Resource Documents: Netherlands (24 items)
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Windparken mengen zich in het weer [Wind facilities interfere with the weather]
Author: Koninklijk Nederlands Meteorologisch Instituut
Uit een recente studie met het KNMI weermodel blijkt dat windparken het weer beïnvloeden. De wind in de buurt van windparken neemt gemiddeld af en ook de temperatuur en luchtvochtigheid veranderen. Het is niet zo dat windenergie klimaatverandering veroorzaakt want het effect van windparken op het weer is plaatselijk. Toch is het effect in bepaalde weersituaties op grote afstand van het windpark nog merkbaar.
Windparken zijn atmosfeer-mixers
Draaiende rotorbladen van een windturbine zetten bewegingsenergie van de wind om in elektriciteit. Hierdoor neemt de wind achter de windturbine af. Bovendien mixen de rotorbladen de luchtlagen en maken ze wervels (turbulentie) waardoor vocht en warmte in de lucht beter doormengen. Dat kan ervoor zorgen dat wolken oplossen of vormen. Kortom: het weer verandert door windturbines, maar de vraag is hoe en hoeveel.
Weermodel inclusief het effect van windparken
Er komen steeds meer en grotere windparken. Daarom gebruikt het KNMI voor het maken van weersverwachtingen en waarschuwingen sinds afgelopen zomer een versie van weermodel HARMONIE-AROME inclusief het effect van die windparken op de atmosfeer. Met deze versie komt de door het model berekende wind in de omgeving van de windparken beter overeen met de metingen (figuur 1).
Figuur 1. Links het rekengebied van het weermodel HARMONIE-AROME met in rood de locatie van windturbines in 2016 en in blauw de positie van de twee lidars die de wind meten. Rechts de gemiddelde wind in 2016 op de locaties van de twee lidars volgens de metingen (kruisjes) en de berekeningen met (zwarte lijnen) en zonder het effect van de windparken (rode lijnen). Bron: Van Stratum et al., JAMES, 2022
Zogeffect het grootst in stabiele weersomstandigheden
Het effect dat een windpark heeft op het gebied in de windschaduw van het windpark (dus stroomafwaarts) heet het zogeffect. Dat effect is het grootst als de atmosfeer stabiel is. Stabiel wil zeggen dat de zee of het aardoppervlak kouder is dan de lucht erboven. Boven zee gebeurt dat vooral in het voorjaar en begin van de zomer. Omdat koude lucht zwaarder is dan warme, zal er in een stabiele atmosfeer minder verticale menging zijn dan in een onstabiele atmosfeer (waar de warme, lichte lucht onderin zit en op wil stijgen). Minder menging met de “onverstoorde” luchtlagen boven het windpark betekent dat zogeffecten minder snel teniet worden gedaan en op grotere afstand van het windpark nog aanwezig zijn. In stabiele situaties zien we dan ook soms op 50-150 km van het windpark nog een afname van de wind.
Ook de effecten op temperatuur en vocht zijn in stabiele situaties het grootst. Boven zee is de lucht in de onderste laag van de atmosfeer bij stabiel weer niet alleen kouder, maar ook vochtiger. De windturbines transporteren die koudere en vochtigere lucht naar luchtlagen boven de ashoogte van de turbines (figuur 2). Dat kan betekenen dat de kans op mist afneemt en de kans op laaghangende bewolking toeneemt, maar dat is nog niet onderzocht.
Figuur 2. Gemiddelde effect in 2016 van windparken op windsnelheid, (potentiële) temperatuur en luchtvochtigheid op de locatie van windpark Prinses Amalia (blauwe doorgetrokken lijn) en Gemini (zwarte onderbroken lijn) volgens berekeningen met het weermodel HARMONIE-AROME. Er is onderscheid gemaakt tussen stabiele (boven) en onstabiele (onder) weersituaties. Bron: Van Stratum et al., JAMES, 2022
Niet alleen zogeffecten
Het maakt uit of je een geïsoleerde rij windturbines hebt of een rij die als voorste rij onderdeel uitmaakt van een windpark. Als ze allebei vol in de wind staan (dus niet in het zog van andere windturbines), dan wekt de geïsoleerde rij meer energie op. Het windpark vormt namelijk een obstakel waar de wind omheen en overheen wil. Dat zorgt ervoor dat de wind wordt afgeremd stroomopwaarts van het windpark. Ook dit effect zit impliciet in het weermodel, maar hoe goed het model dit effect reproduceert is nog niet onderzocht.
Wat is het effect als het aantal windparken fors wordt uitgebreid?
Op de hele Noordzee stond in 2020 19 GigaWatt aan geïnstalleerd vermogen. In 2050 is dat naar verwachting ongeveer 10 keer zoveel! Het geïnstalleerd vermogen is de hoeveelheid energie die windturbines kunnen produceren als ze optimaal draaien. In werkelijkheid zal de opbrengst lager zijn door bijvoorbeeld zogeffecten of het stilstaan van windturbines voor onderhoud.
Wat gebeurt er met het weer als we de Noordzee vol zetten met windturbines? Hoeveel groter zijn die zogeffecten als er zoveel windparken bij komen? Is er een maximum aan hoeveel windenergie we op de Noordzee kunnen produceren? Het KNMI heeft dit samen met het bedrijf Whiffle en de TU Delft onderzocht in het WINS50-project. Het blijkt dat windparken in 2050 veel vaker in elkaars windschaduw komen te staan (figuur 3). Om een goede inschatting te kunnen maken van de electriciteitsproductie van windparken op de Noordzee wordt het daarom nog belangrijker dat we begrijpen hoe windparken zich mengen in het weer.
Figuur 3: Windparken in 2020 (links) en een hypothetisch windparkscenario voor 2050 (rechts) met het weer van 2020. Deel van de tijd (in %) waarvoor het verschil in windsnelheid op 100 m hoogte tussen HARMONIE-AROME met en zonder windparken voor oostenwind (30 graden rond 75°) groter is dan 1 m/s. Bron: https://wins50.nl
KNMI-klimaatbericht door Ine Wijnant, Natalie Theeuwes, Andrew Stepek (KNMI) en Peter Baas (Whiffle)
Geluid van industriële windturbines: De relatie met gezondheid [Industrial wind turbine noise: the association with human health]
Author: de Laat, Jan; et al.
[English abstract] Climate targets will provide the Netherlands with more and higher industrial wind turbines that produce various ‘side effects’, including noise pollution and annoyance. Especially low-frequency noise and infrasonic vibrations can be detected more than 10 km away. In neighbouring residential areas, long-term exposure, especially at night, leads to sleep disturbances, with secondary symptoms, that may be associated with, for example, delay in cognitive development of children. More research is needed.
Jan A.P.M. de Laat, clinical physicist/audiologist, Audiologisch Centrum (KNO), LUMC, Leiden
Wilco Alteveer, civil engineer, Utrecht
A.J.J. (Ronald) Maas, non-practising vestibulologist, Louw Feenstra, ENT specialist and philosopher, afd. Keel-, neus- en oorheelkunde, Erasmus MC, Rotterdam
Sylvia van Manen, general practitioner and mental health care physician, Haspel Foundation, ’s-Hertogenbosch
Nederlands Tijdschrift voor Geneeskunde, 2021;165:D5999
Download original document: “Geluid van industriële windturbines: De relatie met gezondheid”
Wind turbines and solar farms drive down house prices
Author: Koster, Hans; and Dröes, Martijn
Countries that invest in renewable energy production face frequent opposition from local homeowners. Using a detailed housing transactions dataset covering the whole of the Netherlands since 1985, this column compares the overall impact that wind turbines and solar farms have on housing prices. It finds that tall wind turbines (over 150 metres) have a negative effect, and solar farms generate losses as well (2-3% for homeowners within a 1km orbit). This evidence should be factored into finding the optimal allocation of renewable energy production facilities.
Renewable energy is on the rise (Newbery 2018). While global demand is still strongly increasing amidst the Covid-19 pandemic, the demand for fossil fuels has steeply declined (IEA 2020). Wind turbines are an important source of renewable energy, with 30% of total capacity located in Europe and 17% in the US in 2018. China has invested especially heavily in wind energy, overtaking the EU in 2015 as the largest producer of wind energy. Currently, 36% of worldwide capacity is located in China (GWEC 2019). Wind turbines have become taller over time: turbines in the 1980s were still around 30 metres, while the newest generation of wind turbines are well above 100 metres.
A related trend is the commercial production of renewable energy via solar farms. The first solar farm was constructed in 1982 in California. Yet, with advances in technology, the commercial exploitation of solar farms has only become attractive in the last decade or so (Heal 2009). These solar farms have also become bigger over time; the largest solar farm currently is 40km2 and located in Bhadla, India.
Even though wind turbines comprise a larger part of renewable energy production, last year’s growth in solar photovoltaics capacity was about twice that of wind turbines (REN21 2020). Whether the current surge in the construction of tall wind turbines and large solar farms will continue remains to be seen, but some countries have already suggested that the economic recovery after Covid-19 should be a green one (Jordans 2020).
Wind turbines make noise, cast shadows, cause flickering, and visually pollute the landscape, typically leading to substantial opposition from the local population, including homeowners. A similar story applies for ground-mounted solar panels, as they reflect ambient sound, sunlight, create a buzzing sound, and are also not so great to look at. In line with a large literature on hedonic pricing, we would expect that such ‘external effects’ capitalise into local house prices. Increasing our understanding of these external effects is important to gaining insight into the optimal allocation of renewable energy production facilities.
In a recent study (Dröes and Koster 2020), we examine the effects of tall wind turbines and solar farms on residential property values. Using a detailed housing transactions dataset covering the whole of the Netherlands since 1985, and a difference-in-differences regression methodology, we compare changes to house prices in areas that will receive a turbine in the future to areas in which a turbine already has been built, taking into account a host of other factors determining house prices such as location, general economic trends, and housing quality. In this way, we ensure that we compare apples with apples (i.e. houses in areas that have a turbine compared to houses in near-identical areas without a turbine), rather than apples with oranges. A comparable approach is used to measure the effects of solar farms.
In Figures 1a and 1b, we plot the spatial distribution of (respectively) wind turbines and solar farms across the Netherlands. It is easy to observe that turbines are more common than solar farms.
Figure 1a. The location of wind turbines in the Netherlands
Figure 1b. The location of solar farms in the Netherlands
Most solar farms have been built in recent years. Turbines are particularly common in coastal areas where wind is ubiquitous. Solar farms are mainly built in the northwest of the Netherlands, as more space is available to facilitate large solar farms.
With regard to the empirical results for wind turbines, residential property values are negatively impacted when properties are in close proximity to a wind turbine. In particular, the house prices of properties within a 2km radius decrease on average by 2% relative to comparable properties with no wind turbines nearby. However, we find considerable heterogeneity in the effect of turbines on house prices (see Figure 2). For example, a tall wind turbine (>150m tip height) generates a negative price effect of about 5% within 2km, while we do not find a significant effect for turbines below 50m. We show that our results are robust when (i) we allow for changes in perception to wind turbines, (ii) we look at removals of turbines rather than placements, and (iii) we allow for the effects of multiple turbines. Regarding the latter, we find that only the first turbine within 2km has an effect on property prices. From a policy standpoint, this suggest that it is preferable to cluster wind turbines into large wind farms. We also show that the impact area of turbines is essentially the same for turbines taller than 50m, while the effects are more localised for turbines under 50m.
Figure 2. Wind turbines and house prices
Taking the empirical results at face value, we calculate the overall loss in housing wealth as a result of wind turbines and solar farms. It appears that just 25 turbines account for almost 50% of the total loss, which shows that it is very important to build turbines not too close to residential properties. Indeed, the median loss per turbine is much lower and about €166,000, or about €89 per megawatt hour (MWh). Given the construction costs of about €1.27 million per MW, and the median installed capacity of 3MW, the median loss in housing values is about 4.4% of the median construction costs. Interestingly, the median loss per MWh varies considerably across turbines of different heights. For example, because tall turbines generate more power, the median loss per MWh is about €10, while it is €844 for small turbines. Hence, despite the smaller effects of small turbines on house prices, the lower power output means it is not more efficient to build small turbines.
For solar farms the results are less convincing because the number of solar farms is much lower, making the estimated coefficients less precise. Still, we find evidence suggesting that solar farms lead to a house price decrease of about 2-3%. Unsurprisingly, the effect is more localized than the effect of turbines and confined to 1km. Because fewer solar farms are constructed, the total loss is just over €84 million. Here it also seems more informative to look at the median loss of a solar farm, which amounts to about €0.5 million – somewhat larger than the median loss for one turbine. However, this is mainly because solar farms are generally larger and generate more electricity. The median loss per MWh is €63, which is in the same order of magnitude as the median loss per MWh for wind turbines (i.e. €89 per MWh).
Producing energy in a sustainable way is an important step towards a climate-neutral economy with net-zero greenhouse gas emissions (Castle and Hendry 2020). Wind and solar energy are important sources of renewable energy. However, while reductions in CO₂ emissions benefits the whole population, external effects are borne only by households living close to production sites. Hence, insights into these external effects is paramount, as the size of external effects directly informs the local support for the opening of production sites, such as wind turbines and solar farms. Our study shows that the location of production sites of renewable energy matters, as a few sites cause the lion’s share of losses in housing values in the Netherlands. The results also highlight that when building tall turbines in the right locations, reductions in housing values are a relatively small share (<5%) of the total construction costs of turbines.
Hans Koster, Professor of Urban Economics and Real Estate, Vrije Universiteit Amsterdam
Martijn Dröes, Assistant Professor of Real Estate Finance, University of Amsterdam
20 September 2020
References
Jordans, F (2020), “Germany, Britain call for ‘green recovery’ from pandemic”, Associated Press Berlin, 27 April.
Castle, J and D Hendry (2020), “Decarbonising the Future UK Economy”, VoxEU.org, 4 June.
Dröes, M and H Koster (2020), “Wind turbines, solar farms, and house prices“, CEPR Discussion Paper 15023.
GWEC (2019), Global Wind Report 2018, Global Wind Energy Council.
Heal, G (2009), “Can Renewable Energy Save the World?” VoxEU.org, 29 October.
IEA (2020), Global energy review 2020.
Newbery, D (2018), “Evaluating the Case for Supporting Renewable Electricity”, VoxEU.org, 20 July.
REN21 (2020), Renewables 2020 Global Status Report.
Mortality limits used in wind energy impact assessment underestimate impacts of wind farms on bird populations
Author: Schippers, Peter; et al.
Abstract—
1. The consequences of bird mortality caused by collisions with wind turbines are increasingly receiving attention. So‐called acceptable mortality limits of populations, that is, those that assume that 1%–5% of additional mortality and the potential biological removal (PBR), provide seemingly clear‐cut methods for establishing the reduction in population viability. 2. We examine how the application of these commonly used mortality limits could affect populations of the Common Starling, Black‐tailed Godwit, Marsh Harrier, Eurasian Spoonbill, White Stork, Common Tern, and White‐tailed Eagle using stochastic density‐independent and density‐dependent Leslie matrix models. 3. Results show that population viability can be very sensitive to proportionally small increases in mortality. Rather than having a negligible effect, we found that a 1% additional mortality in postfledging cohorts of our studied populations resulted in a 2%–24% decrease in the population level after 10 years. Allowing a 5% mortality increase to existing mortality resulted in a 9%–77% reduction in the populations after 10 years.
Peter Schippers, Ralph Buij, Alex Schotman, Jana Verboom, Henk van der Jeugd, Eelke Jongejans
Wageningen Environmental Research, Wageningen University & Research; Environmental Systems Analysis, Wageningen University; Vogeltrekstation – Dutch Centre for Avian Migration and Demography, Wageningen; Animal Ecology and Physiology, Radboud University, Nijmegen, The Netherlands
Ecology and Evolution. Published on line 04 June 2020. doi: 10.1002/ece3.6360
Download original document: “Mortality limits used in wind energy impact assessment underestimate impacts of wind farms on bird populations”
