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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spectral Rear Irradiance Testing and Modeling for Degradation and Performance of Solar Fields

This work investigates how the spectrum of irradiance incident on the rear of solar modules impacts the degradation and performance of backsheets. We model the spectral irradiance incident on the rear of modules through raytrace simulations and validate with measured field data collected from a 75kW single axis-tracked bifacial test site. A generic equation to estimate relative degradation is proposed, and we show that current acceleration factors for UV damage in chambers can be sub-estimate up to 4.5% absolute from the usually assumed 10% dosage on the rear surfaces.

bifacial performance↗
DOE OSTI2021

Dopant Diffusion Control for Improved Tandem Cells Grown by D-HVPE

GaInP top cell current-density presently limits the performance of HVPE-grown two-junction devices, in large part due to unwanted dopant diffusion. Here, we institute mitigation strategies to lower the diffusion of dopants from both the front contact and back surface field. Successful application of these strategies resulted in a short-circuit current density of 12.1 mA/cm 2 in a GaInP/GaAs cell, an improvement of 0.9 mA/cm2 over our previous best cell. The reduced Se diffusion results in a thinner unpassivated emitter, which can lead to higher series resistance. Despite the increased resistance we obtained an efficiency increase from 23.7% to 24.8%.

42 ENGINEERING↗
DOE OSTI2022

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗
DOE OSTI2022

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗
DOE OSTI2022

Fort Mojave Indian Tribe Aha Macav Power Service Renewable Energy Project

Aha Macav Power Service (AMPS), on behalf of the Fort Mojave Indian Tribe received a Department of Energy Solar grant. Partnering with Stockbridge Energy Group and the Department of Energy, AMPS was able to construct, install, test and successfully put into operation a 2.3 MW solar field. As provided in the solar data, this project has helped to offset the cost of open market purchase power needed to meet the needs of the Tribe. The estimated value of the solar energy produced in FY2021 currently is more than $294,000. Eventual expansion of the solar project is projected to create future energy independence for the Fort Mojave Indian Tribe.

14 SOLAR ENERGY↗
DOE OSTI2022

Enhanced Control, Optimization, and Integration of Distributed Energy Applications (ECO-IDEA)

With support from the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy Laboratory (NREL) partnered with Xcel Energy, Schneider Electric, Varentec, and Electric Power Research Institute (EPRI) to meet the goals of the Enabling Extreme Real-Time Grid Integration of Solar Energy (ENERGISE) program. This project developed and validated an innovative data-enhanced hierarchical control architecture that enables the efficient, reliable, resilient, and secure operation of future distribution systems with a high penetration of distributed energy resources like solar energy. The architecture enables a hybrid control approach where a centralized control layer is complemented by distributed control algorithms for solar inverters and autonomous control of grid edge devices. It is fully interoperable and includes all the cybersecurity aspects necessary for reliable and secure system operation. The hybrid approach can seamlessly integrate multiple voltage-regulation technologies, both at central and grid-edge levels, which enables reliable and efficient system operation in the face of unpredictable conditions. The overarching goal of the Eco-Idea project is to develop, validate, and deploy a unique and innovative Data-Enhanced Hierarchical Control (DEHC) architecture that comprehensively addresses the formidable challenges associated with proliferation of high penetration of distributed PV such as reverse power flows, transients from variability of PV systems, feeder load balancing, and voltage stability. These issues are exposing the weaknesses of existing grid operations and controls - including, but not limited to, lack of grid situational awareness, heuristic and slow-acting control actions, latency of control for emergency situations, and points of failure in communications. The proposed architecture will comprehensively resolve the deficiencies of current operational settings - where monitoring and control solutions proposed across industry and academia may not be interoperable and may not coexist in the same system - and will enable an efficient, reliable, resilient, and secure operation of future distribution systems with penetration of solar energy well beyond current limits. The DEHC architecture was developed and validated rigorously through hardware-in-loop simulations in the laboratory environment and deployed on the field.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

OPALCO - Decatur Island Solar and Energy Storage Project: An Assessment of Battery Technical Performance

Orcas Power & Light Cooperative (OPALCO) is a member-owned, nonprofit cooperative utility that provides energy services to approximately 11,200 customers across 20 islands in San Juan County, Washington. OPALCO’s mostly hydroelectric power is generated by Bonneville Power Administration and delivered to the islands by submarine cables. In 2016, as part of the second round of funding from the Washington state Clean Energy Fund, OPALCO received a $1 million matching grant to support a project that deployed a 504-kW LG community photovoltaic (PV) system in combination with a 1 MW/2 MWh lithium-iron-phosphate battery energy storage system (BESS) on Decatur Island, Washington. The Decatur Island Substation is essential to ensuring reliable energy for the residents of the San Juan Islands as it is the point of interconnection with the mainland transmission system. The BESS, in combination with the community solar array, will deliver an innovative method to both defer the costly upgrade of the transmission system and allow for other high-value applications intended to benefit the utility and its customers. In 2018, Pacific Northwest National Laboratory (PNNL) completed a preliminary economic assessment for several identified use cases in collaboration with OPALCO. Between August 2021 and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (a) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline) and are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (b) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with OPALCO. Four use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) outage mitigation, and 4) transmission deferral. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help OPALCO understand the performance of the Decatur Island BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗
DOE OSTI2023

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↗
DOE OSTI2023

PV encapsulant formulations and stress test conditions influence dominant degradation mechanisms

Polyethylene-based poly(ethylene-co-vinyl acetate) (EVA), polyolefin elastomer (POE), and thermoplastic polyolefin (TPO) are common polymer candidates for photovoltaic (PV) module encapsulants. The choice of encapsulant must be carefully considered in novel module designs, such as bifacial glass/glass laminates, to limit performance degradation through loss of optical transmittance, mechanical integrity, and corrosion - as well as potential-induced degradation. Encapsulant quality and resilience against environmental stressors are readily influenced by the additives in the encapsulant formulation. Here, we show that, the changes in optical transmittance after UV aging result from the discoloration caused by interactions between additives, and optical scattering from changes in the polymer crystal structure. We observed competing cross-linking and chain scission mechanisms, with their kinetics influenced by the presence of oxygen and elevated temperatures. Increasing chamber temperatures from 55 °C to 85 °C during the UV stress test amplified encapsulant discoloration and promoted polymer cross-linking, causing severe, irreversible damage that remains to be proven field relevant. Damp heat aging was found to be insufficient to produce significant encapsulant degradation; however, combining stress tests sequentially allowed detection of further degradation beyond the limitations of the damp heat test alone. Appropriate degradation screening methods are necessary to uncover potential encapsulant weaknesses.

14 SOLAR ENERGY↗
DOE OSTI2025

Comparing Outdoor to Indoor Performance for Bifacial Modules Affected by Polarization-Type Potential-Induced Degradation

Bifacial photovoltaic (PV) modules have the advantage of using light reflected off of the ground to contribute to power production. Predicting the energy gain is challenging and requires complex models to do so accurately. Often, module degradation over time is neglected in models for the sake of simplicity or is underestimated. Comparing outdoor and indoor current–voltage (I–V) performance for bifacial modules is more challenging than for monofacial modules, as there are additional variables to consider such as rear albedo non-uniformity, cell mismatch, and their effects on temperature. This challenge is compounded when heterogeneous degradation modes occur, such as polarization-type potential-induced degradation (PID-p). To examine the effects of PID-p on I–V predictions using an empirical data-driven approach, 16 bifacial PERC modules are installed outdoors on racks with different albedo conditions. A subset is exposed to high-voltage biases of −1500 V or +1500 V. Outdoor data are traced at irradiance ranges of 150–250 W/m 2 , 500–600 W/m 2 , and 900–1000 W/m 2 . These curves are corrected using control module temperature, wire resistivity, and module resistance measured indoors. We examine several methods to transform indoor I–V curves to accurately, and more simply than existing methods, approximate outdoor performance for bifacial modules without and with varying levels of PID-p degradation. This way, bifacial performance modeling can be more accessible and informed by fielded, degraded modules. Distributions of percent errors between indoor and outdoor performance parameters and Mean Absolute Percent Errors (MAPEs) are used to assess method quality. Results including low-irradiance data (150–250 W/m 2 ) are discussed but are filtered for quantifying method quality as these data introduce substantial errors. The method with the most optimal tradeoff between low MAPE and analysis simplicity involves measuring the front side of a module indoors at an irradiance equal to plane-of-array irradiance plus the product of module bifaciality and albedo irradiance. This method gives MAPE values of 1–6.5% for non-degraded and 1.6–5.9% for PID-p degraded module performance.

14 SOLAR ENERGY↗
DOE OSTI2023

Innovation in complementary energy technologies from renewable energy policies

Complementary renewable technologies support renewable energy use as they can help balance the intermittency of solar and wind generation. Previous research has shown that environmental policies directly targeting renewable energy can drive innovation in solar PV and wind technology. This study explores the impact of renewable policies on innovation in complementary renewable technology that assists with integration, including combustion with mitigation potential, efficient power transmission or distribution, and enabling technologies. We use negative binomial models and a panel of 25 OECD countries from 1997 to 2015 to evaluate these relationships. We are not able to find evidence that renewable policies incentivize innovation in complementary combustion or transmission and distribution technologies, and only limited evidence that demand-pull instruments are associated with increased innovation in smart grid technology. Technology-push policies, such as public research and development funds for renewable energy, have had limited impact on grid-supporting energy storage innovation. Our findings suggest that policymakers wishing to accelerate these complementary technologies need to go beyond policies targeting renewable energy in order to drive innovation in complementary fields.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Quantifying Bulk and Surface Recombination in CdTe Solar Cells Using Time-Resolved Terahertz Spectroscopy

Understanding the nature of recombination mechanisms is essential for higher power conversion efficiency in photovoltaic (PV) devices. Here we use a combination of time-resolved terahertz spectroscopy and numerical modeling to determine the bulk Shockley-Read-Hall lifetime and interface and back surface recombination velocities in CdTe thin film stacks. Furthermore, the measurement was facilitated by fabricating wire-grid device structures using conventional laser scribing. Evaluation of a glass/FTO/SnO2/CdS/CdTe stack treated with CdCl2 allowed separation of the CdTe absorber bulk lifetime, 1.6 ns, from the back surface recombination velocity, ~6x10 4 cm/s, and indicated that CdTe/CdS interface recombination velocity had no significant impact on carrier dynamics.

14 SOLAR ENERGY↗
DOE OSTI2021

Chemical Passivation of Crystalline Si by Al 2 O 3 Deposited Using Atomic Layer Deposition: Implications for Solar Cells

The atomistic-level mechanism for the chemical passivation of the monocrystalline Si (c-Si) surface with thermally annealed Al 2 O 3 was studied using in situ infrared spectroscopy and photoconductance decay measurements. Al 2 O 3 was deposited on high-lifetime, float-zone c-Si substrates using atomic layer deposition (ALD) from trimethylaluminum (TMA), and H 2 O or O 3 . Surface-sensitive attenuated total reflection Fourier transform infrared spectroscopy was used to monitor the c-Si/Al 2 O 3 interface, as well as the bulk of the Al 2 O 3 film during the entire process. Our results show that some surface Si–H bonds are preserved after the ALD of Al 2 O 3 on H-terminated Si. During the annealing step at 400 °C, restructuring occurs at the c-Si/Al 2 O 3 interface to form interfacial SiO x . Isotope labeling was used to differentiate interfacial SiD bonds on the c-Si surface from H incorporated in Al 2 O 3 . Within the sensitivity of our infrared setup (~10 13 cm –2 ), we did not observe any net migration of atomic H or D from Al 2 O 3 to the c-Si/Al 2 O 3 interface. To isolate the effects of chemical and field-effect passivation of Al 2 O 3 thin films, we carried out surface passivation studies on c-Si/SiO 2 /Al 2 O 3 stacks. We also annealed these stacks in different atmospheres to test the influence of annealing atmospheres on the chemical passivation of c-Si by Al 2 O 3 and observed that O 2 -containing atmosphere led to the best surface chemical passivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Data-Driven Global Sensitivity Analysis Framework for Three-Phase Distribution System with PVs

Global sensitivity analysis (GSA) of distribution systems with respect to stochastic PV and load variations plays an important role in designing optimal voltage control schemes. This paper proposes a data-driven framework for GSA of distribution systems. In particular, two representative surrogate modeling-based approaches are developed, including the traditional Gaussian process-based and the analysis of variance (ANOVA) kernel ones. The key idea is to develop a surrogate model that captures the hidden global relationship between voltage and real and reactive power injections from the historical data. With the surrogate model, the Sobol indices can be conveniently calculated through either the sampling-based method or the analytical method to assess the global sensitivity of voltage to variations of PV and load power injections. The sampling-based method approximates the Sobol indices using Monte Carlo simulations while the analytical method calculates them by resorting to the ANOVA expansion framework. Comparison results with other model-based GSA methods on the unbalanced three-phase IEEE 37-bus and 123-bus distribution systems show that the proposed framework can achieve much higher computational efficiency with negligible loss of accuracy. The results on a real 240-node distribution system using actual smart meter data further validate the feasibility and scalability of the proposed framework.

14 SOLAR ENERGY↗
NASA NTRS1993

The stability of hibonite and other aluminous phases in silicate melts: Implications for the origin of hibonite-bearing inclusions

Phase fields in which hibonite (Hib) and silicate melt coexist with spinel (Sp), CaAl4O7 (CA2), gehlenitic melilite (Mel), anorthite (An), or corundum (Cor) in the system CaO-MgO-Al203-SiO2-TiO2 (CMAST) were determined and activity models developed for Mel and Hib solid solutions. Experimentally determined partition coefficients for Ti between Hib and coexisting melt, D sub t, vary from 0.8 to 2.1 and generally decrease with increasing TiO2 content in the liquid (L). Based on Ti partioning between Hib and melt, bulk inclusion compositions and Hib-saturated liquid use phase diagrams, the Hib in Fluffy Type A inclusions (FTA's) from Allende and at least some of the Hib from Hib-rich inclusions is relict; much of the Hib from Hib-glass spherules probably crystallized from a melt under nonequilibrium conditions. Bulk compositions for all of these Ca-Al-rich inclusions (CAI's) are consistent with an origin as Mel + Hib + Sp + perovskite (Pv) proto-inclusions in which Mel was partially altered. In some cases, the proto-inclusion was partially or completely melted with vaporization occurring over a period of time sufficient to remove any Na introduced by the alteration process but frequently insufficient to dissolve all of the original hibonite. If equilibration temperatures based on Hib-bearing CAI's reflect condensation in a cooling gas of solar composition, then Hib + Cor condensed at approximately 1260 C (referenced to 10 exp -3 atm) and Hib + Sp + Mel at approximately 1215 +/- 10 C. Simple thermochemical models for the substitution of trace elements into the Ca-site of meteoritic Hib suggest that virtually all Eu is divalent in early condensate Hibs but that Eu(2+)/Eu(3+) decreases by a factor of 20 or more during the course of condensation, primarily because the ratio is proportional to the partial pressure of Al, which decreases dramatically as aluminous phases condense. The relative sizes of Eu and Yb anomalies in meteoritic Hibs and CAI's may be influenced by this effect.

Beckett, J. R.↗
DOE OSTI2025

Comprehensive Evaluation of Agrivoltaics Research: Breadth, Depth, and Insights for Future Research

Agrivoltaics integrates agricultural production with solar energy generation to address challenges related to land use, food security, and renewable energy development. This study provides the most comprehensive evaluation to date of global agrivoltaic research, aiming to classify the literature, identify strengths and gaps, and guide future work. We systematically screened over 3000 English-language publications through 2023 for relevant agrivoltaic publications. A total of 670 studies were categorized in the InSPIRE Data Portal across five agrivoltaic activities and multiple hierarchical themes, including physical, biological, technological, social, and crosscutting domains. We found that research was concentrated on crop production, microclimate dynamics, and PV performance, with gaps in areas like human health, wildlife, policy, and standardized methodologies. Although the U.S. emphasizes animal grazing and habitat-based systems in practice, most U.S.-based studies focused disproportionately on crop production. The analysis revealed uneven geographic and topical representation and highlighted a lack of integrated, interdisciplinary approaches. This study concludes that while agrivoltaic research has grown rapidly, more coordinated efforts could support standardized data collection, address overlooked ecological and social impacts, and align research focus with real-world system implementation, ultimately improving the scalability and successful deployment of agrivoltaic systems.

14 SOLAR ENERGY↗
NASA NTRS1999

Constructing Synoptic Maps of Stratospheric Column Ozone from HALOE, SAGE and Balloonsonde Data Using Potential Vorticity Isentropic Coordinate Transformations

In this study we utilize potential vorticity - isentropic (PVI) coordinate transformations as a means of combining ozone data from different sources to construct daily, synthetic three-dimensional ozone fields. This methodology has been used successfully to reconstruct ozone maps in particular regions from aircraft data over the period of the aircraft campaign. We expand this method to create high-resolution daily global maps of profile ozone data, particularly in the lower stratosphere, where high-resolution ozone data are sparse. Ozone climatologies in PVI-space are constructed from satellite-based SAGE II and UARS/HALOE data, both of which-use solar occultation techniques to make high vertical resolution ozone profile measurements, but with low spatial resolution. A climatology from ground-based balloonsonde data is also created. The climatologies are used to establish the relationship between ozone and dynamical variability, which is defined by the potential vorticity (in the form of equivalent latitude) and potential temperature fields. Once a PVI climatology has been created from data taken by one or more instruments, high-resolution daily profile ozone field estimates are constructed based solely on the PVI fields, which are available on a daily basis from NCEP analysis. These profile ozone maps could be used for a variety of applications, including use in conjunction with total ozone maps to create a daily tropospheric ozone product, as input to forecast models, or as a tool for validating independent ozone measurements when correlative data are not available. This technique is limited to regions where the ozone is a long-term tracer and the flow is adiabatic. We evaluate the internal consistency of the technique by transforming the ozone back to physical space and comparing to the original profiles. Biases in the long-term average of the differences are used to identify regions where the technique is consistently introducing errors. Initial results show the technique is useful in the lower stratosphere at most latitudes throughout the year,and in the winter hemisphere in the middle stratosphere. The results are problematic in the summer hemisphere middle stratosphere due to increased ozone photochemistry and weak PV gradients. Alternate techniques in these regions will be discussed. An additional limitation is the quality and resolution of the meteorological data.

Hollandsworth, Stacey M.↗
DOE OSTI2024

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗