Conference Agenda

The large-scale deployment of renewable energy sources (RES) produces local environmental and economic benefits as well as burdens. These are usually distributed unevenly in space. A spatially more equitable deployment of renewable energy sources (RES) is frequently discussed to address concerns of spatial distributive injustices and declining local acceptance. We explore and compare systematically the feasibility and impacts of alternative approaches to spatial equity in RES deployment. Our analysis uses an energy location model with highly resolved spatial data for around 46,000 potential sites for wind turbines and 7,060 km2 of potential sites for ground-mounted PV in Germany. Our analysis shows that reallocating RES deployment can lead to improvements in spatial equity if compared to the current spatial allocation and future allocation scenarios driven solely by cost-minimization. At the same time, we also find clear limitations to reaching perfect spatial equity through siting due to restrictions in land availability. Moreover, we identify relevant intra-equity trade-offs: different approaches to spatial equity may lead to vary different spatial allocations of RES deployment. Finally, our results suggest moderate equity-efficiency trade-offs, particularly for onshore wind power. Generation costs my increase by up to 14% if the spatial allocation of RES deployment is optimized with respect to spatial equity. We conclude that comprehensive strategy to address spatial distributive justice and local acceptance cannot solely rely on regulating the spatial allocation of RES deployment. It has to be complemented by other means, like a spatial redistribution of financial benefits as well just procedures for decision-making.

The success of energy transition in addressing climate change depends on several factors, including the affordability of new technologies and the influence of peers within communities. However, concerns about affordability raise questions about how economic inequalities shape peer effects and whether they create barriers to equitable adoption. To this end, we explore how inequalities influence peer effects in the uptake of renewable heating sources. We leverage over 260,000 observations from unique and unpublished microdata from the Polish Clean Air Priority Programme – one of the largest retrofit schemes in Europe. Our results show that peer effects accelerate technology uptake, with each additional installation increasing the likelihood of subsequent adoption by 0.014 pp. Peer influence is affected by economic inequality. In more economically homogeneous regions, affluent individuals considerably impact their peers. In areas with higher economic disparities, this influence diminishes. Our findings highlight the role of heating technology type and adopter wealth in shaping peer effect magnitude. Less wealthy adopters of biomass stoves emerge as a significant driver of peer influence, especially in regions with lower income inequality. We advise direct transfers to address technology adoption inequalities, leveraging social capital in low-inequality regions and adopting individualised strategies in high-inequality areas.

The recent surge in European energy prices led governments to implement compensation schemes, mostly untargeted price subsidies that disproportionately benefited high-consumption and, on average, high-income households. While lump-sum transfers would maintain energy-saving incentives and could be perceived as fairer, public awareness of the efficiency and distribution of compensation schemes remains limited. We experimentally assess how information about compensation distribution and electricity-saving incentives affects public support for price subsidies and lump-sum transfers. While initial support for price subsidies is very high, informing participants about distributional effects significantly reduces this support and increases preference for lump-sum transfers. In contrast, information on electricity-saving incentives has no overall effect, likely because it has a weaker impact on households that benefit the most from a price subsidy. Our findings suggest that correcting misperceptions about subsidy distribution drives these shifts in support. Although providing information shifts support in favor of the lump-sum scheme, the price subsidy remains the preferred option.

This article develops and applies to two case studies a methodology for the parametric evaluation of the landscape external costs of renewable energy installations. The main novelty of the methodology is the estimation of the economic value of landscape services in Italy as a function of the main distinctive attributes of the landscape, allowing its application to a variety of national landscape contexts. The monetary valuation of landscape services was estimated by means of a discrete choice experiment (DCE) based on a survey administered to a representative sample (N = 2352) of the Italian population. The estimates obtained with the DCE made it possible to estimate a set of 50 unit values (euro per hectare) of the Italian population's willingness to pay for landscape services, appropriately differentiated by qualitative classes of three landscape attributes: naturalistic quality, richness of cultural heritage and presence of historic rural areas. A distinctive feature of this study is the connection with the available national landscape cartography allowing to apply the monetary values with the spatial analysis of the visual intrusion of the renewable energy plants with a GIS application. The methodology is applied to two case studies located in Central Italy: an onshore wind farm and a utility-scale photovoltaic plant. Considering the different landscape contexts, the estimated external landscape cost of the photovoltaic plant analyzed was considerably lower than that of the wind farm, both in absolute terms (39,000 euro/year against 232,000) and in relation to the energy annually produced (0.41 euro/MWh against 1.34). In the context of energy planning, the proposed methodology can be used to identify the most suitable areas for the location of wind and solar power plants with an approach consistent with welfare economics (minimisation of social landscape costs).