An expert system for contingency analysis in transmission networks

Power systems are presently remotely operated and controlled from control centers that receive online information about the power system state. Control center operators have very high-demanding tasks that makes their training a key issue for the performance of the whole power system. Simulators are usually used by electrical utilities for this purpose, but they are very expensive applications as they have to model the control center as well as the power system. On the other hand, their use requires the preparation of the training sessions by a qualified training staff, which is a very time consuming task. Intelligent tutoring systems (ITS) provide some new possibilities for training control center operators without much assistance of the teaching staff. Also, the expert system used in the control center can easily be adapted to an ITS. This paper presents the training module of SPARSE, the expert system for fault analysis and power restoration assistance in the Portuguese transmission network. >

Cape Town City Council is responsible for the supply of electricity to the city area. To achieve this, the council owns and operates thermal and pumped-storage power stations and extensive HV transmission and LV distribution networks. Power is also purchased from the national supply authority. Prior to the introduction of the control system described in this paper limited supervisory control and data acquisition facilities existed to provide some degree of remote control for the network. In addition to duties associated with supervision of both the HV and LV networks, the control centre operators were also responsible for energy management involving generator scheduling and control, and load-shedding when required. To assist the operators in their extensive and onereous duties a new computer-based control centre has been developed and was commissioned in 1984. Because of the unusual mix of power sources special software had to be developed for energy management purposes. Descriptions are given of the functional and practical aspects of the control centre, and of associated hardware and software facilities and also some commissioning experiences.

Expert systems have found widespread use in alarm processing, short term load forecasting, power system planning, economic dispatch and contingency analysis. Expert systems need a precise description of the power system using a lot of consistent rules. Research going on in this field is aimed at making the expert system adaptive by making it learn from new experiences. This challenge could possibly be met by embedding expert systems with neural networks. With research in the field of evolutionary computations, the prospects for expert systems seem bright. If these ventures are successful, there will probably be much more efficient and reliable power systems. Thus, expert systems seem to be promising for power systems.

Automated driving has started to be used commercially for individual mobility and public transport in recent years. As soon as automated driving is commercially exploited, automated vehicle fleets require assistance which can be provided by an operational control center as known from air traffic, public transport or process technology. The need for assistance is shown by two aspects. The aspects are human interaction and efficiency of journeys. Based on that, a control center is proposed to address those aspects. Further, a concept for a control center is derived. For that, the methods of interviewing experts, observation and literature research are used. Specific tasks for the control center are defined. These tasks were examined and categorized into three service categories. The three service categories are emergency service, fleet service and teleoperation service. Due to the categories, future-built control centers will be scalable and adaptable to its demand. Whereas two of three categories are well covered by industry or research, the teleoperation service as the essential problem solving technique needs further development. Moreover, further research will be required to quantify the control center demand.

Contingency analysis (CA) is a vital technique of assessing power system resilience during outages by detecting overloads, voltage issues, and generator faults, strengthening grid security and emergency response planning. For the Ethiopian Electric Power (EEP) network, an N‑1 contingency analysis was conducted on Extra High Voltage (EHV) transmission lines. A dual‑depth Deep Feed Forward Neural Network (DFFNN) was employed on MATLAB/MATPOWER platform to predict bus voltage magnitudes and active power flows across branches. The DFFNN achieved strong training performance, with Mean Square Error (MSE) values of 3.887 x 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> and 7.32 x10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup>, alongside high regression values of 0.99234 and 0.99479, confirming its predictive accuracy. These predictions were used to implement a novel Hybrid Performance Index (PI<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hyb</sub>), which ranks contingencies according to severity. Results revealed that failure of either circuit of the Dedessa–Holeta 500 kV double-line, sourced from the Great Ethiopian Renaissance Dam (GERD), was the most severe contingency. This event produced a PI<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hyb</sub> of 1.798, causing voltage instability at 19 buses and severe overloading of the Dedessa–Nekemte 132 kV line. Subsequent critical contingencies were also linked to GERD, with PI<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hyb</sub> values of 0.473 and 0.321. Corrective and preventive measures are recommended to mitigate these risks, ensuring protection against cascading failures that could ultimately lead to a total blackout.

Transmission open access was mandated by FERC Orders 888 and 889 which became effective on January 1, 1997. Transmission owners and operators were required to provide transmission access to all users of transmission system on a comparable basis as they are using themselves. Order 889 also required functional separation of transmission operations and wholesale merchant functions. Transmission service providers were required to file with FERC open access transmission tariff (OATT) that should be conforming with the FERC pro-forma tariff so that terms and conditions used for their own use are the same as those applicable to other users. Transmission providers were required to establish open access same time information system (OASIS) for exchange of transmission information and processing of requests for transmission service. This order impacted control center operations significantly. This required new capabilities for control centers for tracking the transmission information and also to share information with customers. This resulted in new way of doing business and more complex control center operations.

In this paper, a knowledge-based system for static security assessment of power system is proposed and investigated. An expert system (ES) for screening the consequences of transformers' and electrical lines' single outage was developed. The rules derived from a simulation model, irrespective of the size of the power system, are thus obtained. A dedicated artificial intelligence language (Prolog) for rules implementation was used to build the ES named CONTIG. The results show that such ES can be very effective for contingencies' selection. The benefits for a moderate size power system (25 buses and 30 branches) were analyzed using CONTIG. This approach has a great potential for online application

This paper presents a rule-based expert system which is an extension of an ERP system of a fashion company. The fashion company needs a system for analyzing sales reports from mobile devices in many locations. An expert system is suggested, which can work with the company's ERP system. The expert system analyzes sales data and supports decision making strategy on the data. Rules in the proposed expert system are represented in JESS, Java Expert System Shell.

An Expert System for the Analysis of Disturbances in Electrical Networks

The requirements for corrosion expert systems have never been clearly stated, though many expert system developers must have had a “typical” user in mind, when designing their application. Reviewing some of the developed systems has shown that there exist quite some different approaches. In this paper, some general guidelines will be presented which pertain both to the development of expert systems in general, as well as to the development of expert systems for corrosion, in particular. Most of these guidelines stem from experience with the development of a large-scale expert system for materials selection and corrosion analysis, PRIME. The following topics will be discussed: concepts that affect design and construction, architectural issues, the selection of requisite expert system components in conjunction with user requirements, design issues affected by task type and organizational constraints.

Knowledge management is one of the most important goals of any organization. Therefore, several automatic tools are used for that purpose, e.g. Knowledge Based Systems (KBS), Experts Systems, Data Mining Applications and Computer Aided Decision Systems. The validation and verification (V&V) process is fundamental in order to ensure the quality of used knowledge. The usage of automatic verification tools can be a reliable, inexpensive and reusable way to overcome the constant growth of the Knowledge Bases, the shortening of development times and the costs of Validation, specially field tests. This paper addresses the verification of Knowledge Based Systems, focussing on VERITAS, a verification tool initially developed to verify a KBS used to assist operators of Portuguese Transmission Control Centers in incident analysis and power restoration VERITAS performs knowledge base structural analysis allowing the detection of knowledge anomalies.

An expert system is developed to determine the steady state security of a power system after a contingency. Line, transformer and generator outages are considered. For any load in the system, overloaded branches are determined by comparing the system load to three load levels closest to the actual system load and using generator shift or branch outage distribution factors. The expert system, in conjunction with the DC load flow, is designed to identify the harmless and harmful contingencies as well as the overload branches. If a contingency cannot be determined as harmless or harmful then an AC load flow is suggested. Turbo-Prolog is used for symbolic manipulations and reasoning. The developed system is applied to a 12 bus power system. The results indicate that the expert system can be used in contingency screening as well as online operation to assist the operator. >

Expert systems have been proposed for a wide range of civil engineering applications. They have been applied most successfully in situations governed by simple rules. Many civil engineering decisions, however, must be made in environments in which simple rules are not possible, but rather large amounts of data must be analyzed and evaluated. This paper presents a methodology in which an expert system shell (INSIGHT 2+) is used to evaluate and display information on drought management planning. A linear programming model is used to generate optimal operating policies as a function of numerous past drought experiences. These policies are incorporated into an expert system where the user is required to identify the degree to which the current drought situation is similar to past events. The expert system then aids the user in developing appropriate management policies based on time of year, descriptions of drought intensity, and other system characteristics.

This paper presents a parallel particle swarm optimization (PSO) technique for reactive power and voltage control (Volt/Var Control: VVC) investigating dependability. High penetration of renewable energies and deregulation of power systems force power flow to change suddenly and operators in control centers have to control voltage in wider power systems. Therefore, VVC is required to shorten the control interval and handle larger-scale power systems. One of the solutions for the problem is applications of parallel and distributed computing. Since power system is one of the infrastructures of social community, sustainable voltage control is crucial and dependability is strongly required for VVC. This paper investigates not only fast computation by parallel computation but also dependability of parallel PSO for VVC with IEEE 14, 30, 57, and 118 bus systems.

This paper presents a planning methodology using an application of a mathematical and a rule-based expert system (ES) to expand the transmission network in a deregulated environment. In this methodology, the ES suggests a realistic set of generation additions with proper economic signals to the participants, before proceeding with the transmission expansion. A feasible list of transmission alternatives is then assumed to accommodate the proposals for generation. A mathematical method is performed based on marginal cost allocation to optimize the location for the new generation and its transmission expansion scheme simultaneously for each alternative. The optimum alternative that minimizes the overall system's cost function and satisfies the future demand is obtained. The ES interacts with the power system planning tools to produce the optimum expansion plan. A practical application is given to demonstrate the effectiveness of the developed prototype system.