Spatial Analysis of Financial Participation Schemes to Offset Property Value Losses near Wind Turbines

Wind turbines are essential to the renewable energy transition but can negatively impact local property values. To address these externalities and improve local acceptance, financial participation schemes are frequently discussed and adopted. However, these schemes often fail to account for regional disparities in property value losses, limiting their cost-effectiveness. This study evaluates the cost-effectiveness of three financial participation schemes designed to offset property value losses near wind turbines.

 

We used Causal Forests to quantify turbine-induced property value losses, utilizing data from ImmobilienScout24 (2000–2022) and the Core Energy Market Data Register (CEMDR). Property values were modeled based on proximity to turbines (0–1 km, 1–2 km, and 2–3 km) and socio-demographic factors. The cleaned dataset of 682,576 observations was analyzed to estimate Conditional Average Treatment Effects (CATEs). Generalized Additive Models (GAMs) extrapolated these effects to unobserved areas, providing spatially comprehensive property value loss estimates.

Compensation schemes analyzed included payments per kWh, per kW, and per turbine, distributed either by area or the number of houses within a 3 km radius. Payment ranges spanned €0.0–0.2 per kWh or kW and €0–1,000,000 per turbine.

 

We find that wind turbines reduce property values by 3.6% within 1 km, 2.4% at 1–2 km, and 0.9% at 2–3 km. GAM-based extrapolation revealed regional disparities: while most areas report minimal losses, extreme cases range from -€27.66 million to €4.33 million per 1 km². Total estimated property value losses related to current wind power deployment in Germany amount to €21.9 billion. To evaluate the schemes, we compare the total transfer required to offset 50% of the damages (€10.9 billion) and identify the corresponding tariff levels.

The most cost-effective scheme is the household-based per-turbine payment (€29.09 billion at €55,000 per turbine), followed by household-based per-kW tariffs (€33.54 billion at €3.1/kW) and area-based per-kW schemes (€37.30 billion at €4.2/kW), which better align with localized property losses than energy production-based models. Per-kWh schemes involve the highest transfers and overcompensation, particularly under area-based distributions (€39.81 billion at €1.8/kWh). Household-based per-kWh models (€35.29 billion at €1.3/kWh) slightly reduce overcompensation but remain less efficient. All schemes exhibit substantial targeting errors, overcompensating some communities while undercompensating others.

Our results also evaluate current financial participation schemes in Germany. At the national level, the Renewable Energy Act (EEG) provides €0.002 per kWh, covering only 14.6% of total damages. At the state level, Brandenburg's €10,000 per turbine payment covers 15.1%, and Saxony-Anhalt's €0.06 per kW tariff covers 57.3%. These policies inadequately address regional disparities in turbine-induced property losses.

 

In conclusion, our analysis demonstrates that financial participation can help to offset a substantial part of the property value losses produced by wind power deployment. However, fully compensating losses is financially impractical with existing models due to significant overpayment. Consequently, a combination of refined financial schemes, other localized benefits, e.g., through community ownership, and procedural participation is essential for fostering public acceptance.