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At least 253 records · Page 14

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↗

Measurement of DC Arc-Flash Incident Energy in Large-Scale Photovoltaic Plants: A Basis for Standardization

The deployment of high-power dc equipment is increasing in solar photovoltaic (PV) plants, but very few studies have quantified dc arc-flash risks. Currently, PV plant owners and operators rely on theoretical, simplified models, such as those in NFPA-70E and other publications, for the assessment of risk associated with dc arc-flash. Here, this article presents an overview of arc-flash risks in a PV system based on a series of field experiments based on IEEE-1584 in two large-scale ground-mounted PV plants. The experiments include various high-power dc equipment of a PV plant, such as central inverters, combiner boxes, recombiner boxes, string inverters, and multiple configurations of electrodes in a 20-in calibration cube. The study reveals that none of the available dc arc-flash models are applicable for a PV plant. This work is an important first step toward developing an improved model that more accurately assesses dc arc-flash risk in a PV plant.

14 SOLAR ENERGY↗

The electric vehicles-solar photovoltaics Nexus: Driving cross-sectoral adoption of sustainable technologies

Residential and transportation energy consumption account for more than one-half of the overall energy consumption in the United States. Adoption of electric vehicles (EVs) can play a key role in decarbonizing the transportation sector, while the adoption of renewable energy sources (e.g., solar photovoltaics [PVs]) could bring similar benefits to the residential energy sector and in turn support transport electrification. Although the market shares for both EVs and PVs continue to grow, both of these emerging technologies are deployed rather disjointly, without considering the existence of potential similarities among users who own (or aspire to own) these technologies. This might be due to lack of understanding of the behavioral interdependence in consumer preferences toward these technologies. To fill this gap in knowledge, this study utilizes data from the 2018 WholeTraveler Transportation Behavior Study to develop an integrated model system that explores interactive EV and PV adoption behaviors. A structural equation model is employed that incorporates direct effects as well as error correlations among the adoption behaviors for EVs and PVs. Model results indicate that the adoption behavior for both these technologies is indeed interconnected and significantly influenced by attitudes, values, and personality traits. Findings from this research suggest that incentives (e.g., subsidies) that drive bundled adoption of EV-PV systems could accelerate the adoption of both of these sustainable technologies. In conclusion, this study highlights the need to consider transport and building energy-efficient technology adoption behavior in a single integrated structure.

14 SOLAR ENERGY↗

Information Searching in the Residential Solar PV Market

This paper examines the consumer information search behavior of households in San Diego County with solar photovoltaic (PV) systems. We focus on whether solar PV households financing the technology through third-party ownership (TPO) versus host-ownership (HO), which is equivalent to leasing or buying goods in other markets, have heterogeneous preferences as reflected by information search. Conditional on adoption, we find that TPO households tend to seek more information on home modifications required for solar installation whereas HO households seek more information on the financial returns of solar investments. These preferences may be correlated with the consumption of other goods and services, and thus, if used to inform marketing strategies, our results could help reduce solar PV customer acquisition costs and accelerate technology diffusion. They also have indirect implications for marketing goods and services in other contexts where consumers exhibit similar preferences.

California↗

U.S. Solar Photovoltaic BESS System Cost Benchmark Q1 2020 Report

NREL has been modeling U.S. solar photovoltaic (PV) system costs since 2009. This year, our report benchmarks costs of U.S. PV for residential, commercial, and utility-scale systems, with and without storage, built in the first quarter of 2020 (Q1 2020). The methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems and it models the capital costs and levelized cost of energy for such systems.

14 SOLAR ENERGY↗

Validation of Photovoltaic Modeling Tool Solargraf Against Measured Data

Solargraf is a cloud-based 3D design tool by Enphase Energy that allows users to design solar and storage systems with a variety of elements. Through a Cooperative Research and Development Agreement (CRADA), Enphase Energy collaborated with the National Renewable Energy Laboratory (NREL) to validate Solargraf's 3D design simulation against measured PV system performance. This study follows the same methodology of similar validation studies completed at NREL. The predicted performance results from simulations in both Solargraf and NREL's System Advisor Model (SAM) tool were compared with measured data to evaluate performance predictions.

14 SOLAR ENERGY↗

Voltage Violation Prediction in Unobservable Distribution Systems

Recently, distributed energy resources (DERs) such as photovoltaic (PV) systems have garnered significant attention due to their economic and environmental benefits. However, DERs can also pose new technical challenges to distribution system operation including under/over voltage issues. In this regard, voltage violation prediction (VVP) becomes an essential component of system operation as it enables proactive control strategies. Unfortunately, classical voltage monitoring techniques assume full availability of state measurements across all nodes in the system. In real-world scenarios, distribution systems are limited with few measurement devices, rendering the system unobservable. Therefore, this paper proposes a new Bayesian matrix completion (BMC) based VVP technique that accurately predicts the probability of nodal voltage violations in unobservable (and unbalanced) distribution systems. The proposed approach is tested via simulations on the IEEE 37 test system. Results show that the proposed method offers over 90% violation prediction accuracy with as low as 50% fraction of available data.

Abujubbeh, Mohammad↗

Enhancing Power Resilience for Remote Communities: A Comprehensive Renewable Energy Solution for Itbayat Island

The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.

14 SOLAR ENERGY↗

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

NREL has been modeling U.S. solar photovoltaic (PV) system costs since 2009. This year, our report benchmarks costs of U.S. PV for residential, commercial, and utility-scale systems, with and without storage, built in the first quarter of 2021 (Q1 2021). The methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems and it models the capital costs and levelized cost of energy for such systems.

14 SOLAR ENERGY↗

U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2020 [PowerPoint]

NREL has been modeling U.S. photovoltaic (PV) system costs since 2009. This report benchmarks costs of U.S. solar PV for residential, commercial, and utility-scale systems, with and without storage, built in the first quarter of 2020 (Q1 2020). Our methodology includes bottom-up accounting for all system and project-development costs incurred when installing residential, commercial, and utility-scale systems, and it models the capital costs for such systems.

14 SOLAR ENERGY↗

Renewable hydrogen horizon: Geospatial techno-economic feasibility and life cycle greenhouse gas analysis in the Middle East and North Africa

Renewable hydrogen is receiving increasing attention for its potential as a flexible energy carrier in sectors such as transportation and industry. Specific cost and carbon intensity (CI) of renewable hydrogen production vary largely based on the location, owing to differences in renewable energy resources, as well as the supply chain dynamics. This study maps the techno-economic and life cycle greenhouse gas emissions of renewable hydrogen production in the Middle East and North Africa region, leveraging abundant solar and wind resources. The work investigates the variability in hydrogen costs and CI, optimally sizing proton-exchange membrane (PEM) electrolyzers to account for partial and cyclic loading, and explores standalone versus grid-connected systems. PEM capacity ratios of 52 %–63 % for photovoltaic (PV) systems and 28 %–82 % for wind systems were identified as optimal, with hydrogen production costs ranging from $\$3.8$-$\$4.8$/kg for PV and $2.0-$7.0/kg for wind. CIs span from 1.9 to 3.7 kg CO 2 ,eq /kg H 2 for PV and 0.4–7.7 kg CO 2,eq /kg H 2 for wind systems. The study highlights significant cost and CI reductions achievable with technological advancements and co-product revenue from oxygen and excess electricity sales.

Carbon Intensity↗

High-Resolution Floating Solar PV Data

This dataset contains over two years of 1-minute resolution data collected from four floating solar sites, as well as data from a land-based PV system co-located with one of the floating sites. The dataset includes highly granular module temperature measurements - five modules per floating site, with three sensors per module, totaling 15 module temperature sensors per floating site. In addition to the module temperature data, meteorological data collected at the floating sites is also included, along with traditional PV system-level parameters. The data is intended for analysis of solar energy production, efficiency, and performance degradation over time. For information about the data file usage see the "README" resource below. See "Metadata File" for information about individual files and other metadata information.

Array↗

A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid

Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMGs are challenged with limited resource availability, absence of robust grid support, and heightened demand-supply uncertainty. Here, this paper proposes a secure and adaptive three-stage hierarchical multi-timescale framework for scheduling and real-time (RT) dispatch of CMGs with hybrid PV systems to address these challenges. The framework enables the CMG to dynamically expand its boundary to support the neighboring grid sections and is adaptive to the changing forecast error impacts. The first stage solves a stochastic extended duration scheduling (EDS) problem to obtain referral plans for optimal resource rationing. The intermediate near-real-time (NRT) scheduling stage updates the EDS schedule closer to the dispatch time using new obtained forecasts, followed by the RT dispatch stage. To make the decisions more secure and robust against forecast errors, a novel concept called delayed recourse is designed. The approach is evaluated via numerical simulations on a modified IEEE 123-bus system and validated using OpenDSS and hardware-in-loop simulations. The results show superior performance in maximizing load supply and continuous secure distribution network operation under different operating scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Residential Solar-Adopter Income and Demographic Trends: 2024 Update [Slides]

The report describes income, demographic, and other socio-economic trends among U.S. residential rooftop solar adopters. The report is based on address-level data for roughly 4.1 million residential rooftop solar systems installed through 2023, representing 87% of all U.S. systems. With its unique size, geographic scope, and level of detail, this report is intended to serve as a foundational reference document for policy-makers, industry stakeholders, and researchers. Key findings include the following: -The median income of households that installed solar in 2023 was about $\$$115k/year, compared to a U.S. median of $\$$75k/year for all households and $\$$94k/year for all U.S. owner-occupied households. -Compared to owner-occupied households in the same state, 2023 solar-adopter incomes were 7% higher in the median case, and in 10 states, median solar-adopter incomes were below the corresponding median income for all owner-occupied households. -Roughly 49% of solar adopters in 2023 had incomes below 120% of their area median income (AMI), a threshold sometimes used to define “low-and-moderate income” (or LMI), while 26% were below 80% of AMI, often used to define “low-income”. -Solar adoption continues to shift toward less affluent households over time, with the median present-day income of solar adopters dropping from $\$$141k for households that installed systems in 2010 to $\$$115k in 2023. -PV systems installed in 2023 by households earning less than $\$$50k had a median size of 6.4 kW, 33% were third-party owned, and 6% included battery storage, compared to corresponding values of 8.0 kW, 18%, and 14% for households earning more than $\$$200k. -Compared to all households in their respective state, solar adopters in 2023 were slightly more likely to be college educated and to live in rural areas; had higher home values; and were more likely to live outside a disadvantaged community (DAC), be middle-aged, identify as non-Hispanic white, work in a business or financial occupation, and own a single-family home. In conjunction with the report, Berkeley Lab has published an updated accompanying set of online data visualizations that allow users to further explore the underlying data. Berkeley Lab is also offering related analytical support to states, local agencies, and other organizations on issues related to solar adoption among low-to-moderate income households; requests for analytical support may be submitted through this online form.

14 SOLAR ENERGY↗

Addressing Soiling: From Interface Chemistry to Practicality

Natural soiling has reduced the energy output of photovoltaic (PV) systems since the technology was first used. Projecting even a small average annual soiling loss translates to billions of dollars in annual lost revenue worldwide. Production losses due to soiling can be very high in some locations, substantially increasing the levelized cost of electricity (LCOE) due to lost power production, increased operating and maintenance costs, and/or increased finance cost due to the uncertainty. Furthermore, although soiling has been discussed in the literature for more than 70 years, solutions to many problems are still needed. The National Renewable Energy Laboratory (NREL) is working with the PV industry to develop the tools/knowledge so that the effects of soiling can be predicted for different environmental conditions and cost-effective mitigation can be implemented. For this project, NREL performed a number of research and development tasks/subtasks in the following general areas to 1) predict PV module soiling losses based on environmental factors at a PV installation and from its energy production data, 2) quantitatively measure the adhesion forces to understand the physics enabling soiling, and 3) develop related standards on PV module coatings and artificial soiling. At the inception of the project, the PV industry considered these efforts to be the most important and immediate soiling issues that we could address to have the highest impact on LCOE. These focused efforts have led to outstanding accomplishments that have been communicated and very well received by the community.

14 SOLAR ENERGY↗

Performance Index Assessment for the PV Fleet Performance Data Initiative

We report on 250 PV systems throughout the United States, comprising 157 MWdc of system capacity and more than 10,000 monthly performance index (PI) values. Loss factors were isolated including first-year start-up issues, snowfall, soiling and inverter downtime. Inverter availability was found to contribute significant system energy loss during the first six months of operation, with an average of 8% loss occurring during this period, and 2.3% on average thereafter. Other start-up issues beyond inverter downtime, such as partial string outage, contributed additional underperformance in the first year of operation across the fleet. Winter performance was also found to be below summer performance on average, likely due to snowfall. A relationship was found between monthly snowfall accumulation in centimeters and monthly under-performance, indicating a 6%-40% loss in months with measured snowfall, depending on climate. After correcting for availability, snow and startup loss, over 90% of systems were performing within 10% of monthly expectation based on satellite resource data and PVWatts production estimates.

loss factors↗

Open‐source photovoltaic model pipeline validation against well‐characterized system data

Abstract All freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.

14 SOLAR ENERGY↗

Blackfeet Community College Renewable Energy Project

The Blackfeet Community College (BCC), under Topic Area 1.a. Energy Generating System(s), received funds to install solar photovoltaic (PV) systems to support four existing campus buildings. Blackfeet Community College seeks to bring renewable energy benefits to the Blackfeet Reservation Community.

14 SOLAR ENERGY↗