Drivers of People’s Preferences for Spatial Proximity to Energy Infrastructure Technologies: A Cross-country Analysis

Harold, Jason; Bertsch, Valentin; Lawrence, Thomas; Hall, Magie

doi:10.5547/01956574.42.4.jhar

“…For wind power, local acceptance of wind projects is a more important factor than overall public opinion because of potential disamenity costs [15,52]. Based on data from previous studies [15,53], we assumed that local acceptance is 35% lower than overall public acceptance for wind power and then used this gure to apply the same approach as for other technologies to represent power technologies rejection. Conversely, widespread positive opinion about renewable generation technologies over the population creates pressure on governments for the adoption of support policies [54].…”

Section: Representation Of Societal Transformation Factors In the Modelmentioning

confidence: 99%

Multi-country evidence on societal factors to include in energy transition modeling

Fisch-Romito,

Jaxa-Rozen,

Wen

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Integrated assessment and energy system models are challenged to account for societal transformation dynamics to produce feasible low-carbon pathways. Yet, empirical evidence is lacking on which factors should be incorporated, how and to what extent this would improve the quality and relevance of modeled pathways. Here, we include six societal factors related to (i) infrastructure dynamics, (ii) actors and decision making and (iii) societal and institutional context into an open-source simulation model of the national power system transition. We apply this model for 31 European countries and, using hindcasting (1990–2019), quantify which societal factors improved the modeled pathways. We find that, if well-chosen and in most cases, incorporating societal factors can improve the hindcasting performance by up to 24% in terms of modelled installed capacity of individual technologies, but there are also situations where hindcasting performance can become worse. The combinations of most relevant societal factors differ among countries and model outputs, but infrastructure lock-in, public acceptance and investment risks contribute more strongly and frequently to model performance improvement. Our study hence paves the road to evidence-based choice of societal factors to be included in energy transition modeling in a systematic and transparent way.

show abstract

“…For wind power, local acceptance of wind projects is a more important factor than overall public opinion because of potential disamenity costs [15,52]. Based on data from previous studies [15,53], we assumed that local acceptance is 35% lower than overall public acceptance for wind power and then used this gure to apply the same approach as for other technologies to represent power technologies rejection. Conversely, widespread positive opinion about renewable generation technologies over the population creates pressure on governments for the adoption of support policies [54].…”

Section: Representation Of Societal Transformation Factors In the Modelmentioning

confidence: 99%

Multi-country evidence on societal factors to include in energy transition modeling

Fisch-Romito,

Jaxa-Rozen,

Wen

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Integrated assessment and energy system models are challenged to account for societal transformation dynamics to produce feasible low-carbon pathways. Yet, empirical evidence is lacking on which factors should be incorporated, how and to what extent this would improve the quality and relevance of modeled pathways. Here, we include six societal factors related to (i) infrastructure dynamics, (ii) actors and decision making and (iii) societal and institutional context into an open-source simulation model of the national power system transition. We apply this model for 31 European countries and, using hindcasting (1990–2019), quantify which societal factors improved the modeled pathways. We find that, if well-chosen and in most cases, incorporating societal factors can improve the hindcasting performance by up to 24% in terms of modelled installed capacity of individual technologies, but there are also situations where hindcasting performance can become worse. The combinations of most relevant societal factors differ among countries and model outputs, but infrastructure lock-in, public acceptance and investment risks contribute more strongly and frequently to model performance improvement. Our study hence paves the road to evidence-based choice of societal factors to be included in energy transition modeling in a systematic and transparent way.

show abstract

“…For wind power, local acceptance of wind projects is a more important factor than overall public opinion because of potential disamenity costs [15,52]. Based on data from previous studies [15,53], we assumed that local acceptance is 35% lower than overall public acceptance for wind power and then used this gure to apply the same approach as for other technologies to represent power technologies rejection. Conversely, widespread positive opinion about renewable generation technologies over the population creates pressure on governments for the adoption of support policies [54].…”

Section: Representation Of Societal Transformation Factors In the Modelmentioning

confidence: 99%

Multi-country evidence on societal factors to include in energy transition modeling

Fisch-Romito,

Jaxa-Rozen,

Wen

et al. 2024

Preprint

0

View full text Add to dashboard Cite

Integrated assessment and energy system models are challenged to account for societal transformation dynamics to produce feasible low-carbon pathways. Yet, empirical evidence is lacking on which factors should be incorporated, how and to what extent this would improve the quality and relevance of modeled pathways. Here, we include six societal factors related to (i) infrastructure dynamics, (ii) actors and decision making and (iii) societal and institutional context into an open-source simulation model of the national power system transition. We apply this model for 31 European countries and, using hindcasting (1990–2019), quantify which societal factors improved the modeled pathways. We find that, if well-chosen and in most cases, incorporating societal factors can improve the hindcasting performance by up to 24% in terms of modelled installed capacity of individual technologies, but there are also situations where hindcasting performance can become worse. The combinations of most relevant societal factors differ among countries and model outputs, but infrastructure lock-in, public acceptance and investment risks contribute more strongly and frequently to model performance improvement. Our study hence paves the road to evidence-based choice of societal factors to be included in energy transition modeling in a systematic and transparent way.

show abstract

Drivers of People’s Preferences for Spatial Proximity to Energy Infrastructure Technologies: A Cross-country Analysis

Cited by 11 publications

References 47 publications

Multi-country evidence on societal factors to include in energy transition modeling

Multi-country evidence on societal factors to include in energy transition modeling

Multi-country evidence on societal factors to include in energy transition modeling

Multi-country evidence on societal factors to include in energy transition modeling

Contact Info

Product

Resources

About