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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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A powered building system that includes an electric power distribution system configured to distribute electrical power to a plurality of receptacles; one or more load sources; and one or more battery systems associated with: a respective receptacle of the plurality of receptacles and a respective load source of the one or more load sources.
In a three-phase, four-wire electrical distribution system, a zig-zag transformer and at least one Cascade Multilevel Modular Inverter (CMMI) is coupled between the distribution system and the neutral. A controller modulates the states of the H-bridges in the CMMI to build an AC waveform. The voltage is chosen by the controller in order to control an equivalent impedance that draws an appropriate neutral current through the transformer. This neutral current is generally chosen to cancel the neutral current sensed in the line. The chosen neutral current may be based on a remotely sensed imbalance, rather than on a local value, determined by the power utility as a critical load point in the system. The desired injection current is then translated by the controller into a desired zero-sequence reactive impedance, based on measurement of the local terminal voltage, allowing the controller to regulate the current without generating or consuming real power.
The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.
Traditionally, prototype hardware is built for validation testing to ensure battery systems design changes meet vehicle-level requirements, which is expensive both in cost and time. Virtual engineering (VE) of battery systems for electric vehicle (EV) propulsion offers a reduced-cost alternative to the traditional development process and uses multi-scale modeling to virtually probe the impact of design changes in a particular part on the overall performance of the system. This allows for rapid iteration over multiple design spaces, without committing to build hardware. This perspective article discusses current trends in VE for EV applications and proposes improvements to accelerate EV adoption.
High-impact low-probability (HILP) events can wreak havoc on electric power systems without appropriate preparedness. In this paper, the recent development of a tool, named Recovery Simulator and Analysis (RSA), is described and demonstrated. While there are many issues to consider when recovering electric power systems, the focus of RSA is on the coordination of transmission and subtransmission recovery with generation dispatch to minimize unserved energy. RSA focuses on recovery simulation to evaluate resilience as part of a planning process. RSA is demonstrated on an approximately 1400-bus Puerto Rican power system for 100 simulated instances of Hurricane Maria. Analysis of the recovery determines how many lines are critical to the recovery and which loads may experience delayed recovery. The results demonstrate the potential uses of RSA for identifying recovery decisions with low unserved energy and for identifying assets critical to recovery which can then be hardened prior to a HILP event.
A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.
Electrification and the growth of distributed energy resources (DERs), including flexible loads, are changing the energy landscape of electric distribution systems and creating new challenges and opportunities for electric utilities. Changes in demand profiles require improvements in distribution system load models, which have not historically accounted for device controllability or impacts on customer comfort. Although building modeling research has focused on these features, there is a need to incorporate them into distribution load models that include DERs and can be used to study grid-interactive buildings. In this paper, we present the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) model. OCHRE is a controllable thermal-electric residential energy model that captures building thermal dynamics, integrates grid-dependent electrical behavior, contains models for common DERs and end-use loads, and simulates at a time resolution down to 1 minute. It includes models for space heaters, air conditioners, water heaters, electric vehicles, photovoltaics, and batteries that are externally controllable and integrated in a co-simulation framework. Using a proposed zero energy ready community in Colorado, we co-simulate a distribution grid and 498 all-electric homes with a diverse set of efficiency levels and equipment properties. We show that controllable devices can reduce peak demand within a neighborhood by up to 73% during a critical peak period without sacrificing occupant comfort. We also demonstrate the importance of modeling load diversity at a high time resolution when quantifying power and voltage fluctuations across a distribution system.
We model the effect of plug-in electric vehicle (EV) adoption on U.S. power system generator capacity investment, operations, and emissions through 2050 by estimating power systems outcomes under a range of EV adoption trajectory scenarios. Our EV adoption scenarios are informed by 1) an Energy Information Administration scenario with no policy intervention, 2) EV growth expected under the Inflation Reduction Act (IRA), 3) a Biden Administration 50% EV sales target by 2030, 4) the Environmental Protection Agency’s projections under vehicle emissions standards, and 5) the International Energy Agency’s roadmap to Net Zero by 2050. We find across these scenarios that increasing EV adoption induces investment in new wind, solar, storage, and natural gas capacity, affecting power generation mix and emissions. The net effect of increasing EV adoption beyond our IRA base case is to increase power sector emissions by about 5 mtCO 2 eq per EV-year in 2026 (comparable to displaced gasoline vehicle combustion emissions), but this effect rapidly drops to annual levels below 1 mtCO 2 eq per EV-year by 2032 and continues below this level through 2050. Consequential effects of EV adoption vary regionally, with most regions primarily increasing wind or solar capacity and some regions primarily increasing natural gas capacity, even in 2050. Our national emissions estimates per EV-year are relatively robust to the level of EV adoption beyond our baseline and to variation in assumptions about power systems, EV behavior, and policy.
Integrating renewable energy and energy storage systems provides a way of operating the electrical grid system more energy efficiently and stably. Thermal storage and batteries are the most common devices for integration. However, it is not clear which integrated storage system performs better in terms of overall economics. Ice storage has low initial and maintenance costs, but there is an efficiency penalty for charging of storage and it can only shift electrical loads associated with building cooling requirements. A battery's round-trip efficiency, on the contrary, is quite consistent and batteries can be used to shift both HVAC and non-HVAC loads. However, batteries have greater initial costs and a shorter life. Finally, this research presents a tool, using model predictive control and optimal sizing, and provides a case study for comparing life-cycle economics of battery and ice storage systems for commercial buildings that have chillers for cooling and an on-site photovoltaic system.
A new Dynamic zOnal Model with Air-diffuser (DOMA) was developed. Several case studies were investigated and tested to evaluate and validate this program using measurement data. This new model was integrated into a TRaNsient SYstems Simulation program library and coupled with the multi-zone thermal model. The DOMA/TRNSYS coupled model was then used to predict room temperature distribution over an entire day of a single-zone building. The results show that increasing the heating outputs of the electric floor system, for example, from 75 to 200 W/m 2 , would not effectively improve the indoor thermal comfort, since the thermostat will reach the set point first and then turn off the system before the room gets enough heat and reach a comfortable level. This indicates the importance of selecting an appropriate location and set point for the thermostat when using a floor heating system. This potential thermal comfort issue can only be identified through the two-node model with a dynamic zonal model rather than the conventional PMV model, which thus suggests that for optimizing indoor thermal comfort of a building equipped with a time-sensitive control strategy and/or HVAC system, the TSENS results obtained from the two-node model integrated with DOMA are more appropriate than PMVs.
The use of electric vehicles (EVs) in the United States has grown significantly during the last decade, posing benefits to the environment but also potential challenges to our grid. To better understand this scenario , the Department of Energy (DOE) asked Pacific Northwest National Laboratory (PNNL) to perform an authoritative study of the impacts of EVs at scale on the electric grid. The Phase I study focused on the bulk power electricity impacts . This EV-at-scale Phase II work addresses key questions of interest to DOE related to the impacts of EV in the distribution systems: 1. When (which year), where, and how many EVs will be adopted and how will they be charged? 2. Given some prospective answers to the above question, what would be the EV hosting capability of a distribution system circuit? 3. How could the hosting capability be expanded to accommodate more EVs and what would be the potential measures and cost? This report documents the methodologies developed as part of this project and provides EV adoption modeling examples using distribution system circuit data provided by industry partner, Southern California Edison (SCE).
We describe supporting near real-time situational awareness of the electric distribution system by visualizing novel data from voltage sensors deployed on existing broadband cable television network equipment. Our scalable web-based visual analytics platform supports interactive geospatial exploration, time-series analysis, and summarization of grid behavior during potentially anomalous events. The broadband cable television sensor network provides observability of the electrical distribution system at a higher local spatial resolution than is typically available to most utilities, revealing the operational state of the network and aiding in the detection of abnormal behaviors or deviations from expected patterns, particularly across electric utility service areas. We outline the design and development of interactive geospatial and time-series visualization components and the scalable data services that supply metadata, historical, and real-time streams of sensor data across the network. We evaluate our platform during periods of extreme weather, demonstrating its ability to assist in detecting patterns of operation that affect power availability, quality, resiliency, and service restoration.
This work presents the optimization of a wind-battery IES using the multiscale optimization framework proposed in our previous work to quantify errors from the price-taker assumption. The framework, built over Prescient (an open-source package for solving production cost models), is applied to the RTS-GMLC dataset, an open-source dataset that is representative of the southwest U.S. wholesale electricity market. The framework provides detailed bidding, market clearing, and control processes of an IES, and it can quantify how the IES interacts with the market. In this work, we use the retrofit of a wind farm with a battery storage system as an example to show the difference in the market outcomes and revenues obtained from both price-taker and multiscale optimization approaches. Our work goes beyond price-taker and deep dives into quantifying IES-market interaction in optimizing IES. This framework enables users to explore how different design and operation decisions of energy systems interact with the market and provides a more accurate evaluation than the price-taker assumption.
This report provides a set of best practices in response to Section 4(d) of Executive Order 14308, Empowering Commonsense Wildfire Prevention and Response. The information contained herein is expected to be used in conjunction with other materials at the Federal Energy Regulatory Commission Wildfire Risk Mitigation Technical Conference (Docket No. AD25-16-000), with possible direction to the North American Electric Reliability Corporation to take action. The objective of this report is to provide an overview of existing and emerging best practices currently employed or planned by utilities for wildfire mitigation, demonstrating how these efforts align with the executive order’s emphasis on reducing electric utility–caused wildfires while also balancing cost-effectiveness. Additionally, while most practices in utility-developed wildfire mitigation plans focus on risk reduction through robustness and operational reliability, this report also discusses best practices for resilience. The best practices are adopted from publicly available utility wildfire mitigation plans from the United States and Canada, recent findings from wildfire risk reduction research, and industry engagement.
A microgrid can enhance a site’s electrical power system during normal operations, as well as provide reliable backup power to critical loads when electric utility power is interrupted. When components of a microgrid (and potentially the entire system) can be justified economically and paid for out of energy savings or avoided costs, implementation by one of several privately financed federal procurement mechanisms is possible. However, it is typically difficult to achieve enough savings and avoided costs to cover the design, equipment, and installation of certain microgrid components that are required to integrate the system. This presentation explores procurement options and agreements that may be useful to federal agencies interested in implementing microgrids at their sites. This information will be most useful to agencies when they are exploring electric energy system resilience options and/or considering different procurement options to meet their needs.
The North American electric power system is undergoing significant change, with renewable resources now contributing more generation than ever before. This transformation is poised to continue given decreasing technology costs and ambitious decarbonization goals at the federal, state, local, corporate, and consumer levels. The North American Renewable Integration Study (NARIS) aims to inform grid planners, utilities, industry, policymakers, and other stakeholders about challenges and opportunities for continental system integration of large amounts of wind, solar, and hydropower to support a low-carbon future grid. The National Renewable Energy Laboratory (NREL) conducted a detailed, continent-wide analysis with planning scenarios of transmission, generation, and demand to reach 80%–92% carbon reductions (from 2005) for the Canadian electric power system, and up to 80% reductions continent-wide. We used a suite of models to study future scenarios and gain insights, including potential impacts on costs, emissions, resource adequacy, and the specific technologies that help enable the transition to a low-carbon grid. Our analysis had a particular focus on the potential role of cooperation among the three North American countries and between regions within each country, and how transmission can support sharing of supply and demand diversity. The NARIS project began in 2016. This report describes a U.S. perspective in coordination with the U.S. Department of Energy, and a companion report describes a Canadian perspective in coordination with the Natural Resources Canada. NARIS was an extension of a previous body of work, including the Western Wind and Solar Integration Study, the Eastern Renewable Generation Integration Study, Interconnections Seam Study, and the Pan Canadian Wind Integration Study. NARIS analyzed the entire continent in detail while studying higher renewable generation than previous studies. The scenarios in NARIS were informed by the goals in the Mid-Century Strategies for the Paris Agreement in each country.
The North American electric power system is undergoing significant change, with renewable resources now contributing more generation than ever before. This transformation is poised to continue given decreasing technology costs and ambitious decarbonization goals at the federal, state, local, corporate, and consumer levels. The North American Renewable Integration Study (NARIS) aims to inform grid planners, utilities, industry, policymakers, and other stakeholders about challenges and opportunities for continental system integration of large amounts of wind, solar, and hydropower to support a low-carbon future grid. The National Renewable Energy Laboratory (NREL) conducted a detailed, continent-wide analysis with planning scenarios of transmission, generation, and demand to reach 80%–92% carbon reductions (from 2005) for the Canadian electric power system, and up to 80% reductions continent-wide. We used a suite of models to study future scenarios and gain insights, including potential impacts on costs, emissions, resource adequacy, and the specific technologies that help enable the transition to a low-carbon grid. Our analysis had a particular focus on the potential role of cooperation among the three North American countries and between regions within each country, and how transmission can support sharing of supply and demand diversity. The NARIS project began in 2016. This report describes a Canadian perspective in coordination with the Natural Resources Canada, and a companion report describes a U.S. perspective in coordination with the U.S. Department of Energy. NARIS was an extension of a previous body of work, including the Western Wind and Solar Integration Study, the Eastern Renewable Generation Integration Study, Interconnections Seam Study, and the Pan Canadian Wind Integration Study. NARIS analyzed the entire continent in detail while studying higher renewable generation than previous studies. The scenarios in NARIS were informed by the goals in the Mid-Century Strategies for the Paris Agreement in each country.
The imperative for strong and rapid emissions reductions to mitigate global warming and enhance air quality necessitates a transition to net-zero emissions. This shift requires significant changes throughout the entire energy supply-demand ecosystems, tailored to various sectors. Transportation stands as the least-diversified energy sector and the largest source of U.S. GHG emissions. As the primary enabler for vehicle decarbonization when paired with clean electricity, electric vehicles (EVs) will play a pivotal role in the future. This talk summarizes current status of EV technologies and markets, future projections, and opportunities associated with a conversion to EV for all on-road vehicles. Moreover, EVs are poised to drive substantial growth in electricity demand and presents a unique opportunity to provide demand-side flexibility that is crucial for future renewable-dominated electricity systems. Smart integration of EVs can strengthen the grid, reducing costs and enhancing resilience.