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At least 1,657 records · Page 92

MULTI-FIDELITY MODELING AND UNCERTAINTY QUANTIFICATION OF INVERTER BASED RESOURCES IN INTEGRATED T&D SYSTEMS

Uncertainty quantification plays a pivotal role in improving the accuracy and reliability of inverter operation within modern power systems that are increasingly dominated by inverter-based resources (IBRs). IBRs, especially those operating under grid forming (GFM) control, rely heavily on a complex set of control parameters and system measurements to maintain voltage, frequency, and power balance. Traditional deterministic modeling approaches often fail to capture these parameter deviations, potentially resulting in suboptimal control actions, reduced system stability, or even instability under high penetration of IBRs. In this paper, we demonstrate the application of model calibration and uncertainty quantification (UQ) principles to an integrated transmission and distribution (T&D) model involving a GFM converter and provide a framework for prioritizing control improvements, guiding robust design, and informing adaptive strategies that can accommodate real-time variability in system conditions. The proposed approach could be valuable in enhancing the robustness of current and future power systems under increased IBR penetrations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deep Reinforcement Learning based Model-free On-line Dynamic Multi-Microgrid Formation to Enhance Resilience

Multi-microgrid formation (MMGF) is a promising solution for enhancing power system resilience. This paper proposes a new deep reinforcement learning (RL) based model-free on-line dynamic MMGF scheme. Additionally, the dynamic MMGF problem is formulated as a Markov decision process, and a complete deep RL framework is specially designed for the topologytransformable micro-grids. In order to reduce the large action space caused by flexible switch operations, a topology transformation method is proposed and an action-decoupling Q-value is applied. Then, a convolutional neural network (CNN) based multi-buffer double deep Q-network (CM-DDQN) is developed to further improve the learning ability of the original DQN method. The proposed deep RL method provides real-time computing to support the on-line dynamic MMGF scheme, and the scheme handles a long-term resilience enhancement problem using an adaptive on-line MMGF to defend changeable conditions. The effectiveness of the proposed method is validated using a 7-bus system and the IEEE 123-bus system. The results show strong learning ability, timely response for varying system conditions and convincing resilience enhancement.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MPCPy: An Open-Source Software Platform for Model Predictive Control in Buildings

Within the last decade, needs for building control systems that reduce cost, energy, or peak demand, and that facilitate building-grid integration, district-energy system optimization, and occupant interaction, while maintaining thermal comfort and indoor air quality, have come about. Current PID and schedule-based control systems are not capable of fulfilling these needs, while Model Predictive Control (MPC) could. Despite the critical role MPC-enabled buildings can play in future energy infrastructures, widespread adoption of MPC within the building industry has yet to occur. To address barriers associated with system setup and configuration, this paper introduces an open-source software platform that emphasizes use of self-tuning adaptive models, usability by non-experts of MPC, and a flexible architecture that enables application across projects.

Blum, David↗

MFIX-Exa: Performance prediction of multiphase energy conversion devices

MFIX-Exa targets the high-fidelity CFD-DEM model in which particles are unresolved by the fluid grid (typically using a fluid mesh approximately twice the particle diameter) but discrete particle dynamics including collisions are resolved with a simple linear-spring dashpot model. The fluid field is solved with a modern low Mach number formation of a cell-centered, nodal-pressure approximate projection method using a Godunov scheme . Physics capabilities include: complex geometries via embedded boundaries (EBs), open and closed system ideal gas equations of state, species transport and heterogeneous chemi- cal reactions. MFIX-Exa is built on the AMReX software framework, the ECP Block-Structured Adaptive Mesh Refinement (AMR) Co-Design Center, which allows the code to be portable and performant.Further integration into the ECP ecosystem includes HYPRE linear solvers and Ascent for in situ visualization. Current project efforts focus on scaling up realistic simulations to the KPP of the challenge problem: NETs 50kW chemical looping reactor, shakedown and scaling on JSLE and OLCF TDS systems and reaching for any remaining performance improvements.

Musser, Jordan↗

Evaluation of Global Climate Models for Use in Energy Analysis

The interplay between energy, climate, and weather is becoming more complex due to increasing contributions of renewable energy generation, energy storage, electrified end uses, and the increasing frequency of extreme weather events. Energy system analyses commonly rely on meteorological inputs to estimate renewable energy generation and energy demand; however, these inputs rarely represent the estimated impacts of future climate change. Climate models and publicly available climate change datasets can be used for this purpose, but the selection of inputs from the myriad of available models and datasets is a nuanced and subjective process. In this work, we assess datasets from various global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We present evaluations of their skills with respect to the historical climate and comparisons of their future projections of climate change for two climate change scenarios. We present the results for different climatic and energy system regions and include interactive figures in the accompanying software repository. Previous work has presented similar GCM evaluations, but none have presented variables and metrics specifically intended for comprehensive energy systems analysis including impacts on energy demand, thermal cooling, hydropower, water availability, solar energy generation, and wind energy generation. We focus on GCM output meteorological variables that directly affect these energy system components including the representation of extreme values that can drive grid resilience events. The objective of this work is not to recommend the best climate model and dataset for a given analysis, but instead to provide a reference to facilitate the selection of climate models and scenarios in subsequent work.

14 SOLAR ENERGY↗

Geothermal Play Fairway Analysis, Part 2: GIS methodology

Play Fairway Analysis (PFA) in geothermal exploration originates from a systematic methodology developed within the petroleum industry and is based on a geologic, geophysical, and hydrologic framework of identified geothermal systems. We tailored this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region, but it can be adapted to other geothermal resource settings. We adapted the PFA approach to geothermal resource exploration by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building a code-based ‘processing model’ to process results. A geographic information system was used to compile a range of different data types, which we refer to as elements (e.g., faults, vents, heat flow, etc.), with distinct characteristics and measures of confidence. Discontinuous discrete data (points, lines, or polygons) for each element were transformed into continuous interpretive 2D grid surfaces called evidence layers. Because different data types have varying uncertainties, most evidence layers have an accompanying confidence layer which reflects spatial variations in these uncertainties. Risk layers, as defined here, are the product of evidence and confidence layers, and are the building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal, using a weighted sum for permeability and heat, but a different approach with seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map, using a modified weighted sum, for results that reveal favorable areas for geothermal exploration. Additional maps are also presented that do not mix contributions from evidence and confidence (to allow an isolated view of evidence and confidence), as well as maps that calculate favorability using the product of components instead of a weighted sum (to highlight where all components are present). Our approach helped to identify areas of high geothermal favorability in the western and central Snake River Plain during the first phase of study and helped identify more precise local drilling targets during the second phase of work. By identifying favorable areas, this methodology can help to reduce uncertainty in geothermal energy exploration and development.

15 GEOTHERMAL ENERGY↗

Sensor network based solar forecasting using a local vector autoregressive ridge framework

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

54 ENVIRONMENTAL SCIENCES↗

Distributed Wind Guidebook: Agricultural Producers and Rural Small Business Owners

Distributed wind energy technologies generate clean, carbon-free power close to the point of consumption (i.e., close to people and their energy needs). Distributed wind energy can help individuals, farms, businesses, and communities meet their unique goals, such as reducing impacts on climate change, decreasing electricity bills, boosting energy independence or autonomy from the electric grid, and enhancing grid reliability and resilience. This guidebook is designed to support you in (1) deciding if distributed wind energy is right for you, (2) installing a proven wind turbine technology by working with a reputable installer, and (3) setting up your project for success through its lifetime. The information in this guidebook is tailored to rural small businesses and agricultural producers who are interested in exploring distributed wind energy to meet their electricity, resilience, financial, and environmental goals. You will find gray boxes with key topics, definitions, and considerations throughout the guidebook. The report has been adapted from the Distributed Wind Guidebook, which offers a comprehensive view on core aspects of deploying distributed wind energy technologies. In comparison, this edition of the guidebook is designed to offer a more succinct and tailored guidebook for rural small businesses and agricultural producers. For additional detail on any topic presented within this edition, readers are advised to reference the original version of the Distributed Wind Guidebook.

17 WIND ENERGY↗

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗

3x3 array module of 8×8×32 mm 3 position-sensitive virtual frisch-grid CdZnTe detectors for imaging and spectroscopy of cosmic gamma-rays

Here, we evaluated the performance of the 3x3 array of 32-mm long position-sensitive virtual Frisch-grid (VFG) CdZnTe (CZT) detectors read out by the IDEAS GDS-100 data acquisition system. The array is a mechanically solid module designed for integration into a large effective area gamma-ray telescope proposed for imaging and spectroscopy of cosmic gamma-rays. The array employs the bar-shaped 8x8x32 mm 3 CZT crystals which recently became available from Redlen Technologies, Inc. and Kromek-eV Group PLC at affordable costs. The waveform sampling IDE3421 application-specific integrated circuit (ASIC), developed by the University of Michigan and IDEAS for CZT pixel detectors, was adapted to capture the signals from the array's VFG detectors. We showed good spectral performance of the Redlen detectors with an energy resolution of <1% FWHM at 662 keV and slightly poorer performance of the Kromek-eV detectors with a resolution of <2% measured at a reduced temperature of 13 °C. By testing the same detectors as single devices using hybrid charge-sensitive preamplifiers, we demonstrated improved energy resolutions at a normal temperature of ~25°C: <1% and 1.3-1.7%, respectively. However, the Kromek-eV detectors did not perform as well as the Redlen ones. We explained this by the space charge formation (polarization) decreasing the electric field and the electron drift times. The polarization was likely caused by the high injections of holes from the anode contacts. The absence of polarization in Redlen detectors suggested that the quality of the contacts might have played a role in this case.

47 OTHER INSTRUMENTATION↗

Optimization of a High Pressure Turbine Blade and Sector-Based Annular Rig Design for Supercritical CO2 Power Cycle Representative Testing

Abstract As part of the ongoing research into the design of hardware for zero emission cycles, a first-stage high-pressure turbine (HPT) blade is optimized for a 300 MWe supercritical CO2 (sCO2) power cycle using the surrogate-assisted genetic algorithm optimizer in Numeca FINE/Design three-dimensional with objectives of increasing efficiency and decreasing heat load to the blade. Supercritical CO2 property tables are constructed from NIST REFPROP data for the condensable gas simulation in FINE/Turbo. A detailed mesh sensitivity study is performed for a baseline design to identify the proper-grid refinement and efficiently allocate resources for the optimization. Seventy design variables are selected for the initial population generation. Self-organizing maps are then used to focus the design variables on the most important ones affecting the objective functions. The optimization results in approximately 3000 three-dimensional Reynolds Averaged Navier Stokes simulations of different blade shapes with increases in efficiency of up to 0.85% and decreases in heat load of 14%. Families of blade shapes are identified for experimental testing in an annular rig at the Purdue Experimental Turbine Aerothermal Laboratory. A design to adapt the annular cascade for testing optimized geometries is introduced, which features eccentric radius sectors allowing for scaled-up geometries of sCO2 optimized blade profiles to be tested at design cycle representative conditions at high Reynolds numbers in dry air. Analysis into the effects of Reynolds number, working fluid, and geometric relations are presented to prove the efficacy of the test method.

Engineering↗

Guide de base pour l'energie solaire hors reseau en Haiti: 2. Produits cles et assurance qualite pour le solaire hors reseau

Cette formation donne un apercu des informations et des concepts cles de l'energie solaire hors reseau en Haiti, renforcant ainsi les connaissances fondamentales et la capacite de catalyser l'interet pour l'energie solaire hors reseau pour l'electrification rurale en Haiti. Ce cours a rythme libre est offert en anglais et en francais et couvre une variete de sujets lies a l'acces a l'energie en Haiti, notamment les produits solaires hors reseau, le potentiel du marche en Haiti, les considerations liees a l'offre et a la demande, la conception, l'installation et la maintenance du systeme, -modeles commerciaux solaires en reseau, modelisation financiere, genre et acces a l'energie, utilisation productive de l'energie et adaptation au climat. La formation est destinee aux etudiants universitaires, aux partenaires gouvernementaux, aux ONG, aux bailleurs de fonds, aux partenaires de developpement, aux professionnels, etc. Aucune connaissance prealable du solaire hors reseau ou d'Haiti n'est requise pour beneficier de cette formation. See NREL/PR-7A40-89245 for the English translation of this document.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Guide de base pour l'energie solaire hors reseau en Haiti: 10. Utilisation productive de l'energie

Cette formation donne un apercu des informations et des concepts cles de l'energie solaire hors reseau en Haiti, renforcant ainsi les connaissances fondamentales et la capacite de catalyser l'interet pour l'energie solaire hors reseau pour l'electrification rurale en Haiti. Ce cours a rythme libre est offert en anglais et en francais et couvre une variete de sujets lies a l'acces a l'energie en Haiti, notamment les produits solaires hors reseau, le potentiel du marche en Haiti, les considerations liees a l'offre et a la demande, la conception, l'installation et la maintenance du systeme, -modeles commerciaux solaires en reseau, modelisation financiere, genre et acces a l'energie, utilisation productive de l'energie et adaptation au climat. La formation est destinee aux etudiants universitaires, aux partenaires gouvernementaux, aux ONG, aux bailleurs de fonds, aux partenaires de developpement, aux professionnels, etc. Aucune connaissance prealable du solaire hors reseau ou d'Haiti n'est requise pour beneficier de cette formation. See NREL/PR-7A40-89253 for the English translation of this document.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Systematic Comparison of the Influence of Cool Wall versus Cool Roof Adoption on Urban Climate in the Los Angeles Basin

This study for the first time assesses the influence of employing solar reflective “cool” walls on the urban energy budget and summertime climate of the Los Angeles basin. Here, we systematically compare the effects of cool walls to cool roofs, a heat mitigation strategy that has been widely studied and employed, using a consistent modeling framework (the Weather Research and Forecasting model). Adoption of cool walls leads to increases in urban grid cell albedo that peak in the early morning and late afternoon, when the ratio of solar radiation onto vertical walls versus horizontal surfaces is at a maximum. In Los Angeles County, daily average increase in grid cell reflected solar radiation from increasing wall albedo by 0.80 is 9.1 W m –2 , 43% of that for increasing roof albedo. Cool walls reduce canyon air temperatures in Los Angeles by 0.43 K (daily average), with the peak reduction (0.64 K) occurring at 09:00 LST and a secondary peak (0.53 K) at 18:00 LST. Per 0.10 wall (roof) albedo increase, cool walls (roofs) can reduce summertime daily average canyon air temperature by 0.05 K (0.06 K). Results reported here can be used to inform policies on urban heat island mitigation or climate change adaptation.

54 ENVIRONMENTAL SCIENCES↗

Autonomous Navigation by a Mobile Robot

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Huntsberger, Terrance↗

Guide de base pour l'energie solaire hors reseau en Haiti: 3. Potentiel du marche de l'energie solaire hors reseau en Haiti

Cette formation donne un apercu des informations et des concepts cles de l'energie solaire hors reseau en Haiti, renforcant ainsi les connaissances fondamentales et la capacite de catalyser l'interet pour l'energie solaire hors reseau pour l'electrification rurale en Haiti. Ce cours a rythme libre est offert en anglais et en francais et couvre une variete de sujets lies a l'acces a l'energie en Haiti, notamment les produits solaires hors reseau, le potentiel du marche en Haiti, les considerations liees a l'offre et a la demande, la conception, l'installation et la maintenance du systeme, -modeles commerciaux solaires en reseau, modelisation financiere, genre et acces a l'energie, utilisation productive de l'energie et adaptation au climat. La formation est destinee aux etudiants universitaires, aux partenaires gouvernementaux, aux ONG, aux bailleurs de fonds, aux partenaires de developpement, aux professionnels, etc. Aucune connaissance prealable du solaire hors reseau ou d'Haiti n'est requise pour beneficier de cette formation. See NREL/PR-7A40-89246 for the English translation of this document.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Guide de base pour l'energie solaire hors reseau en Haiti: 9. Genre et acces a l'energie

Cette formation donne un apercu des informations et des concepts cles de l'energie solaire hors reseau en Haiti, renforcant ainsi les connaissances fondamentales et la capacite de catalyser l'interet pour l'energie solaire hors reseau pour l'electrification rurale en Haiti. Ce cours a rythme libre est offert en anglais et en francais et couvre une variete de sujets lies a l'acces a l'energie en Haiti, notamment les produits solaires hors reseau, le potentiel du marche en Haiti, les considerations liees a l'offre et a la demande, la conception, l'installation et la maintenance du systeme, -modeles commerciaux solaires en reseau, modelisation financiere, genre et acces a l'energie, utilisation productive de l'energie et adaptation au climat. La formation est destinee aux etudiants universitaires, aux partenaires gouvernementaux, aux ONG, aux bailleurs de fonds, aux partenaires de developpement, aux professionnels, etc. Aucune connaissance prealable du solaire hors reseau ou d'Haiti n'est requise pour beneficier de cette formation. See NREL/PR-7A40-89252 for the English translation of this document.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Guide de base pour l'energie solaire hors reseau en Haiti: 4. Considerations relatives a la demande et a l'offre pour l'energie solaire hors reseau

Cette formation donne un apercu des informations et des concepts cles de l'energie solaire hors reseau en Haiti, renforcant ainsi les connaissances fondamentales et la capacite de catalyser l'interet pour l'energie solaire hors reseau pour l'electrification rurale en Haiti. Ce cours a rythme libre est offert en anglais et en francais et couvre une variete de sujets lies a l'acces a l'energie en Haiti, notamment les produits solaires hors reseau, le potentiel du marche en Haiti, les considerations liees a l'offre et a la demande, la conception, l'installation et la maintenance du systeme, -modeles commerciaux solaires en reseau, modelisation financiere, genre et acces a l'energie, utilisation productive de l'energie et adaptation au climat. La formation est destinee aux etudiants universitaires, aux partenaires gouvernementaux, aux ONG, aux bailleurs de fonds, aux partenaires de developpement, aux professionnels, etc. Aucune connaissance prealable du solaire hors reseau ou d'Haiti n'est requise pour beneficier de cette formation. See NREL/PR-7A40-89247 for the English translation of this document.

customers↗