Many hydropower plants use old technology from the large hydropower projects in the middle of the 20th century. At the same time, the largest developments have already been made in Norway and other developed countries. Therefore, upgrading existing hydropower plants is both more profitable and more relevant than building new ones. But how do you know if upgrades will pay off?
In his doctoral work, Andreas Kleiven has developed models that can help the power industry by calculating what are optimal investments and operating plans in hydropower plants.
Difficult to predict prices for the long life of hydropower projects
Hydropower plants in Norway have a long lifespan, and potential cash flows must be calculated several decades into the future. It is far beyond the horizon where there are futures contracts to control unwanted risk. In addition, there are very large costs associated with carrying out upgrades in existing hydropower plants.
When a power company plans for the years ahead, they often aim to create an operating and investment plan that maximizes the market value of existing and potentially new assets. For a hydropower producer who wants to maximize profit, this means, among other things, valuing the flexibility to choose when you want to produce and invest, based on information about, among other things, electricity prices and inflows to water reservoirs.
Accurate and reliable mathematical models and methods are essential to support decisions on renewal and upgrade projects.
Highlights from the doctoral thesis:
- When a power producer plans maintenance activities, long-term electricity price expectations can be used as a basis for deciding when and which activity to choose. The analysis highlights the importance of having several possible activities under consideration when prices are uncertain.
- When a power producer has to create an operating plan for next year, the marginal water value is underestimated if (negative) co-variation between prices and hydrological balance locally and in the power system is ignored. The potential gain from including co-variation between prices and resource availability when optimizing the operating plan is nevertheless modest.
- An intuitive method for integrating seasonal planning under price and inflow uncertainty, and short-term optimization within the week is proposed to evaluate upgrade projects. The analysis demonstrates how assumptions about price variations within the week affect the timing and size of upgrades.
- The thesis also offers a modelling framework for investment decisions in hydropower plants with a focus on downside risk. The analysis shows that a robust approach can reduce the variation in the cash flow associated with an irreversible long-term investment.
Can be implemented by industry
The factors considered and the models presented in the thesis can be implemented by industry.
Regarding the effect of covariation between hydrological balance and electricity prices on water values, the researchers are hesitant to propose explicitly modelling the relationship between local inflow, system hydrology and prices, given the modest gains that can potentially be made.
Rather, they suggest that short-term operating models and seasonal planning can be integrated and combined with long-term market price movements to evaluate investment alternatives. They also suggest that a robust framework with a focus on downside risk can be useful in assessments related to investment decisions when one has limited long-term information on electricity prices.
Overall, the analysis and results contribute useful and valuable insight into issues in the power industry.