A Practical Inference Engine for Risk Assessment of Power Systems based on Hybrid Fuzzy Influence Diagrams

Risk became the crucial decision making criteria in evaluation of some control actions in power systems, but very often, these decisions are made in a highly uncertain environment. In this paper, a new graphical tool for risk assessment and decision making under uncertainty – hybrid influence diagram with fuzzy probability values and fuzzy random variables is proposed. Influence diagram is a generalization of a Bayesian network, in which not only probabilistic inference problems but also decision making problems can be modeled and solved. Unlike classical Bayesian networks, which are using conditional probability tables, that are often difficult or impossible to obtain, a verbal expression of probabilistic uncertainty, represented by fuzzy sets is used in this approach. Besides discrete random variables, this hybrid model allows the use of continuous variables through the process of fuzzification. Through this integrated method, both type of inference support: bottom-up and top-down inference, including decision nodes in the analysis are enabled. Key words— Bayesian networks, fuzzy logic, influence diagrams, risk assessment