In Environmental and Resource Economics, Hertie School researchers provide comprehensive cost-potential curves of wind energy for European countries and find that for most countries, disamenity costs are not a game changer.
In November 2022, Hertie School researchers Dr. Oliver Ruhnau, Raffaele Sgarlato, and Professor of Energy Policy Lion Hirth published a paper on the role of disamenity costs in the cost-potential curves of onshore wind energy in the journal Environmental Resource Economics. The publication provides a comprehensive set of cost-potentials curves for all European countries, which can be used for modeling energy systems. They find that incorporating disamenity costs, or estimated costs of negative external effects of wind energy production, into cost-potential curves is not a “game changer” for on-shore wind energy in Europe, increasing estimated costs by 0.2–12.5 €/MWh.
Numerical models are used to determine the optimal energy mix in energy systems. Cost-potential curves estimate how much energy can be generated at what cost. These estimates are often based on engineering costs (e.g. materials, fuel), but in reality, the perceived negative effects of on-shore wind energy (disamenity costs) also impact decisions about wind energy expansion. Public perception of these costs can be seen in the form of local resistance to expansion plans, regulatory constraints, or legal challenges. Incorporating disamenity costs into cost-potential curves allows for numerical energy system models to reflect real-world conditions more closely.
The researchers found that disamenity costs only play a minor role in the expansion of onshore wind energy. Only in countries with high population densities were large increases in the levelised cost of electricity (LCOE) seen when disamenity costs were included in cost-potential curves. Including disamenity costs in modelling can, however, lead to more nuanced decisions in how on-shore wind energy is planned, such as changes in turbine placement. Incorporating disamenity costs may make places with relatively low wind speeds more attractive due to the balancing effect the reduced disamenity costs have on the higher engineering costs.
The authors note that many decisions about turbine placements do not follow a cost-optimisation model. They are the result of regional planning which arguably already accounts (potentially in biased ways) for disamenity costs. By making their data openly available, the authors have provided a tool that can help energy system models analyse trade-offs based on local conditions on a granular level.
Read the full paper in Environmental and Resource Economics here.
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