Intelligent Decision Aiding Agent Using the Causal Network in a Power System Contingency Analysis
The main objective of this paper is to enhance the security process by using agents in decision making during contingency analysis. The causal network is used to build decision aiding agents. Logic and probability reasoning with epistemic state and beliefs are represented by probability measure defined some state space. The probability is expected to be used in estimating the operating risk of the system at a given time. That is, the higher the probability of outages, the higher the risk of operation. In this paper, the component (equipments) failure rates and weather information are considered. However, other models that use more reliability parameters can be used.