Sustainable energy technology, adoption, rebound, and resilience

Diffusion;PV systems;Time-series analysis;Machine-learning;Rebound effect;Resilience

Hashemi Toroghi, Shahaboddin ; Thomas, Valerie M. Castro-Lacouture, Daniel Building Construction Oliver, Mathew Song, Xinyi Drummond, William ; Thomas, Valerie M.

University:Georgia Institute of Technology

Department:Building Construction

关键词: Diffusion;    PV systems;    Time-series analysis;    Machine-learning;    Rebound effect;    Resilience;   

Others  :  https://smartech.gatech.edu/bitstream/1853/62631/1/HASHEMITOROGHI-DISSERTATION-2019.pdf

美国|英语

来源: SMARTech Repository

【 摘 要 】

While in the United States, centralized generation and distribution network are the basis of the current electric infrastructure, the recent surge in uptake of solar photovoltaic (PV) systems introduces a new avenue to decentralize this system. Furthermore, PV systems can substitute the grid electricity and increase the share of renewable energy sources. While by 2018, five states in the U.S. (California, Hawaii, Nevada Massachusetts, and Vermont) could reach 10% threshold for the share of solar sources in generating electricity, at the country level this share is still less than 3%; whereas in some other countries, such as Germany and Japan, it has already reached more than 6%. This dissertation examines the diffusion of PV systems from three perspectives, addressing three gaps in knowledge: an empirical study of the diffusion of PV systems in Georgia, a method to estimate renewable rebound effect, and a framework to quantify the resilience capacity of an electric infrastructure system with emergency electricity generators, including PV systems. Three studies present the primary contributions of this research. Study 1 examines the diffusion of PV systems in Georgia, identifies characteristics of adopters and patterns of adoption, and forecasts the future adoption of PV systems. Study 2 introduces a new approach to estimate the direct rebound effect, subsequent of a major adoption of PV systems. Study 3 presents a state-of-the-art framework that quantifies the resilience capacity of an electric infrastructure system with emergency electricity generators. The findings of the study 1 provides a benchmark for the future adoption of PV systems and highlights the impact of socio-economic and location-based factors in the diffusion of PV systems in Georgia. These findings can be used to shape a more effective policy, aiming to increase the share of PV systems, or evaluate the effectiveness of a policy. The finding of the study 2 opens a new avenue to compute the rebound effect and can support development of a policy to mitigate the renewable rebound effect in a targeted region. The finding of the study 3 can help system designers to customize the design of a resilient system based on its characteristics. The introduced framework can further be used to investigate improvement of the resilience capacity in an electric infrastructure system by increasing the penetration of PV systems, or other decentralized electricity generators in a region.