Vulnerability of wind power resources to climate change in the continental United States

Renewable energy resources will play a key role in meeting the world's energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities.     

Simulating the future wind energy resource of Ireland using the COSMO‐CLM model

We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of regional climate model (RCM) simulations. The RCM used in this work is the Consortium for Small‐scale Modelling–climate limited‐area modelling (COSMO‐CLM) model. The COSMO‐CLM model was evaluated by performing simulations of the past Irish climate, driven by European Centre for Medium‐Range Weather Forecasts ERA‐40 data, and comparing the output with observations. For the investigation of the influence of the future climate under different climate scenarios, the Max Planck Institute's global climate model, ECHAM5, was used to drive the COSMO‐CLM model. Simulations are run for a control period 1961–2000 and future period 2021–2060. To add to the number of ensemble members, the control and future simulations were driven by different realizations of the ECHAM5 data. The future climate was simulated using the Intergovernmental Panel on Climate Change emission scenarios, A1B and B1. The research was undertaken to consolidate, and as a continuation of, similar research using the Rossby Centre's RCA3 RCM to investigate the effects of climate change on the future wind energy resource of Ireland. The COSMO‐CLM projections outlined in this study agree with the RCA3 projections, with both showing substantial increases in 60 m wind speed over Ireland during winter and decreases during summer. The projected changes of both studies were found to be statistically significant over most of Ireland. The agreement of the COSMO‐CLM and RCA3 simulation results increases our confidence in the robustness of the projections. Copyright © 2012 John Wiley & Sons, Ltd.     

Characterization of the wind speed variability and future change in the Iberian Peninsula and the Balearic Islands

Wind energy is susceptible to global climate change because it could alter the wind patterns. Then, improvement of our knowledge of wind field variability is crucial to optimize the use of wind resources in a given region. Here, we quantify the effects of climate change on the surface wind speed field over the Iberian Peninsula and Balearic Islands using an ensemble of four regional climate models driven by a global climate model. Regions of the Iberian Peninsula with coherent temporal variability in wind speed in each of the models are identified and analysed using cluster analysis. These regions are continuous in each model and exhibit a high degree of overlap across the models. The models forced by the European Reanalysis Interim (ERA‐Interim) reanalysis are validated against the European Climate Assessment and Dataset wind. We find that regional models are able to simulate with reasonable skill the spatial distribution of wind speed at 10 m in the Iberian Peninsula, identifying areas with common wind variability. Under the Special Report on Emissions Scenarios (SRES) A1B climate change scenario, the wind speed in the identified regions for 2031–2050 is up to 5% less than during the 1980–1999 control period for all models. The models also agree on the time evolution of spatially averaged wind speed in each region, showing a negative trend for all of them. These tendencies depend on the region and are significant at p = 5% or slightly more for annual trends, while seasonal trends are not significant in most of the regions and seasons. Copyright © 2015 John Wiley & Sons, Ltd.     

A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean

Renewable energy resources, such as wind, are available worldwide. Locating areas with high and continual wind sources are crucial in pre-planning of wind farms. Vast offshore areas are characterized by higher and more reliable wind resources in comparison with continental areas. However, offshore wind energy production is in a quite preliminary phase. Elaborating the potential productivity of wind farms over such areas is challenging due to sparse in situ observations. The Mediterranean basin is not an exception. In this study we are proposing numerical simulations of near-surface wind fields from regional climate models (RCMs) in order to obtain and fill the gaps in observations over the Mediterranean basin. Four simulations produced with two regional climate models are examined here. Remote sensing observations (QuikSCAT satellite) are used to assess the skill of the simulated fields. A technique for estimating the potential energy from the wind fields over the region is introduced. The wind energy potential atlas and the map of a wind turbine's functional range are presented, locating the potentially interesting sub-regions for wind farms. The ability of models to reproduce the annual cycle and the probability density function of wind speed anomalies are detailed for specified sub-regions.     

Future changes in wind energy resource over the Northwest Passage based on the CMIP6 climate projections

The preferential use of renewable energy sources such as wind power has been proposed as one of the most effective strategies in reducing greenhouse gas emissions in the energy sector. However, wind energy resources are vulnerable to climate change, which might have a huge impact on the area under consideration. In this research, we used the wind speed data obtained from the seven coupled global climate models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) to quantitatively analyze the differences in wind energy resource (WER) between the future and the historical period, geared toward understanding the impact of climate change on wind energy sources. Relevant results show that the future WER would decreases below 20% in the region south of the Northwest Passage, while would significantly increase in the north region of 72°N (specifically in the Beaufort Sea). Further, reports predict that by the end of the 21st century, if no interventions are made to mitigate greenhouse gas emissions, the northern region's WER would increase even more with some grid points exceeding 30% and have a significant growth trend, but at the same time the intra‐annual variability in these region would also increase significantly with some grid points exceeding 140% of that in the historical period. Moreover, the maximum wind speed values would encounter a noteworthy increase of up to 20%, which will bring great challenge to the development of wind energy in these region. Although the current models still have great uncertainties in the future climate prediction, our work still has certain guiding significance for the future development of wind energy over the Northwest Passage.     

Projected changes in wind speed and its energy potential in China using a high‐resolution regional climate model

Following its commitment to Paris Agreement in 2015, China has started to explore potential renewable energy solutions with low carbon emissions to mitigate global warming. Though wind energy is one of the most cost‐effective solutions and has been favored for climate policy development around the world, its high sensitivity to climate change raises some critical issues for the long‐term effectiveness in providing sustainable energy supply. Particularly, how wind speed and its energy potential in China will change in the context of global warming is still not well understood. In this paper, we simulate the near‐surface wind speed over China using the PRECIS regional climate modeling system under different RCP emission scenarios for assessing the possible changes in wind speed and wind energy availability over China throughout the 21^st century. Overall, the PRECIS model can reasonably reproduce the mesoscale climatological near‐surface wind speed and directions as documented in reanalysis data across most regions of China, while some local discrepancies are reported in the southwestern regions. In the future, the annual mean wind speed would be decreasing in most regions of China, except for a slightly increase in the southeast. The expected changes in wind speed are characterized with different amplitudes and rates under different RCP emission scenarios. The changes in the spatial distribution of wind speed seem to be sensitive for RCP climate emission scenarios, especially in the late 21^st century. The spatiotemporal changes in wind energy potential exhibit a similar behavior to those in near‐surface wind speed, but the magnitudes of these changes are larger. In general, the wind power density is expected to increase by over 5% in winter in the major wind fields in China (ie, Northwest, Northcentral and Northeast), while significant decreases (by about 6% on average) are projected for other seasons (ie, spring, summer and autumn). By contrast, the wind energy potential in the northeast would increase over most months in the year, especially in winter and summer. The results of this research are of great importance for understanding where and to what extent the wind energy can be utilized to contribute renewable energy system development in China in support of its long‐term climate change mitigation commitment.     

Climate change implications for wind power resources in the Northwest United States

Using statistically downscaled output from four general circulation models (GCMs), we have investigated scenarios of climate change impacts on wind power generation potential in a five-state region within the Northwest United States (Idaho, Montana, Oregon, Washington, and Wyoming). All GCM simulations were extracted from the standardized set of runs created for the Intergovernmental Panel on Climate Change (IPCC). Analysis of model runs for the 20th century (20c3m) simulations revealed that the direct output of wind statistics from these models is of relatively poor quality compared with observations at airport weather stations within each state. When the GCM output was statistically downscaled, the resulting estimates of current climate wind statistics are substantially better. Furthermore, in looking at the GCM wind statistics for two IPCC future climate scenarios from the Special Report on Emissions Scenarios (SRES A1B and A2), there was significant disagreement in the direct model output from the four GCMs. When statistical downscaling was applied to the future climate simulations, a more coherent story unfolded related to the likely impact of climate change on the region's wind power resource. Specifically, the results suggest that summertime wind speeds in the Northwest may decrease by 5–10%, while wintertime wind speeds may decrease by relatively little, or possibly increase slightly. When these wind statistics are projected to typical turbine hub heights and nominal wind turbine power curves are applied, the impact of the climate change scenarios on wind power may be as high as a 40% reduction in summertime generation potential.     

Co-fluctuation patterns of per capita carbon dioxide emissions: The role of energy markets

This paper applies principal component analysis to investigate the linkages, or dominant co-fluctuation patterns, of per capita carbon dioxide emissions across countries for the time period 1950–2000. Energy resource world markets are investigated as an offsetting mechanism possibly coordinating emission fluctuations between countries. The results of the analysis provide evidence that world energy resource markets are acting as a coordinating mechanism for emission fluctuations in most cases. The results also suggest that until recently the dominant emission co-fluctuation pattern for developed countries differs from the dominant emission co-fluctuation pattern for developing countries. The common fluctuation pattern found in the 1984–2000 time period suggests that an offsetting mechanism does exist and will help contain global per capita emissions into the future. The strong degree that emissions are linked between countries and energy markets acting as an offsetting mechanism suggests that to be successful a global agreement to address climate change must require emission reductions by all major emitters, not just the developed countries.     

Offshore wind speed estimates from a high‐resolution rapidly updating numerical weather prediction model forecast dataset

In association with the Department of Energy–funded Position of Offshore Wind Energy Resources (POWER) project, we present results from compositing a 3‐year dataset of 80‐m (above ground level) wind forecasts from the 3‐km High‐Resolution Rapid Refresh (HRRR) model over offshore regions for the contiguous United States. The HRRR numerical weather prediction system runs once an hour and features hourly data assimilation, providing a key advantage over previous model‐based offshore wind datasets. On the basis of 1‐hour forecasts from the HRRR model, we highlight the different climatological regimes of the nearshore environment, characterizing the mean 80‐m wind speed as well as the frequency of exceeding 4, 12, and 25 m s^?1 for east and west coast, Gulf of Mexico, and Great Lake locations. Preliminary verification against buoy measurements demonstrates good agreement with observations. This dataset can inform the placement of targeted measurement systems in support of improving resource assessments and wind forecasts to advance offshore wind energy goals both in New England and other coastal regions of the United States.     

The Hydropower Potential Assessment Tool (HPAT): Evaluation of run-of-river resource potential for any global land area and application to Falls Creek,Oregon, USA

Small-scale hydropower systems are popular both in the United States and much of the developing world due to the emphasis on renewable energy and the general cost-competitiveness of hydroelectric power generation. We present a novel modeling package, referred to as the Hydropower Potential Assessment Tool (HPAT), to assess historic and projected future small-scale run-of-river hydropower resource potential at a single location or distributed over a study region. HPAT implements a fully-distributed streamflow model, which is coupled to a digital elevation model to assess hydropower resource potential. To demonstrate HPAT, we implement the models for a privately-owned run-of-river facility on Falls Creek outside of Sweet Home, Oregon, USA. We use an ensemble of Global Climate Models (GCMs) for two future climate scenarios to project a plausible range of future changes at this site. For the Falls Creek facility, HPAT projects that the timing of peak streamflow will shift from spring to winter and that mean annual hydropower potential will likely decrease slightly from average 1980–2010 historic conditions through the end of the 21st century. All inputs to HPAT are globally available, except for streamflow observations necessary for calibration.     

An investigation of the impacts of climate change on wave energy generation: The Wave Hub,Cornwall, UK

In this paper a generic methodology is presented that allows the impacts of climate change on wave energy generation from a wave energy converter (WEC) to be quantified. The methodology is illustrated by application to the Wave Hub site off the coast of Cornwall, UK. Control and future wave climates were derived using wind fields output from a set of climate change experiments. Control wave conditions were generated from wind data between 1961 and 2000. Future wave conditions were generated using two IPCC wind scenarios from 2061 to 2100, corresponding to intermediate and low greenhouse gas emissions (IPCC scenarios A1B and B1 respectively). The quantitative comparison between future scenarios and the control condition shows that the available wave power will increase by 2–3% in the A1B scenario. In contrast, the available wave power in the B1 scenario will decrease by 1–3%, suggesting, somewhat paradoxically, that efforts to reduce greenhouse gas emissions may reduce the wave energy resource. Meanwhile, the WEC energy will yield decrease by 2–3% in both A1B and B1 scenarios, which is mainly due to the relatively low efficiency of energy extraction from steeper waves by the specific WEC considered. Although those changes are relatively small compared to the natural variability, they may have significance when considered over the lifetime of a wave energy farm. Analysis of downtime under low and high thresholds suggests that the distribution of wave heights at the Wave Hub will have a wider spread due to the impacts of climate change, resulting in longer periods of generation loss. Conversely, the estimation of future changes in joint wave height-period distribution provides indications on how the response and power matrices of WECs could be modified in order to maintain or improve energy extraction in the future.     

Wind speed variability across the UK between 1957 and 2011

By using surface data from 57 UK meteorological stations, a national [British Atmospheric Data Centre (BADC)‐57] and regional wind index for the UK has been calculated for the period 1983–2011. For a subset of seven stations, an additional national index (BADC‐7) has been calculated for the period 1957–2011. The indices show an annual variability of 4% over their respective periods, corresponding to a variation in typical wind turbine capacity factor of 7%. These indices are compared with indices calculated from other sources, namely an index generated using a gridded dataset of observed values interpolated across the UK, an index calculated from an area bounding the UK using the ERA‐40 re‐analysis dataset, indices calculated from bilinear interpolation of the ERA‐40 re‐analysis dataset to the 57 and 7 stations and another independent UK wind index. The indices show variation in trends, with all showing some level of decline with the exception of that generated using the ERA‐40 re‐analysis dataset averaged over the UK, which shows a significant increase. The various indices show varying degrees of agreement with correlation coefficients, after trends are removed, ranging between 0.611 and 0.979. The effect of changes in site exposure, instrument bias and measuring height was considered for the BADC‐7 and BADC‐57 indices. The change in instrument measurement height appears to have a significant biasing effect, and it is likely that this along with changes in exposure at urban sites has caused the decline in annual wind speeds observed for some of the indices. There does not appear to be evidence for significant changes in large‐area (mesoscale) surface roughness. The correlation between annual mean wind speeds at the seven surface station sites used to calculate the BADC‐7 index is seen to be quite weak, indicating very localized variations in inter‐annual variability. When regional differences in the index are investigated, it is seen that wind speeds show a very slight decline across the UK in all regions except the south‐east, which shows a slight increase. The greatest decrease is seen in the north‐west. These changes are in the same direction as the tentative predictions given by climate models for future changes in wind speed across the UK, although the uncertainty is large given the large degree of inter‐annual variation. Copyright © 2013 John Wiley & Sons, Ltd.     

Modelling the effects of climate change on the energy system—A case study of Norway

The overall objective of this work is to identify the effects of climate change on the Norwegian energy system towards 2050. Changes in the future wind- and hydro-power resource potential, and changes in the heating and cooling demand are analysed to map the effects of climate change. The impact of climate change is evaluated with an energy system model, the MARKAL Norway model, to analyse the future cost optimal energy system. Ten climate experiments, based on five different global models and six emission scenarios, are used to cover the range of possible future climate scenarios and of these three experiments are used for detailed analyses. This study indicate that in Norway, climate change will reduce the heating demand, increase the cooling demand, have a limited impact on the wind power potential, and increase the hydro-power potential. The reduction of heating demand will be significantly higher than the increase of cooling demand, and thus the possible total direct consequence of climate change will be reduced energy system costs and lower electricity production costs. The investments in offshore wind and tidal power will be reduced and electric based vehicles will be profitable earlier.     

Energy scarcity and economic growth reconsidered

The analysis in this paper is concerned with the effect of energy scarcity on economic growth in the United States. After defining the notion of scarcity and introducing two measures of scarcity, unit costs and relative energy price, changes in the trend in resource scarcity for natural gas, bituminous coal, anthracite coal, and crude oil over the most recent three decades are investigated. Each of the energy resources became significantly more scarce resources during the decade of the 1970s in the Malthusian Stock Scarcity and Malthusian Flow Scarcity sense. Unit costs exhibit a similar change for natural gas and crude oil but not for bituminous coal and anthracite coal. The situation reversed itself during the 1980s. Natural gas, bituminous coal, anthracite coal, and crude oil all became significantly less scarce resources during the decade of the 1980s than they had been during the 1970s. That is, the increase in scarcity as measured by relative energy prices observed during the decade of the 1970s was not reversed completely during the 1980s for natural gas and crude oil. Unit costs for natural gas and crude oil demonstrate analogous patterns and test results. Given that change has taken place, it has implications for future economic growth to the extent resource scarcity and economic growth are interrelated. To see whether this is a relevant concern, subsequent to the examination of changing resource scarcity trends, an objective effort is made to identify a long-run equilibrium relationship between energy scarcity and economic growth. Relying on co-integration techniques, only for crude oil is there a suggestion that resource scarcity has affected economic growth in the United States over the period 1889–1992.     

The vulnerability of wind power to climate change in Brazil

The availability and reliability of wind power depend a great deal on current and future climate conditions, which may vary in light of possible global climate change (GCC). Long-term energy planning, however, does not normally take possible future GCC into consideration, which may turn out to be a risky exercise. In the case of Brazil, the untapped wind power potential is known to be impressive, provided that climate conditions remain the same over time. The focus of this study is to analyze some possible impacts of GCC on the wind power potential of Brazil, by simulating wind conditions associated with the IPCC A2 and B2 Scenarios. Results based on the HadCM3 general circulation model and the analysis of the country's wind database indicate that the wind power potential in Brazil would not be jeopardized in the future due to possible new climate conditions. On the contrary, improved wind conditions are expected, particularly in the Northeast coast of the country. Therefore, investments in wind power generation can be an interesting way to expand renewable energy production in Brazil. However, given the large uncertainties associated with GCC models and scenarios, the findings of this paper should be viewed as a possibility rather than as a projection.     

Simulating climate change and its effects on the wind energy resource of Ireland

We consider the impact of climate change on the wind energy resource of Ireland using an ensemble of Regional Climate Model (RCM) simulations. The RCM dynamically downscales the coarse information provided by the Global Climate Models (GCMs) and provides high resolution information, on a subdomain covering Ireland. The RCM used in this work is the Rossby Center's RCM (RCA3). The RCA3 model is evaluated by performing simulations of the past Irish climate, driven by European Center for Medium‐Range Weather Forecasts ERA‐40 data, and by comparing the output to observations. Results confirm that the output of the RCA3 model exhibits reasonable and realistic features as documented in the historical wind data record. For the investigation of the influence of the future climate under different climate scenarios, the Max Plank Institute's GCM, European Center Hamburg Model, is used to drive the RCA3 model. Simulations are run for a control period 1961‐2000 and future period 2021‐2060. The future climate was simulated using the four Intergovernmental Panel on Climate Change emission scenarios A1B, A2, B1 and B2. The results for the downscaled simulations show a substantial overall increase in the energy content of the wind for the future winter months and a decrease during the summer months. The projected changes for summer and winter were found to be statistically significant over most of Ireland. However, the projected changes should be viewed with caution since the climate change signal is of similar magnitude to the variability of the evaluation and control simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

Global wind power development: Economics and policies

Existing literature indicates that theoretically, the earth's wind energy supply potential significantly exceeds global energy demand. Yet, only 2–3% of global electricity demand is currently derived from wind power despite 27% annual growth in wind generating capacity over the last 17 years. More than 95% of total current wind power capacity is installed in the developed countries plus China and India. Our analysis shows that the economic competitiveness of wind power varies at wider range across countries or locations. A climate change damage cost of US$20/tCO₂ imposed to fossil fuels would make onshore wind competitive to all fossil fuels for power generation; however, the same would not happen to offshore wind, with few exceptions, even if the damage cost is increased to US$100/tCO₂. To overcome a large number of technical, financial, institutional, market and other barriers to wind power, many countries have employed various policy instruments, including capital subsidies, tax incentives, tradable energy certificates, feed-in tariffs, grid access guarantees and mandatory standards. Besides, climate change mitigation policies, such as the Clean Development Mechanism, have played a pivotal role in promoting wind power. Despite these policies, intermittency, the main technical constraint, could remain as the major challenge to the future growth of wind power.     

Climate change impacts on wind energy: A review

Expansion of wind energy installed capacity is poised to play a key role in climate change mitigation. However, wind energy is also susceptible to global climate change. Some changes associated with climate evolution will likely benefit the wind energy industry while other changes may negatively impact wind energy developments, with such ‘gains and losses’ depending on the region under consideration. Herein we review possible mechanisms by which global climate variability and change may influence the wind energy resource and operating conditions, summarize some of the tools that are being employed to quantify these effects and the sources of uncertainty in making such projections, and discuss results of studies conducted to date. We present illustrative examples of research from northern Europe. Climate change analyses conducted for this region, which has shown considerable penetration of wind energy, imply that in the near-term (i.e. to the middle of the current century) natural variability exceeds the climate change signal in the wind energy resource and extreme wind speeds, but there will likely be a decline in icing frequency and sea ice both of which will tend to benefit the wind energy industry. By the end of the twenty-first century there is evidence for small magnitude changes in the wind resource (though the sign of the change remains uncertain), for increases in extreme wind speeds, and continued declines in sea ice and icing frequencies. Thus the current state-of-the-art suggests no detectable change in the wind resource or other external conditions that could jeopardize the continued exploitation of wind energy in northern Europe, though further research is needed to provide greater confidence in these projections.     

Testing Hubbert

The Hubbert theory of oil depletion, which states that oil production in large regions follows a bell-shaped curve over time, has been cited as a method to predict the future of global oil production. However, the assumptions of the Hubbert method have never been rigorously tested with a large, publicly available data set. In this paper, three assumptions of the modern Hubbert theory are tested using data from 139 oil producing regions. These regions are sub-national (United States state-level, United States regional-level), national, and multi-national (subcontinental and continental) in scale. We test the assumption that oil production follows a bell-shaped curve by generating best-fitting curves for each region using six models and comparing the quality of fit across models. We also test the assumptions that production over time in a region tends to be symmetric, and that production is more bell-shaped in larger regions than in smaller regions.     

An indicator framework for assessing US state carbon emissions reduction efforts (with baseline trends from 1990 to 2001)

States are at the forefront of climate-related energy policy in the US, developing innovative policy and regional institutions for reducing carbon dioxide and other greenhouse gases. States matter because the larger ones use more energy and produce more carbon emissions than most nations and because their policies, though heterogeneous and until recently quite limited in scope, are shaping the context for national climate action. Despite this significance, little is known about trends in state carbon emissions or the effectiveness of state policies in reducing emissions. This paper describes a framework for analyzing and comparing state carbon emissions performance using sectoral indicators of emissions, energy consumption and carbon intensity linked to key policy domains. The paper also describes the range of state experience across indicators during the period 1990–2001, establishing a baseline of leading, lagging and average experience against which future state and regional change can be assessed. The conceptual framework and the empirical analysis of emission trends are intended to provide a better understanding of, and means for monitoring, state contributions toward achieving energy system sustainability.