Statkraft is owned by the Norwegian state and is Norway’s largest, and the Nordic region’s second-largest, power producer. Statkraft has 353 power plants with a total installed
capacity of 19,080 MW. This includes 12,899 MW hydro in Norway, and 1,267 MW hydro in Sweden.
Reflections Bjørn Rasmus Dah, VP Spot sales, Energy Management, Statkraft:
We are working with long-term price prognoses. Several of our reservoirs are so large that water could be stored for more than one year, meaning production planning is a long-term decision. We have to evaluate the situation many months ahead to manage the water correctly, and we have to plan this management based on many uncertain factors. A risk of flooding must be weighed up against the risk of emptying the reservoirs prematurely, restrictions must be complied to, and we should have water left if the prices rise. Based on the price prognoses and updated fuel prices, reservoir levels and weather prognosis, water values are calculated each day for each plant. To make the detailed operational plan we use the SHOP model. This program is run several timers per day (see box below for the models utilised).
Actual reservoir levels, weather forecasts, fuel prices, import and export capacities as well as wind generation in Sweden and Denmark are important for the
formation of prices in Norway.
The flexibility of our hydro is primarily activated in the day-head market and as regulating power. It can also be used in the intra-day market. The use of the intra-day market has traditionally been low, but the volume traded in Norway is increasing. For a generator with hydro plants, it is often possible to correct imbalances within our own system, e.g. with other hydro plants. In the future, it is likely that Norwegian hydro will increase the supply of flexibility to other countries with high shares of wind and solar.
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Examples of models that Statkraft uses in its hydro operational planning
EMPS30 - multi-area power-market simulator - is a tool for forecasting and planning in electricity markets. It has been developed for optimisation and simulation of hydrothermal power systems with a considerable share of hydropower. It takes into account transmission constraints and hydrological differences between major areas or regional subsystems. The objective is to minimise the expected cost in the entire system subject to all constraints. In principle, this solution will coincide with the outcome in a well-functioning electricity market. The simulated system can e.g. be the Nordic system or Northern Europe. The basic time step in the EMPS model is one week, with a horizon of up to ten years. Within each week, the time-resolution is 1 hour or longer. In the strategy evaluation, incremental water values (marginal costs for hydropower) are computed for each area using stochastic dynamic programming. A heuristic approach is used to treat the interaction between areas. In the simulation part of the model total system costs are minimized week by week for each climate scenario (e.g. 1931 – 2012) in a linear problem formulation.
SHOP31 (Short-term Hydro Operation Planning) is a program for short-term hydro operation planning. The program is based on an optimisation formulation where complex hydraulic configurations of water courses can be modelled. The program is able to handle any number of cascaded watercourses. The optimisation is based on successive linear programming and may include mixed integer formulation. The general objective of the program is to utilise the available resources, and to maximise the profit within the period in consideration, by exploiting the options for buying and selling in the spot market, while fulfilling firm load obligations. The study period is flexible, typically 7 to 14 days. The time resolution is typically 1 hour or 15 minutes.
30 “EMPS - multi area power-market simulator”, SINTEF, 2018, www.sintef.no/en/software/emps-multi-area-power-market-simulator
31 “Short-term Hydro Operation Planning”, SINTEF, 2018, www.sintef.no/en/software/shop
Part II Europe
1514.6 Additional sources
For more details regarding Nordic and European hydro capacity (including pumped hydro capacity) see Euroelectric; VREB Powertech, 201832. In addition, numerous publicly available sources provide historical hydro data33. For a review of studies regarding European wind and solar production balanced with Nordic hydropower, see Ingeborg Graabak, 2016 .
4.7 Relevance in a Chinese context
The deregulation of the power market in Nordic regions also led to the deregulation of hydro power stations. In this deregulated and liberalized market context, each of the power stations makes decisions on their own. This is in sharp contrast with the traditional centralized paradigm, in which all the generation programs are determined by one central dispatching centre. Although all the decisions are individually made, they collectively leads to a very efficient power system, as evidenced by the high level utilisation of renewable energy in this region.
Unlike wind and solar power, the marginal cost of hydro power plant with a reservoir is not zero, it equals to the opportunity cost of generating now compared to withholding the water for later generation. One of the key concepts in the decision making processes is water value, which reflects the timely value of a unit of water in the reservoir. In a nutshell, the water value would be higher when there is less water in the reservoir, or a higher price expected in the future, and vice versa. When the current market price is higher than the water value calculated, the power stations will generate. Thus the revenue of a hydro power station is largely depends on it accuracy of all kinds of prognoses: price prognoses, weather prognoses, etc.
Practices in Nordic regions shed some lights on the on-going power market reform in
Southeast provinces, such as Yunnan and Sichuan, which also have abundant hydro power and increasingly more wind power plants. One of the learnings for the hydro power station owners is that the capability building on price prognoses on various time scales (hours ahead, days ahead, months ahead, even a year ahead) would be crucial for their financial performance.
32 Facts of Hydropower in the EU”, Euroelectric; VGB Powertech, 2018.
33 Examples of sources include:
• The Norwegian Water Resources and Energy Directorate, NVE, (www.nve.no/hydrology) publish real time data and weekly data about hydrology. This includes reservoir level and information about the volume of snow on the mountains (in water equivalents).
• Nord Pool publishes weekly data about reservoir levels in the Nordic system (www.nordpoolgroup.com/
historical-market-data).
• Data for European hydro can also be obtained from ENTSO-E’s Transparency platform (transparency.
entsoe.eu).
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5. Demand-side management in Finland
5.1 Key messages and takeaways
• Demand-side management (DSM) can serve as a cost-effective flexibility resource in all the different power markets (spot, intra-day, balancing and particularly ancillary services)
• It is necessary to undertake contractual and technical requirement updates in order to allow demand side to participate in existing markets
• Stakeholder consultations and pilot projects are important for the development of DSM
• The use of aggregators can facilitate the introduction of small units in the market
• Participating in DSM allows individual stakeholders to realise value for their flexibility