Application of Markovian Processes for the risk-based decision making

Nowadays, the electricity generation industry works with complex systems. A complex system can be defined as composed of several subsystems, elements, components, or different equipments, interacting spatially and temporarily in a nonlinear way. A system's complexity is related to the amount of different elements, intensity of the relations, and the functions that each element carries out to reach the expected operational performance. Oil production platforms and nuclear plants are examples of complex and dynamic systems. This paper presents a proposal based on the application of non homogenous Markovian Processes for availability estimation and for the decision making related to the design modification of a complex system. In this proposal the operational state are modeled according to the system failure scenario. The transition rates between those scenarios are failure rate (lambda(t)) and repair rate (mu(t)). The probabilities analysis of each operational state, calculated from the Markovian analysis process, are used as input to the decision making process. That process is based on the calculation of the expected mean cost of each decision alternative. The method is applied for the decision making on installing a water-supply redundant system of heat recovery steam generator used in a combined cycle thermal power plant operating in Brazil.