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At least 73 records · Page 4

Optimizing the Orientation of Solar Photovoltaic Systems Considering the Effects of Irradiation and Cell Temperature Models with Dust Accumulation

To cope with the growing installation capacities of solar photovoltaic (PV) systems in desert areas, it is necessary to revisit the energy production models and the optimal angles of PV panels given the significant impacts of ambient temperature, wind speed, dust accumulation, and cleaning frequency. In this study, these four factors are examined for four PV technologies (polycrystalline, microcrystalline, monocrystalline, and thin-film) at three cities in Jordan, Egypt, and Tunisia using precise ground-level meteo-solar measurements. Different models are compared to estimate the diffuse irradiance, as well as account for the effects of operating temperature, wind speed, and dust accumulation on energy production and optimal tilt and azimuth angles of the panels. The results reveal 1.5 % higher energy production estimates using the isotropic model, compared to the anisotropic model in the summer months. Considering the cooling effect of wind speed decreases the operating cell temperature drops by up to 7.05 % for thin film panels. The annually produced energy decreases by 24 % when the panels are cleaned bi-monthly. When the dust accumulation rate doubles, the energy production decreases by ~10 % for all studied cases. Also, the variations in optimal tilt and azimuth angles with dust accumulation rate are within ~3.0 degrees .

14 SOLAR ENERGY↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2022 Edition

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2021, and is based on data from roughly 2.5 million systems. New to the report this year is an expanded coverage of paired PV-plus-storage systems, including details on system design and pricing trends. The report describes trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state, including preliminary data for first half of 2022 -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis

14 SOLAR ENERGY↗

Updated sustainability status of cadmium telluride thin‐film photovoltaic systems and projections

This paper provides a comprehensive assessment of the up-to-date life-cycle sustainability status of cadmium-telluride based photovoltaic (PV) systems. Current production modules (Series 6 and Series 7) are analyzed in terms of their energy performance and environmental footprint and compared with the older series 4 module production and current single-crystalline Silicon (sc-Si) module production. For fixed-tilt systems with Series 6 modules operating under average US irradiation of 1800 kWh/m 2 /year, the global warming potential (GWP) is reduced from 16 g CO 2eq /kWh in Series 4 systems to 10 CO 2 eq /kWh in Series 6 systems. For operation in US-SW irradiation of 2300 kWh/m 2 /year, the GWP is reduced from 11 to 8 CO 2eq /kWh and for 1-axis tracking systems operating in Phoenix, Arizona, with point-of array irradiation of 3051 kWh/m 2 /year the GWP is reduced to 6.5 CO 2eq /kWh. Similar reductions have happened in all environmental indicators. Energy payback times (EPBT) of currently installed systems range from 0.6 years for fixed–tilt ground–mounted installations at average US irradiation at latitude tilt installations to 0.3 years for one-axis trackers at high US-SW irradiation, considering average fossil-fuel dominated electricity grids with fuel to electricity conversion efficiency of 0.3. The resulting energy return on energy investment (EROI) also depends on the conversion efficiency of the electricity grid and on the operation life expectance. For a 30-year operational life and grid conversion efficiency of 0.3, EROI ranges from 50 (at US average irradiation) to 70 for US-SW irradiation. The EROI declines with increased grid conversion efficiency; for CdTe PV operating in south California with grid conversion efficiency of 49%, the EROI is about 50 and is projected to fall to 30 when the state's 2030 target of 80% renewable energy penetration materializes. Material alternatives that show a potential of further reductions in degradation rates and materials for enhanced encapsulation that would enable longer operation lives have also been investigated. A degradation rate of 0.3%/year, which has been verified by accelerated testing, is assumed in 30-year scenarios; this is projected to be reduced to 0.2%/year in the near-term and potentially to 0.1%/year in the longer term. With such low degradation rates and enhanced edge-sealing, modules can last 40- to 50-years. Consequently, all impact indicators will be proportionally reduced while EROI will increase. This detailed LCA was conducted according to ISO standards and IEA PVPS Task 12 guidelines. Furthermore, the study revealed that the choices of system models, methods and temporal system boundaries can significantly impact the results and points out to the need to include assumptions regarding these choices in the “transparency in reporting” requirements listed in the IEA PVPS Task 12 Guidelines.

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Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (2021 Edition) [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2020, and is based on data from roughly 2.2 million systems, covering 79% of all distributed PV systems installed nationally through 2020. The report describes trends related to project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership. Median installed-price trends, including both long-term and more recent temporal trends at the national and state levels, with comparisons to other recent PV cost and pricing benchmarks as well as to prices reported for other countries. Variability in pricing across individual projects based on system size, state, installer, module efficiency, inverter technology, and non-residential customer type. The report also includes an econometric analysis to estimate the effects of individual drivers on installed prices for host-owned residential systems installed in 2020.

14 SOLAR ENERGY↗

Generation of Data-Driven Expected Energy Models for Photovoltaic Systems

Although unique expected energy models can be generated for a given photovoltaic (PV) site, a standardized model is also needed to facilitate performance comparisons across fleets. Current standardized expected energy models for PV work well with sparse data, but they have demonstrated significant over-estimations, which impacts accurate diagnoses of field operations and maintenance issues. This research addresses this issue by using machine learning to develop a data-driven expected energy model that can more accurately generate inferences for energy production of PV systems. Irradiance and system capacity information was used from 172 sites across the United States to train a series of models using Lasso linear regression. The trained models generally perform better than the commonly used expected energy model from international standard (IEC 61724-1), with the two highest performing models ranging in model complexity from a third-order polynomial with 10 parameters (Radj2 = 0.994) to a simpler, second-order polynomial with 4 parameters (Radj2=0.993), the latter of which is subject to further evaluation. Subsequently, the trained models provide a more robust basis for identifying potential energy anomalies for operations and maintenance activities as well as informing planning-related financial assessments. We conclude with directions for future research, such as using splines to improve model continuity and better capture systems with low (≤1000 kW DC) capacity.

14 SOLAR ENERGY↗

Nature of innovations affecting photovoltaic system costs

Innovations improve technology costs through various kinds of engineering advancements, including changes to materials choices and device or process designs. Understanding how these innovations relate to cost change can reveal aspects of the process of technology evolution, yet developing such understanding is often not possible with a strictly quantitative approach due to data limitations. In this paper we develop a hybrid quantitative-qualitative framework for relating specific innovations to cost change by using the variables in a quantitative technology cost change model as an organizing principle. We demonstrate this framework by applying it to the cost decline in photovoltaic (PV) systems over the last five decades. This framework generates new understanding of a set of innovations that contributed to PV modules’ sustained cost decline and the more modest trends observed in balance-of-system (BOS) costs. The results show the great diversity of innovations that affected PV costs, drawing on wide-ranging fields of expertise within scientific research and practice. We find that there are differences in the characteristics of innovations that reduced the cost of PV modules compared to innovations influencing BOS costs. Numerous module innovations reduced costs by advancing manufacturing tools and processes that improved material quality. Many BOS innovations reduced costs through a combination of component design changes, integration, automation, digitalization, and standardization. Overall, most innovations in our sample affected PV hardware. However, some also target ‘soft technologies’ such as task durations through innovations like fast-track permitting, which require improved collaboration and process streamlining. This framework also provides insight into the nature of knowledge spillovers between technologies. Both module and BOS hardware innovations show the benefits of PV’s position within an ‘ecosystem’ of continuously advancing technologies in many industries, in particular semiconductors and electronics, and also point to the importance of public institutions for accelerating testing, permitting, and training.

14 SOLAR ENERGY↗

Light- and Elevated-Temperature-Induced Degradation-Affected Silicon Cells From a Utility-Scale Photovoltaic System Characterized by Deep-Level Transient Spectroscopy

Photovoltaic modules from a utility-scale field experienced power loss by light- and elevated-temperature-induced degradation (LeTID). Samples from the affected monocrystalline silicon cells are cored and extracted from the module packaging and then laser-scribed to form 2-mm diameter isolated areas. Using deep-level transient spectroscopy, a majority-carrier, hole-trap defect with an activation energy of 0.42 eV is detected on degraded and regenerated samples. The LeTID-degraded sample, however, has a larger signal corresponding to a trap density of 1.1 x 10 13 cm -3 , which is about five times larger than the 2.1 x 10 12 cm -3 trap density of the regenerated sample. An increase in filling pulse time from 50 u s to 20 ms shows a slight decrease in activation energy from 0.42 to 0.36 eV suggesting that the defect level may consist of a band of energy states where shallower states continue to fill with long filling times. The capture rate of the defect is directly measured using an increasing series of filling pulsewidths in 15 to 125 ns range. This leads to a measured capture cross section of 5.1 x 10 -17 cm 2 , and using an approximate defect density of 10 13 cm -3 , the majority-carrier-hole lifetime related to this defect is approximately 100 u s when in the LeTID-degraded state.

charge carrier lifetime↗

bifacial_radiance: a python package for modeling bifacial solar photovoltaic systems

bifacial_radiance is a national-laboratory-developed, community-supported, open-source toolkit that provides a set of functions and classes for simulating the performance of bifacial photovoltaic (PV) systems. (Bifacial PV modules collect light on the front as well as the rear side.) bifacial_radiance automates calculations of PV system layout and performance to use along with the popular ray-tracing software tool RADIANCE (Ward, 1994). Specific algorithms include design and layout of PV modules, reflective ground surfaces, shading obstructions, and irradiance calculations throughout the system, among others. bifacial_radiance is an important component of a growing ecosystem of open-source tools for solar energy (William F Holmgren et al., 2018).

97 MATHEMATICS AND COMPUTING↗

An Updated Life Cycle Assessment of Utility-Scale Solar Photovoltaic Systems Installed in the United States

Given the high deployment targets for solar photovoltaics (PV) needed to meet U.S. decarbonization goals, and the limited carbon budget remaining to limit global temperature rise, accurate accounting of the energy-use and greenhouse-gas emissions over the life-cycle of PV systems is needed. In the United States, most PV systems are large utility-scale systems which use single-axis trackers and central inverters, which are not commonly examined in existing life-cycle assessment (LCA) literature. In this study, we present a cradle-to-grave LCA of a typical silicon U.S. utility PV (UPV) installation which is consistent with the utility system features documented in the annual NREL PV system cost benchmark reports. We analyze and present results for four main metrics: cumulative energy demand (CED), greenhouse gas (GHG) emissions, energy payback time (EPBT), and carbon payback time (CPBT). We consider six primary manufacturing options: three based on an imported PV module supply chain (comparing low-carbon imports, high-carbon imports, and average imports), and three based on a potential domestic PV module supply chain (comparing low-carbon U.S. regions, high-carbon U.S. regions, and average U.S. regions). These manufacturing options were then paired with installation locations to create six main cases: low-carbon options were installed in Phoenix (Arizona), high-carbon options were installed in Seattle (Washington), and average options were installed in Fredonia (Kansas). These locations were selected to represent a range of irradiance and grid mixes in the United States, in order to illustrate the likely range of EPBTs and CPBTs possible across the United States. For all six cases, a sensitivity analysis for end-of-life (EOL) handling was explored to capture current and future management options: landfilling, partial recycling, and high-quality recycling. For the purposes of this report, the benchmark system was defined to use an average imported supply chain with partial recycling, installed in Fredonia (Kansas). CED results show ratios at or below 0.1 MJ oil-eq /MJgenerated which demonstrates efficient use of primary energy resources (below a 1:1 ratio), and represents a slight improvement over previous results in literature. GHG emissions per kWh range from 10-36 g CO 2 e, which are consistent with or lower than previous results published by NREL and IEA-PVPS. We use a graphical approach for calculating EPBT and CPBT in this report, which improves upon methods typically used in literature by accounting for non-linearity and avoiding data quality issues associated with long-term projections. EPBT was determined to vary from 0.5 to 1.2 years, with a benchmark EPBT of 0.6 years; CPBT was shown to vary from 0.8 to 20 years, with benchmark CPBT of 2.1 years, which is lower than other estimates from recent literature (typically >2 years).

14 SOLAR ENERGY↗

Preparing Solar Photovoltaic Systems Against Storms. Pre-Storm Solar PV Checklist: Distributed Ground-Mounted Systems

Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most.

disaster preparedness↗

Advanced Signal Decomposition Analysis and Anomaly Detection in Photovoltaic Systems

With the rapid expansion of large-scale photovoltaic (PV) plants, it is paramount for solar stakeholders to understand the reliability and efficiency of their plants to inform maintenance decisions, increase production, and understand the design factors that impact performance. Diagnosing underperformance in PV plants is challenging due to the relatively few monitoring points with respect to the large geographic footprint of the plant. This work introduces a cutting-edge method that transforms the analysis and management of key factors influencing PV plant performance, including performance loss rate (PLR), recoverable soiling, and major system changes. Identifying these factors is critical for deriving actionable insights. Leveraging advanced analytical techniques such as wavelet transformation, robust regression, and extreme point analysis, this approach provides a nuanced understanding of these factors. This method has been tested across two synthetic datasets and one real dataset, consistently surpassing existing benchmarks by achieving a lower median mean absolute error and reduced error variability across all comparable components.

14 SOLAR ENERGY↗

Preparing Solar Photovoltaic Systems Against Storms

Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most.

hurricane↗

Preparing Solar Photovoltaic Systems Against Storms. Pre-Storm Solar PV Checklist: Distributed Roof-Mounted Systems

Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most. This resource was translated from English to Spanish for greater acessibility.

disaster preparedness↗

Preparing Solar Photovoltaic Systems Against Storms. Pre-Storm Solar PV Checklist: Utility-Scale Ground-Mounted Systems

Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most. This resource was translated from English to Spanish for greater accessibility.

POWER TRANSMISSION AND DISTRIBUTION,SOLAR ENERGY↗

Recommendations for Establishing Local Rural Electrification Programs Using Photovoltaic Systems [Recomendaciones Para la Implantacidn de Programas Locales de Electrificacidn Rural con Sistemas Fotovoltaicos]

Photovoltaic (PV) technology is becoming one the best options for supplying electricity to rural communities far from electrical networks and which have a small and disperse demand for electricity. As the cost of the technology goes down and its development advances, opportunities for applying it continue to grow. As a result, in the near future we will probably see an increase in massive application programs of this technology in rural Mexico. This document presents some of the most relevant problems needing immediate solution to increase the possibility of success in establishing photovoltaic programs for rural electrification in Mexico. These problems are influenced by economic, technological, engineering, infrastructural, social and political issues. The paper presents the requirements for an industrial center based on PV technology, the accessibility of replacement parts and maintenance service, development of financial solutions, training of the users and introducing norms and technical regulations. The document summarizes the issue of rural electrification in Mexico, emphasizing the low population density in these areas. A brief description is given of photovoltaics showing different configurations that can be utilized for supplying electricity to the rural areas. The issues involved and recommendations for introducing PV systems to the rural area are described.

14 SOLAR ENERGY↗

A data-driven network optimisation approach to coordinated control of distributed photovoltaic systems and smart buildings in distribution systems

The increasing integration of distributed energy resources, including demand-side resources and distributed photovoltaics (PVs), into distribution systems has resulted in more complicated power system operation. A data-driven network optimisation approach is proposed to coordinate the control of distributed PVs and smart buildings in distribution networks considering the uncertainties of solar power, outdoor temperature and heat gain associated with building thermal dynamics. These uncertain parameters have a significant impact on the operation and control of distributed PVs and smart buildings, bringing challenges to the distribution system operation. In the proposed data-driven distributionally robust optimisation (DRO) approach, the Wasserstein ball is used to construct an ambiguity set for the uncertain parameters, which does not require the probability distributions to be known. Furthermore, a conditional value-at-risk is incorporated into the Wasserstein-based DRO model and converted into a computationally tractable mixed-integer convex optimisation problem. Benchmarked with robust optimisation and chance-constrained programming, the proposed data-driven model can give a less conservative robust solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks: Q1 2021

Based on our bottom-up modeling, the Q1 2021 PV and energy storage cost benchmarks are: $\$2.65$ per watt DC (WDC) (or $\$3.05$/WAC) for residential PV systems, 1.56/WDC (or $\$1.79$/WAC) for commercial rooftop PV systems, $\$1.64$/WDC (or $\$1.88$/WAC) for commercial ground-mount PV systems, $\$0.83$/WDC (or $\$1.13$/WAC) for fixed-tilt utility-scale PV systems, $\$0.89$/WDC (or $\$1.20$/WAC) for one-axis-tracking utility-scale PV systems, $\$30,326$-$\$33,618$ for a 7.15-kWDC residential PV system with 5 kW/12.5 kWh nameplate of storage, $\$2.04$ - $\$2.10$ million for a 1-MWDC commercial ground-mount PV system colocated with 600 kW/2.4 MWhusable of storage, $\$166$ - $\$167$ million for a 100-MWDC one-axis tracker PV system colocated with 60 MW/240 MWhusable of storage. Between 2020 and 2021, there were 3.3% ($\$0.0$9/W), 10.7% ($\$0.19$/W), and 12.3% ($\$0.13$/W) reductions (in 2020 USD) in the residential, commercial rooftop, and utility-scale (one-axis) PV system cost benchmarks respectively. Balance of system (BOS) costs have either increased or remained flat across sectors, year-on-year, unlike in previous benchmark reports, which generally have reported declining BOS costs. The increase in BOS cost has been offset by a 17% reduction in module cost. Overall, modeled PV installed costs across the three sectors have declined compared to our Q1 2020 system costs.

14 SOLAR ENERGY↗