will ultimately determine the overall design of the expert system module
Downloaded from Digital Engineering Library @ McGraw-Hill (wwwdigitalengineeringlibrarycom) Copyright 2004 The McGraw-Hill Companies All rights reserved Any use is subject to the Terms of Use as given at the website
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