Applying AI systems in the T and D arena. [Artificial Intelligence, Transmission and Distribution]

Journal Article · Wed Mar 31 23:00:00 EST 1993 · IEEE Computer Applications and Power; (United States)

DOI:https://doi.org/10.1109/67.207469· OSTI ID:6537798

Venkata, S S; Liu, Chenching ^[1]; Sumic, Z ^[2]; Vadari, S V

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1. Univ. of Washington, Seattle (United States)
2. Univ. of Washington, Seattle (United States) Puget Sound Power and Light Co., Bellevue, WA (United States)

The power engineering community has capitalized on various computer technologies since the early 1960s, with most successful application to solving well-defined problems that are capable of being modeled. Although computing methods have made notable progress in the power engineering arena, there is still a class of problems that is not easy to define or formulate to apply conventional computerized methods. In addition to being difficult to express in a closed mathematical form, these problems are often characterized by the absence of one or both of the following features: a predetermined decision path from the initial state to goal (ill-structured problem); a well-defined criteria for whether an obtained solution is acceptable (open-ended problem). Power engineers have been investigating the application of AI-based methodologies to power system problems. Most of the work in the past has been geared towards the development of expert systems as an operator's aid in energy control centers for bulk power transmission systems operating under abnormal conditions. Alarm processing, fault diagnosis, system restoration, and voltage/var control are a few key areas where significant research work has progressed to date. Results of this research have effected more than 100 prototype expert systems for power systems throughout the US, Japan, and Europe. The objectives of this article are to: expose engineers to the benefits of using AI methods for a host of transmission and distribution (T and D) problems that need immediate attention; identify problems that could be solved more effectively by applying AI approaches; summarize recent developments and successful AI applications in T and D.

• OSTI ID: 6537798
• Journal Information: IEEE Computer Applications and Power; (United States), Journal Name: IEEE Computer Applications and Power; (United States) Vol. 6:2; ISSN ICAPEH; ISSN 0895-0156
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
240100* -- Power Systems-- (1990-)
ARTIFICIAL INTELLIGENCE
COMPUTERIZED CONTROL SYSTEMS
CONTROL SYSTEMS
KNOWLEDGE BASE
ON-LINE CONTROL SYSTEMS
ON-LINE SYSTEMS
POWER DISTRIBUTION SYSTEMS
POWER TRANSMISSION
TECHNOLOGY ASSESSMENT