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Powered By reV [Slides]

The reV model empowers users to calculate energy capacity, generation, and cost based on geospatial intersection with grid infrastructure and land-use characteristics. The tool can model a single site up to an entire continent at temporal resolutions ranging from five minutes to hourly, spanning a single year or multiple decades. By automating access to resource data at unprecedented scale, fidelity, and flexibility, the reV model integrates formerly disparate analysis frameworks in the fields of resource modeling, technical potential, and energy cost supply curves.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Least-cost Optimal Distribution Grid Expansion (LODGE): Utility Pilots

The Least-cost Optimal Distribution Grid Expansion (LODGE) model provides the optimal portfolio of distribution system upgrades—e.g., voltage regulators, feeder reconductoring, transformer upgrades and non-wires alternatives (NWA), such as strategic siting of storage and distributed generation—to interconnect distributed energy resources (DERs) and enable load growth. It can be used to assess grid infrastructure costs and explore policy and regulatory solutions for distribution planning and DER valuation.In 2025, Berkeley Lab conducted three pilot analyses to validate LODGE results with empirical utility data before the model’s first release in 2026. The pilots, done with utilities in Washington, Colorado, and New Mexico, provide examples that illustrate how the model works, what it can do, and the value of the analysis.

Heleno, Miguel↗

Non-Parametric Statistical Analysis of Current Waveforms through Power System Sensors

The protection, control, and monitoring of the power grid is not possible without accurate measurement devices. As the percentage of renewable energy sources penetrating the existing grid infrastructure increases, so do uncertainties surrounding their effects on the everyday operation of the power system. Many of these devices are sources of high-frequency transients. These transients may be useful for identifying certain events or behaviors otherwise not seen in traditional analysis techniques. Therefore, the ability of sensors to accurately capture these phenomena is paramount. In this work, two commercial-grade power system distribution sensors are investigated in terms of their ability to replicate high-frequency phenomena by studying their responses to three events: a current inrush, a microgrid “close-in”, and a fault on the terminals of a wind turbine. Kernel density estimation is used to derive the non-parametric probability density functions of these error distributions and their adequateness is quantified utilizing the commonly used root mean square error (RMSE) metric. It is demonstrated that both sensors exhibit characteristics in the high harmonic range that go against the assumption that measurement error is normally distributed.

47 OTHER INSTRUMENTATION↗

Energy Beam Highways Through the Skies

The emergence of Energy Beam Flight Transportation Systems could dramatically change the way we travel in the 21st Century. A framework for formulating 'Highways of Light' and the top level architectures that invoke radically new Space Power Grid infrastructure, are introduced. Basically, such flight systems, hereafter called Lightcraft, would employ off-board energy beam sources (either laser or microwave) to energize on-board dependent 'motors' -- instead of the traditional autonomous 'engines' with their on-board energy sources (e.g., chemical fuels). Extreme reductions in vehicle dry mass appear feasible with the use of off-board power and a high degree of on-board artificial intelligence. Such vehicles may no longer need airports for refueling (since they require no propellant), and could possibly pick up travelers at their homes -- before motoring over to one of many local boost stations, for the flight out. With off-board power, hyper-energetic acceleration performance and boost-glide trajectories become feasible. Hypersonic MS airbreathing propulsion can enable boosts up to twice escape velocity, which will cut trip times to the moon down to 5.5 hours. The predominant technological, environmental and social factors that will result from such transportation systems will be stressed. This presentation first introduces the remote source siting options for the space power system infrastructure, and then provides three representative laser/microwave Lightcraft options (derived from historical Case Studies): i.e., 'Acorn', 'Toy Top', and 'Disc.' Next the gamut of combined-cycle engine options developed for these Lightcraft are examined -- to illuminate the 'emerging technologies' that must be harnessed to produce flight hardware. Needed proof-of concept experiments are identified, along with the Macro-Level Issues that can springboard these revolutionary concepts into hardware reality.

Myrabo, Leik N.↗

Formally Verified ZTA Requirements for OT/ICS Environments with Isabelle/HOL: Preprint

The clean energy transformation led to the integration of distributed energy resources on a top of the grid, and so a substantial increase in the complexity of power grids infrastructure and the underlying operational technology environment. Operational technology environments are becoming a system of systems, integrating heterogeneous devices which are software/hardware intensive, have ever increasing demands to exploit advances in commodity of software/hardware infrastructures, and this for good reasons - improving energy systems requirements such as cybersecurity and resilience. In such a setting, system requirements at different levels mix, thus undesirable outcomes will surely happen. The use of formal methods will remove ambiguity, increase automation and provide high levels of assurance and reliability. In this paper, we contribute a methodology and a framework for the system level verification of zero trust architecture requirements in operational technology environments. We define a formal specification for the core functionalities of operational technology environments, the corresponding invariants, and security proofs. Of particular note is our modular approach for the formal verification of asynchronous interactions in operational technology environments. The formal specification and the proofs have been mechanized using the interactive theorem proving environment Isabelle/HOL.

formal methods↗

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint

Geothermal cost and performance evaluation implemented via technoeconomic assessment (TEA) modeling is critical for the Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for the Annual Technology Baseline (ATB). The ATB data are inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL’s reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the US generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on technoeconomic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next generation technologies such as closed loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

Annual Technology Baseline↗

Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop

Geothermal cost and performance evaluation implemented via techno-economic assessment (TEA) modeling is critical for the U.S. Department of Energy (DOE) and other geothermal industry stakeholders in assessing the current state of geothermal technologies and to identify existing hurdles to commercially viable geothermal development. The Geothermal Electricity Technology Evaluation Model (GETEM) is a major TEA tool used in estimating the economic feasibility and levelized cost of energy (LCOE) of conventional hydrothermal systems and enhanced geothermal systems (EGS). Since 2021, GETEM has been transitioning from an intricate spreadsheet model to a user-friendly tool within the System Advisor Model (SAM) developed by the National Renewable Energy Laboratory (NREL). Apart from enabling an expanded visibility of the geothermal model among other renewable resources, having GETEM in SAM has the advantage of simulation automation, better usability, updates tracking, active user inputs/feedback, and extended financial modeling. GETEM is used in developing supply curves for NREL's Annual Technology Baseline (ATB), which provides inputs to the Renewable Energy Potential (reV) and the Regional Energy Deployment System (ReEDS) models. The geothermal module in NREL's reV model assesses the geothermal energy potential in the conterminous United States by defining the geospatial intersection of geothermal resources with existing grid infrastructure within the constraint of land use characteristics. The ReEDS model is a capacity expansion model used for simulating the long-term build-out and operation of the U.S. generation and transmission system based on current energy costs and policies. To ensure enhanced representation of current industry trends in our model transitions and development, we organized a two-day virtual workshop to elicit geothermal industry stakeholder input and recommendations on our current approaches and assumptions on techno-economic, resource assessment, and deployment scenarios modeling of geothermal technologies. Participants included developers, operators, investors, regulatory agencies, system modelers, national laboratory researchers, consultants, and other stakeholders. In this workshop, we gained stakeholder insights on current geothermal plant performance (i.e., capacity factors), updated drilling costs and learning curves, and next-generation technologies such as closed-loop and superhot rock geothermal. Other outcomes from this workshop and its impact on future geothermal development feasibility, resource availability, and capacity expansion studies are compiled and discussed.

annual technology baseline↗

Challenges and Opportunities for HVAC + Phase Change Material Thermal Energy Storage in Buildings

Phase-change material (PCM) thermal-energy storage (TES) integrated with HVAC and domestic hot water (DHW) can shift a large share of building thermal loads. By flattening and shifting loads, PCM TES reduces peak electricity use, eases stress on local and grid infrastructure, and lowers costs. It can also defer costly upgrades to service panels, distribution, and transmission. Higher energy density relative to chilled or hot water storage makes PCM TES practical for small, space limited, and retrofit projects, while packaged HVAC-integrated systems expand cost-effective load shifting to commercial buildings that previously lacked options. Despite this promise, deployment faces barriers. This paper presents challenges, opportunities, and lessons learned from lab and field integrations of PCM TES with packaged HVAC systems. Key challenges include misalignment between default heat pump controls tuned for direct-to-load operation and TES charge/discharge objectives, PCM properties that diverge from manufacturer claims and evolve with cycling, and high integration and deployment costs with off-the-shelf products. These studies underscore the need for factory built, integrated systems that arrive as prepackaged modules with proven controls, reducing design and installation effort and delivering predictable performance across projects. The paper outlines steps to enable viable and scalable PCM TES HVAC and DHW systems, including 1) validated methods that can be used to characterize PCM properties and TES system performance, 2) supervisory controls that optimize charge/discharge scheduling, and 3) factory integrated packaging that eliminates bespoke field engineering.

Dutton, Spencer↗

FY 2021 Isolated Grids and Grid-Connected Turbine Reference Systems; Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

For individuals, businesses, and communities focused on building resilient electrical grid infrastructure, wind energy can provide an affordable, accessible, and compatible distributed energy resource option that also enhances the capabilities of local grid operations. The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project is a multi-year distributed wind research effort, driven through a partnership between four Department of Energy National Laboratories and industry to develop and improve the planning, design, and operation of wind-centered microgrids to complement solar, energy storage, and other distributed energy resources for grid-tied and isolated operation (U.S. Department of Energy, 2021). This report documents the application of methods developed through the initial three years of the MIRACL project to two real-world distributed wind reference systems. Specifically, the methods demonstrated in this report include 1) a market valuation framework to comprehensively value the services distributed wind can provide and 2) a resilience framework that enables stakeholders to characterize distribution system resilience and compare grid investment decisions from a resilience perspective. Additional methods mentioned in this report include distributed hybrid system design methods for grid resilience, advanced control co-simulation platforms, and power hardware-in-the-loop (PHIL) models. Preliminary results from these additional methods are presented in this report and will be demonstrated and/or applied to the reference systems in the coming year. The purpose of applying these methods to reference systems is to drive technology transfer of the theories, methodologies, and technologies developed under the MIRACL project and increase the number of referenceable case studies available to stakeholders interested in additional value-added capabilities of wind systems beyond bulk energy supply (i.e. kilowatt-hours).

17 WIND ENERGY↗

The Earth System Grid Federation : an Open Infrastructure for Access to Distributed Geospatial Data

The Earth System Grid Federation (ESGF) is a multi-agency, international collaboration that aims at developing the software infrastructure needed to facilitate and empower the study of climate change on a global scale. The ESGF's architecture employs a system of geographically distributed peer nodes, which are independently administered yet united by the adoption of common federation protocols and application programming interfaces (APIs). The cornerstones of its interoperability are the peer-to-peer messaging that is continuously exchanged among all nodes in the federation; a shared architecture and API for search and discovery; and a security infrastructure based on industry standards (OpenID, SSL, GSI and SAML). The ESGF software is developed collaboratively across institutional boundaries and made available to the community as open source. It has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the entire model output used for the next international assessment report on climate change (IPCC-AR5) and a suite of satellite observations (obs4MIPs) and reanalysis data sets (ANA4MIPs).

search,↗

Seamless Transition of Critical Infrastructures using Droop Controlled Grid-forming Inverters

Seamless recovery of power to critical infrastructures, after grid failure, is a crucial need arising in scenarios that are increasingly becoming more frequent. Here, this article proposes a seamless transition strategy using a single and unified mode-dependent droop controlled grid-forming inverters. The control strategy achieves the following objectives: 1) regulates the output active and reactive power by the droop-controlled inverters to a desired value while operating in on-grid mode; 2) seamless transition and recovery of power injections into the load after grid failure by inverters that operates in grid-forming mode all the time; 3) requires only a single bit of information on the grid/network status for the mode transition. A framework for assessing the stability of the system and to guide the choice of parameters for controllers is developed using control-oriented modeling. A controller hardware-in-the-loop-based real-time simulation study on a test system based on the realistic electrical network of a commercial-scale medical center is conducted for initial prototyping of the control strategy. A hardware experiment is conducted with two 3 - $\phi$, 480 -V, 125 -kVA grid-forming inverters, a 3 - $\phi$, 480 -V, 270 -kVA grid simulator, a physical grid switch, and a physical load bank. The experimental data establishes the effectiveness of the always grid-forming operation and control of inverters in meeting power delivery objectives when on-grid and off-grid under various kinds of loads and scenarios while minimizing transients during transitions. Furthermore, performance comparison with existing strategies showcases the advantage of the proposed strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI-XFC)

Increasing vehicle electrification will require extensive use of extreme fast charging (XFC), especially for larger vehicles. Uncoordinated XFC can create grid challenges, particularly at the distribution level. Two strategies can support widespread XFC: gold-plate the grid (i.e., upgrade all systems to enable worst-case, fully coincident loads) or use integrated planning to codesign a smart system based on advanced controls that leverage load flexibility and distributed energy resources. With the right design and control, XFC can simultaneously support both mobility and grid operations. Fully realizing the potential of XFC, however, will require unprecedented coordination among the charging infrastructure, grid, and vehicles. GEMINI-XFC combines high-fidelity grid and transport modeling at an unprecedented level of resolution and codesigns a smart system based on advanced controls that leverage load flexibility and distributed energy resources to optimize the integration of extreme fast charging (XFC) across a full regional scale with individual customer resolution.

ADVANCED PROPULSION SYSTEMS↗

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗

Advanced Distributed Wind Turbine Controls Series: Part 3-Wind Energy in Grid-Connected Deployments – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

In recent years the technical ability and requirement for distributed wind turbines to provide grid support services beyond maximum energy production has increased. Ancillary services leveraged through advance controls of a wind turbine support grid reliability and resilience. One ancillary service that is significant to a grid-connected wind turbine deployment is fault ride through (FRT) in response to the voltage and frequency events in the power system. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) this paper demonstrates, through desktop simulations, the wind turbine's FRT capabilities to support stable grid operation. We establish that the wind turbine models exceed FRT performance requirements stipulated in IEEE 1547-2018, regarding interconnection and interoperability of distributed energy resources. Utilizing a standalone CART2 (600 kW) wind turbine connected to the NREL's Flatirons Campus grid, we study voltage and frequency FRT utilizing various test cases. One of the test cases under study is a Category III voltage fault defined in IEEE 1547-2018 and derived from CA Rule 21. Some distributed wind turbines were unable to connect to the grid following the Rule 21 enforcement in California. Even if this is not a general requirement elsewhere, the grid codes might evolve in this direction. This study illustrates how a distributed wind turbine can provide some of these FRT services and enable a pathway toward a higher contribution of renewable energy in a distribution grid.

17 WIND ENERGY↗

Adoption of a token-based authentication model for the CMS Submission Infrastructure

The CMS Submission Infrastructure (SI) is the main computing resource provisioning system for CMS workloads. A number of HTCondor pools are employed to manage this infrastructure, which aggregates geographically distributed resources from the WLCG and other providers. Historically, the model of authentication among the diverse components of this infrastructure has relied on the Grid Security Infrastructure (GSI), based on identities and X509 certificates. In contrast, commonly used modern authentication standards are based on capabilities and tokens. The WLCG has identified this trend and aims at a transparent replacement of GSI for all its workload management, data transfer and storage access operations, to be completed during the current LHC Run 3. As part of this effort, and within the context of CMS computing, the Submission Infrastructure group is in the process of phasing out the GSI part of its authentication layers, in favor of IDTokens and Scitokens. The use of tokens is already well integrated into the HTCondor Software Suite, which has allowed us to fully migrate the authentication between internal components of SI. Additionally, recent versions of the HTCondor-CE support tokens as well, enabling CMS resource requests to Grid sites employing this CE technology to be granted by means of token exchange. After a rollout campaign to sites, successfully completed by the third quarter of 2022, the totality of HTCondor CEs in use by CMS are already receiving Scitoken-based pilot jobs. On the ARC CE side, a parallel campaign was launched to foster the adoption of the REST interface at CMS sites (required to enable token-based job submission via HTCondor-G), which is nearing completion as well. In this contribution, the newly adopted authentication model will be described. We will then report on the migration status and final steps towards complete GSI phase out in the CMS SI.

Pérez-Calero Yzquierdo, Antonio↗

A Framework for Identifying Building Energy Models of Localized Utility Service Areas Using Smart Meter Data

Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Grid Technology as a Cyber Infrastructure for Earth Science Applications

This paper describes how grids and grid service technologies can be used to develop an infrastructure for the Earth Science community. This cyberinfrastructure would be populated with a hierarchy of services, including discipline specific services such those needed by the Earth Science community as well as a set of core services that are needed by most applications. This core would include data-oriented services used for accessing and moving data as well as computer-oriented services used to broker access to resources and control the execution of tasks on the grid. The availability of such an Earth Science cyberinfrastructure would ease the development of Earth Science applications. With such a cyberinfrastructure, application work flows could be created to extract data from one or more of the Earth Science archives and then process it by passing it through various persistent services that are part of the persistent cyberinfrastructure, such as services to perform subsetting, reformatting, data mining and map projections.

Hinke, Thomas H.↗