학술논문

Knowledge representation for power system modelling
Document Type
Conference
Source
PICA 2001. Innovative Computing for Power - Electric Energy Meets the Market. 22nd IEEE Power Engineering Society. International Conference on Power Industry Computer Applications (Cat. No.01CH37195) Power industry computer applications Power Industry Computer Applications, 2001. PICA 2001. Innovative Computing for Power - Electric Energy Meets the Market. 22nd IEEE Power Engineering Society International Conference on. :50-56 2001
Subject
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Signal Processing and Analysis
Computing and Processing
Power system modeling
Knowledge representation
Power system management
Application software
Computer integrated manufacturing
Power system control
Power systems
Energy management
Control system synthesis
Resource management
Language
Abstract
Modelling power systems is an area of ongoing interest in the transmission management and control systems community. Continuing development is driven by two forces. The traditional tasks of model maintenance and management must be achieved with fewer resources. At the same time, model exchange and coordination has become a priority. The latter force arises from the disaggregation of utility functions and the introduction of power markets. This paper begins by identifying some of the power system modelling tasks that have become important, but are ill served by current tools and techniques. Among these are model versioning and version control, migration of models between, different schema, the transformation of models for different purposes or applications, and the merging of models from different sources. These tasks are typically handled by semi-manual methods or heavily customized software. The paper then describes the application of knowledge representation to power system modelling. In particular, the power of this approach to provide generic solutions to the, foregoing problems is explored. Knowledge representation is contrasted with more common data representations and put into context with current industry initiatives, EPRI CIM (common information model), UMS DAF (data access facility) and XML/CIM. Finally, the feasibility of using knowledge representation for power system models is illustrated with a case study from a major Australian distribution utility.