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At least 667 records · Page 37

Regional Medium-Term Hourly Electricity Demand Forecasting Based on LSTM: Preprint

This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.

deep learning↗

Advanced Coating Compositions and Microstructures to Improve Uptime and Operational Flexibility in Cyclic, Low-Load Thermal Utility Plants

GE, the University of Tennessee, and Oak Ridge National Laboratory collaborated from 2020 to 2023 developing two key technologies for improving the viability of fuel switching and load following in thermal utility plants: a) cost-effective weld overlay compositions for boiler tubing b) cathodic arc coatings that deliver improvements in both erosion resistance and oxidation resistance in high temperature steam for HP turbine blades The team worked through a robust, logical project map to de-risk these two technologies and advance them from TRL 3 to TRL 6. For the cost-effective weld overlay, the team developed a ferritic filler material which was fabricated at a vendor for 18% the average market cost of Inconel 625 wire, had a corrosion rate 3x lower in conditions simulating a biomass-fired superheater and 10x lower in conditions simulating a coal-fired superheater, and was fabricated into prototype overlaid tubing that passed ASME requirements including transverse bending, dye penetrant inspection, and ASTM G-76 evaluation. For the cathodic arc coatings applied to steam turbine blades, the team developed a novel composition that was successfully transferred to a qualified vendor. The vendor was able to produce coated prototypes with 4x the as-deposited erosion resistance and 10.4x the post-steam-exposure erosion resistance of the TiN coating the vendor currently applies on GE steam turbine components, without significantly increasing process cost. These coated prototypes also passed a GE inspection and showed favorable performance in high temperature erosion, nanoindentation, sliding wear, scratch adhesion, and high cycle fatigue testing. If successfully deployed by GE, it is anticipated that the technologies will enable the following: • 25%-50% increase in time between outages for both boilers and HP turbines. • 50% decrease in cost for weld overlay on a per foot basis relative to todays NiCr alloys. • Adequate oxidation resistance and erosion for HP turbine inlet steam at >620°C and >220 bar. • No need for changes in component supply chain or any notable Capital Expenditures. 5 Decreasing component cost, increasing performance, and extending time between outages represent direct value propositions to GE and their customers. For the American consumer, these objectives translate into increased grid reliability (fewer unexpected outages), decreased Levelized Cost of Electricity, and improved environmental health (low-loading/load following to accelerate penetration of renewables). The results also have implications for wear resistant tooling, wire arc additive manufacturing, more durable components for syngas cleanup, and deployment of more efficient thermochemical pathways for carbon negative fuel production

09 BIOMASS FUELS↗

Hourly Electricity Demand Profiles for Each County in the Contiguous United States

This dataset provides estimated hourly electricity demand for each county in the contiguous United States from 2016-2023. The demand profiles represent the sum of two components: (1) Weighted averages of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. (2) Weighted averages of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector Annual county-level retail sales are estimated by aggregating utility-reported sales to the state level and allocating the results to counties according to each county's share of state population. Annual county-level direct use is calculated by aggregating power plant-reported direct use values. Annual county-level on-site consumption of DPV-generated electricity is estimated by aggregating utility-reported net metering data to determine the amount of DPV-generated electricity sold back to the grid for each state, subtracting those values from modeled state-level DPV generation estimates, and allocating the results to counties according to each county's share of statewide modeled DPV generation. The open-source Python code used to develop this dataset is available at "Historical Load Data Repository" link below.

14 SOLAR ENERGY↗

Parametric study of solid-solid translucent phase change materials in building windows

Thermal energy storage and solar radiation management are crucial to improve the sustainability and energy efficiency of buildings. Compared with the implementation of phase change materials (PCMs) in opaque components, the energy saving potential of incorporating PCMs in transparent glazing windows is much less studied and not well understood. Here we present a comprehensive parametric study of novel PCM windows for building energy saving with a focus on optimizing and quantitatively distinguishing the contributions from the optical and thermal properties of the PCM, which is particularly useful for the design of solid-solid PCM windows. We investigate a reference commercial office building using EnergyPlus by developing an equivalent model of our PCM window that is compatible with EnergyPlus's modeling capabilities. Compared with a clear-clear double-pane window, the integration of 3 mm solid-solid PCMs with optimal properties in warm, mixed, and cold climates can respectively save up to 17.2%, 14.0%, and 5.8% energy for the HVAC (heating, ventilation, and air conditioning) system, and 9.4%, 6.7%, and 3.2% energy for the whole building. We also demonstrate that these energy savings are most sensitive to the solar absorptance of PCMs for all three climates. The optimal transition temperature varies with climate and is related to the climate and solar radiation heat gain. Other issues are also briefly discussed, such as hysteresis, window orientations, and the effect of interior lighting. Finally, although the optimal PCM windows show energy saving performance comparable with low-emissivity windows, the PCM windows provide a unique advantage in terms of shifting HVAC loads which can provide benefits to the electrical grid.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Empirical characterization of vertical-tube inlets in hot-water storage tanks

Hot-water storage in residential and commercial tanks is of growing interest for peak-shifting the electrical demand associated with hot-water loads. How the water enters the tank can significantly affect the extraction efficiency of the storage. Vertical-tube inlets (VTIs) direct cold water into the tank. The VTI design influences whether large-scale mixing occurs, which can reduce the delivery capacity of the hot-water storage. In this work, the mixing at the VTI discharge was characterized by the eddy diffusivity factor (EDF) in an allometric curve fit to the ratio Re:Ri using inlet superficial velocities. The full experimental campaign tested VTI's with Re’s between 170 and 22,300 and Ri's between 0 and 376. Animated visualization of the experimentally measured data is provided, showing tank temperature evolution during inlet flows. The most predictive correlations for EDF are for VTI Re in the transition zone (i.e. ~2300 < Re < ~10,000) and at a Ri corresponding to a stably stratified tank (i.e. Ri > 5). For vertical-tubes that distribute cold water below the thermocline, increasing the EDF will decrease the stratification in a hot-water tank as EDF quantifies inlet mixing. Overall, the new correlations for VTIs can be used to design and model thermally-stratified storage tanks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Combined Effects of Electric Vehicle Charging and Rooftop Solar Integration on Voltage Imbalance in Residential Distribution Networks

Residential electric vehicle (EV) chargers, as single phase loads, contribute to unbalanced voltage drops across phases, while rooftop solar systems, as single phase generators, can exacerbate voltage imbalance by causing unbalanced voltage increases. This paper investigates combined effects of residential EV charging and rooftop solar generation on voltage imbalance in residential distribution grids. The study examines these simultaneous impacts using the IEEE 8500-node test system, enhanced with a secondary network to realistically model the EV chargers and rooftop solar integration. To account for the variability and uncertainty in the EV charging loads and solar generation, a Monte Carlo approach is employed to capture and quantify the simultaneous impact of the EV charging and rooftop solar integration. In this approach, multiple influencing factors are considered, including state-of-charge (SOC), maximum charging power levels, and geographic distribution of chargers. The results provide practical insights for utilities and stakeholders, offering expectations for planning and operating strategies that effectively manage the increasing adoption of EVs and solar power while maintaining grid reliability.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗

Graphite-Embedded High-Performance Insulated Metal Substrate for Wide-Bandgap Power Modules

Emerging wide-bandgap (WBG) semiconductor devices such as silicon carbide (SiC) metal–oxide semiconductor field-effect transistors (MOSFETs) and gallium nitride high-electron-mobility transistors can handle high power in reduced semiconductor areas better than conventional Si-based devices owing to superior material properties. With increased power loss density in a WBG-based converter and reduced die size in power modules, thermal management of power devices must be optimized for high performance. Here, we present a graphite-embedded insulated metal substrate (thermally-annealed-pyrolytic-graphite-embedded insulated metal substrate—IMSwTPG) designed for WBG power modules. Theoretical thermal performance analysis of graphite-embedded metal cores is presented, with design details for IMSwTPG with embedded graphite to replace a direct-bonded copper (DBC) substrate. The proposed IMSwTPG is compared with an aluminum nitride-based DBC substrate using finite-element thermal analysis for steady-state and transient thermal performance. The solutions’ thermal performances are compared under different coolant temperature and thermal loading conditions, and the proposed substrate's electrical performance is validated with static and dynamic characterization. Using graphite-embedded substrates, junction-to-case thermal resistance of SiC MOSFETs can be reduced up to 17%, and device current density can be increased by 10%, regardless of the thermal management strategy used to cool the substrate. Reduced transient thermal impedance of up to 40% of dies owing to increased heat capacity is validated in transient thermal simulations and experiments. The half-bridge power module's electrical performance is evaluated for on -state resistance, switching performance, and switching loss at three junction temperature conditions. The proposed substrate solution has minimal impact on conduction and switching performance of SiC MOSFETs.

42 ENGINEERING↗

EmissionsFlexibility

Software to calculate the how changes in electricity consumption change the generator which provides the electricity. This is applied to find how load shifting (e.g. data centers) impact the carbon emissions of the power grid.

Rhodes, Noah↗

Project Report: School Retrofit Demonstration of Lighting and Outlet Controls with LED Upgrades

A technology demonstration project funded by the U.S. Department of Energy (DOE) was hosted by Boston Public Schools (BPS). This project evaluated wireless controls technology for lighting systems and plug loads (energy consumed by devices plugged into electrical outlets), implemented along with LED lighting retrofits in two classrooms. This study assesses technology readiness and effectiveness to determine the deployment potential of the technology in schools.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Highly-Accessible Catalysts for Durable High-Power Performance (Final Technical Report)

Reduction of costly Pt usage in proton exchange membrane fuel cell (PEMFC) electrodes is one of the major challenges towards development and commercialization of fuel cell electric vehicles (FCEV). However, reducing the Pt loading results in increasing local mass transport fluxes, and eventual performance loss, especially at high power. In this project, a team of 4 universities, 2 companies, and a national lab came together to develop fuel cell catalysts and electrodes with high performance and durability. The were several key concepts addressed in this project. The first concept is to develop a carbon support that possess internal porosity which are believed to enhance kinetic activity of the catalysts, and yet the pore morphology allows for good reactant transport. The second concept is to improve the Pt-electrolyte interface in hope to reduce the local transport resistance. This was done by using new ionomers and ionic liquids. The last concept involves improving the catalyst stability by introducing Pt alloy catalyst with ordered intermetallic phase. The collaborative platform provided by DOE funding enabled development of a highly active and durable catalyst with performance that exceeds previous catalysts and meets the DOE targets for light duty vehicle application.

08 HYDROGEN↗

Providencia Island White Papers: Potential for Increasing the Physical Resilience of Distributed Energy Resources

Using technologies such as solar photovoltaics (PV) to provide power to a site during a large-scale grid outage can be an effective solution for enhancing resilience, if designed appropriately. This paper discusses storm-hardening strategies including wind-loading standards, secure racking systems, balance of electrical systems and pre-storm preparations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Field Validation of Innovative Air-Source Heat Pumps for Cold-Climate Heating Applications

Air-source heat pumps (ASHPs) have historically found application in milder climates in the United States (US). Their application in cold climates has been hindered by reduced performance as outdoor temperatures fall below freezing and the need for backup or auxiliary electric resistance heaters to meet peak heating loads. Recent advances in cold-climate air-source heat pumps (ccASHPs) with features such as variable-speed compressors, multistage systems, and highly optimized thermal design have improved performance by increasing the coefficient of performance (COP), low-ambient-temperature capacity, and heating seasonal performance factor (HSPF) dramatically. Despite their benefits, ccASHPs are still not widely prescribed for cold climate conditions. This is due in part to a lack of verified, demonstrated performance and analysis in cold climates. Ultimately, high-efficiency ccASHPs play a key role in emerging energy/grid renovation efforts in addition to their potential energy savings and avoided carbon emissions, but their actual performance in various cold climate field settings must be better understood. The primary objective of this project was to measure the in-field performance of variable-capacity air-source heat pumps in cold climates with the goal of enabling the development of field-based performance maps. Specifically, the study looked at how the heat pumps operated in the field, the frequency of cycling, the frequency of defrost events, and the time spent in each mode of operation. The results are intended to be used by DOE to inform research and development of energy-efficient equipment and to develop guidelines for optimizing primary energy savings when using air-source heat pumps in heating-dominated regions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Overview of Building Electrification Technologies and Market Opportunities

This report provides an overview of building electrification drivers and select building electrification technologies and their markets and performance. Covered topics: Building Electrification Drivers and Context; Heat Pumps for Space Conditioning; Heat Pump Market Opportunities; Life Cycle GHG Emissions Impacts of Heat Pump Space Conditioning Technologies; Heat Pump Water Heaters; Electrification of Gas Loads: Commercial and Residential; Residential Panel Capacity; Electric Vehicle Impacts and Connections to Buildings; and Building Envelope Improvements and Thermal Energy Storage (TES) Opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

UHT-CAMANCHE: Ultra-High Temperature Ceramic Additively Manufactured Compact Heat Exchangers

The conceptual basis for this project is the convergence of advanced ultra-high temperature ceramic materials and additive manufacturing technologies to produce compact ceramic heat exchangers with complex internal flow path geometries. Task areas were broadly divided into materials and manufacturing development, heat exchanger design, component testing, and techno-economic analysis. Technical challenges included the design and commissioning of new test facilities, improving feature resolution and deposition rate of ceramic additive manufacturing techniques, establishing process-structure-property relationships in additively manufactured ultra-high temperature ceramics, and assessing high temperature materials compatibility in CO 2 environments. The primary candidate material evaluated in this work is a composite comprising zirconium diboride (ZrB2) with 30 vol. % silicon carbide (SiC) which was selected based on its desirable combination of high temperature mechanical properties, high thermal and electrical conductivities, and oxidation resistance. High solids loaded ZrB2-SiC pastes suitable for extrusion-based additive manufacturing were developed for the first time as part of this work. Materials compatibility studies indicate this material oxidizes in CO 2 to form a protective borosilicate scale which transforms to pure silica above 1000°C. Parts made by additive manufacturing displayed enlarged grain sizes produced by pressureless sintering as compared to hot-press sintering. Increases in microstructural coarseness have outsized effect on oxidation performance up to 1400°C due to incomplete oxidation of coarse large diameter SiC particles resulting in lower amounts of silica that apparently inhibit protective scale formation. Additive manufacturing as a forming technique did not appear to significantly affect thermal conductivity, hardness, or elastic modulus, though flexural strength was reduced by half or more as compared to traditionally hot-pressed materials. This effect was attributed to the presence of strength-limiting flaws (ca. 40 microns in size) originating from extrudate inhomogeneities that could potentially be eliminated with further process improvements. Attempts to attain economies of scale for production of multi-kilowatt scale heat exchangers by ceramic additive manufacturing proved difficult. Lack of automation and a modest extrusion rate while retaining fine feature resolution made the overall process labor intensive and limited experimental throughput. A number of full-scale components were taken through post-process heat treatments including drying, binder burnout, and sintering; however, none survived without significant flaws or cracks. Therefore, no operational data from a newly installed heat exchanger test loop were able to be obtained during the performance period. Continued research and development is recommended to improve economic feasibility of ceramic additive manufacturing by standardizing the use of advanced sensors, artificial intelligence, and automation tools to reduce associated labor costs and accelerate production rates. The materials and manufacturing techniques demonstrated in this work are likely to find applications in defense and energy applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Editorial: Advanced water splitting technologies development: Best practices and protocols

As the level of deployment and utilization of renewable energy sources, including wind and solar, continues to rise, large-scale, long-term energy storage technologies that could accommodate weekly and seasonal energy fluctuations will play a significant role in the overall deployment of renewable energies in the future. Harnessing and storing renewable energy resources via electrochemical, photoelectrochemical, or thermochemical processes by converting renewable energy into sustainable (energy storage) fuels have the potential to meet the long-term, terawatt scale energy storage challenge. Renewable hydrogen production is the cornerstone for sustainable fuel production and deep decarbonization of multiple sectors in our society. Cost-competitive clean hydrogen provides value to applications, such as 1) in the transportation sector for fuel cell vehicles, 2) in the electric grid sector for system stability and load balancing, and 3) in the industrial sector with metal refineries, cement production, and biomass upgrading (carbon-free fertilizer production). In addition, coupling clean renewable hydrogen with the carbon and nitrogen cycles enables known and well-established thermal-chemical processes to generate renewable hydrocarbon fuels and ammonia. The Advanced Water Splitting Technologies (AWST): low temperature electrolysis (LTE), high temperature electrolysis (HTE), photoelectrochemical (PEC) and solar thermo-chemical hydrogen (STCH) provide four unique and parallel approaches to produce low cost, low greenhouse gas (GHG) emission hydrogen at scale (Figure 1). Cost competitive clean hydrogen production using these four technologies is a current high priority focus for governments and industry. In June of 2022, the U.S. Department of Energy (DOE) launched the first in a series of Earthshot Initiatives. The Hydrogen Shot, “1 1 1” aims to reduce the cost of clean hydrogen by more than 80% to one dollar per one kilogram in 1 decade ($\$$1/kg H 2 ). The European Green Deal and the International Energy Agency (IEA) have implemented a strong focus on green hydrogen production for a clean and secure energy future.

benchmarking, low temperature electrolysis↗

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100)

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Puerto Rico Energy Public Policy Act (Act 17). To meet these goals and support widespread end-use electrification, Puerto Rico is exploring renewable energy and innovative technologies for energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads that can be deployed in each of Puerto Rico's cities and communities. Launched in February 2022, a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100) will perform a comprehensive analysis of stakeholder-driven pathways to Puerto Rico's clean energy future. This fact sheet describes the five activities this robust and objective energy analysis entails.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗