Source: ICEM-2002. Old St. Jan Conference Center, Brugge, Belgium, Conference Record N 9.
This paper outlines the basic architecture of "HELMOS", a knowledge based expert system implemented for the fault diagnosis and the detailed monitoring of generators and distribution substations in power plants.
Every circuit breaker and switch operation is recorded in the Digital Fault Recorder (DFR) of the plant. All current and voltage value are measured by the installed current and voltage transformers respectively. These signals are acquired by the presented computational system and are subsequently used for the generator and the substation state estimation.
The estimated state is compared to the measured state in order to detect any conflict that could intimate an abnormal situation. An intelligent algorithm is executed during a program scan cycle incorporating the stored knowledge of the expert operator. A thoughtfully designed monitoring system displays selected information in the control room that helps even not well trained personnel to recognize and face emergency signals whenever they appear.
Artificial Intelligence (AI) programs are developed and used in computer science since the early days of digital computers. Only during the last two decades though industry has taken advantage of those special features that make AI so unique in modeling and representing knowledge, as well as imitating the common sense reasoning. The continuous augmentation of available computational strength and low cost of modern microprocessors on one hand, and the software tools recently developed on the other, leaded in the remarkable expansion of AI applications in the domain of electrical power systems and power electronics.
Expert Systems among others is a very popular AI technique in industry. According to the working group D10 of the line protection subcommittee [1], an Expert System (ES) is a computer program that uses knowledge and inference procedures to solve problems that are ordinarily solved through human expertise. The main components of an ES are: a) inference engine, b) database, c) user interface ES incorporate rule kind of programming. They are currently being used in many applications in the area of power systems and power electronics. Several systems for the short or long term load forecasting have been already introduced based on ES technology [2],[3]. Intelligent SCADA and offline training systems for non-expert operators is another application where ES are often used [4],[5]. All these offline applications are nevertheless not critical for the power system robustness and stability. More and more applications are currently using ES in real timemonitoring and/or control, and AI turns to be a common practice in industrial automation. Regarding the category of real time monitoring and control, many applications have already been proposed, focusing mainly on topology estimation and fault diagnosis in distribution substations [6],[7],[8], and on the fault diagnosis and restoration strategies for transmission networks [9],[10],[11],[12],[13].
Expert Systems basically mimic the problem solving behavior of experts using domain knowledge acquired through interviews during the knowledge acquisition phase. Knowledge based ES as mentioned go beyond in a sense that they enrich problem-solving strategy with methods that are not ordinarily employed by human experts [1]. The proposed system is designed for the generators and distribution substations protection in power plants. Especially in weak interconnected power systems, operation of plants with high installed power can be of great importance for the stability and efficiency of the whole system. An unhandled fault can have a significant impact on power availability for an expanded area of the transmission network. Besides, a damage on a generator would add a very high financial overhead. Such unhandled faults have though been reported in the past and can lead even to human casualties. The system is designed to instantly recognize and report abnormalities that can be related to a mechanical equipment failure or to an electrical, or electronic equipment malfunction, or even to a mistaken human operator control command.
Distribution substations are the interlocking connection points of power plants to the electrical power grid. The state of all substation components (circuit breakers, disconnectors, protection relays etc.) is monitored and recorded to Digital Fault Recorders (DFR) while the electrical values of every circuit breaker, bus, transformer and generator terminal are measured by ad hoc installed current and voltage transformers. From the operator perspective an alarm situation arises when a monitored value exceeds a predefined upper or lower limit, activating a sound or light alert on control panel. An expert operator would handle this situation by first checking the control panel indications, trying then to locate the faulted area, according to the theoretical state of the switching equipment and the current values of the measurement points. This procedure may take some time especially when operators act under stress conditions. On the other hand inference process can be a very complicated task when some input data or measurements are faulted. For example, a very difficult fault to diagnose has been reported in the past, when after a voltage transformer explosion a bypass switch broke and caused a short-circuit, supplying the generator with an unbalanced load. In this case the switch position was mistakenly reported and the operator could not easily detect the real current flow path.
The time between the fault appearance and its recognition and restoration inference can be critical for the equipment and personnel safety.
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| Figure 1. Basic system architecture diagram |
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