Forecasting Technologies for Operation of Modern Electric Energy Systems Under Uncertainty

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Over the past two decades, three major changes have been introduced to electric power systems. First, deregulation of power industry has led to uncertain prices of wholesale electricity. Second, environmental concerns have given raise to deployment of wind- and solar-powered electricity generation, which are by nature variable and uncertain. Third, the new paradigm of smart grid is expected to create new opportunities for consumers to manage their energy use and participate in power markets. Smart grids benefit from an extra layer of intelligence on top of the existing grid to add to power systems flexibility and reliability. Smart grids are expected to lead to more dynamic and price-responsive loads compared to today's static load. These three major changes have introduced uncertainty in electricity prices, power generation, and power consumption. The proposed research proposal focuses on techniques and tools to mitigate the impact of such uncertainties on power systems operation and planning by predicting future values of uncertain variables. In particular, forecasting technologies for electricity prices, electricity demand, solar power and wind power will be developed. Price and demand forecasting techniques will take into account the mutual impact of these two on each other in a smart grid environment. In particular, dynamics of electricity load, electric vehicles, market incentives for electricity consumers and feed-in tariffs in smart grids will be modelled and incorporated. For wind power forecasting, the focus will be on wind ramping events, i.e, to predict the rate at which wind power will change at certain times in the future. Moreover, practical applications of wind power forecasts will be tied to training and building forecasting engines for improved performance. Solar power and solar energy prediction will also be investigated considering the variations in irradiation patterns over time.Hybrid models that benefit from sky-imaging and data analysis will be built for this part of the research.