Recent data on relationship between domestic electricity prices and wind and solar installed capacity

autam Kalghatgi FREng FSAE FIMEchE FCI FISEES

Currently, Visiting Professor, University of Oxford (Engineering Science)

It has been noted in many publications that household electricity prices are higher in countries with a larger share of wind and solar in electricity generation [1-6]. The primary reason [3,4.5] appears to be the intermittent nature of wind and solar – variable renewable energies (VRE). They do not necessarily produce enough energy when societies need it and too much energy when they do not. This problem becomes more acute as the share of VREs in electricity generation increases. Hence countries like Germany need to buy electricity at high cost from neighbouring countries when there is a shortage but pay them to take excess electricity when there is too much of it – otherwise the distribution system will be put in danger.The modeling by Hirth [5] showed that the “economic value” of solar and wind would drop by 50% and by 40% in Europe when they got to 15% and 30% respectively of total electricity generation. Secondly, VRE require a lot of land, are geographically dispersed and are often located far away from population centers where electricity is needed. Hence transmission costs will be higher – this could be particularly the case for offshore wind. Thirdly regulations such as the Renewable Portfolio Standards (RPS) in the U.S. which require a certain percentage of electricity to be produced by renewable sources by a certain date can make some of the existing power generation redundant. The costs of these “stranded assets” are passed on to the consumer [4]. To tackle the intermittency problem, VREs require some form of reliable back-up power source such as natural gas plants and hydroelectricity which can step in quickly when needed. Eventually, the intermittency problem of VREs will need to be addressed with adequate storage capacity for excess renewable production but all this will add significantly to the capital cost of VREs.

A strong correlation between the domestic electricity price and installed wind and solar capacity per capita (X) was demonstrated across twentyone European countries in [1] – see Fig.1a. However, these data are from 2014. It would be of interest to see if this correlation still holds because a significant reduction in the cost of VREs in recent years has been claimed. In this note the most recent available data are anaylsed. Residential electricity price for different countries for March 2020 is extracted from [7] because it gives the price in a common currency (U.S. dollars per kWh) and is listed in Table 1. The following data for these countries are also listed in Table 1 –

a)      Total installed wind and solar capacity (GW), the total electricity generation, the actual electrical energy contribution of wind and solar in TWh in 2019 from [8]

b)     Population in 2019 taken from [9]

Only countries with installed wind capacity of at least 1 GW are considered. India and Turkey are not considered in electricity price correlations because the subsidy regime is complicated. The electricity price for China is not available in [7]. The total number of countries considered is 23 though only 20 are included in the price correlations.

Domestic Electricity Price Correlations:

Figure 1b shows the domestic electricity price in US c/kWh, P, plotted against, X, the per capita installed VRE capacity in 2019. There is still a correlation between P and X but the correlation is poor and the correlation coefficient (R2) is much lower than in Fig.1a; it does not change much if only European countries are considered as in Fig. 1a. The greater scatter in Fig.1b might be partly due to exchange rate variations between the different currencies and the US dollar. Of course, P does not depend only on X because many other factors such as pricing policy, taxes and subsidies, complexities and opportunities for dynamical trading of wholesale electricity and better matching of supply and demand also come into play [4,5,6]. It is worth noting, from Fig.s 1a and 1b that X has increased significantly between 2014 and 2019 e.g. almost doubling in the U.K. 

Fig.1a Correlation between average domestic electricity price and per capita installed (wind+solar) capacity. Copied from Mearns, Ref.1. Data from 2014.

Figure 2 shows P plotted against the actual share of electricity generation from wind and solar (Y), from columns 4,5,6 in Table 1. Denmark has the highest actual contribution of electricity from wind and solar – this share is around 24% in the U.K. Figure 3 shows P plotted against Z, the ratio of (total installed wind and solar power) to the (continuous power required to meet all electricity generation) using columns 4, 7 and 8 in Table 1. This correlation has the highest R2 value of the various linear correlations tried. In Fig.3, a linear correlation between P and Z has a R2 value of 0.706 and is described by

P (US c/kWh) = 14 Z+12 … (1)

Capacity Factor: It can be seen from Figure 3 that the U.K., for instance, has enough wind and solar capacity to supply all its electricity if they worked without interruption at rated power but in fact only supply about 24% of the total electricity (Fig.2). This highlights the need to consider the capacity factor (CF) for intermittent sources of power. CF is the ratio of the actual electricity delivered by the VRE to the electricity that would be generated if the VRE operated continuously at rated power. CF can be calculated from columns 5,6,7 and 8 and is shown for different countries in Fig.4. Averaged across the countries shown, CF for wind, solar and (wind+solar) is respectively, 0.275, 0.128 and 0.225. Thus, on average, wind provides only 27.5 % of the electricity expected from its installed capacity.

Implications for the U.K

To meet its net zero greenhouse gas (GHG) target, the U.K. will have to move out of fossil fuels as much as possible and offset the rest of the CO2 against natural and artificial sinks such as forests and carbon capture and storage. In addition, it has to dismantle the existing energy infrastructure and improve energy efficiency as much as possible [10]. In 2019, 6.21 EJ (exajoules = 1018) of energy was supplied by fossil fuels in the U.K. Even if we optimistically expect that because of improved efficiency and some offsetting, we need to replace just 60% of this (3.73 EJ or 1036 TWh), the U.K. would require 118 GW of additional continuous CO2-free power generation [10]. If this is to be supplied primarily by offshore wind and we assume a much improved average CF of 0.4 for wind (the current value is 0.3, Fig.4), additional wind capacity of 295 GW has to be built by 2050. The existing wind and solar capacity is 37.2 GW. So, by 2050, the U.K. will have to have around 332 GW of VRE and the actual electric energy generation would be 1360 TWh (323.7+1036) in 2050 and the Z value in Fig. 3 would be 2.14 and P would be 42 US c/kWh from Eq.1 i.e. around 60% higher than in 2019. This is an optimistic projection. In fact, the future might require more than 60% of current fossil fuel use to be replaced because of additional energy requirements because of of initiatives such as bringing on the hydrogen economy and carbon capture and storage. If that is the case and/or the average CF for wind was less than 0.4, the value of Z and hence, P would be higher. Then there are the very substantial environmental, economic (e.g. capital and operating costs) and material requirement challenges that such a massive scale-up of primarily off-shore wind would pose and also the other requirements of meeting net-zero targets such as the dismantling of the existing energy infrastructure [10].   

Of course, correlation does not imply causation and P depends on many other factors as well. In that context it is surprising the R2 value is as high as it is in Fig.3. Perhaps correlations such as in Fig.3 cannot be used to predict actual future domestic electricity prices. However, Fig.3 indicates some desirable and not surprising actions. P can be reduced by reducing Z by any or all of the following

a)      Reducing the capacity requirement for VRE by increasing the capacity factor – note that Z=Y/CF. The fact that the R2 value in Fig.3 is higher than in Fig. 2 suggests that more efficient VRE use (higher CF), in addition to lowering the actual share of VRE in the electricity generation results in lower P.

b)     Reducing the overall future requirements for energy e.g. through efficiency improvements and lifestyle changes so that requirement for VRE capacity is also reduced

c)      Reducing the proportion of future energy to be supplied by VRE by increasing other CO2-free energy sources such as nuclear power but they might have other cost and environmental implications.

All changes to the energy infrastructure need to be assessed honestly on a life cycle basis to ensure that they actually deliver the benefits they promise and do not have unintended consequences.   

REFERENCES

 1.      Mearns, E., 2015, “Green Mythology and the High Price of European Electricity”, http://euanmearns.com/green-mythology-and-the-high-price-of-european-electricity/

2.      Shellenberger, M. 2018, “If Solar And Wind Are So Cheap, Why Are They Making Electricity So Expensive?, https://www.forbes.com/sites/michaelshellenberger/2018/04/23/if-solar-and-wind-are-so-cheap-why-are-they-making-electricity-more-expensive/?sh=705bec0c1dc6

3.      Brian Murray, 2019. “The Paradox of Declining Renewable Costs and Rising Electricity Prices” https://www.forbes.com/sites/brianmurray1/2019/06/17/the-paradox-of-declining-renewable-costs-and-rising-electricity-prices/?sh=47ef8a7b61d5

4.      Greenstone, M and Nath, I. 2019, “Do Renewable Portfolio Standards Deliver?”, Energy Policy Institute, University of Chicago, https://epic.uchicago.edu/wp-content/uploads/2019/07/Do-Renewable-Portfolio-Standards-Deliver.pdf

5.      Hirth, L., 2013, “The market value of variable renewables. The effect of solar wind power variability on their relative price”, Energy Economics, Vol 38,pp 218-236. https://neon.energy/Hirth-2013-Market-Value-Renewables-Solar-Wind-Power-Variability-Price.pdf

6.      Seels, J., Mills, A, Wiser, R. et al. 2018, “Impacts of High Variable Renewable Energy Futures on Wholesale Electricity Prices and on Electric-Sector Decision Making” , Lawrence Berkely National Laboratory, https://eta-publications.lbl.gov/sites/default/files/report_pdf_0.pdf

7.      https://www.globalpetrolprices.com/electricity_prices/#hl183

8.      https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy/downloads.html

9.      https://en.wikipedia.org/wiki/List_of_countries_by_population_(United_Nations)

10.  Kalghatgi, G, 2020, “Challenges of energy transition needed to meet decarbonization targets set up to address climate change”, J Automotive Safety and Energy, Vol. 11 ,pp 276-286. Can be downloaded from https://www.journalase.com/EN/Y2020/V11/I3/276