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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Kaste, Joshua A. M.↗
DOE OSTI2020

Selectivity Control in Catalytic Reductive Amination of Furfural to Furfurylamine on Supported Catalysts

Abstract Amines are widely used in the manufacture of pharmaceuticals, agricultural chemicals, polymers, and surfactants. However, amines are mostly produced via petrochemical means, which motivates amine production from renewable resources, such as biomass. However, biomass compounds present added challenges involving poor carbon balances. We show that furfural reacts homogeneously with ammonia to produce reactive primary imines, which form large side products and leads to significant carbon losses. The carbon balance is improved by mixing furfural with furfurylamine prior to reaction to form a secondary imine for use as the reaction substrate. While controlling the primary to secondary amine selectivity is a common challenge in reductive amination, supported metal catalysts, including Ni/SiO 2 , Co/SiO 2 , and Ru/SiO 2 optimize the primary amine yield to 90 to 94 % by using the secondary imine as the reaction substrate. A qualitative correlation between the primary to secondary amine selectivity with the nitrogen binding energy of metals is identified.

Gould, Nicholas S.↗
DOE OSTI2024

Energy‐Water Asynchrony Principally Determines Water Available for Runoff From Snowmelt in Continental Montane Forests

ABSTRACT Changes in the volume, rate, and timing of the snowmelt water pulse have profound implications for seasonal soil moisture, evapotranspiration (ET), groundwater recharge, and downstream water availability, especially in the context of climate change. Here, we present an empirical analysis of water available for runoff using five eddy covariance towers located in continental montane forests across a regional gradient of snow depth, precipitation seasonality, and aridity. We specifically investigated how energy‐water asynchrony (i.e., snowmelt timing relative to atmospheric demand), surface water input intensity (rain and snowmelt), and observed winter ET (winter AET) impact multiple water balance metrics that determine water available for runoff (WAfR). Overall, we found that WAfR had the strongest relationship with energy‐water asynchrony (adjusted r 2 = 0.52) and that winter AET was correlated to total water year evapotranspiration but not to other water balance metrics. Stepwise regression analysis demonstrated that none of the tested mechanisms were strongly related to the Budyko‐type runoff anomaly (highest adjusted r 2 = 0.21). We, therefore, conclude that WAfR from continental montane forests is most sensitive to the degree of energy‐water asynchrony that occurs. The results of this empirical study identify the physical mechanisms driving variability of WAfR in continental montane forests and are thus broadly relevant to the hydrologic management and modelling communities.

Webb, Ryan William↗
DOE OSTI2025

Phosphorus budgets of intensively managed row crops at a long–term agroecosystem research site in the upper US Midwest

Phosphorus (P) budgets for cropping systems provide insights for keeping soil P at optimal levels for crops while avoiding excess inputs. We quantified 12 years of P inputs (fertilizer and atmospheric deposition) and outputs (harvest and leaching losses) for replicated maize (Zea mays L.)—soybean (Glycine max L.)—wheat (Triticum aestivum) crop rotations under conventional, no-till, reduced input, and biologically based (organic without compost or manure) management systems at the Kellogg Biological Station LTAR site in southwest Michigan. Conventional, no-till, and reduced input systems were fertilized between 13 and 50 kg P ha –1 depending on year. Soil test phosphorus (STP) was measured at 0- to 25-cm depth every autumn. Leached P was measured as dissolved P in the soil solution sampled beneath the rooting depth and combined with modeled percolation. Fertilization and harvest were the predominant P fluxes in the fertilized systems, whereas only harvest dominated P flux in the unfertilized organic system. Leaching losses were minor terms in the budgets, but leachate concentrations were nevertheless close to the range of concern for downstream eutrophication. Over the 12-year study period, the organic system exhibited a negative P balance (–82.0 kg P ha –1 ), coinciding with suboptimal STP levels, suggesting a need for P supplementation. In contrast, the fertilized systems showed positive P balances (mean: 70.1 kg P ha –1 ) with STP levels well above agronomic optima. Results underscore the importance of tailored P management strategies to sustain crop productivity while mitigating environmental impacts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Seismic savanna: machine learning for classifying wildlife and behaviours using ground‐based vibration field recordings

Abstract We develop a machine learning approach to detect and discriminate elephants from other species, and to recognise important behaviours such as running and rumbling, based only on seismic data generated by the animals. We demonstrate our approach using data acquired in the Kenyan savanna, consisting of 8000 h seismic recordings and 250 k camera trap pictures. Our classifiers, different convolutional neural networks trained on seismograms and spectrograms, achieved 80%–90% balanced accuracy in detecting elephants up to 100 m away, and over 90% balanced accuracy in recognising running and rumbling behaviours from the seismic data. We release the dataset used in this study: SeisSavanna represents a unique collection of seismic signals with the associated wildlife species and behaviour. Our results suggest that seismic data offer substantial benefits for monitoring wildlife, and we propose to further develop our methods using dense arrays that could result in a seismic shift for wildlife monitoring.

Szenicer, Alexandre↗
DOE OSTI2021

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Evaluating the contribution of plant metabolic pathways in the light to the ATP:NADPH demand using a meta-analysis of isotopically non-stationary metabolic flux analyses

Abstract Balancing the ATP: NADPH demand from plant metabolism with supply from photosynthesis is essential for preventing photodamage and operating efficiently, so understanding its drivers is important for integrating metabolism with the light reactions of photosynthesis and for bioengineering efforts that may radically change this demand. It is often assumed that the C3 cycle and photorespiration consume the largest amount of ATP and reductant in illuminated leaves and as a result mostly determine the ATP: NADPH demand. However, the quantitative extent to which other energy consuming metabolic processes contribute in large ways to overall ATP: NADPH demand remains unknown. Here, we used the metabolic flux networks of numerous recently published isotopically non-stationary metabolic flux analyses (INST-MFA) to evaluate flux through the C3 cycle, photorespiration, the oxidative pentose phosphate pathway, the tricarboxylic acid cycle, and starch/sucrose synthesis and characterize broad trends in the demand of energy across different pathways and compartments as well as in the overall ATP:NADPH demand. These data sets include a variety of species including Arabidopsis thaliana , Nicotiana tabacum , and Camelina sativa as well as varying environmental factors including high/low light, day length, and photorespiratory levels. Examining these datasets in aggregate reveals that ultimately the bulk of the energy flux occurred in the C3 cycle and photorespiration, however, the energy demand from these pathways did not determine the ATP: NADPH demand alone. Instead, a notable contribution was revealed from starch and sucrose synthesis which might counterbalance photorespiratory demand and result in fewer adjustments in mechanisms which balance the ATP deficit.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

High dimensional binary classification under label shift: phase transition and regularization

Label Shift has been widely believed to be harmful to the generalization performance of machine learning models. Researchers have proposed many approaches to mitigate the impact of the label shift, e.g., balancing the training data. However, these methods often consider the underparametrized regime, where the sample size is much larger than the data dimension. The research under the overparametrized regime is very limited. Here, to bridge this gap, we propose a new asymptotic analysis of the Fisher Linear Discriminant classifier for binary classification with label shift. Specifically, we prove that there exists a phase transition phenomenon: Under certain overparametrized regime, the classifier trained using imbalanced data outperforms the counterpart with reduced balanced data. Moreover, we investigate the impact of regularization to the label shift: The aforementioned phase transition vanishes as the regularization becomes strong.

binary classification↗
DOE OSTI2024

Warming but not elevated CO 2 depletes soil organic carbon in a temperate rice paddy

In this article, global climate change has the potential to alter soil organic carbon (SOC) stocks in rice paddies, because increases in temperature and atmospheric carbon dioxide concentration ([CO 2 ]) both influence the primary input (i.e., net primary production, NPP) and output (i.e. heterotrophic respiration) of carbon (C). We used two types of open-top chambers representing present conditions (+0°C, +0 ppm CO 2 ) and projected climate change conditions (+2°C, +200 ppm CO 2 ) to investigate the net effect of climate change on SOC stock in rice paddy. Additional chambers with elevated temperature only (+2°C, +0 ppm CO 2 ) allowed us to quantify the individual effects of temperature and [CO 2 ]. We calculated changes in SOC stock using net ecosystem C balance (NECB) analysis (i.e., the balance between C inputs and outputs). Compared to present conditions, projected climate change did not change grain yield due to a trade-off between the effects of warming and [CO 2 ] on grain yield components. NPP during the fallow season significantly decreased under combined warming and CO 2 , as the impact of warming outweighed that of elevated [CO 2 ]. However, rice NPP remained unchanged during the cropping season. Warming plus elevated CO 2 increased SOC mineralization by 157–429 %, particularly through warming-induced soil CO 2 emission during the fallow season. Consequently, climate change conditions decreased (119–271 %) NECB values compared to present conditions, primarily through the response to warming. Our findings demonstrate that rice paddies represent positive feedback on climate change, because accelerated C release from warmed soils will override C gains from NPP under elevated CO 2 . Reducing SOC depletion in rice paddy agriculture under a changing climate therefore requires conservative soil management practices during the fallow season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Land cover change-induced decline in terrestrial gross primary production over the conterminous United States from 2001 to 2016

As one of the most dynamic aspects of global environmental change, land cover change (LCC) has a profound impact on terrestrial carbon sequestration. However, LCC-induced carbon fluxes are still the most uncertain terms in global and regional carbon budgets. Ecosystem gross primary production (GPP) is the total carbon uptake by vegetation through photosynthesis, serving as a major control on ecosystem function and land carbon balance during and after the modification of the land surface. However, accurately capturing LCC-induced GPP changes requires both high-quality land cover data and controlling for variation driven by other environmental factors such as climate. In this study, we comprehensively examined the effects of LCC on annual GPP trends over the conterminous United States (CONUS) from 2001 to 2016 using the USGS National Land Cover Database, a remote sensing-driven ecosystem model, and the Google Earth Engine cloud computing platform. We designed a series of model experiments to identify LCC effects on GPP by controlling climate effects. During the study period, LCC exerted a strong negative effect on total GPP across the CONUS ([-2.2, -1.8] Tg C yr -2 ), while climate had smaller positive effects ([0.17, 0. 92] Tg C yr -2 ). The LCC-induced reduction of GPP was mainly caused by net forest loss ([-1.98, -1.39] Tg C yr -2 ) and urban expansion ([-2.03, -1.92] Tg C yr -2 ), but was partially offset by increases in crop area ([+0.66, +0.79] Tg C yr -2 ). Ensemble simulations from TRENDY did not capture the strong negative LCC influences on GPP, likely due to limitations of the adopted land use/cover data. Overall, our study provides a novel perspective on LCC-induced GPP changes, which could help to improve our understanding of ecosystem function changes and constrain the estimation of land carbon balance in the context of anthropogenic activity and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating ecosystem water use efficiency and recovery dynamics during flash droughts: insights from observations and model simulations

Flash droughts (FD), rapidly emerging in a warming future, disrupt ecosystems, agriculture, and water security. Ecosystem water use efficiency (WUE), the ratio of gross primary production (GPP) to actual evapotranspiration (AET), balances carbon assimilation and water loss. FD rapidly disrupts this balance, making WUE critical for assessing plant stress and recovery. Here, this study investigates the dynamics of landscape-scale WUE, and the components of GPP and AET under FD utilizing both observed data from the Missouri Ozark AmeriFlux site (US-MOz) and version 2 of the U.S. Department of Energy’s Earth, Energy, Exascale System Model (E3SM) Land Model (ELMv2). Observations and simulations reveal GPP as dominant for WUE during earlier FD events (2005, 2007, 2012), shifting to AET in recent events (2014, 2018). This agreement indicates that the ELM can capture the shifting dynamics of GPP and AET in regulating WUE under FD conditions. However, the ELM systematically underestimates both GPP and AET and does so in a manner that does not preserve their ratio. As a result, WUE is also underestimated, suggesting that GPP is more strongly underestimated than AET. Furthermore, the ELM also underestimates the speed of GPP recovery, producing an artificially prolonged GPP recovery time following FD events. Observed environmental drivers such as vapor pressure deficit (VPD), soil moisture (SM), and predawn leaf water potential (PLWP) effectively predict WUE, but ELM primarily highlights SM, underestimating VPD’s role. This study demonstrates that relying solely on soil moisture fails to capture the rapid hydraulic recovery observed in PLWP, underscoring the necessity of integrating plant hydraulics into land surface models to improve flash drought predictability.

Evapotranspiration↗
DOE OSTI2022

Catalyst design to direct high-octane gasoline fuel properties for improved engine efficiency

The paraffin-to-olefin (P/O) ratio in gasoline fuel is a critical metric affecting fuel properties and engine efficiency. In the conversion of dimethyl ether (DME) to high-octane hydrocarbons over BEA zeolite catalysts, the P/O ratio can be controlled through catalyst design. Here, we report bimetallic catalysts that balance the net hydrogenation and dehydrogenation activity during DME homologation. The Cu-Zn/BEA catalyst exhibited greater relative dehydrogenation activity attributed to higher ionic site density, resulting in a lower P/O ratio (6.6) versus the benchmark Cu/BEA (9.4). The Cu-Ni/BEA catalyst exhibited increased hydrogenation due to reduced Ni species, resulting in a higher P/O ratio (19). The product fuel properties were estimated with an efficiency merit function and compared against finished gasolines and a typical alkylate blendstock. Merit values for the hydrocarbon product from all three BEA catalysts exceeded those of the comparison fuels (0–5.3), with the product from Cu-Zn/BEA exhibiting the highest merit value (9.7).

Catalyst design↗
DOE OSTI2024

Mechanisms and site requirements for NO and NH 3 oxidation on Cu/SSZ-13

Two series of Cu/SSZ-13 catalysts were synthesized via aqueous solution and solid-state ion exchange using SSZ-13 supports of varying Si/Al ratios. The isolated and multinuclear Cu content of these catalysts were determined by H 2 temperature programmed reduction (H 2 -TPR). Multinuclear Cu in these catalysts, including in situ Cu- dimers formed from ZCu II OH coupling and permanent CuO clusters, are active species for dry NO oxidation. NH 3 oxidation on these catalysts follows an internal SCR (i-SCR) mechanism, i.e., a portion of NH 3 is first oxidized to NO, then NO is selectively reduced by the remaining NH 3 to N 2 . NH 3 oxidation displays distinct kinetic behavior below ~300 °C and above ~400 °C. At low temperature the results indicate that NH 3 -solvated mobile Cu-ions are the active centers. CuO clusters, when present, also contribute to the low temperature activity by catalyzing NH 3 oxidation to NO. At high temperature, in situ Cu-dimers and CuO clusters catalyze NH 3 oxidation to NO, and isolated Cu-ions catalyze SCR to realize the cascade turnovers. For both NO and NH 3 oxidation, Cu-dimers balanced by framework charges of close proximity appear to be more active than Cu-dimers balanced by distant framework charges. However, the former Cu-dimers are less stable than the latter and tend to split into monomers in the presence of vicinal Brønsted acid sites. Via density functional theory (DFT) calculations, the i-SCR mechanism for low temperature NH 3 oxidation, i.e., the energetic favorability for the involvement of the NO intermediate, is justified. Furthermore, the DFT results also agree with experimental data that the formation of Cu-dimers from ZCu II OH dimerization is essential for NH 3 oxidation at high temperature.

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

Timing Value of Marine Renewable Energy Resources for Potential Grid Applications

In this paper, the applicability of marine renewable energy for potential grid applications is presented. We show that many of the unique value streams from marine-based electricity generation stem from their inherent temporal characteristics, especially when compared to wind and solar. Specifically, in this work, we evaluate the timing value for three types of marine energy resources - (a) tidal (b) wave and (c) ocean currents. Firstly, through a suite of novel metrics such as resource availability, persistence and versatility, we evaluate the temporal value characteristics of these resources. Secondly, through a more grid-oriented numerical study, we comment on the potential ramifications of those temporal characteristics in context of energy balancing and effective load carrying capability, for one marine-based resource i.e. wave. Subsequently, we further our understanding of the relative advantages which may be leveraged by operating wave-based generation resources in tandem with more established renewable choices, such as solar and wind. Our results indicate that compared to wind and solar, marine energy resources are consistently more available and persistent on an hourly level, throughout an entire year of operation. In addition to this, wave resources are also seen to reduce both the magnitudes and the degree of volatility in balancing requirements within the power system. Our work not only focuses on sites specific to the Unites States (US), but also includes a parallel study for a location in Great Britain (GB). Results are found to be consistent for sites in both the US and GB, implying that the grid benefits discussed in this work could apply to a number of locations globally.

Bhattacharya, Saptarshi↗
DOE OSTI2022

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Temporal complementarity of marine renewables with wind and solar generation: Implications for GB system benefits

Wave and tidal energy have the potential to provide benefits to power systems with high proportions of stochastic renewable generation. This is particularly applicable with wind and solar photovoltaics, as the offsetting of these renewable resources results in more reliable renewable generation. This study utilises ten metrics to quantify the temporal complementarity and supply-demand balancing requirements of the energy mix in Great Britain, to investigate the potential magnitude of these system benefits. Wave and tidal generation profiles are created using historical resource data and hydrodynamic models. The results show that the inclusion of wave and tidal generation creates a renewable energy mix which is more available under multiple conditions: throughout a year of operation; at times of peak demand; for multiple consecutive hourly time periods; and at times when wind and solar generation are not available. Three regional case studies also show that the inclusion of marine energy allows for improved regional supply-demand matching, reducing instances of energy shortage and excess and potentially relieving transmission congestion at particularly constrained locations within GB. Finally, the implications of these findings are discussed in terms of GB wholesale market operation, system balancing and system security.

16 TIDAL AND WAVE POWER↗