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.
more »
« less
A Data-Driven Framework for Optimal Placement of Grid-Connected Solar Generation
This work presents a decision making approach for selecting an optimal placement of the grid-connected solar generation using Geographical Information System (GIS) as the decision making tool. A terrain analysis for solar radiation assessment, as well as buildings and vegetation spatial data are analyzed in order to determine the shadow impact that can be anticipated for medium or large-scale PV installation. In addition, different historical weather conditions are considered and integrated into the model to show the impact of this variable on the solar generation output. Some details of the methodology, testbed development and results related to the selection of potential sites for PV installation are presented. To illustrate the process and proposed methodology, an example using large scale synthetic networks is implemented.
more »
« less
- Award ID(s):
- 1636772
- NSF-PAR ID:
- 10110823
- Date Published:
- Journal Name:
- IEEE PES General Meeting, Atlanta, Georgia, August, 2019
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)Solar photovoltaic (PV) energy technology can play a key role in decreasing the amount of carbon emissions associated with electrical energy production, while also providing an economically justifiable alternative to fossil fuel production. Solar energy technology is also extremely flexible in terms of the size and siting of technological development. Large scale PV farms, however, require access to large tracts of land, which can create community-scale conflict over siting solar energy development projects. While previous scholarship offers frameworks for understanding the mechanisms at play in socio-technological system transitions, including the renewable energy transition, those frameworks fail to center community priorities, values, and concerns, and therefore often do not provide an effective means of addressing community conflict over solar siting. This paper provides a conceptual exploration of how a proposed framework can guide decision making for solar development across multiple scales and settings, while also illuminating the potential barriers and bottlenecks that may limit the potential of solar energy development to occur in scales and forms that receive community acceptance and at the pace necessary to address the greenhouse gas emissions currently contributing to the rapidly changing global climate.more » « less
-
To address the critical issues in solar energy, the current research has focused on developing advanced solar harvesting materials that are low cost, lightweight, and environmentally friendly. Among many organic photovoltaics (PVs), the porphyrin compounds exhibit unique structural features that are responsible for strong ultraviolet (UV) and near infrared absorptions and high average visible transmittance, making them ideal candidates for solar-based energy applications. The porphyrin compounds have also been found to exhibit strong photothermal (PT) effects and recently applied for optical thermal insulation of building skins. These structural and optical properties of the porphyrin compounds enable them to function as a PT or a PV device upon sufficient solar harvesting. It is possible to develop a transparent porphyrin thin film with PT- and PV-dual-modality for converting sunlight to either electricity or thermal energy, which can be altered depending on energy consumption needs. A building skin can be engineered into an active device with the PT- and PV-dual modality for large-scale energy harvesting, saving, and generation. This review provides the current experimental results on the PT and PV properties of the porphyrin compounds such as chlorophyll and chlorophyllin. Their PT and PV mechanisms are discussed in correlations to their electronic structures. Also discussed are the synthesis routes, thin film deposition, and potential energy applications of the porphyrin compounds.more » « less
-
Installation of line surge arresters on transmission towers can significantly improve the line lightning performance. However, it is not always economically beneficial to install the line surge arresters on every tower in the network. This paper proposes the method for optimal placement of line surge arresters that minimizes the overall risk of lightning related outages and disturbances, while staying within the required budgetary limits. A variety of data sources was used: utility asset management, geographical information system, lightning detection network, historical weather and weather forecasts, vegetation and soil properties. The proposed solution is focused on predicting the risk of transmission line insulators experiencing an insulation breakdown due to the accumulated deterioration over time and an instant impact of a given lightning strike. The linear regression prediction-based algorithm observes the impact of various historical events on each individual component. In addition, the spatial distribution of various impacts is used to enhance the predictive performance of the algorithm. The developed method is fully automated, making it a unique large scale automated decision-making risk model for real-time management of the transmission line lightning protection performance. Based on the observation of risk tracking and prediction, the zones with highest probability of lightning caused outages are identified. Then the optimization algorithm is applied to determine the best placement strategy for the limited number of line surge arresters that would provide the highest reduction in the overall risk for the network. Economic factors are taken into account in order to develop installation schedule that would enable economically efficient management of line lightning protection performance for utilitiesmore » « less
-
more » « less
Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique.
This article is categorized under:
Photovoltaics > Economics and Policy
Fossil Fuels > Climate and Environment
Energy Systems Economics > Economics and Policy
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
