Long term power prices and renewable energy market values in Norway – A probabilistic approach

Eirik Ogner Jåstad, Ian M. Trotter and Torjus Folsland Bolkesjø

Energy Economics, 2022, vol. 112, issue C

Abstract: The transition to renewable energy will require large investments in renewable power generation capacity, made under large risks regarding future revenues. This study presents an analysis of different risk factors for future power prices and renewable energy market values in Norway, a region dominated by renewable power. We use a combination of global sensitivity analysis and Monte Carlo simulations to estimate the influence of the different parameters, including electricity demand, politically driven capacity constraints, fuel and carbon prices, investment costs of new generation capacity, and other production costs. The novelty of this study lies in the thorough analysis of how the future power market may be affected by the above-mentioned risk factors using a probabilistic approach. The results show that the carbon price and natural gas prices remain the two major power price drivers in 2040, despite lower fossil fuel shares. The mean annual Norwegian power price from the Monte Carlo simulations is estimated to be 39 ± 4 €/MWh and long-term price levels below 23 €/MWh or above 50 €/MWh seem highly unlikely in an average weather year. The market values of renewable power technologies differ substantially with hydropower at 53 ± 6 €/MWh, onshore wind at 32 ± 4 €/MWh, offshore wind at 33 ± 3 €/MWh, and solar PV as low as 20 ± 3 €/MWh. By comparing these market values to LCOE estimates in the literature we estimate 98% and 2% probabilities that revenues from onshore wind and solar PV will be within a half standard deviation away from their LCOE. We conclude that for the 2040 power prices, international drivers will be more important than price drivers inside the Norwegian market, and that policy support would continue to be necessary for large-scale deployment of offshore wind and solar PV in Norway.

Keywords: Energy sector modelling; Global sensitivity analysis; Monte Carlo; Morris screening; Power and heat market; Uncertainty and risk (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:112:y:2022:i:c:s0140988322003346

DOI: 10.1016/j.eneco.2022.106182

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