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New & Renewable Energy
Abbreviation: New. Renew. Energy
ISSN: 1738-3935 (Print) 2713-9999 (Online)
Online publication date 13 Nov 2024
Received 04 Sep 2024 Revised 02 Oct 2024 Accepted 14 Oct 2024
DOI: https://doi.org/10.7849/ksnre.2024.0023
시장잠재량 모형과 확산 모형을 결합한 태양광 보급전망 방법론
조상민1), * ; 장연재2) ; 윤창열3)
A Methodology for Forecasting Photovoltaics Deployment by Combining Market Potential and Diffusion Models
Sangmin Cho1), * ; Yenjae Chang2) ; ChangYeol Yun3)
1)Senior Research Fellow, Department of Renewable Energy Policy Research, Korea Energy Economics Institute
2)Research Fellow, Department of Renewable Energy Policy Research, Korea Energy Economics Institute
3)Principal Researcher, Renewable Energy Big Data Laboratory, Korea Institute of Energy Research
Correspondence to : *smin0621@keei.re.kr Tel: +82-52-714-2110 Fax: +82-52-714-2026
© 2024 by the New & Renewable Energy This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

In this study, we propose a methodology that combines the diffusion and market potential models in order to forecast the diffusion path of PV deployment. Potential volume (m), a key feature of this approach and one of the main parameters of the diffusion model, , is not estimated within the model itself. Instead, the market potential is estimated using the market potential model and then substituted into the diffusion model. A significant difference was found when comparing the two-parameter results projected by this methodology with the three-parameter results estimated within the model. However, the projected results of the two-parameter model, particularly under the current setback regulation scenario, were similar to the solar deployment targets set by the government. The advantage of the model proposed in this study is that it can be used to estimate the impact of changes in influencing factors, such as regulatory and support policies, on the diffusion path of PV deployment. Scenario analysis indicated that changes in municipalities’ setback distance regulations, which have recently been identified as having the greatest impact on PV deployment, can affect market potential, and that changes in market potential can, in turn, influence the diffusion path of PV deployment.