Degradation assessment for critical assets in power generation has great significance for power industry. Existing degradation assessment models failed either in combining the multimodal condition monitoring data or in removing time-varying working condition influences, resulting in inaccurate and/or unreliable degradation assessment results. In order to achieve robust and accurate degradation assessment for power generation critical assets, this project aims at developing new models based on both maintenance data and condition monitoring data from ENMAX.
The partner company, ENMAX Energy Corporation, is a leading electricity and natural gas supplier in Alberta. Modern techniques from stochastic processes and numerical analysis are widely used in energy risk management and trading. The intern research project involved the development of an optimal portfolio of products in the energy industry as well as the study of the pricing of new forms of contracts for energy products. In addition, stochastic dynamic programming techniques were applied to investigate optimal portfolios.