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Proceedings Paper

Automated AI-based designer of electrical distribution systems
Author(s): Zarko Sumic
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Paper Abstract

Designing the electrical supply system for new residential developments (plat design) is an everyday task for electric utility engineers. Presently this task is carried out manually resulting in an overdesigned, costly, and nonstandardized solution. As an ill-structured and open-ended problem, plat design is difficult to automate with conventional approaches such as operational research or CAD. Additional complexity in automating plat design is imposed by the need to process spatial data such as circuits' maps, records, and construction plans. The intelligent decision support system for automated electrical plate design (IDSS for AEPD) is an engineering tool aimed at automating plate design. IDSS for AEPD combines the functionality of geographic information systems (GIS) a geographically referenced database, with the sophistication of artificial intelligence (AI) to deal with the complexity inherent in design problems. Blackboard problem solving architecture, concentrated around INGRES relational database and NEXPERT object expert system shell have been chosen to accommodate the diverse knowledge sources and data models. The GIS's principal task it to create, structure, and formalize the real world representation required by the rule based reasoning portion of the AEPD. IDSS's capability to support and enhance the engineer's design, rather than only automate the design process through a prescribed computation, makes it a preferred choice among the possible techniques for AEPD. This paper presents the results of knowledge acquisition and the knowledge engineering process with AEPD tool conceptual design issues. To verify the proposed concept, the comparison of results obtained by the AEPD tool with the design obtained by an experienced human designer is given.

Paper Details

Date Published: 1 March 1992
PDF: 13 pages
Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); doi: 10.1117/12.56907
Show Author Affiliations
Zarko Sumic, Puget Sound Power & Light Co. and Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 1707:
Applications of Artificial Intelligence X: Knowledge-Based Systems
Gautam Biswas, Editor(s)

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