Modeling the technological adoption of solar energy neighborhoods: The case of Chile

被引:3
作者
Ardila, Laura [1 ]
Jaime Franco, Carlos [1 ]
Cadavid, Lorena [1 ,2 ]
Pablo Torres, Juan [3 ]
机构
[1] Univ Nacl Colombia, Carrera 80 65-223, Medellin, Colombia
[2] Inst Tecnol Metropolitano, Calle 73 76A 354, Medellin, Colombia
[3] Univ Chile, Fac Econ & Negocios, Dept Adm, Diagonal Paraguay 257, Santiago, Region Metropol, Chile
关键词
Innovation adoption; Social networks; Solar panels; Energy policy; Agent-based simulation; MULTICRITERIA DECISION-ANALYSIS; SOCIAL NETWORKS; DIFFUSION; TRENDS; HOUSEHOLDS; SYSTEMS;
D O I
10.1016/j.jclepro.2022.132620
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper presents an agent-based model of the technological adoption of solar panels, including potential adopters' characteristics and their interactions. This study analyzes the theoretical impact of seven social influence strategies on the adoption of solar panels by householders within a solar neighborhood in the Providencia district, Chile. In this case study, established adopters account for 0.9% of the population, opinion leaders for 1.3%, and individuals in the network for 97.8%. Considering the population's high-level ambition and tolerance of uncertainty, we found that householders are mainly characterized as optimizers (89.7%), followed by inquirers (7.6%), repeaters (2.3%), and imitators (0.3%) agents. Our agent-based simulation model evaluated the social influence strategies based on economic, environmental, and social benefits. The results show that social influence strategies lead to a 19.27% increase, on average, in the total number of adopters concerning the base case. Then, we performed a multi-objective analysis to select the best adoption strategy. These results show that selecting the most connected agents in the network is a robust strategy the decision-makers have environmental or financial concerns. However, if the decision-makers' primary interest is maximizing the diffusion scope of solar panel neighborhoods, random agent selection is the most advisable strategy, given its ease of implementation.
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页数:10
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共 83 条
  • [31] El Comercio, 2014, LEY 20527 REG PAG TA
  • [32] ENEL EBP TIKUNA., 2018, INF FACT PROYECT MIC, P72
  • [33] EVALUATING STRUCTURAL EQUATION MODELS WITH UNOBSERVABLE VARIABLES AND MEASUREMENT ERROR
    FORNELL, C
    LARCKER, DF
    [J]. JOURNAL OF MARKETING RESEARCH, 1981, 18 (01) : 39 - 50
  • [34] Goicoechea A., 1982, Multiobjective Decision Analysis with Engineering and Business Applications
  • [35] Peer effects in the adoption of solar energy technologies in the United States: An urban case study
    Graziano, Marcello
    Fiaschetti, Maurizio
    Atkinson-Palombo, Carol
    [J]. ENERGY RESEARCH & SOCIAL SCIENCE, 2019, 48 : 75 - 84
  • [36] Hachem-Vermette C., 2020, SOLAR BUILDINGS NEIG
  • [37] Adoption of energy efficient technologies by households - Barriers, policies and agent-based modelling studies
    Hesselink, Laurens X. W.
    Chappin, Emile J. L.
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2019, 99 : 29 - 41
  • [38] When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles
    Hidayatno, Akhmad
    Jafino, Bramka Arga
    Setiawan, Andri D.
    Purwanto, Widodo Wahyu
    [J]. ENERGY POLICY, 2020, 138
  • [39] Information Administration Energy., 2019, INT EN OUTL 2019 PRO, P85
  • [40] International Energy Agency (IEA), 2019, TECH REP, DOI DOI 10.1787/WEO-2018-EN