Search NASA⌕ Search

SEARCH · Search NASA

Results for “INTERCONNECTED POWER SYSTEMS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,376 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2012

Review of the WECC EDT phase 2 EIM benefits analysis and results report.

A region-wide Energy Imbalance Market (EIM) was recently proposed by the Western Electricity Coordinating Council (WECC). In order for the Western Area Power Administration (Western) to make more informed decisions regarding its involvement in the EIM, Western asked Argonne National Laboratory (Argonne) to review the EIM benefits study (the October 2011 revision) performed by Energy and Environmental Economics, Inc. (E3). Key components of the E3 analysis made use of results from a study conducted by the National Renewable Energy Laboratory (NREL); therefore, we also reviewed the NREL work. This report examines E3 and NREL methods and models used in the EIM study. Estimating EIM benefits is very challenging because of the complex nature of the Western Interconnection (WI), the variability and uncertainty of renewable energy resources, and the complex decisions and potentially strategic bidding of market participants. Furthermore, methodologies used for some of the more challenging aspects of the EIM have not yet matured. This review is complimentary of several components of the EIM study. Analysts and modelers clearly took great care when conducting detailed simulations of the WI using well-established industry tools under stringent time and budget constraints. However, it is our opinion that the following aspects of the study and the interpretation of model results could be improved upon in future analyses. The hurdle rate methodology used to estimate current market inefficiencies does not directly model the underlying causes of sub-optimal dispatch and power flows. It assumes that differences between historical flows and modeled flows can be attributed solely to market inefficiencies. However, flow differences between model results and historical data can be attributed to numerous simplifying assumptions used in the model and in the input data. We suggest that alternative approaches be explored in order to better estimate the benefits of introducing market structures like the EIM. In addition to more efficient energy transactions in the WI, the EIM would reduce the amount of flexibility reserves needed to accommodate forecast errors associated with variable production from wind and solar energy resources. The modeling approach takes full advantage of variable resource diversity over the entire market footprint, but the projected reduction in flexibility reserves may be overly optimistic. While some reduction would undoubtedly occur, the EIM is only an energy market and would therefore not realize the same reduction in reserves as an ancillary services market. In our opinion the methodology does not adequately capture the impact of transmission constraints on the deployment of flexibility reserves. Estimates of flexibility reserves assume that forecast errors follow a normal distribution. Improved estimates could be obtained by using other probability distributions to estimate up and down reserves to capture the underlying uncertainty of these resources under specific operating conditions. Also, the use of a persistence forecast method for solar is questionable, because solar insolation follows a deterministic pattern dictated by the sun's path through the sky. We suggest a more rigorous method for forecasting solar insolation using the sun's relatively predictable daily pattern at specific locations. The EIM study considered only one scenario for hydropower resources. While this scenario is within the normal range over the WI footprint, it represents a severe drought condition in the Colorado River Basin from which Western schedules power. Given hydropower's prominent role in the WI, we recommend simulating a range of hydropower conditions since the relationship between water availability and WI dispatch costs is nonlinear. Also, the representation of specific operational constraints faced by hydropower operators in the WI needs improvements. The model used in the study cannot fully capture all of the EIM impacts and complexities of power system operations. In particular, a primary benefit of the EIM is a shorter dispatch interval; namely, 5 minutes. However, the model simulates the dispatch hourly. Therefore it cannot adequately measure the benefits of a more frequent dispatch. A tool with a finer time resolution would significantly improve simulation accuracy. When the study was conducted, the rules for the EIM were not clearly defined and it was appropriate to estimate societal benefits of the EIM assuming a perfect market without a detailed specification of the market design. However, incorporating a more complete description of market rules will allow for better estimates of EIM benefits. Furthermore, performing analyses using specific market rules can identify potential design flaws that may be difficult and expensive to correct after the market is established. Estimated cost savings from a more efficient dispatch are less than one percent of the total cost of electricity production.

14 SOLAR ENERGY↗
DOE OSTI2019

Remote Technology to Retrieve Waste Below the 324 Building at the Hanford Site - 19622

The Waste Technology Engineering Laboratory (324 Building) is a Category 2 Nuclear Facility at Hanford. The 324 Building Disposition Project is responsible for the removal and remedial actions under CERCLA. Additionally, there are RCRA Dangerous Waste Management Units which the CERCLA actions are presumed to satisfy. The Radiochemical Engineering Complex (REC) is a group of four hot cells (A, B, C and D Cells) with an interconnecting airlock inside of the 324 Building. Underneath the REC B-Cell are contaminated soils that have an estimated 12,793 R/Hr dose rate and remediation is under CERCLA 300-FF-2 Operable Unit. The current action consists of debris removal from the floor of B-Cell, B-Cell floor removal, and excavation of the soils beneath the floor to a depth of up to twelve feet with four Remote Excavator Arms (REA). This paper provides insight into the preparation and performance of high tolerance core drilling into a hot cell complex. Installation of the REA Through Support (REA TS) mechanism through the 4'-6' concrete shield walls is a complex series of tasks with demanding tolerances at each of four locations around the perimeter of B-Cell. The use of training mock ups was included in the completion of this work. The REA TS is two 11 inch diameter high strength steel sleeves that have expandable collars at each end allowing the interstitial space between the outside of the sleeve and inside of the core drill to be grouted to form a substantial structural connection, and a 10 inch pipe with hydraulic hoses to power the REA. There are three cores required for each REA location. The REAs themselves are customized excavator arms, mounted on support columns to be used in the excavation and transfer of the contaminated soil into storage facilities. The tasks for the installation of the REA TSs are: 1) Characterization of B-Cell Cubicles. 2) Embedded Pipe Fill. 3) Interference Removal. a. Internal Walls, b. External Walls. 4) Core Drilling. 5) Go/No-Go gauge, and video inspection. 6) Installation of REA Through Support Assembly. The 324 Building REC Hot Cells have internal, external, and embedded utilities throughout the shield walls in conflict with the REA TS locations. Some of the embedded utilities have connection points inside of the B-Cell Cubicles. There were two separate issues at the conflicted locations. The first issue was the core drill cooling water would flow along the embedded utility potentially spreading legacy chemical and radiological contamination to areas of the facility that was unwanted. The second issue was that the REA TS required a substantial structural connection to the B-Cell wall, the cored diameter is larger than the REA TS and these interstitial areas required a full grouted connection. The embedded utilities posed a hazard that if unfilled, the interstitial grout would flow into the embedded utility and destabilize the required grouted structural connection. The B-Cell Cubicles had not been opened in over 10 years. A mockup was completed to install a glovebag over the cubicle opening and then to verify functionality and port requirements. The embedded utility pipe connections in the cubicles were then opened inside a glovebag to verify the correct connection points, connection method for future embedded pipe fill material delivery system, radiological characterization, and air flow to show that the embedded utility pipes were not blocked and would not pressurize. The embedded pipe fill material and grout system was mocked up and run several times to verify methodology and functionality. The B-Cell Cubicles were then reentered and the embedded utility pipe fill was completed using a hand pump. External interferences at the core drill locations were removed using standard interference removal techniques. Internal interferences at the core drill locations were removed using a remote cutting tool that was controlled through the use of the B-Cell crane, remote cameras and remote lighting. The core drilling was mocked up two separate times, the project's purpose built 'Mock Up Facility' was core drilled to verify tolerances and methodology prior to subcontract award, the core drill subcontractor built a 'dummy wall' to train and practice on achieving the demanding tolerances, coordinated alignments between the cores, short term and long term dose shielding techniques, and contamination control techniques. A core drill template, and additional anchoring techniques were used to maximize accuracy and precision of the REA TS core drills. A 'Go/No-Go' gauge was built and installed at each of the four REA TS locations to verify that the core drill met tolerances. The core drill locations were visually inspected using a boroscope. The REA TS installation was mocked up at the projects 'Mock Up Facility' beginning with basic hazard controls, then with intermediate hazard controls, and finally with full occupational safety, industrial hygiene, and radiological controls. The REA TSs were installed and grouted into place. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection Description This dataset contains input and output data for the manuscript Mongird, K. et al. (under review) titled "Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection". Input data corresponds to gridded spatial siting attributes that are necessary to conduct a random forest machine learning analysis of siting feature importance. Output data includes SHAP feature analysis outputs, and classification report values. For data on power plant siting results referred to in the manuscript, please refer to the CERF: IM3 Projected Western US Power Plant Locations data download page. The downloadable data includes values for eight different future scenarios for the Western US. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Technical Information The dataset includes two sets of data files: (1) CERF gridded siting parameters and (2) Feature analysis outputs and classification reports. All downloadable data is in csv file format. Files with x/y coordinate information use the Albers Equal Area Conic projection (ESRI:102003). 1. CERF Gridded Siting Parameters This directory provides a balanced sample of gridded CERF siting parameters data for eight different scenarios for the Western US through 2055, seven different technologies, and eight timesteps. This data serves as input to the feature analysis. It contains the following parameters. region_name - name of region (i.e., state) sited - binary value representing whether the grid cell received a siting of that technology type (1=True) rcp - binary value representing scenario resource concentration pathway (0 = RCP4.5, 1 = RCP8.5) ssp - binary value representing scenario shared socioeconomic pathway (0 = SSP3, 1 = SSP5) climate - binary value representing cooler (0) or hotter (1) GCM forcing tech_name - generation technology name sited_year - year that values correspond to transmission_cost - cost of transmission interconnection pipeline_cost - cost of natural gas pipeline interconnection interconnection_cost - total interconnection cost (sum of transmission cost and gas pipeline cost) lmp - associated locational marginal value ($/MWh) associated with the grid cell, timestep, scenario, and technology xcoord - x-coordinate of location ycoord - y-coordinate of location 2a. Feature Analysis Output The dataset includes the feature analysis shap output for locational marginal price and interconnection cost. It contains the following parameters. technology - generator technology name scenario - name of scenario feature - name of feature, either locational_marginal_price or interconnection_cost value - the mean of absolute value of SHAP values for given feature 2b. Feature Analysis Classification Report This download includes the classification report associated with each random forest model. The dataset contains the following parameters. technology - generation technology name scenario - name of scenario test - one of precision (the proportion of predicted positives that are actually correct), recall (the proportion of actual positives that were correctly identified), f1-score (the harmonic mean of precision and recall) 0.0 - value of test for classification of 0 (grid cell not chosen for siting) 1.0 - value of test for classification of 1 (grid cell chosen for siting) accuracy - accuracy of model (i.e., fraction of all predictions that were right) macro avg - Simple average of test values for all classes weighted avg - Weighted average of test values for all classes, weighted based on Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗
DOE OSTI2018

Advanced Photovoltaic Inverter Control Development and Validation in a Controller-Hardware-in-the-Loop Test Bed

Penetration of solar photovoltaic (PV) installations into the grid has increased in recent years. In the past, photovoltaic installations have not included grid-support functionality. Grid support functions including Volt-VAR (VVAR), Frequency-Watt (FW), Volt-Watt (VW), frequency/voltage-ride through, as well as other inverter functions such as anti-islanding are recommended by standards such as IEEE 1547 to allow PV inverters to contribute to acceptable operation and stability of distribution systems with high penetrations of PV and to ensure predictable response of the PV inverters. First, low-level and high-level grid support inverter control functions were developed and tested in simulation. The developed controller is able to integrate advanced controller functions in a coordinated approach, avoiding any conflict between the different control objectives. The algorithms were then programmed on an off-the-shelf embedded controller that included a dual-core CPU and FPGA. The details of the high-level grid support function and the lower level switching control will be presented. Second, this programmed controller is tested using a controller-hardware-in-the-loop (CHIL) test bed setup using an FPGA-based real-time simulator. The CHIL setup has the capability to run at a 500 nano-second time-step to accommodate the 20 kHz switching frequency of the developed controller. The advanced control function and CHIL test bed details provided here will aide future researchers to design, implement, and test advanced inverter functions for PV inverters.

14 SOLAR ENERGY↗
DOE OSTI2019

Evaluation of Hydrogen Production Feasibility for a Light Water Reactor in the Midwest

Increased electricity production from renewable energy resources coupled with low natural gas prices has caused existing light-water reactor (LWRs) to experience ever diminishing returns from the electricity market. Via partnership among Idaho National Laboratory (INL), The National Renewable Energy Laboratory (NREL), Argonne National Laboratory (ANL), Exelon, and Fuel Cell Energy a techno-economic analysis on the viability of retrofitting existing pressurized water reactors (PWRs) to produce hydrogen (H2) via high temperature steam electrolysis (HTSE) has been conducted. Such integration would allow nuclear facilities to expand into additional markets that may be more profitable in the long-term. To accommodate such an integration, a detailed analysis of HTSE process operation, requirements, and flexibility was conducted. Technical analysis includes proposed nuclear system control scheme modifications to allow dynamic operation of the HTSE via both thermal and electrical connection to the nuclear plant. High fidelity Modelica simulations showcase the viability of such control schemes. However, due to limited knowledge of solid oxide fuel cell (SOFC) stack degradation due to thermal gradients; thermal cycling of the HTSE was not included. Therefore, the control schemes proposed are only utilized to re-distribute steam at startup and only the portion of electricity utilized in the electrolyzers is cycled. From the detailed analysis of the nuclear integration and the HTSE process design, a comprehensive cost estimation was conducted in the APEA and H2A models to elucidate capital and operational costs associated with the production, compression, and distribution of hydrogen from a nuclear facility. Alongside this costing analysis, market analyses were conducted by NREL and ANL on the electric and hydrogen markets respectively in the PJM interconnect. Utilizing the electricity data market projections in the PJM interconnect from NREL and hydrogen demand/pricing projections from ANL a five variable sweep over component capacities, discount rates, and hydrogen pricing was completed using the stochastic framework RAVEN (Risk Analysis Virtual ENVironment) through its resource dispatch plugin HERON (Heuristic Energy Resource Optimization Network). Each combination of variables was evaluated stochastically four times over a seventeen year timespan from 2026-2042 (inclusive) to determine the most economically advantageous solution. Following the five variable sweep an optimization was conducted about the best sweep point to determine optimal component sizing and setpoints. Results suggest positive gain is achievable at all projected hydrogen market pricing levels and at all discount rates. However, exact component sizing and net returns vary based on these values and if incorrect sizing is selected; major net losses can occur. The optimal result occurred with set points as follows: high hydrogen prices, the largest possible HTSE unit in the sweep set at 7.47 kg/sec [645.4 tpd], a contractual hydrogen market agreement 7.29 kg/sec [629.8 tpd], and a hydrogen storage size 115,188 kg. The analysis suggested that with a discount rate of 8%, a ΔNPV = 1.2 billion over the seventeen year span can be achieved. The results illuminate that by operating in multiple markets the nuclear facility is capable of avoiding sale of electricity during times of low electricity market pricing, while maintaining the ability to capitalize on the high electricity market pricing. It should be noted that the analysis conducted in this report is a differential cash flow analysis and as such does not present profit levels. Instead it highlights the net benefit between building and competing in the hydrogen market utilizing nuclear facilities and conducting business as usual in the electricity markets. Additionally, results presented in this report exhibit conservatism due to four key assumptions: Given the limited knowledge on SOFC stack degradation due to thermal gradients the high temperature steam electrolysis plant is not allowed to thermally cycle. This limitation decreases electricity generation capacity in the nuclear plant, reducing capacity payments and the maximum output to the electrical grid. This analysis considers building a separate hydrogen pipeline for use in the nuclear facility. Research is currently being conducted to determine if existing natural gas pipelines can accommodate direct hydrogen injection. If hydrogen can be integrated into existing natural gas pipelines then a capital savings of ~$19,000,000 per kg/sec [1 kg/sec = 86.4 tpd] of installed HTSE capacity could be realized. Fast transients in the electric grid are typically served by flywheels and electric batteries. With electrolysis only operation the nuclear plant can flex its electricity just as quickly. However, for this analysis, the ancillary services market has been neglected. Should the nuclear plant have the ability to operate in the ancillary services market during periods when it is producing hydrogen, an additional substantial income stream that would increase overall system profitability could be considered. Subsidies for non-emitting generation technologies are not introduced in the cash flow analysis, but instead are completed assuming zero subsidies. Profitability is based solely on electricity pricing. Electric pricing is assumed to never go negative. Instead, it is assumed overall system curtailment by the Independent System Operator (ISO) will occur in such a manner that pricing remains at or above zero. This assumption inflates the “business as usual” scenario, thus decreasing the ΔNPV calculated. If negative pricing scenarios continue to occur as they do today, one would expect a further increase in ΔNPV. Overall, results advocate that, through market diversification, nuclear power plants have the potential to substantially increase current profit margins, increase market penetration, and ultimately solidify their place as a mainstay in energy production.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

PHEV-EV Charger Technology Assessment with an Emphasis on V2G Operation

More battery powered electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) will be introduced to the market in 2011 and beyond. Since these vehicles have large batteries that need to be charged from an external power source or directly from the grid, their batteries, charging circuits, charging stations/infrastructures, and grid interconnection issues are garnering more attention. This report summarizes information regarding the batteries used in PHEVs, different types of chargers, charging standards and circuits, and compares different topologies. Furthermore, it includes a list of vehicles that are going to be in the market soon with information on their charging and energy storage equipment. A summary of different standards governing charging circuits and charging stations concludes the report. There are several battery types that are available for PHEVs; however, the most popular ones have nickel metal hydride (NiMH) and lithium-ion (Li-ion) chemistries. The former one is being used in current hybrid electric vehicles (HEVs), but the latter will be used in most of the PHEVs and EVs due to higher energy densities and higher efficiencies. The chargers can be classified based on the circuit topologies (dedicated or integrated), location of the charger (either on or off the vehicle), connection (conductive, inductive/wireless, and mechanical), electrical waveform (direct current (dc) or alternating current (ac)), and the direction of power flow (unidirectional or bidirectional). The first PHEVs typically will have dedicated, on-board, unidirectional chargers that will have conductive connections to the charging stations or wall outlets and will be charged using either dc or ac. In the near future, bidirectional chargers might also be used in these vehicles once the benefits of practical vehicle to grid applications are realized. The terms charger and charging station cause terminology confusion. To prevent misunderstandings, a more descriptive term of electric vehicle supply equipment (EVSE) is used instead of charging station. The charger is the power conversion equipment that connects the battery to the grid or another power source, while EVSE refers to external equipment between the grid or other power source and the vehicle. EVSE might include conductors, connectors, attachment plugs, microprocessors, energy measurement devices, transformers, etc. Presently, there are more than 40 companies that are producing EVSEs. There are several standards and codes regarding conductive and inductive chargers and EVSEs from the Society of Automotive Engineers (SAE), the Underwriter Laboratories (UL), the International Electrotechnical Commission (IEC), and the National Electric Code (NEC). The two main standards from SAE describe the requirements for conductive and inductive coupled chargers and the charging levels. For inductive coupled charging, three levels are specified: Level 1 (120 V and 12 A, single-phase), Level 2 (208 V-240 V and 32 A, single-phase), and Level 3 (208-600 V and 400 A, three-phase) . The standard for the conductive-coupled charger also has similar charging ratings for Levels 1 and 2, but it allows higher current ratings for Level 2 charging up to 80 A. Level 3 charging for this standard is still under development and considers dc charging instead of three-phase ac. More details in these areas and related references can be found in this Oak Ridge National Laboratory (ORNL) report on PHEV-EV charger technology assessment.

25 ENERGY STORAGE↗
DOE OSTI2025

IM3 Data Center Driven Grid Stress Dataset for the U.S. Western Interconnection

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from an open-source grid operations modeling framework - GO), for the Integrated Multisector, Multiscale Modeling (IM3) project, under varying levels of data center demand growth between 2025 and 2035 in the U.S. Western Interconnection. The scenarios and sensitivity experiments are combinations of different data center demand growth rates and energy, weather, population and economic pathways. Data center demand growth projections were sourced from the Electric Power Research Institute (EPRI). The data center demand growth projection names are: Low (3.71% annual data center demand growth) Moderate (5% annual data center demand growth) High (10% annual data center demand growth) Higher (15% annual data center demand growth) Energy, weather, population and economic pathways are informed by two Shared Socioeconomic Pathways (SSP3 and SSP5) and two Representative Concentration Pathways (RCP4.5 and RCP8.5) following the hotter general circulation model (GCM) forcing group from a set of perturbed thermodynamics simulations. The resulting pathway names are: rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 The main scenarios and sensitivity experiments are detailed below. Reference scenario: The projected grid stress and reliability results for the U.S. Western Interconnection from a previous study. This scenario does not consider data center demand growth explicitly. Data center scenario: Building on the reference scenario, this scenario considers various data center growth rates and how they impact the U.S. Western Interconnection. Data center loads are modeled as flat 8760-hr profiles. This scenario does not consider new generation and transmission capacities specifically designed to meet the new data center demands. The related folder is named "flat". Delayed generator retirements sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different levels of natural gas and nuclear generator retirement delays. The resulting scenario names are: (1) postponing 100% nuclear retirements; (2) postponing 100% nuclear and 25% natural gas retirements; (3) postponing only 50% natural gas retirements; (4) postponing 100% nuclear and 50% natural gas retirements; (5) postponing 100% nuclear and 75% natural gas retirements; and (6) postponing 100% nuclear and 100% natural gas retirements. The related folder names are: no_gen_retire_0_gas, no_gen_retire_25_gas, no_gen_retire_50_gas, no_gen_retire_50_gas_only, no_gen_retire_75_gas, and no_gen_retire_100_gas. Demand response through curtailment sensitivity experiment: Building on the data center scenario, this experiment explores the impact of different participation and compensation levels of data center demand response. The resulting scenario names are: (1) 5% demand available for curtailment with 750 $/MWh compensation; (2) 5% demand available for curtailment with 500 $/MWh compensation; (3) 5% demand available for curtailment with 250 $/MWh compensation; (4) 15% demand available for curtailment with 750 $/MWh compensation; (5) 15% demand available for curtailment with 500 $/MWh compensation; and (6) 15% demand available for curtailment with 250 $/MWh compensation. The related folder names are: dr_cost_250_drup_0_drdown_5, dr_cost_250_drup_0_drdown_15, dr_cost_500_drup_0_drdown_5, dr_cost_500_drup_0_drdown_15, dr_cost_750_drup_0_drdown_5, and dr_cost_750_drup_0_drdown_15. Combination of delayed generator retirements and demand response through curtailment sensitivity experiment: The impact of combining postponing 100% nuclear and 25% natural gas retirements with 5% demand available for curtailment with 750 $/MWh compensation is simulated. The related folder is named "dr_cost_750_drup_0_drdown_5_nuc_100_gas_25". Please refer to the README file for a detailed description of the dataset including individual files and references.

Artificial Intelligence↗