Operator Training Simulator for power systems: Training evaluation methodologies based on fuzzy logic

Abstract

Operator training is a relevant aspect of power system operation. In control centers, operators manage the power system through a man machine interface that is a source of further complexity for this critical infrastructure. This paper presents an approach for improving the features of power system Operator Training Simulator (OTS). The OTS program is aimed at training control center operators through the simulation of possible contingency scenarios. The trainees, through simulations, learn to manage the power system during real-time operations and assess on-line dynamic security through the adoption of suitable corrective actions in emergency conditions. Usually, trainees learn only from the experience acquired during the simulation sessions. The OTS is also aimed at improving operator training by adding to the experiential learning the tacit knowledge acquired by senior control center operators. The tacit knowledge can be made explicit and transferred to trainees through well-suited OTS sessions including case studies based on past performed senior operator experiences. The proposed approach is aimed at defining a training evaluation methodology based on fuzzy logic able to reduce the gap between required knowledge and skills and the measured knowledge and skills of operators and to define improvements of each submitted training sessions.