This paper presents a knowledge based model for power system steady-state studies. In this model, a power system is represented by three components: power system states, power system operations, and the knowledge base which contains the knowledge about the use of the operations. In the proposed model, the knowledge representation and inference are different from the existing approaches in this area in three aspects. First, the knowledge about power system states and operations is represented by two sets of predicates and frame based structures. This allows efficient data exchange between the model and power flow software. Second, in this model, power system operations are represented by the data structures which are similar to bus and branch data structures used in a power flow program. Third, a special-purpose inference algorithm is developed to manipulate the process of analysis, calculation, and modification of power flow studies. This model is implemented on the IBM 4381 computer and shows high efficiency when used to study a practical power system problem.
- artificial intelligence
- knowledge representation
- power flow
- power system steady state
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering