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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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Visualization of hourly generation, load, unserved load, and locational marginal energy prices in the western United States during a July 22-28 heatwave event in 2018 and 2058. In addition to hourly time series data of each of the parameters, choropleth maps showing the hourly value for each balancing authority are provided as well as a county-level choropleth map of temperature.
As part of continuing efforts to develop support, understanding, and infrastructure of data center integration onto the electric grid, our work aims to model and analyze the behavior of data center loads in a microgrid power system. Our model consists of renewable energy sources, batteries, and a nuclear reactor-steam Rankine cycle to power data center loads. The simulation studies investigate the electrical behavior of the microgrid system to assess its ability in supporting large data center electrical demands.
The final hardware and system qualification phase of a two part stand-alone photovoltaic (PV) system development is covered. The final design incorporated modular, power blocks capable of expanding incrementally from 320 watts to twenty kilowatts (PK). The basic power unit (PU) was nominally rated 1.28 kWp. The controls units, power collection buses and main lugs, electrical protection subsystems, power switching, and load management circuits are housed in a common control enclosure. Photo-voltaic modules are electrically connected in a horizontal daisy-chain method via Amp Solarlok plugs mating with compatible connectors installed on the back side of each photovoltaic module. A pair of channel rails accommodate the mounting of the modules into a frameless panel support structure. Foundations are of a unique planter (tub-like) configuration to allow for world-wide deployment without restriction as to types of soil. One battery string capable of supplying approximately 240 ampere hours nominal of carryover power is specified for each basic power unit. Load prioritization and shedding circuits are included to protect critical loads and selectively shed and defer lower priority or noncritical power demands. The baseline system, operating at approximately 2 1/2 PUs (3.2 kW pk.) was installed and deployed. Qualification was successfully complete in March 1983; since that time, the demonstration system has logged approximately 3000 hours of continuous operation under load without major incident.
Instrument tests various electric power generating devices by connecting the devices to the input of the load and comparing their outputs with a reference voltage. The load automatically adjusts until voltage output of the power generating device matches the reference.
As part of a Grid Modernization Laboratory Consortium (GMLC) project looking at defining grid services for a range of devices, NREL used a custom controller to investigate the ability of a HPWH to provide load add and load shed in hybrid and electric resistance mode using standard set point control. Based on those results, changes were made to the controls to increase the amount of grid services delivered, especially in the load-add case, and speed up the recovery from those events. The custom controls also include less common methods, such as duty cycling of the heat pump or elements. The improved controls led to an increase the amount of demand response that could be provided and enabled faster recovery. Results from the laboratory experiments will be presented, along with details about the custom controls that were implemented.
The planning of district-scale electric grids, i.e., distribution grids, has traditionally relied on finding the most cost-effective design such that they are able to supply the peak loads in a district. With the advent of electric demand side flexibility (DSF), there is the opportunity to reshape peak loads such that the investment cost of the electric grid decreases in exchange for a minor increase in the operation cost. This paper formulates an optimal planning approach for the electric grid at the district scale, which incorporates the DSF from thermal building systems, e.g., heating ventilation and air-conditioning (HVAC) systems. The problem is formulated as a mixed-integer linear program (MILP) and aims at minimizing the investment cost for the grid along with the operation cost of the flexible loads. This is subjected to the fixed electricity demand and thermal comfort constraints of building occupants. To this end, linear models for the thermal comfort in the buildings and the power flow in electric grid are considered. The approach is tested on a district planning test case based in Singapore, where the results show up to 30.9 % reductions in investment cost and up to 3.7 % reduction in total annualized cost. Urban planning authorities, developers and utility companies can all benefit from the presented approach to make optimized investment decisions. For building operators, the results point to the need of adopting their control systems for DSF.
Utilizing smart control algorithms for electric water heaters (EWHs) is essential for fully harnessing the demand response (DR) potential of EWHs. For this reason, the use of reinforcement learning (RL) algorithms for EWHs has received increasing attention in recent years. However, existing RL approaches are either simulation-based or use pretrained RL agents. To this end, this paper presents the real-world deployment of a set of model-free RL approaches that aim to minimize the electricity cost of a EWH under a time-of-use electricity pricing policy using standard DR commands (e.g., shed, load up). The experiment results showed that the RL agents can help save electricity cost in the range of 11% to 14% compared to the baseline operation. This study demonstrated that RL-based EWH controllers can be deployed in real world without any prior training and can still save electricity cost.
There are many factors that determine how demand for electricity may change over time. Medium-term load forecasting is a subset of load forecasting that focuses on the next year. This presentation summarizes analysis performed by NREL on medium-term load forecasting performed for the Moroccan energy system. This analysis includes hourly regressions and load clustering. This work also describes potential next steps that can be implemented by ONEE to improve this medium-term load forecasting.
Refrigerated display cases are widely-used, critical equipment in supermarkets for maintaining product safety and quality. Energy-efficient medium temperature liquid-cooled refrigerated display cases can save 25-70% of the total supermarket energy, according to manufacturers. Traditionally, cases operate by maintaining a temperature around a user-input setpoint that is dependent on the product in the case. Although cases are major electrical energy consumers, they are hardly ever considered for implementing load-flexibility strategies. With added load-flexibility capabilities, refrigerated display cases can shed (reduce), or shift (by adding and subsequently shedding) load. Supermarkets can reduce their energy costs and enhance electric grid integrity by implementing these smart load-flexibility control strategies. Advanced controls can also enable load-shifting to coincide with optimum periods of renewable energy generation. This will further improve operational costs and reduce greenhouse gas emissions without compromising food safety and quality. In this research, we have evaluated the energy savings of liquid-cooled medium temperature display cases and developed load flexibility strategies leveraging an advanced controls system, a variable speed compressor, and heat rejection via a water-cooled condenser. This study further assessed the impact of load flexibility strategies in a controlled environment chamber for a single refrigerated display case.
Design loads are presented for the General Electric MOD-SA wind turbine. The MOD-SA system consists of a 400 ft. diameter, upwind, two-bladed, teetered rotor connected to a 7.3 mW variable-speed generator. Fatigue loads are specified in the form of histograms for the 30 year life of the machine, while limit (or maximum) loads have been derived from transient dynamic analysis at critical operating conditions. Loads prediction was accomplished using state of the art aeroelastic analyses developed at General Electric. Features of the primary predictive tool - the Transient Rotor Analysis Code (TRAC) are described in the paper. Key to the load predictions are the following wind models: (1) yearly mean wind distribution; (2) mean wind variations during operation; (3) number of start/shutdown cycles; (4) spatially large gusts; and (5) spatially small gusts (local turbulence). The methods used to develop statistical distributions from load calculations represent an extension of procedures used in past wind programs and are believed to be a significant contribution to Wind Turbine Generator analysis. Test/theory correlations are presented to demonstrate code load predictive capability and to support the wind models used in the analysis. In addition MOD-5A loads are compared with those of existing machines. The MOD-5A design was performed by the General Electric Company, Advanced Energy Program Department, under Contract DEN3-153 with NASA Lewis Research Center and sponsored by the Department of Energy.
Areas investigated include: (1) load analysis; (2) power distribution, conversion techniques and generation; (3) design criteria and performance capabilities of hydraulic and pneumatic systems; (4) system control and protection methods; (5) component and heat transfer systems cooling; and (6) electrical system reliability.
The electric utility industry relies on robust communication protocols to manage complex electrical grid data. The inherent networked nature of electrical grids, coupled with the radial structure of the “last mile” portion delivering power to end-use customers, presents difficulties in describing electrical models using simple data constructs. The paper provides an overview of communication protocols that address electric utility data, including grid data, and classifies these protocols through identification key characteristics that make them suitable for different electric grid data domains. Because of their variety, grid edge devices and their associated dedicated protocols are assessed by groups: those primarily designed for energy production and storage, those related to flexible loads, and those related to electric vehicles. The intent of this report is to provide guidance for stakeholders to navigate the challenges posed by the numerous overlapping protocols available to address electric grid data. Although further industry review, refinement, and validation of the categorization of these protocols is recommended, the authors propose this categorization as a start to improve electric grid awareness and understanding. In addition, this report includes three recommended industry actions regarding protocols to improve communications on the electric grid.
Extreme weather events, many of which are climate change related, are occurring with increasing frequency and intensity and causing catastrophic outages. One of the major modern-day concerns of utilities is dealing with such extreme outages and consequently, its repercussions on the lives of people in society and social aspects. Traditionally, operators have been using rolling blackouts as a contingency plan to serve critical loads during such events when electricity supply is scarce. However, such blackouts practices are executed on a last-minute mandatory basis, depriving customers having low-capacity high priority loads (i.e. refrigeration, water, telecommunication, etc) that should also be serviced if at all possible. Historically, policymakers have often adopted quota-based regulatory actions or rationing for other commodities (such as gasoline, butter, sugar) to handle scarcity situations. Motivated from such quota based systems, our contribution presented in this work is an alternative transactive rationing mechanism that would provide some minimum level of service to all of the customers and serve the critical loads using market-based control during such scarcity-based contingencies. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on two real-life use cases having feeder-level and microgrid-level configurations respectively. The simulation results clearly demonstrate the capability of the rationing scheme to serve customers’ high-priority loads through prolonged outages even during extreme scarcity scenarios.
“Stay-at-home” orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. Here, we conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apartment’s consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a possible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is predicted to be 15% – 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% – 53% higher than that under pre-pandemic conditions. We conclude that the projected increase in peak demand - which might arise if stay-at-home guidelines coincided with hot weather conditions - could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted.
As space direct current (dc) power systems continue to grow in size, switching power converters are playing an ever larger role in power conditioning and control. When designing a large dc system using power converters of this type, special attention must be placed on the electrical stability of the system and of the individual loads on the system. In the design of the electric power system (EPS) of the International Space Station (ISS), the National Aeronautics and Space Administration (NASA) and its contractor team led by Boeing Defense & Space Group has placed a great deal of emphasis on designing for system and load stability. To achieve this goal, the team has expended considerable effort deriving a dear concept on defining system stability in both a general sense and specifically with respect to the space station. The ISS power system presents numerous challenges with respect to system stability, such as high power, complex sources and undefined loads. To complicate these issues, source and load components have been designed in parallel by three major subcontractors (Boeing, Rocketdyne, and McDonnell Douglas) with interfaces to both sources and loads being designed in different countries (Russia, Japan, Canada, Europe, etc.). These issues, coupled with the program goal of limiting costs, have proven a significant challenge to the program. As a result, the program has derived an impedance specification approach for system stability. This approach is based on the significant relationship between source and load impedances and the effect of this relationship on system stability. This approach is limited in its applicability by the theoretical and practical limits on component designs as presented by each system segment. As a result, the overall approach to system stability implemented by the ISS program consists of specific hardware requirements coupled with extensive system analysis and hardware testing. Following this approach, the ISS program plans to begin construction of the world's largest orbiting power system in 1997.
No abstract available
Large data centers, which now represent a significant and growing share of the total U.S. grid load, can inadvertently destabilize the electrical grid when they disconnect simultaneously during brief voltage disturbances. The July 10, 2024, Eastern Interconnection incident, in which a sub-100-millisecond transmission fault triggered the cascading loss of approximately 1,500 MW of data center load, illustrates this vulnerability. While commercial battery energy storage systems (BESS) deployed in data centers provide device-level fault ride-through per IEEE 1547, they lack coordination with facility protection logic and uninterruptible power supplies (UPS), limiting their effectiveness as grid-stabilizing assets. This report presents the Verrus StabiliGrid architecture, a coordinated control framework that integrates BESS, UPS, and point-of-interconnection (POI) protection settings to enable data centers to ride through both undervoltage and overvoltage grid contingencies without disconnecting. The four-step strategy encompasses: (1) high-resolution power quality monitoring to detect the grid state during events such as undervoltage, overvoltage, underfrequency, and overfrequency; (2) POI protection settings that allow for extended ride-through and grid-connected operation during grid contingencies; (3) grid state-driven autonomous dispatch of assets to improve grid resilience by reducing power draw during undervoltage or absorbing more power during overvoltage events; and (4) coordinated post-recovery dispatch of data center assets to restore firm load to pre-contingency levels. Validated through controller-hardware-in-the-loop (C-HIL) simulations at the National Laboratory of the Rockies, results show grid import restoration to pre-fault levels within 100 milliseconds of voltage recovery. This work advances the ability of data centers to transition from passive, disturbance-sensitive loads to active participants in grid stability, a capability increasingly required by emerging NERC and ERCOT regulatory frameworks.
Existing energy load forecasting tools rely upon historical load and forecasted weather to predict load within energy company service areas. The shortcomings of load forecasts are often the result of weather forecasts that are not at a fine enough spatial or temporal resolution to capture local-scale weather events. This project aims to improve the performance of load forecasting tools through the integration of high-resolution, weather-related NASA Earth Science Data, such as temperature, relative humidity, and wind speed. Three companies are participating in operational testing one natural gas company, and two electric providers. Operational results comparing load forecasts with and without NASA weather forecasts have been generated since March 2010. We have worked with end users at the three companies to refine selection of weather forecast information and optimize load forecast model performance. The project will conclude in 2012 with transitioning documented improvements from the inclusion of NASA forecasts for sustained use by energy utilities nationwide in a variety of load forecasting tools. In addition, Battelle has consulted with energy companies nationwide to document their information needs for long-term planning, in light of climate change and regulatory impacts.