H.S. Galster , A.J. Van der Wal , A.E. Batenburg , V. Koning , A.P.C. Faaij
{"title":"A comprehensive review of integrating behavioral drivers of technology adoption and energy service use in energy system models","authors":"H.S. Galster , A.J. Van der Wal , A.E. Batenburg , V. Koning , A.P.C. Faaij","doi":"10.1016/j.rser.2025.115520","DOIUrl":null,"url":null,"abstract":"<div><div>Energy System Models (ESMs) that aim at describing and exploring pathways towards a decarbonized future energy system currently account insufficiently for the behavior of households and individuals. To address this shortcoming, this study evaluates models' existing approaches to incorporate behavior considering social science insights to advance the models' behavioral realism. A structured literature review and expert interviews were employed, selecting sixteen ESMs and two sectoral energy models for further investigation. Main data sources for the analysis were model descriptions and interview notes. The results show a predominant focus of models on financial aspects of adoption decisions and energy service use, while there is less consideration of non-economic behavioral drivers. Models also often rely on a weak empirical foundation for behavioral drivers. Based on these findings, advancing the representation of behavior in ESMs is needed to strengthen the realism of models’ explorative and descriptive insights. This analysis outlines concrete strategies to guide such an endeavor. It is recommended to consider relevant drivers of energy-related behavior, to employ a data-driven approach which relates behavioral outcomes to these drivers, and to define actor heterogeneity according to meaningful behavioral differences. In comparison to optimization approaches, the flexibility of simulation modelling provides a wider range of options for incorporating and analyzing behavioral aspects in ESMs. Future interdisciplinary research should further align social science insights with energy system modelling, building on the suggested strategies, to improve the accuracy of model predictions and to facilitate the consideration of behavioral aspects in the energy transition.</div></div>","PeriodicalId":418,"journal":{"name":"Renewable and Sustainable Energy Reviews","volume":"214 ","pages":"Article 115520"},"PeriodicalIF":16.3000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Renewable and Sustainable Energy Reviews","FirstCategoryId":"1","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1364032125001935","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Energy System Models (ESMs) that aim at describing and exploring pathways towards a decarbonized future energy system currently account insufficiently for the behavior of households and individuals. To address this shortcoming, this study evaluates models' existing approaches to incorporate behavior considering social science insights to advance the models' behavioral realism. A structured literature review and expert interviews were employed, selecting sixteen ESMs and two sectoral energy models for further investigation. Main data sources for the analysis were model descriptions and interview notes. The results show a predominant focus of models on financial aspects of adoption decisions and energy service use, while there is less consideration of non-economic behavioral drivers. Models also often rely on a weak empirical foundation for behavioral drivers. Based on these findings, advancing the representation of behavior in ESMs is needed to strengthen the realism of models’ explorative and descriptive insights. This analysis outlines concrete strategies to guide such an endeavor. It is recommended to consider relevant drivers of energy-related behavior, to employ a data-driven approach which relates behavioral outcomes to these drivers, and to define actor heterogeneity according to meaningful behavioral differences. In comparison to optimization approaches, the flexibility of simulation modelling provides a wider range of options for incorporating and analyzing behavioral aspects in ESMs. Future interdisciplinary research should further align social science insights with energy system modelling, building on the suggested strategies, to improve the accuracy of model predictions and to facilitate the consideration of behavioral aspects in the energy transition.
期刊介绍:
The mission of Renewable and Sustainable Energy Reviews is to disseminate the most compelling and pertinent critical insights in renewable and sustainable energy, fostering collaboration among the research community, private sector, and policy and decision makers. The journal aims to exchange challenges, solutions, innovative concepts, and technologies, contributing to sustainable development, the transition to a low-carbon future, and the attainment of emissions targets outlined by the United Nations Framework Convention on Climate Change.
Renewable and Sustainable Energy Reviews publishes a diverse range of content, including review papers, original research, case studies, and analyses of new technologies, all featuring a substantial review component such as critique, comparison, or analysis. Introducing a distinctive paper type, Expert Insights, the journal presents commissioned mini-reviews authored by field leaders, addressing topics of significant interest. Case studies undergo consideration only if they showcase the work's applicability to other regions or contribute valuable insights to the broader field of renewable and sustainable energy. Notably, a bibliographic or literature review lacking critical analysis is deemed unsuitable for publication.