Economically optimal hydropower development with uncertain climate change

Abstract

Climate change affects the planning, construction, operation and management of hydropower plants in various ways. Evaluating hydropower generation with nonstationary climate changes is important for planning electric power infrastructure development. For a new hydropower plant with climate change, specifying too large a reservoir may result in excessive investment if the future becomes drier, while too small a reservoir may cause insufficient utilization of hydropower resources. Whether to build a new hydropower station at once or build it dynamically in stages over time is challenged by uncertainty in future conditions. This study proposes a planning method for developing a flexible hydropower construction schedule to adapt to long-term uncertain hydrology with climate changes. Projected uncertain nonstationary hydrology scenarios were developed first, and Bayes’ theorem is used to update the probability of each scenario based on observed hydrologic conditions over time. A profit maximization model integrates stochastic dynamic programming and linear programming for a cascade hydropower system to evaluate hydropower plant expansion and how to build it dynamically with uncertain nonstationary climate conditions. In this, stochastic dynamic programming evaluates and prescribes inter-stage reservoir upgrades and linear programming prescribes inner-stage hydroelectric power generation. The case study of Jinsha cascade hydropower system in China’s Yunnan province illustrates the method. The intensity and trend of climate change effects on streamflow directly affect the optimized results. If streamflow decreases in the future, the best strategy is to build a small reservoir initially, without future changes. If streamflow increases in the future, it is better to build a small reservoir first, and gradually increase capacity according to observed changes in streamflow and economies of scale in capacity construction. If there is no clear trend in streamflow change, it is also better to build a small reservoir at first, then decide whether to expand the reservoir according to future observed changes in streamflow. This method with uncertain nonstationary climate change and upgrading adaptively with observed hydrology usually produced better results than optimization for a deterministic nonstationary hydrology.