Electricity price effects of different energy generation sources in Europe

_ Yuri Kofner, economist, MIWI Institute. Munich, 28 October 2021.

Introduction

“The expansion of renewables in the energy mix reduces the electricity price”. This claim is put forward as an economic argument by proponents of a speedier energy transition for the sake of climate protection. Especially in Germany.

However, this argument contradicts with several simple observations.

Over the past 20 years, between 2000 and 2020, the share of renewables in gross electricity generation in Germany has increased almost 7-fold: from 6.6 to 44.7 percent.[1]

Over the same period, however, electricity prices in Germany have doubled and tripled: for households from 140 to 314 euros per MWh and for industry from 60 to 186 euros per MWh. Germany now has some of the highest electricity prices in the world.[2]

The main reason for this increase in electricity prices lies in the need to finance the transition to renewable energy generation. This was done through the Renewables Energy Act surcharge (EEG Umlage), which increased by the factor of 6.5 (industry) and 26 (households) and now makes up 21.5 percent of the electricity price for industry and 36.4 percent for households, and the costs for grid stabilization measures, which have risen by a factor of 40 in the past 10 years – from 23 million euros per year to almost 1 billion euros.[3]

However, there are still contradicting viewpoints on the price effect of the energy transition.

Cludius et al. (2014), using time-series regression analysis, estimated that electricity generation by wind and PV has reduced spot market prices in Germany by up to 10 euros per MWh by 2012.[4]

According to model simulations by the ifo Institute, electricity prices in Germany will increase the least by 2040 in a scenario with drastically expanding renewables in the generation mix in comparison to scenarios with relatively more gas power plants. This is argued to be due to merit order effects and increased electricity exports.[5]

In a recent statement the öko-Institute estimates renewables to be the cheapest electricity generation method – with 30 to 55 euros per MWh (solar) and 40 to 80 euros per MWh (wind) – and nuclear the most expensive – with 110 to 170 euros per MWh.[6]

However, Blümm (2021), using data from the IEA and the OECD, on the contrary estimates the electricity generation costs in Germany from existing and future nuclear plants to be the lowest – with 27 to 40 euros per MWh, the costs from photovoltaics and wind turbines to be higher – with 82 to 123 euros per MWh.[7]

Methodology and data

In order to answer the question, if the expansion of renewables in the energy mix will lead to lower electricity prices (for end users), the author has employed a panel data time series regression analysis checking for time and country fixed effects.

For this task, the author compared the average annual electricity price for non-household consumers (i.e., industry) of 27 EU member states from 2008 to 2015 and the annual electricity generation mix of these countries.  The electricity price data was taken from Eurostat and is measured in euros per MWh.[8] The power generation mix data was taken from the German Federal Ministry for Economic Affairs and Energy and is given in a percentage share of each generation method (coal, natural gas, crude oil, nuclear power, hydro power, photovoltaics, and wind energy) in total electricity generation.[9] In all 216 observations, 27 countries, 7 years and 9 variables were analysed.

Results

The electricity price is correlated to the energy mix by 85.6 percent (R-squared = 8.55). Except for solar power, the expansion of all other generation sources has a price reducing effect.

The expansion of oil-based generation has the strongest price reducing effect of -0.167. In other words, the expansion of crude oil combustion in the energy mix of the EU member states by 1 percent lowers the average industry electricity price by 1.67 euros per MWh on average. With a p-value of 0.013 the correlation may still be considered statistically significant. However, this effect may be exaggerated since oil-based generation on average makes up less than 1 percent of the energy mix.

Nuclear power has the second-largest price decreasing effect: increasing its share in the generation mix by 1 percent lowers the average electricity price for non-household consumers by 1.36 euros per MWh. With a p-value of 0.007 this effect is statistically significant.

Increasing hydropower by 1 percent in the electricity generation mix lowers the average industry electricity price by 1.27 euros per MWh. With a p-value of 0.005 this effect is statistically significant.

Expanding gas and coal-based generation by 1 percent lowers the average electricity price by 1 euro and 0.73 euro per MWh, respectively. The correlations are more or less statistically significant with p-values of 0.058and 0.165 respectively.

Increasing the share of wind turbines in the power mix by 1 percent lowers the average electricity price by 0.62 euros per MWh. And only the expansion of PV generation in the energy mix by 1 percent increases the average electricity price by 0.32 euro per MWh. However, the correlation of these two independent variables is statistically not significant with a p-value of 0.352 and 0.726 respectively.

Notes

[1] BDEW (2021). Anteil Erneuerbarer Energien an der Bruttostromerzeugung in Deutschland in den Jahren 1990 bis 2020. URL: https://de.statista.com/statistik/daten/studie/1807/umfrage/erneuerbare-energien-anteil-der-energiebereitstellung-seit-1991/

[2] Faltlhauser M. (2020). Zahlen und Fakten zur Stromversorgung in Deutschland. Wirtschaftsbeirat Bayern. URL: https://www.wbu.de/media/news/positionen/publikationen/2020_ZahlenundFaktenzurStromversorgunginD2020.pdf

[3] Kofner Y. (2021). Safe, inexpensive and environmentally friendly energy for Bavaria. MIWI Institute. URL: https://miwi-institut.de/archives/1259

[4] Cludius J. (2014). The merit order effect of wind and photovoltaic electricity generation in Germany 2008–2016: Estimation and distributional implications. Energy Economics. URL: https://www.sciencedirect.com/science/article/pii/S0140988314001042

[5] Gawlick J. et al. (2020). Szenarien für die Bayerische Stromversorgung bis 2040. ifo Institut, TUM, IHK Oberbayern und München. URL: https://www.ihk-muenchen.de/ihk/Energie/200311_ifo-TUM-Studie_Stromversorgung_Bayern_2040.pdf

[6] Matthes F. (2021). Strompreise und Energie- kosten in der Energiewende zur Klimaneutralität. öko-Institut.

[7] Blümm F. (2021). Vollkosten pro kWh: Welche ist die günstigste Energiequelle? Tech for Future. URL: https://www.tech-for-future.de/kosten-kwh/

[8] Eurostat (2021). Electricity prices for non-household consumers. Annual data. URL: https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nrg_pc_205&lang=en

[9] BMWi (2021). Energiedaten – Datensammlung des BMWi. URL: https://www.bmwi.de/Redaktion/EN/Artikel/Energy/energy-data.html

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