Hybrid agent-based modeling of rooftop solar photovoltaic adoption by integrating the geographic information system and data mining technique
Authored by Minhyun Lee, Taehoon Hong
Date Published: 2019
DOI: 10.1016/j.enconman.2018.12.096
Sponsors:
Korean National Research Foundation (NRF)
Platforms:
Repast
Model Documentation:
Other Narrative
Flow charts
Model Code URLs:
Model code not found
Abstract
Modeling energy technology adoption involves heterogeneity and dynamic
interactions of individuals based on the physical, technical, and
economic environments in the decision making process. In this context,
this study aims to develop a hybrid model integrating an agent-based
modeling (ABM) with the geographic information system and logistic
regression for simulating rooftop solar photovoltaic (PV) adoption in
the study area. Towards this end, this study regarded ``building{''} as
an ``agent{''} to simulate the market diffusion of rooftop solar PV
systems in the Nonhyeon neighborhood, located in the Gangnam district,
Seoul, South Korea, based on various factors affecting the adoption
(i.e., physical, demographic \& socioeconomic, technical, economic, and
social factors). This study considered three behavioral rules of rooftop
solar PV adoption, which were determined using panel logistic regression
according to different motivators for rooftop solar PV adoption. Based
on these different behavioral rules, three hybrid ABM models were
developed to simulate the market diffusion of rooftop solar PV systems.
It was shown that models including the various potential motivators for
the adoption proposed in this study better represented the reality of
aggregate decision-making processes, while the model including only the
motivators proposed in the previous ABM studies failed to perform well,
rarely adopting the rooftop solar PV system during the runs. The ABM
proposed in this study allows the estimation of the aggregate amount and
patterns of future market diffusion for rooftop solar PV systems, which
can be widely used by governments and electric utilities for evaluating
policies and business models.
Tags
Simulation
Agent-based modeling
diffusion
patterns
Peer effects
Error
Determinants
Pv
Barriers
Energy technology adoption
Geographic information system
Renewable energy adoption
Rooftop solar photovoltaic system
Logistic
regression