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The state of California is the foremost leader in solar photovoltaics (PV) installations in the United States. With 1,390,240 installations and 24.76% of the state's energy coming from solar, the demand for PV modules is steadily increasing. Most PV modules have an expected lifetime of 25-30 years. However, due to repowering or early module failure, module lifetime can often be shorter than anticipated. Current studies calculate the environmental impact of PV systems based on ideal installation conditions and a full 25-year module lifetime. This study considers the impact on the life cycle of PV systems from early PV module retirement and actual system installation in California. Using the life cycle cumulative energy demand, electricity data from the Energy Information Administration (EIA), and greenhouse gases, carbon payback time (CPBT) was evaluated. Data from various PV module rooftop residential installations in 2019 were collected from the California NEM database. Information on the system design (tilt, azimuth, module model) and module specification sheets were used to calculate the cumulative electricity generated in kilowatt-hours (kWh) over the system' lifetime. The calculated average CPBT was 2.8 years, shorter than most of the system lifetimes, and the mean number of zero carbon years experienced by earlier retired systems was about 5 years. Although the rapid movement towards solar energy is promising and essential as reliance on greener energy increases, attention must be paid to the diverse lifespans of PV modules, system design, and performance to substantiate or reject the assumption that PV always have a positive impact on the environment.
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Social Network Influence on Residential Solar Photovoltaic Adoption in an Agent-Based Electricity System Model
Abstract As the United States phases out traditional fossil fuels in favor of renewable energy sources, it is important to capitalize on all available avenues to increase renewable penetration. In the last decade, the costs associated with residential solar photovoltaic (PV) installations have decreased significantly, providing more homeowners with the opportunity to generate their own clean electricity. Research has found that the decision to invest in a residential solar PV system is guided by economic, social, and personal factors. Accounting for such complexities, the joint power of agent-based modeling and social network analysis is leveraged in this study to evaluate the effect of social influence on solar PV adoption. Featuring residential consumer agents with data-driven attributes, a logistic regression function to predict solar adoption, and random and small-world social network implementations, this work simulates residential solar PV adoption in New Jersey. Results indicate that including social influence in an agent-based electricity system model leads to increased installed residential solar capacity, but not necessarily higher adoption rates. These findings suggest that, with an understanding of the intricacies of consumer social networks, there are potential opportunities to bolster residential solar installations through low-cost social campaigns that motivate individuals to adopt home solar through their social ties.
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- Award ID(s):
- 1953774
- PAR ID:
- 10580417
- Publisher / Repository:
- American Society of Mechanical Engineers
- Date Published:
- ISBN:
- 978-0-7918-8837-7
- Format(s):
- Medium: X
- Location:
- Washington, DC, USA
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Conference Paper:
- https://doi.org/10.1115/DETC2024-140793
