The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of ...their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments of wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, constraints due to regulation or public opposition, expert and stakeholder workshops, willingness to pay/accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research.
•Review of over 300 studies on large-scale onshore wind potential assessments.•Analysis of geographic, technical, economic and ‘feasible’ potentials.•Identify weaknesses in methods and best practice examples.•Methods could improve transparency, validation, and sensitivities.•Further interdisciplinary research required on ‘feasible’ potentials.
Abstract
US wind power generation has grown significantly over the last decades, in line with the number and average size of operating turbines. However, wind power density has declined, both ...measured in terms of wind power output per rotor swept area as well as per spacing area. To study this effect, we present a decomposition of US wind power generation data for the period 2001–2021 and examine how changes in input power density and system efficiency affected output power density. Here, input power density refers to the amount of wind available to turbines, system efficiency refers to the share of power in the wind flowing through rotor swept areas which is converted to electricity and output power density refers to the amount of wind power generated per rotor swept area. We show that, while power input available to turbines has increased in the period 2001–2021, system efficiency has decreased. In total, this has caused a decline in output power density in the last 10 years, explaining higher land-use requirements. The decrease in system efficiency is linked to the decrease in specific power, i.e. the ratio between the nameplate capacity of a turbine and its rotor swept area. Furthermore, we show that the wind available to turbines has increased substantially due to increases in the average hub height of turbines since 2001. However, site quality has slightly decreased in this period.
Rinne et al. (2018) conduct a detailed analysis of the impact of wind turbine technology and land-use on wind power potentials, which allows important insights into each factor’s contribution to ...overall potentials. The paper presents a detailed and very valuable model of site-specific wind turbine investment cost (i.e. road- and grid access costs), complemented by a model used to estimate site-independent costs.
However, the site-independent cost model is flawed in our opinion. This flaw most likely does not impact the results on cost supply-curves of wind power presented in the paper. However, we expect a considerable generalization error. Thus the application of the wind turbine cost model in other contexts may lead to unreasonable results. More generally, the derivation of the wind turbine cost model serves as an example of how applications of automated regression analysis can go wrong.
Reanalysis data are widely used for simulating renewable energy and in particular wind power generation. While MERRA-2 has been a de-facto standard in many studies for a long time, the newer ...ERA5-reanalysis recently gained importance. Here, both datasets were used to simulate wind power generation and evaluate their quality in terms of correlations and error measures compared to historical data of wind power generation. Due to their coarse resolution, reanalyses are known to fail to represent local climatic conditions adequately. Hence, mean bias correction was applied with two versions of the Global Wind Atlas (GWA) to the reanalysis data and the quality of the resulting simulations was assessed. Potential users of these datasets can also benefit from our analysis of the impact of spatial and temporal aggregation on indicators of simulation quality. We also assessed regions which differ significantly in terms of the prevailing climate, some of which are underrepresented in similar studies: the US, Brazil, South-Africa, and New Zealand. Our principal findings are threefold. (i) ERA5 outperforms MERRA-2 in terms of the assessed error measures. (ii) Bias-correction with GWA2 does not improve simulation quality substantially, while bias-correction with GWA3 is detrimental. (iii) Temporal aggregation increases correlations and reduces errors, while spatial aggregation does so consistently only when comparing very fine and very coarse granularities.
•ERA5 outperforms MERRA-2 for wind power simulation.•GWA bias correction does not consistently reduce the error.•GWA2 can be used for bias correction, while GWA3 is not recommended.•Bias between observed and simulated wind power varies strongly depending on location.•Temporal aggregation increases simulation quality, spatial aggregation does not.
The cost of undisturbed landscapes Wehrle, Sebastian; Gruber, Katharina; Schmidt, Johannes
Energy policy,
December 2021, 2021-12-00, 20211201, Volume:
159
Journal Article
Peer reviewed
Open access
By 2030, Austria aims to meet 100% of its electricity demand from domestic renewable sources, such as wind energy. Apart from the benefit of reducing CO2 emissions and, potentially, system cost, wind ...power is also associated with negative impacts at the local level, particularly its interference with landscape aesthetics. Some of these negative impacts might be avoided by using alternative renewable energy technologies. To better understand the trade-offs involved, we quantify the opportunity cost of wind power versus its best feasible alternative, which is solar photovoltaics in Austria. Methodologically, our analysis relies on the power system model medea, a technology-rich, partial-equilibrium model of the Austro-German electricity and district heating markets. Our findings suggest that the cost of undisturbed landscapes is considerable, even more so when solar PV is mainly realised on rooftops. Under a wide range of assumptions, the opportunity cost of wind power is high enough to allow for significant compensation of the ones affected by local, negative wind turbine externalities.
•We assess the cost of not disturbing Austrian landscapes with wind turbines.•Net System Cost are introduced as a measure of welfare.•The cost of undisturbed landscapes is substantial.•Significant compensation for local negative wind turbine externalities possible.
Hydrogen produced from renewable electricity will play an important role in deep decarbonisation of industry. However, adding large electrolyser capacities to a low-carbon electricity system also ...increases the need for additional electricity generation from variable renewable energies. This will require hydrogen production to be variable unless other sources provide sufficient flexibility. Existing sources of flexibility in hydro-thermal systems are hydropower and thermal generation, which are both associated with sustainability concerns. In this work, we use a dispatch model for the case of Sweden to assess the power system operation with large-scale electrolysers, assuming that additional wind power generation matches the electricity demand of hydrogen production on average. We evaluate different scenarios for restricting the flexibility of hydropower and thermal generation and include 29 different weather years to test the impact of variable weather regimes. We show that (a) in all scenarios electrolyser utilisation is above 60% on average, (b) the inter-annual variability of hydrogen production is substantial if thermal power is not dispatched for electrolysis, and (c) this problem is aggravated if hydropower flexibility is also restricted. Therefore, either long-term storage of hydrogen or backup hydrogen sources may be necessary to guarantee continuous hydrogen flows. Large-scale dispatch of electrolysis capacity supported by wind power makes the system more stable, if electrolysers ramp down in rare hours of extreme events with low renewable generation. The need for additional backup capacities in a fully renewable electricity system will thus be reduced if wind power and electrolyser operation are combined in the system.
•Hydrogen production from electrolysis in almost fully renewable system•Dispatch model for Sweden applied to 29 different weather years•On average, electrolyzer utilization above 60% is achieved in all scenarios•Significant inter-annual variability of hydrogen production•Thermal and hydro power reduce variability causing emissions and hydropeaking
We contrast a recent assessment by Mandys et al. that dropping PV LCOE in the UK will lead to photovoltaics becoming the most competitive renewable energy technology by 2030, by arguing that (1) ...strong seasonal variation, (2) too little demand correlation, and (3) highly concentrated production periods still lead to overall more competitiveness and less system cost of wind power production.
We contrast a recent assessment by Mandys et al. that dropping PV LCOE in the UK will lead to photovoltaics becoming the most competitive renewable energy technology by 2030, by arguing that (1) strong seasonal variation, (2) too little demand correlation, and (3) highly concentrated production periods still lead to overall more competitiveness and less system cost of wind power production.
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