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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Flight and Direct to Earth/Space Relay Communication System Architecture for GSFC CubeSat Missions

The CubeSat platform is finding increasing use in space science applications due to its low cost and comparative ease of launch. It is becoming a key scientific discovery tool in low Earth orbit (LEO) and beyond, including geosynchronous equatorial orbit (GEO), the Lagrange Points, Lunar missions, and more. The increasing complexity of these missions and their scientific goals must be supported by equal advancements in communications technology. Higher data rates and greater reliability are required every year. However, the reduced Size, Weight, and Power (SWaP) constraints of CubeSat platforms introduce unique challenges in the area of satellite communications. There is currently a lack of communication equipment tailored specifically to the CubeSat platform. This lack of standardized, tested equipment extends development time and reduces mission confidence. Furthermore, missions utilizing the CubeSat platform are often subject to more difficult design constraints. Antenna placement, size, and pointing are often subordinate to the requirements of the payload instruments and mission goals. Traditional link margin estimation techniques are insufficient in these cases, as they emphasize worst case scenarios. In reality the actual link parameters may vary widely even during a single pass. This presents new challenges in predicting communications performance and scheduling ground station contacts, but also new opportunities for improving efficiency. This paper presents the integration, testing, and validation process for a new software defined radio (SDR) designed for the CubeSat platform in conjunction with Vulcan Wireless, Inc. The SDR is planned for use on 5 upcoming CubeSat missions at NASAs Goddard Space Flight Center (GSFC) including a Geosynchronous Transfer Orbit (GTO) mission and it may also serve as a standard and well-tested option for future missions by enabling a standardized, rapid and low cost CubeSat communication system network integration process. Detailed simulations have been developed to estimate the communication performance of these missions, taking the unique antenna placements and attitude behavior of each satellite into account. These simulations allow a much more accurate analysis of the expected link margin, which varies considerably during each pass for the NASA Space Relay (SR) and Direct to Earth (DTE) network. The modelling procedures are outlined, and the results are used to predict communications performance of the missions.

Space Networks↗
DOE OSTI2016

Waste Estimation from a Wide-Area Radiological Incident: The Impact of Geography and Urban Footprint - 16256

In the planning and preparedness stages for a response to a radiological incident, it is important to include waste management considerations when developing the decontamination/demolition/cleanup approach because waste management can be a driver for time and cost for return to normalcy. Waste management is also inextricably linked to the geography and urban footprint of the impacted area. The U.S. Environmental Protection Agency's (EPA's) Waste Estimation Support Tool (WEST) is a novel application based on the Federal Emergency Management Agency (FEMA) Hazus-MH software. WEST enables users to estimate the characteristics, amount, and residual radioactivity of waste generated from remediation and cleanup activities after a radiological incident, including incidents caused by radiological dispersal devices and improvised nuclear devices, as well as nuclear power plant accidents. These waste estimates are generated as a function of user-defined decontamination strategies and are specific to a geographic location. This paper will describe the recently released version 3 update to WEST, and how differences in geography and urban footprints can impact the waste that is generated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

wtDigiTwin (Wind Turbine Digital Twin) [SWR-21-15]

This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.

Branlard, Emmanuel↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1995

T/BEST: Technology Benefit Estimator Select Features and Applications

A Technology Benefit Estimator (T/BEST) system has been developed to provide a formal method to assess advanced aerospace technologies and quantify the benefit contributions for prioritization. An open-ended, modular approach is used to allow for upgrade and insertion of advanced technology modules. T/BEST's software framework, beginner-to-expert operation, interface architecture, and key analysis modules are discussed. In this paper, selected features and applications of T/BEST are demonstrated. Sample cases pertaining to structural analysis of titanium and composite blades are presented. The performance of hot and cold composite fan blades is also discussed. The cost required to manufacture titanium and composite fan blades is estimated.

Generazio, Edward R.↗
DOE OSTI2025

EverBESS

SF-25-113 This software is a website for the EverBESS model. This model examines the cost and environmental impacts related to end-of-life management of battery energy storage systems. Users input their system's specifications and the model returns estimates for the costs of decommissioning, transporting, and recycling the system.

Elias, Jakob [Argonne National Laboratory (ANL), A↗
DOE OSTI2026

Improvements in Mirror Surface Measurement with Reflected Computer Vision Targets

Over the last several years, NREL has been developing a system to measure large optical surfaces of heliostat mirrors by reflecting computer vision targets. An advantage of this system, called Reflected Target Nonintrusive Assessment (ReTNA), is that it lends itself well to stitching together many images, each reflecting only part of a larger heliostat. In the last few months, this was taken to a new extreme, with a small target (<5m2) being used to measure a >25m2 long focal length heliostat. These measurements were compared with traditional fringe deflectometry methods, which require a >50m2 target, and photogrammetry. The strengths, weaknesses and limitations of ReTNA are discussed. An estimated uncertainty in this new measurement is presented, along with software improvements and a new wireless data collection system. A bill of materials for this measurement system is presented, which has been designed to use all low-cost, off-the-shelf components. Finally, the next steps for future ReTNA development are presented. Overall, ReTNA can be a valuable optics measurement system, complimentary to existing measurement techniques available for large reflective surfaces.

14 SOLAR ENERGY↗
NASA NTRS1975

Environmental monitoring of North Merritt Island

The environmental impact of the space shuttle operation on North Merritt Island was studied mainly by means of color infrared photos and field visits. An attempt was also made to generate character maps of the Island using LANDSAT data with a view to decreasing the cost of monitoring and making the process more flexible in terms of rapid estimation of the extent of selected ground features. It seems possible that the IMAGE-100 output can be improved by using it in conjunction with software systems which are used for generating character maps. All the methods for generating maps show six main plant associations on North Merritt Island. It was shown that the six associations are related by ecological succession, merge into their neighbors in terms of component species and can be observed for changes in terms of component species.

Poonai, P.↗
DOE OSTI2024

Merefa Community Microgrid: Supporting Distributed Energy Resource Deployment in Ukraine

A conceptual design is described for a community microgrid in Ukraine. Microgrid resources include solar photovoltaics, battery energy storage, and conventional natural gas fueled reciprocating engine generators. The conceptual architecture was informed by the microgrid developer, NREL subject matter experts, and the application of REopt, an NREL-developed software tool created for identification of least-cost combination of resources for achieving cost savings, resilience, and renewable energy goals. This fact sheet is a summary of a previously published technical report; see NREL/TP-7A40-89527, which includes conceptual architecture, estimates of key summary financial metrics, and sequence of operations.

battery storage↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
NASA NTRS2021

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗
DOE OSTI2023

Next-Generation Marine Energy Software Needs Assessment

The U.S. Department of Energy (DOE) Water Power Technologies Office’s (WPTO) initial investment in marine energy software was driven by needs identified over a decade ago. WPTO-funded research was first launched because of a U.S. congressional mandate that called for the DOE to officially research marine energy technologies, which also established the DOE WPTO in 2008. A congressional mandate requested the WPTO to evaluate a variety of marine energy devices, establish baseline levelized cost of energy estimates, and provide an overall report to Congress. This congressional mandate led to the Reference Model Project (RMP), for which WPTO funded a national multi-laboratory team to develop these reference models, based on state-of-the-art designs of six marine energy converter archetypes that consisted of three current energy converters and three wave energy converters (WEC). Each device was designed to operate for a specific marine resource, thus allowing the devices to serve as reference models for future studies. The RMP congressional report cited the need for improved marine energy software to handle a variety of device designs, as well as a need to standardize performance outputs. Without validated software packages and established metrics, information presented to the WPTO by technology developers could be incorrect or inaccurate and result in misleading conclusions. The recommendation to coordinate WPTO investment in software for numerical modeling and analysis was given a high priority because it would directly fill needs at the time, and focused funding would amplify impact. By sponsoring software development, WPTO would provide industry developers, university researchers, and national laboratories software that could be used, customized, and advanced, thus supporting the overall advancement of marine energy.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

j5 v2.8.4

j5 automates and optimizes the design of the molecular biological process of cloning/constructing DNA. j5 enables users to benefit from (combinatorial) multi-part scar-less SLIC, Gibson, CPEC, Golden Gate assembly, or variants thereof, for which automation software does not currently exist, without the intense labor currently associated with the process. j5 inputs a list of the DNA sequences to be assembled, along with a Genbank, FASTA, jbei-seq, or SBOL v1.1 format sequence file for each DNA source. Given the list of DNA sequences to be assembled, j5 first determines the cost-minimizing assembly strategy for each part (direct synthesis, PCR/SOE, or oligo-embedding), designs DNA oligos with Primer3, adds flanking homology sequences (SLIC, Gibson, and CPEC; optimized with Primer3 for CPEC) or optimized overhang sequences (Golden Gate) to the oligos and direct synthesis pieces, and utilizes BLAST to check against oligo mis-priming and assembly piece incompatibility events. After identifying DNA oligos that are already contained within a local collection for reuse, the program estimates the total cost of direct synthesis and new oligos to be ordered. In the instance that j5 identifies putative assembly piece incompatibilities (multiple pieces with high flanking sequence homology), the program suggests hierarchical subassemblies where possible. The program outputs a comma-separated value (CSV) file, viewable via Excel or other spreadsheet software, that contains assembly design information (such as the PCR/SOE reactions to perform, their anticipated sizes and sequences, etc.) as well as a properly annotated genbank file containing the sequence resulting from the assembly, and appends the local oligo library with the oligos to be ordered j5 condenses multiple independent assembly projects into 96-well format for high-throughput liquid-handling robotics platforms, and generates configuration files for the PR-PR biology-friendly robot programming language. j5 thus provides a new way to design DNA assembly procedures much more productively and efficiently, not only in terms of time, but also in terms of cost. To a large extent, however, j5 does not allow people to do something that could not be done before by hand given enough time and effort. An exception to this is that, since the very act of using j5 to design the DNA assembly process standardizes the experimental details and workflow, j5 enables a single person to concurrently perform the independent DNA construction tasks of an entire group of researchers. Currently, this is not readily possible, since separate researchers employ disparate design strategies and workflows, and furthermore, their designs and workflows are very infrequently fully captured in an electronic format which is conducive to automation.

Hillson, Nathan↗
NASA NTRS2002

Using Pilots to Assess the Value and Approach of CMMI Implementation

At Goddard Space Flight Center (GSFC), we have chosen to use Capability Maturity Model Integrated (CMMI) to guide our process improvement program. Projects at GSFC consist of complex systems of software and hardware that control satellites, operate ground systems, run instruments, manage databases and data and support scientific research. It is a challenge to launch a process improvement program that encompasses our diverse systems, yet is manageable in terms of cost effectiveness. In order to establish the best approach for improvement, our process improvement effort was divided into three phases: 1) Pilot projects; 2) Staged implementation; and 3) Sustainment and continual improvement. During Phase 1 the focus of the activities was on a baselining process, using pre-appraisals in order to get a baseline for making a better cost and effort estimate for the improvement effort. Pilot pre-appraisals were conducted from different perspectives so different approaches for process implementation could be evaluated. Phase 1 also concentrated on establishing an improvement infrastructure and training of the improvement teams. At the time of this paper, three pilot appraisals have been completed. Our initial appraisal was performed in a flight software area, considering the flight software organization as the organization. The second appraisal was done from a project perspective, focusing on systems engineering and acquisition, and using the organization as GSFC. The final appraisal was in a ground support software area, again using GSFC as the organization. This paper will present our initial approach, lessons learned from all three pilots and the changes in our approach based on the lessons learned.

Godfrey, Sara↗
DOE OSTI2020

Minimum Detectable Quantity Calculation for Radiation Portal Monitors

The minimum detectable quantity of a radiation portal monitor is the smallest amount of radioactive material that can be detected passing through the monitor (with a specified detection probability). The minimum detectable quantity is a function of many factors, including isotope, velocity, distance between pillars, height of portal and vehicle, source distribution and position, background radiation, background suppression, detector volume and positions, detector efficiency, decision metrics and algorithms, the presence of NORM (naturally occurring radioactive material), and alarm thresholds. Experimentally testing a radiation portal monitor to failure for all combinations of these factors is extremely time-consuming and often cost prohibitive. This document outlines a straightforward method for quickly estimating the minimum detectable quantity for moving sources over a large variety of conditions with a minimal number of static measurements. The document also describes a proof of concept software application that the International Atomic Energy Agency has designed based on the described method that can be used by Member States to estimate a monitor’s minimum detectable quantity.

Blessinger, Christopher S.↗
DOE OSTI2023

Impact of genotype‐calling methodologies on genome‐wide association and genomic prediction in polyploids

Abstract Discovery and analysis of genetic variants underlying agriculturally important traits are key to molecular breeding of crops. Reduced representation approaches have provided cost‐efficient genotyping using next‐generation sequencing. However, accurate genotype calling from next‐generation sequencing data is challenging, particularly in polyploid species due to their genome complexity. Recently developed Bayesian statistical methods implemented in available software packages, polyRAD, EBG, and updog, incorporate error rates and population parameters to accurately estimate allelic dosage across any ploidy. We used empirical and simulated data to evaluate the three Bayesian algorithms and demonstrated their impact on the power of genome‐wide association study (GWAS) analysis and the accuracy of genomic prediction. We further incorporated uncertainty in allelic dosage estimation by testing continuous genotype calls and comparing their performance to discrete genotypes in GWAS and genomic prediction. We tested the genotype‐calling methods using data from two autotetraploid species, Miscanthus sacchariflorus and Vaccinium corymbosum , and performed GWAS and genomic prediction. In the empirical study, the tested Bayesian genotype‐calling algorithms differed in their downstream effects on GWAS and genomic prediction, with some showing advantages over others. Through subsequent simulation studies, we observed that at low read depth, polyRAD was advantageous in its effect on GWAS power and limit of false positives. Additionally, we found that continuous genotypes increased the accuracy of genomic prediction, by reducing genotyping error, particularly at low sequencing depth. Our results indicate that by using the Bayesian algorithm implemented in polyRAD and continuous genotypes, we can accurately and cost‐efficiently implement GWAS and genomic prediction in polyploid crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Using ASCEM Modeling and Visualization to Inform Stakeholders of Contaminant Plume Evolution and Remediation Efficacy at F-Basin Savannah River, SC – 15156

Communication with stakeholders, regulatory agencies, and the public is an essential part of implementing different remediation and monitoring activities, and developing site closure strategies at contaminated sites. Modeling of contaminant plume evolution plays a critical role in estimating the benefit, cost, and risk of particular options. At the same time, effective visualization of monitoring data and modeling results are particularly important for conveying the significance of the results and observations. In this paper, we present the results of the Advanced Simulation Capability for Environmental Management (ASCEM) project, including the discussion of the capabilities of newly developed ASCEM software package, along with its application to the F-Area Seepage Basins located in the U.S. Department of Energy Savannah River Site (SRS). ASCEM software includes state-of-the-art numerical methods for simulating complex flow and reactive transport, as well as various toolsets such as a graphical user interface (GUI), visualization, data management, uncertainty quantification, and parameter estimation. Using this software, we have developed an advanced visualization of tritium plume migration coupled with a data management system, and simulated a three-dimensional model of flow and plume evolution on a high-performance computing platform. We evaluated the effect of engineered flow barriers on a nonreactive tritium plume, through advanced plume visualization and modeling of tritium plume migration. In addition, we developed a geochemical reaction network to describe complex geochemical processes at the site, and evaluated the impact of coupled hydrological and geochemical heterogeneity. These results are expected to support SRS’s monitoring activities and operational decisions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

The National Solar Permitting Database

"The soft costs of solar — costs not associated with hardware — remain stubbornly high. Among the biggest soft costs are those associated with inefficiencies in local permitting and inspection. A study by the National Renewable Energy Laboratory and Lawrence Berkeley National Laboratory estimates that these costs add an average of $0.22/W per residential installation. This project helps reduce non-hardware/balance of system (BOS) costs by creating and maintaining a free and available site of permitting requirements and solar system verification software that installers can use to reduce time, capital, and resource investments in tracking permitting requirements. Software tools to identify best permitting practices can enable government stakeholders to optimize their permitting process and remove superfluous costs and requirements. Like ""a Wikipedia for solar permitting"", users can add, edit, delete, and update information for a given jurisdiction. We incentivize this crowdsourcing approach by recognizing users for their contributions in the form of SEO benefits to their company or organization by linking back to users' websites."

Gunderson, Renic↗