arXiv subjects

Sebastian Wehrle

Publications and source records attributed to Sebastian Wehrle.

6 recordsLinked to original sources

arXiv2021

Explaining the decline of US wind output power density

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.

stat.AP↗

arXiv2021

Reviewing methods and assumptions for high-resolution large-scale onshore wind energy potential assessments

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 relating to 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, 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.

econ.GN↗

arXiv2020

Towards a global dynamic wind atlas: A multi-country validation of wind power simulation from MERRA-2 and ERA-5 reanalyses bias-corrected with the Global Wind Atlas

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, the newer ERA5- reanalysis recently gained importance. Here, we use these two datasets to simulate wind power generation and evaluate the respective quality in terms of correlations and errors when validated against historical wind power generation. However, due to their coarse spatial resolution, reanalyses fail to adequately represent local climatic conditions. We therefore additionally apply mean bias correction with two versions of the Global Wind Atlas (GWA) and assess the respective quality of resulting simulations. Potential users of the dataset can also benefit from our analysis of the impact of spatial and temporal aggregation on simulation quality indicators. While similar studies have been conducted, they mainly cover limited areas in Europe. In contrast, we look into regions, which globally differ significantly in terms of the prevailing climate: the US, Brazil, South-Africa, and New Zealand. Our principal findings are that (i) ERA5 outperforms MERRA-2, (ii) no major improvements can be expected by using bias-correction with GWA2, while GWA3 even reduces simulation quality, and (iii) temporal aggregation increases correlations and reduces errors, while spatial aggregation does so only consistently when comparing very low and very high aggregation levels.

stat.AP↗

arXiv2020

The Cost of Undisturbed Landscapes

By 2030 Austria aims to meet 100% of its electricity demand from domestic renewable sources, with most of the additional generation coming from wind and solar energy. Apart from the benefit of reducing CO2 emissions and, potentially, system cost, wind power is associated with negative impacts at the local level, such as interference with landscape aesthetics. Some of these impacts might be avoided by using alternative renewable energy technologies. Thus, we quantify the opportunity cost of wind power versus its best feasible alternative solar photovoltaics, using the power system model medea. Our findings suggest that the cost of undisturbed landscapes is considerable, particularly when solar PV is mainly realized on roof-tops. 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.

econ.GN↗

arXiv2019

The perils of automated fitting of datasets: the case of a wind turbine cost model

Rinne et al. conduct an interesting analysis of the impact of wind turbine technology and land-use on wind power potentials, which allows profound insights into each factors contribution to overall potentials. The paper presents a detailed 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. We believe that propose a cutting edge model of site-specific investment costs. However, the site-independent cost model is flawed in our opinion. This flaw most likely does not impact the results presented in the paper, although 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.

stat.AP↗

arXiv2018

District heating systems under high CO2 emission prices: the role of the pass-through from emission cost to electricity prices

Low CO2 prices have prompted discussion about political measures aimed at increasing the cost of carbon dioxide emissions. These costs affect, inter alia, integrated district heating system operators (DHSO), often owned by municipalities with some political influence, that use a variety of (CO2 emis- sion intense) heat generation technologies. We examine whether DHSOs have an incentive to support measures that increase CO2 emission prices in the short term. Therefore, we (i) develop a simplified analytical framework to analyse optimal decisions of a district heating operator, and (ii) investigate the market-wide effects of increasing emission prices, in particular the pass- through from emission costs to electricity prices. Using a numerical model of the common Austrian and German power system, we estimate a pass-through from CO2 emission prices to power prices between 0.69 and 0.53 as of 2017, depending on the absolute emission price level. We find the CO2 emission cost pass-through to be sufficiently high so that low-emission district heating systems operating at least moderately efficient generation units benefit from rising CO2 emission prices in the short term.

econ.GN↗