The figure shows the geographical area included in the market model. The blue color shows the level of detail in the modelling.
Many of the projects in HydroCen concern the development of technological solutions, improved planning methods and tools that will increase hydropower's efficiency and ability to deliver flexibility.
In order to be able to measure the usefulness of such improvements, you need forecasts for the value of hydropower production, i.e. the price of electricity in the future.
Price forecasts are used as input to most investment and upgrade projects in the power industry. The forecasts also include information about uncertainty in relation to rainfall and other weather-dependent production and variation in prices throughout the day. This is what gives the value of flexibility.
The researchers have used a fundamental market model to calculate such prices.
A fundamental market model is based on everything you need to produce, transport and use electricity in an electrical system. This means everything from hydropower, wind power, gas and coal power, to the power grid and consumption.
The market model simulates the balance between production and consumption that complies with the physical restrictions in the system at each point in the simulation period.
In the project, the researchers have chosen to analyze the future electricity system as it is expected by a qualified guess to be in 2030. The year 2030 was chosen because this is a long way in the future and thus relevant for investments, but also because it is no further in the future than that there are relatively good forecasts for which physical system you then have.
The forecasts are based on open sources from, among others, NVE, Statnett and Eurelectric.
The results are useful in market models and research projects
The price forecasts are used in projects where the consequences of various types of changes for individual waterways are to be assessed. So far, this has either been linked to other HydroCen activities or in industrial projects where, for example, the profitability of a new pumped power plant in an existing watercourse is assessed.
The data set is also implemented in the models that are already in use at SINTEF and is used in many research and industrial projects. These are projects that, among other things, deal with the consequences of new cables to England and Europe, large-scale offshore wind development in the North Sea, flow-based market clearing and overall consequences of new condition revisions for the hydropower plants.