Improving the value of variable and uncertain power generation in energy systems

Project: Academy of Finland project

Project Details


The energy sector is under transformation. The share of variable power generation, such as wind power and photovoltaic (PV), is increasing rapidly. Their output is dependent on weather and therefore much more variable and uncertain than the output from more conventional power generation. Variability and uncertainty brings challenges to power system operators and lowers the value of wind power and PV for the overall energy system and therefore also for the society at large. Variability decreases value since it causes periods with surplus electricity and periods with high net demand (demand minus the generation from wind power and PV – i.e. what other power plants need to provide for). Uncertainty decreases value since decision making under uncertainty is more difficult. Uncertainty leads to suboptimal decisions concerning e.g. when to store energy and when to start up power plants.

VaGe project objective is to improve operational decision making in the power systems when considering the variability and uncertainty of wind, solar, water inflow, heat and electricity demand, their correlations and possible sources of flexibility. Decision making under weather related variability and uncertainty is improved in two different time scales: 1) short-term power plant unit commitment and dispatch decisions (look-ahead up to 36 hours) and 2) medium-term optimization of storage use, consumer resources and other slow processes (look-ahead up to two weeks). More information, i.e. better and more comprehensive forecasts, and energy system flexibility can mitigate variability and uncertainty. Due to systemic interactions, it is important to assess all relevant sources of flexibility.
Effective start/end date1/01/1531/12/18

Research Output

Impact of 15-day energy forecasts on the hydro-thermal scheduling of a future Nordic power system

Rasku, T., Miettinen, J., Rinne, E. & Kiviluoma, J., 1 Feb 2020, In : Energy. 192, 33 p., 116668.

Research output: Contribution to journalArticleScientificpeer-review

  • 1 Citation (Scopus)
    82 Downloads (Pure)

    Selection of representative slices for generation expansion planning using regular decomposition

    Helistö, N., Kiviluoma, J. & Reittu, H., 22 Aug 2020, In : Energy. 211, 118585.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
  • 29 Downloads (Pure)

    Simulating wind power forecast error distributions for spatially aggregated wind power plants

    Miettinen, J., Holttinen, H. & Hodge, B. M., 1 Jan 2020, In : Wind Energy. 23, 1, p. 45-62 18 p.

    Research output: Contribution to journalArticleScientificpeer-review

  • 1 Citation (Scopus)


    • 1 Visiting an external academic institution


    Erkka Rinne (Visiting researcher)

    15 Oct 201816 Nov 2018

    Activity: Visiting an external institution typesVisiting an external academic institution