Investigation of stochastic optimization methods for operating reservoirs with snowmelt-dominant local inflows and limited storage capability in British Columbia during the spring freshet

• Main Author: Rasmussen, Ryan
• Language: English
• Published: University of British Columbia 2014
• Online Access: http://hdl.handle.net/2429/51558

The reservoir operations model developed in this thesis is a stochastic dynamic programming decision support tool for the optimization of the operation of snowmelt-driven reservoirs with small storage flexibility hydropower systems during the spring freshet. The model operates under the objective of maximizing the value of electricity generation through electricity trading over a short-term planning period. Project and watershed data, stochastic inflows, and estimated electricity prices are used to calculate optimal expected turbine release policies over a short-term planning period. Results are used to provide decision support to operators in the form of a daily expected optimal turbine release volume and marginal value of energy of the reservoir. Including stochasticity in the model allows for inflow probabilities, which may not be easily evaluated by an operator, to be reflected in an operation decision. A combination of forecast, historical, and current state of the system data is included in the model to reflect the most up-to-date view of uncertain conditions. Case studies indicate that although operators may deviate from the expected optimal policy to meet other interests and requirements in real-time, the model provides an optimal expected policy during the freshet period and has shown in a case study to increase the value of a single reservoir’s operations by 6% during one three-month freshet period. === Applied Science, Faculty of === Civil Engineering, Department of === Graduate