Investigation of extended fuzzy reasoning and neural classification for load-shedding prediction to prevent voltage instability

This paper first illustrates an intelligent load-shedding approach, which makes use of knowledge base and extended fuzzy reasoning, for curative control to prevent a power system from moving towards a dynamic voltage-insecurity state following disturbances. Using the same training patterns, layered artificial neural networks are then employed to perform the same graded classification. From the investigation, it is found that there is difficulty for even well trained artificial neural networks to return consistently satisfactory results for previously untrained cases. (C) 1997 Elsevier Science S.A.