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At least 793 records · Page 44

Viewfactor and Raytracing for AgriPV Modeling

View factor models are used in due diligence software to calculate rear irradiance for bifacial modules. An intermediate step in this calculation is the irradiance at the ground level, which can be leveraged for evaluating the Photo Active Radiation available for crops in Agrivoltaic setups. This paper presents the metrics and modifications to the model for ground irradiance study with the view factor approach, compares it to the raytracing method, and validates it with field measurements of ground irradiance. It is found that for the clearances, row-to-row setups, and tilts studied, the view factor method matches with raytracing results within 2% MBD. The comparison is performed for the nine most common agriPV configurations using high-performance computing and the NSRDB database for the whole US, with results and data made available open-source on the InSPIRE AgriPV website.

AgriPV↗

Deep Reinforcement Learning Enabled Physical-Model-Free Two-Timescale Voltage Control Method for Active Distribution Systems

Active distribution networks are being challenged by frequent and rapid voltage violations due to renewable energy integration. Conventional model-based voltage control methods rely on accurate parameters of the distribution networks, which are difficult to achieve in practice. This paper proposes a novel physical-model-free two-timescale voltage control framework for active distribution systems. To achieve fast control of PV inverters, the whole network is first partitioned into several subnetworks using voltage-reactive power sensitivity. Then, the scheduling of PV inverters in the multiple sub-networks is formulated as Markov games and solved by a multi-agent soft actor-critic (MASAC) algorithm, where each subnetwork is modeled as an intelligent agent. All agents are trained in a centralized manner to learn a coordinated strategy while being executed based on only local information for fast response. For the slower time-scale control, OLTCs and switched capacitors are coordinated by a single agent-based SAC algorithm using the global information with considering control behaviors of the inverters. Particularly, the two-level agents are trained concurrently with information exchange according to the reward signal calculated from the data-driven surrogate model. Comparative tests with different benchmark methods on IEEE 33-and 123-bus systems and 342-node low voltage distribution system demonstrate that the proposed method can effectively mitigate the fast voltage violations and achieve systematical coordination of different voltage regulation assets without the knowledge of accurate system model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Search for direct CP violation in charged charmless B→PV decays

Measurements of C P asymmetry in charmless B → P V decays are presented, where P and V denote a pseudoscalar and a vector meson, respectively. Five different B → P V decays from four final states, B ± → π ± π + π - , B ± → K ± π + π - , B ± → K ± K + K - and B ± → π ± K + K - are analyzed. The measurements are based on a method that does not require full amplitude analyses, and are performed using proton-proton collision data at a center-of-mass energy of 13 TeV collected by LHCb between 2015 and 2018, corresponding to an integrated luminosity of 5.9 fb - 1 . In the π + π - P -wave, in the region dominated by the B ± → ρ ( 770 ) 0 K ± decay, a C P asymmetry of A C P = + 0.150 ± 0.019 ± 0.011 is measured, where the first uncertainty is statistical and the second is systematic. This is the first observation of C P violation in this process. For the other four decay channels, in regions dominated by the B ± → ρ ( 770 ) 0 π ± , B ± → K ( ¯ ) * ( 892 ) 0 π ± , B ± → K ( ¯ ) * ( 892 ) 0 K ± and B ± → Φ ( 1020 ) K ± decays, C P asymmetries in the P -wave compatible with zero are measured.

79 ASTRONOMY AND ASTROPHYSICS↗

Cost Efficient and Highly Weather-Resistant Solar Panel Backsheet Produced through Continuous Co-Extrusion Processing

The efficient generation and delivery of ‘clean energy” through photovoltaic (PV) technology relies heavily on the cost, performance and reliability of solar panels, along with the individual components used in assembly of those panels. In order to continue towards the Department of Energy’s (DOE) goals of driving costs down, the lifetime of high-output power generation equipment (i.e. solar modules) must be extended to reduce costs associated with power output degradation and replacement of failed or degraded panels. One of the major sources of module failures in the past 30 years has been the failure of the solar panel backsheet. Failure of this component causes severe output losses due to oxidation and yellowing of the module while creating safety concerns as the major electrical insulation of the module is compromised. Tomark-Worthen LLC was formed in 2012 with the goal of designing and manufacturing novel PV backsheets and encapsulants that would be produced in the United States of America and exceed expectations of domestic and international module producers. These backsheets would improve upon known backsheet design failures (i.e. Isovoltaic’s AAA backsheet) and create domestic manufacturing jobs in the PV sector. This goal became a reality with a first-generation product in 2018 and now, with the support of the DOE, Tomark-Worthen has launched a second-generation product known as PhotoMark® Reflections™ 205-3 and 360-3. This 2+ year effort began in late 2017 with a screening of potential polymeric materials and backsheet structural designs. Performance evaluations of each material provided the necessary data needed to select the proper material combinations and move forward into the design of the manufacturing process. These decisions were made by teaming with a local university, well-respected government laboratories, and private research organizations who provided the tools necessary to predict long-term performance of these materials in much shorter periods of time. Once the go/no-go criteria were met at the mid-point of the project, the effort transitioned to predicting 30+ year performance, achieving certifications, and improving manufacturing efficiencies designed to lower costs in order to be competitive in a cost-driven market. Major project accomplishments include recognition of the new backsheet by Underwriters Laboratories (UL) and international certification for 1000V and 1500V modules by TUV Sud. Both 1000V and 1500V products have been proven on several module manufacturing lines and initial customer orders have been received by both domestic and international module producers. Accelerated exposure testing has shown that the performance of this backsheet exceeds the prior polyamide-based backsheet known to fail in the field. Cost-models and initial customer orders have shown the ability to produce this backsheet at a cost acceptable to many domestic manufacturers, while International costs for standard backsheet remains extremely low. Tomark-Worthen remains one of the only U.S. companies manufacturing backsheet domestically and this has drawn interest from many domestic module manufacturers looking to improve their material supply logistics by avoiding long lead times and custom’s headaches while avoiding current tariffs on Chinese-made components. Along with the launch of a new PV backsheet, this project has provided a critical deliverable to the PV R&D community. This deliverable is the knowledge that not all polyamide-containing backsheets are doomed to failure as the earlier versions did. There has been a fear amongst the PV community to consider these materials due to the failure of one design. This effort has brought a new level of interest to the scientific community as it has been shown that polyamides can be used successfully in a well-designed backsheet. As we move forward from this project, we are excited to see how backsheet technology and manufacturing in the U.S. will continue to progress and grow.

14 SOLAR ENERGY↗

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Laboratory-based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Additionally, there is a growing concern on characterizing the non-uniformity of field exposure. Therefore, data from field surveys are critical to assess the performance of component lifetimes. Using a documented field survey protocol, 19 field surveys were conducted. The focus of this survey strategy is to investigate spatial continuity in degradation modes. By combining field survey data with real-time satellite weather data, stressor / response models have been trained. Generalized additive Models (GAM) model was created to predict the value of degradation based on measured predictors. Two different GAM constructions were testing using different implementations of basis splines. The model includes variables on the environmental stressors of the system and the location of each measurement in the PV mounting structure. The incorporation of hierarchical structure into the models allowed for material specific degradation rates, while maintaining the assumption of a global trend. The model performed well with an adjusted R2 of 0.975 for yellowness index prediction.

backsheet↗

Chemical Data Assimilation: A Case Study of Solar Occultation Data From the Atlas 1 Mission of the Atmospheric Trace Molecule Spectroscopy Experiment

A key advantage of using data assimilation is the propagation of information from data-rich regions to data-poor regions, which is particularly relevant to the use of solar occultation data such as from ATMOS. For the first time an in depth uncertainty analyses is included in a photochemical model-data intercomparison including observation, representativeness, and theoretical uncertainty. Chemical data assimilation of solar occultation measurements can be used to reconstruct full diurnal cycles and to evaluate their chemical self-consistency. This paper considers as an example the measurements made by the Atmospheric Trace Molecule Spectroscopy Experiment (ATMOS) instrument Atlas-1 during March 1992 for a vertical profile flow tracking coordinates at an equivalent PV latitude of 38 S. ATMOS was chosen because it simultaneously observes several species. This equivalent PV latitude was chosen as it was where ATMOS n observed the atmosphere's composition over the largest range of altitudes. A single vertical profile was used so that the detailed diurnal information that assimilation utilizes could be highlighted. There is generally good self-consistency between the ATMOS Atlas-1 observations and photochemical theory.

Lary, D. J.↗

Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost, scalable, and high-throughput manufacturing techniques. One of the critical challenges of developing a new fabrication technique is the high-dimensional parameter space for optimization, but machine learning (ML) can readily be used to accelerate perovskite PV scaling. Herein, we present an ML-guided framework of sequential learning for manufacturing process optimization. We apply our methodology to the Rapid Spray Plasma Processing (RSPP) technique for perovskite thin films in ambient conditions. With a limited experimental budget of screening 100 process conditions, we demonstrated an efficiency improvement to 18.5% as the best-in-our-lab device fabricated by RSPP, and we also experimentally found 10 unique process conditions to produce the top-performing devices of more than 17% efficiency, which is 5 times higher rate of success than the control experiments with pseudo-random Latin hypercube sampling. Our model is enabled by three innovations: (a) flexible knowledge transfer between experimental processes by incorporating data from prior experimental data as a probabilistic constraint; (b) incorporation of both subjective human observations and ML insights when selecting next experiments; (c) adaptive strategy of locating the region of interest using Bayesian optimization first, and then conducting local exploration for high-efficiency devices. Furthermore, in virtual benchmarking, our framework achieves faster improvements with limited experimental budgets than traditional design-of-experiments methods (e.g., one-variable-at-a-time sampling). This framework shows the capability of incorporating researchers’ domain knowledge into the ML-guided optimization loop; therefore, it has the potential to facilitate the wider adoption of ML in scaling to perovskite PV manufacturing.

14 SOLAR ENERGY↗

DEPRECATED - Sharing the Sun Community Solar Project Data (June 2022)

This data set is no longer current – The most current data and all historical data sets can be found at https://data.nrel.gov/submissions/244 This database represents a list of community solar projects identified through various sources as of June 2022. The list has been reviewed but errors may exist and the list may not be comprehensive. Errors in the sources e.g. press releases may be duplicated in the list. Blank spaces represent missing information. NREL invites input to improve the database including to - correct erroneous information - add missing projects - fill in missing information - remove inactive projects. Updated information can be submitted to the contact(s) located on the current data set page linked at the top.

14 SOLAR ENERGY↗

A Comparison of PV Resource Modeling for Sizing Microgrid Components

Microgrid systems are being deployed with increased frequency to meet critical building loads during unplanned power outages. Determining the appropriate type and size of components that make up a microgrid can greatly affect its ability to meet this need. This paper presents a new tool to appropriately size PV, battery, and generator capacities to meet all site loads, given a resilience goal. It uses a statistical model to simulate microgrid behavior under a large range of solar resource conditions, providing resilience planners with confidence that critical loads will be met even under extreme weather conditions. We compare this model with one that uses typical weather data for sizing microgrids, and quantify the resilience effects of using these different methods. Our method produces more conservative generator capacities and fuel requirements in an outage, predicting up to 30% more fuel required in the most extreme case. Microgrid systems that are designed using more conservative estimates are more likely to continue to serve load during emergency outages under a large range of conditions.

Newman, Sarah F.↗

Life after 30 years - a PV system in Colorado

The PV system consisted of 155 monocrystalline Si Arco M53 panels, installed in 1987. 80 were installed on a fixed tilt rack, and 75 on 5 separate dual-axis passive trackers. The system was decommissioned in 2017 due a campus re-design and building expansion at the Platte River Power Authority (PPRA) site. Prior to decommissioning a site visit established the following failure type observations: EVA browning (100%), cracked cells (60%), and cracked wires or grommets (9%, or more if replacements were made selectively on cracked parts). EVA browning is typical in modules of this vintage, whereas the occurrence of so many cracked cells is surprising and is likely weather-related. The fairly frequent occurrence of cracked wires and grommets serves as a reminder that accelerated testing of these components is important for goals of low-cost 50-year energy generation. In smaller numbers, thermal effects (7%), bent frames (1%), and cell corrosion (<1%) were observed. A sample of 20 modules was selected and brought to NREL for in-depth characterization. Because baseline measurements were not available using the nameplate rating, which can be inaccurate, revealed a mean module sample degradation of 0.7 %/year. Sporadic production data during the 30 years determined a system degradation rate closer to 1.2 %/year. Subsequently, four of these modules were re-mounted outdoors at NREL and are now approaching a total lifetime of 34 years.

durability↗

A Retrospective Analysis of Distributed Solar Interconnection Timelines and Related State Mandates

Most distributed residential photovoltaic (PV) systems must secure an interconnection agreement prior to operation that ensures the local electrical system will operate safely within the broader electrical grid. PV installers generally submit an interconnection application to the local utility that provides all the necessary details the utility needs to evaluate the proposed system. To encourage timely execution of this process, many states’ utility commissions have established mandates that limit the maximum number of days allowed for utility review and approval of interconnection for certain small, often residential applications. In this paper, we derive the median and range of cycle times for the pre-installation approval phase of the interconnection process (i.e., from application submission to approval by the utility) across 24 U.S. states, using a data set of approximately 170,000 projects. We evaluate the percentage of projects that are approved within respective state-mandated timelines from 2017– 2019. We further evaluate how timelines have evolved since 2012 for a subset of five states: Arizona, California, Colorado, New Jersey, and New York. The analyses are divided into two size ranges: systems that are ≤10 kilowatts (kW), and systems that are 11–50 kW.

14 SOLAR ENERGY↗

Implantable photoelectronic charging (I-PEC) for medical implants

Medical implants with functionalities such as sensing, health monitoring, stimulation, diagnosis, and physiological treatment are rapidly growing. With the increasing functional sophistication and addition of modules such as data transmission, on-chip processing, and data storage, energy demand of the implantable system is also growing. Using implantable energy harvester either to recharge or ultimately replace hazardous battery is essential to provide a long-term sustainable solution. Furthermore, energy harvesting techniques using piezoelectric, thermoelectric, radio frequency power transmission, biofuel, and photoelectronic (or sometimes termed as “photovoltaic” in terms of solar light harvesting, i.e., PV) conversion, have been attempted for the implantable, but these methods are currently limited by insufficient power output, large footprint, and low efficiency. Nevertheless, the planar PV with potential of lighter weight, higher energy density, and higher efficiency, provides promising power solution for in-body medical implants. In this short review, we will discuss the potential opportunities and challenges associated with PV's for medical implants, covering materials, to devices, and to system level requirements.

60 APPLIED LIFE SCIENCES↗

Mineralogy and Thermal Properties of V-Type Asteroid 956 Elisa: Evidence for Diogenitic Material from the Spitzer IRS (5-35 Micrometers) Spectrum

We present the thermal infrared (5-35 micrometer) spectrum of 956 Elisa as measured by the Spitzer Infrared Spectrograph ("IRS"; Houck,1.R. et .11. [20041. Astrophys, 1. SuppL 154, 18-24) together with new ground-based lightcurve data and near-IR spectra. From the visible lightcurve photometry, we determine a rotation period of 16.494 +/- 0.001 h, identify the rotational phase of the Spitzer observations, and estimate the visible absolute magnitude (Hv) at that rotational phase to be 12.58 +/- 0.04. From radiometric analysis of the thermal flux spectrum, we find that at the time of observation 956 Elisa had a projected radius of 5.3 +/- 0.4 km with a visible albedo pv = 0.142+/- 0.022, significantly lower than that of the prototype V-type asteroid, 4 Vesta. (This corresponds to a radius of 5.2 +/- 0.4 km at lightcurve mean.) Analysis with the standard thermal model (STM) results in a sub-solar temperature of 292.3 +/- 2.8 K and beaming parameter eta = 1.16 +/- 0.05. Thermophysical modeling places a lower limit of 20 J m(exp -2)K(exp -1)s(exp -1/2) on the thermal inertia of the asteroid's surface layer (if the surface is very smooth) but more likely values fall between 30 and 150 J m(exp -2)K(exp -1)s(exp -1/2) depending on the sense of rotation. The emissivity spectrum, calculated by dividing the measured thermal flux spectrum by the modeled thermal continuum, exhibits mineralogically interpretable spectral features within the 9-12 micrometer reststrahlen band, the 15-16.5 micrometer Si-O-Si stretching region, and the 16-25 micrometer reststrahlen region that are consistent with pyroxene of diogenitic composition: extant diogenitic pyroxenes fall within the narrow compositional range W0(sub 2+/-1)En(sub 74+/-2)Fs(sub 24+/-1). Spectral deconvolution of the 9-12 micrometer reststrahlen features indicates that up to approximately 20% olivine may also be present, suggesting an olivine-diogenite-like mineralogy. The mid-IR spectrum is inconsistent with non-cumulate eucrite as the major component on the surface of 956 Elisa, although cumulate eucrite material may be present at abundances lower than that of the diogenite component. Analysis of new near-IR spectra of 956 Elisa with the Modified Gaussian Model (MGM; Sunshine, J,M., Pieters, C.M., Pratt, S.F.[1990]. J. Geophys. Res, 95 (May), 6955-6966) results in two pyroxene compositions: 75% magnesian low-Ca pyroxene and 25% high-Ca pyroxene. High-Ca pyroxene is not evident in the mid-IR data, but may belong to a component that is underrepresented in the mid-IR spectrum either because of its spatial distribution on the asteroid or because of its particle size. High-Ca pyroxenes that occur as exsolution lamellae may also be more evident spectrally in the NIR than in the mid-IR. In any case, we find that the mid-IR spectrum of 956 Elisa is dominated by emission from material of diogenite- like composition, which has very rarely been observed among asteroids.

Lim, Lucy F.↗

Potential Infrastructure Cost Savings at Hybrid Wind Plus Solar PV Plants

This report documents the creation of NREL's Balance of System model for Hybrid Renewable Energy Systems (HybridBOSSE). Balance of System (BOS) costs account for approximately 30% of the capital expenditure required to install a land-based wind plant, and as much as 40% of the cost of installing a solar PV plant. Hybrid Renewable Energy systems present an opportunity to combine balance of system components to achieve cost savings, and HybridBOSSE aims to provide a component-level model to determine the associated BOS costs in a hybrid renewable energy system. Prior BOS models for hybrid systems (at NREL and elsewhere) have relied on empirical curve fits of legacy industry data, limiting their utility and their predictive ability for new technology combinations and configurations, such as those found in Hybrid Plants. Hybrid plants at the utility scale have considerably more interest in the last number of years, with ever-growing capacities in the interconnection queues, and many large developers pivoting to only consider hybrid plants going forward. As these plants become a commercial reality, the need for a detailed analysis of costs in a hybrid plant to fully exploit the available cost savings grows. The tool developed and documented in this work, HybridBOSSE, provides an open-source, python-based method of assessing the costs in hybrid plants. This analysis capability unlocks greater certainty in hybrid plant costs, as well as the ability to examine scenarios of hybridization and glean combinations that offer the greatest flexibility and cost reduction.

14 SOLAR ENERGY↗

Battery Reinitialization of the Photovoltaic Module of the International Space Station

The photovoltaic (PV) module on the International Space Station (ISS) has been operating since November 2000 and supporting electric power demands of the ISS and its crew of three. The PV module contains photovoltaic arrays that convert solar energy to electrical power and an integrated equipment assembly (IEA) that houses electrical hardware and batteries for electric power regulation and storage. Each PV module contains two independent power channels for fault tolerance. Each power channel contains three batteries in parallel to meet its performance requirements and for fault tolerance. Each battery consists of 76 Ni-Hydrogen (Ni-H2) cells in series. These 76 cells are contained in two orbital replaceable units (ORU) that are connected in series. On-orbit data are monitored and trended to ensure that all hardware is operating normally. Review of on-orbit data showed that while five batteries are operating very well, one is showing signs of mismatched ORUs. The cell pressure in the two ORUs differs by an amount that exceeds the recommended range. The reason for this abnormal behavior may be that the two ORUs have different use history. An assessment was performed and it was determined that capacity of this battery would be limited by the lower pressure ORU. Steps are being taken to reduce this pressure differential before battery capacity drops to the point of affecting its ability to meet performance requirements. As a first step, a battery reinitialization procedure was developed to reduce this pressure differential. The procedure was successfully carried out on-orbit and the pressure differential was reduced to the recommended range. This paper describes the battery performance and the consequences of mismatched ORUs that make a battery. The paper also describes the reinitialization procedure, how it was performed on orbit, and battery performance after the reinitialization. On-orbit data monitoring and trending is an ongoing activity and it will continue as ISS assembly progresses.

Hajela, Gyan↗

A Method for Estimating Time-Series PV Production Loss From Solar Tracking Failures

Solar tracking system failures can dramatically reduce photovoltaic (PV) system energy output through suboptimal irradiance capture and self-shading loss. Detecting tracker failures is not always straightforward; unlike other common PV system failures like inverter outages and blown fuses which take portions of a system completely offline, tracker failures only partially reduce output power and can go unnoticed as a result. Additionally, tracker failures can take one of several forms, each with their own loss characteristics. Here we present two methods of detecting tracker failure events from time-series production data and a method for estimating the associated production loss. Compared with existing detection methods, the proposed power-based detection method showed 0-17% reductions in Type I error rate depending on weather conditions. Here, the loss model estimated production loss with low error (mean bias error = -2.3 %, root-mean-squared error = 6%) in a rudimentary validation.

14 SOLAR ENERGY↗

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗

Measuring the Stress Factors for Photovoltaic (PV) Backsheet Degradation

Back sheet failure has resulted in power loss and large-scale recall of photovoltaic modules, resulting in billions of dollars in lost revenue. The light exposure on the backside of a photovoltaic module comes primarily from reflected light which alters the distribution of natural sunlight. Because of this, modelling the backside exposure and duplicating the exposure is much more difficult than modeling the frontside exposure. This project aims to study how various back sheets and junction box materials degrade under different conditions and to develop Python code to help model and predict degradation. The stress factors for back-sheet degradation must be quantified to extrapolate accelerated stress tests to the field. Test samples were placed in the A3, A4, and A5 conditions, as defined in IEC 62788-7-2, to assess the temperature and humidity dependence of ultraviolet (UV) induced degradation. We are utilizing a custom chamber with exposure from 0.5 UV-suns to 5 UV-suns to understand the dependence of degradation on light intensity. A group of samples put in the A3 condition had glass filters with 50% UV cut-offs of 320 nm, 335 nm, and 360 nm to assess the wavelength dependence of UV degradation. All this data is necessary to assess the impact of non-standard UV light exposure. The material evaluation tests include gloss measurements, attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR), UV-visible reflectance/transmittance utilizing a Cary Ci7000 spectrophotometer, and a nano-indenter for surface hardness and modulus measurements. Alongside the experimental work, there is a computational effort using raytracing and Python open-source tools in PVDeg , PVLib, and Bifacial_Radiance. This code will create specific exposure scenarios and enable the evaluation of chamber degradation relative to field degradation. Equation 1 is a strawman equation used to model degradation on the backside of a PV module. We will create simplified code, based on the results of ray-tracing calculations, which uses a view factor approach to provide fast calculations for the most common exposure scenarios.

14 SOLAR ENERGY↗