Combining Modified Weibull Distribution Models for Power System Reliability Forecast (1805.10420v2)

Abstract: In recent years, under deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. To help achieve this goal, this research proposes a novel statistical approach to forecast power system asset population reliability. It uniquely combines a few modified Weibull distribution models to build a robust joint forecast model. At first, the classic age based Weibull distribution model is reviewed. In comparison, this paper proposes a few modified Weibull distribution models to incorporate special considerations for power system applications. Furthermore, this paper proposes a novel method to effectively measure the forecast accuracy and evaluate different Weibull distribution models. As a result, for a specific asset population, the suitable model(s) can be selected. More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model to forecast future asset reliability. Finally, the proposed methods were applied to a Canadian utility company for the reliability forecast of electromechanical relays and the results are discussed in detail to demonstrate the practicality and usefulness of this research.