9 Jul 2019 #spotlight

China's PV potential with pollution-free 1960s surface radiation

Historic (1960 – 2015) capacity factors (red) and SO2 (blue) and black carbon (black) emissions in China as a percentage of peak emissions in 1994 and 2005 respectively. Thin lines are annual, thick lines 5-year moving mean values. Adapted from Sweerts, Pfenninger, Yang, Folini, van der Zwaan and Wild (2019).

Historic (1960 – 2015) capacity factors (red) and SO2 (blue) and black carbon (black) emissions in China as a percentage of peak emissions in 1994 and 2005 respectively. Thin lines are annual, thick lines 5-year moving mean values. Adapted from Sweerts, Pfenninger, Yang, Folini, van der Zwaan and Wild (2019).

Using solar radiation data from 119 stations across China we show that photovoltaic electricity potential decreased on average by 11–15% between 1960 and 2015. Given the observed relation between surface radiation and emissions of sulphur dioxide and black carbon, reducing air pollution should let surface radiation increase. Reverting back to 1960s radiation levels could yield a 12–13% increase in China’s solar electricity generation. → Sweerts, Pfenninger, Yang, Folini, van der Zwaan and Wild (2019), Nature Energy.

29 Mar 2019 #spotlight

Photovoltaic electricity is a no-regrets investment in Europe irrespective of climate change

Results for present yearly total PV potential and future relative change and variance compared to the present under the RCP8.5 climate change scenario. Maps show the ensemble mean of the CMIP5 models of the total PV potential (a) for the present (2007–2027), (b) relative difference in yearly sum of produced power, and (c) intra-annual (seasonal) variance between the present (2007–2027) and future (2060–2080) time periods. Adapted from Müller, Folini, Wild and Pfenninger (2019).

Results for present yearly total PV potential and future relative change and variance compared to the present under the RCP8.5 climate change scenario. Maps show the ensemble mean of the CMIP5 models of the total PV potential (a) for the present (2007–2027), (b) relative difference in yearly sum of produced power, and (c) intra-annual (seasonal) variance between the present (2007–2027) and future (2060–2080) time periods. Adapted from Müller, Folini, Wild and Pfenninger (2019).

Photovoltaic power output changes locally by −6% to +3% on annual and −25% to +10% on monthly scales, when comparing present (2007-2027) to future (2060-2080) with a CMIP5 climate model ensemble for the RCP8.5 climate change scenario. Southern Europe sees increased output, while northern Europe sees a decrease; overall, photovoltaic electricity is a no-regrets investment in Europe irrespective of climate change. → Müller, Folini, Wild and Pfenninger (2019).

31 Jul 2017

Balancing European wind power

In a paper published in Nature Climate Change, we used a combination of a meteorological understanding of weather regimes and our Renewables.ninja wind and PV generation time series to show that by smart spatial deployment of future wind farms, based on our knowledge of weather regimes, it is possible to keep the European wind fleet’s multi-day variability to levels the power system is already dealing with today. Time series of six-hourly European wind power output, assuming historical weather conditions from winter 1992-93. Read more...

6 Sep 2016

Renewables.ninja: simulating PV and wind power plants

Together with Iain Staffell, I published two papers, available today, using reanalysis and satellite data to simulate PV and wind power plants across Europe (references at the bottom of this post). Alongside these two publications, we built a large database of measured power output data to validate the simulations and perform bias corrections. This now allows us to accurately model hypothetical European wind and PV power output over several decades, investigating issues like the impact of increasing PV deployment on net power demand: Read more...

18 Dec 2014 #python

Calliope, an open-source energy systems modelling framework

Energy system models are used by analysts in academia, government and industry. They allow researchers to build internally coherent simulations and scenarios of the extraction, conversion, transportation and use of energy, either today or in the future, at scales ranging from cities to entire countries or continents. These models are particularly important because they can help with understanding and planning the transition from a fossil-fuel dominated energy system to one primarily consisting of clean and renewable energy. Read more...