Sub-optimum day-ahead power dispatch for a mixed generation system considering emission and energy storage for semi-liberalized power market

This thesis concentrates on the development of a modified 15-minute interval and cost-based model using dynamic programming (DP) for resolving the day-ahead optimization dispatch schedule of thermal unit commitment (UC) problem including emission, renewable energy resources (RES) costs, and battery energy storage system to mitigate greenhouse gas emissions at minimal possible operation cost under special China semi-liberalized power market. Besides this, a novel modelling approach of Double Cubic power curve of wind turbine is developed to express the relationship between the output power of the wind turbine with the wind speed based on considering the inflection point in the nonlinear portion of the wind power curve. A novel model of forecasting wind speed is developed based on using Weibull method and adding two types of forecasting correction values based on white noise generated by a random number generator to stochastically simulate forecasting wind speeds. The proposed models are tested on a China provincial power network with some unavailable data supplemented from IEEE standard test system.This thesis concentrates on the development of a modified 15-minute interval and cost-based model using dynamic programming (DP) for resolving the day-ahead optimization dispatch schedule of thermal unit commitment (UC) problem including emission, renewable energy resources (RES) costs, and battery energy storage system to mitigate greenhouse gas emissions at minimal possible operation cost under special China semi-liberalized power market. Besides this, a novel modelling approach of Double Cubic power curve of wind turbine is developed to express the relationship between the output power of the wind turbine with the wind speed based on considering the inflection point in the nonlinear portion of the wind power curve. A novel model of forecasting wind speed is developed based on using Weibull method and adding two types of forecasting correction values based on white noise generated by a random number generator to stochastically simulate forecasting wind speeds. The proposed models are tested on a China provincial power network with some unavailable data supplemented from IEEE standard test system