Robust optimal scheduling of hydropower generation systems

点击翻译按钮获取中文摘要

Optimal scheduling of hydropower generation systems involves a complex network of water resource systems, including reservoirs, transmission busses, and their respective hydraulic and transmission requirements. These systems are moreover subject to uncertainty in energy prices, energy loads, rainfall amounts and non-dispatchable energy resources. This project will focus on the investigation of formulation strategies to that avoid excessive variation of the solution under uncertain input data to yield a decision support system that is more robust to uncertainty, leading to greater efficiencies and end-user acceptance. Key approaches for dealing with uncertainty in optimal scheduling are updating of the schedule as information becomes available, inclusion of an uncertainty characterization within the optimization problem formulation and solution, and a combination of the two paradigms. The companion NSERC Engage project will focus on the first of these, whereas the OCE VIP 1 project will focus on robust optimization approaches for this application in which uncertainty is taken into account directly within the optimization algorithm, with the ultimate goal of combining the two approaches within a single framework. Industrial collaboration will aid in the development of a mathematical description of the industrial process that captures the key system characteristics, constraints and operational objectives. Strategies to address the problem will be developed, and their performance evaluated via simulation studies. The findings of this work will contribute key technical information towards the partner companys efforts to solve an important technical problem: management of uncertainty in short-term scheduling decisions. This improvement will result in more efficient operation of hydrothermal generating facilities, which translates to more efficient usage of hydro resources, increased wind/solar resource penetration, as well as reduced emissions from thermal generation facilities.