Modeling, Optimization and Analysis of Energy Systems Under Uncertainty

In order to plan the future energy system, expected technological changes must be accounted for; however, there is significant uncertainty at both the planning and operational levels. Some of the uncertainties involved at the planning level include: the technologies that will be integrated and the degree to which they will be utilized, the localization of plants, the necessary accompanying transmission and distribution infrastructure and the structure of the market and support systems present in the future electricity system. At the operational level, the uncertainty is mainly a result of the variability inherent in many renewable energy technologies. While the flexibility needed to handle the relatively small amount of uncertainty currently present in the system is sufficient to handle lower variable generation penetration rates, fundamental changes to power system planning and operations will be needed in order to accommodate larger penetration rates. These complex problems cannot be solved by considering the technologies alone; models of the system must be able to capture the effects of social, economic and policy decisions in order to capture all of the relevant phenomena that may affect the state of the system. The representation of these new systems requires the concurrent use of a number of tools taken from the process systems engineering, operations research, electrical engineering and statistical fields to characterize system states at various levels of time, geographic dispersion and model fidelity, as dictated by the questions to be answered. In summary, I propose to develop, extend and apply classical and cutting-edge analytical techniques to the study of large-scale and complex problems in the socio-economic technology energy system space where consideration of both engineering and policy aspects is required and sources of system uncertainty must be considered.