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At least 235 records · Page 13

Multi-layered Resilient Microgrid Networks

Distribution grid resilience, especially when the grid is under high penetration of Distributed Energy Resources (DER), e.g. PV and energy storage, is essential to ensure the quality of electric power services. The resiliency aspect is particularly important for critical loads that typically include hospitals, police/fire stations, and national security facilities. Networks of multiple interconnected reconfigurable microgrids help to increase renewable energy penetration and may be used as basic building blocks for implementing future resilient power grids. However, this integration requires additional layers of communications, both horizontal and vertical, which may substantially increase the potential cyber attack surfaces as well as escalate risks for wide-spread malfunctions of automation systems. The Mulit-layered Resilient Microgrid Networks project is an industry-academic collaboration between ABB, Duke Energy and the University of Illinois at Urbana-Champaign (UIUC) that has developed and demonstrated a cyber-physical resilient control and communication architecture for deployment of multiple microgrid networks, as well as retrofitting the existing distribution grids by increasing DER penetration levels.

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Collaborative TPL Assessment of Wave Energy Converters and Farms

The Technology Performance Level (TPL) assessment is a holistic methodology to assess a wave energy converter (WEC) technology’s ability to achieve [continental grid] market competitiveness and acceptability via criteria-based consideration of key cost, performance, environmental, safety, and societal drivers. The TPL assessment can be applied at all technology development stages and associated technology readiness levels (TRLs).

Technology Performance Level↗

Experiments and Project-Based Enhancements for STEM Learning

Motivating K-12 students to pursue careers in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent engagement. Throughout the K-12 student timeline, STEM educators need to continuously pivot their teaching and update their educational materials to motivate the next generation of students. Once students begin their undergraduate education, university professors need to encourage them to consider pursuing graduate studies to ensure that a qualified future workforce can be developed for research and teaching. In this paper, we present our work on developing STEM materials for K-12 student engagement. Our K-12 materials target the grid integration of hydrogen assets that are suitable to engage students in the classroom. Our undergraduate materials target hands-on projects and collaboration with industry to connect classroom learning with real-world applications and needs in renewable energy. Our work leverages available open-source models and tools to create projects for undergraduate students and motivate their interest in pursuing research topics in graduate-level education.

ENERGY PLANNING, POLICY, AND ECONOMY↗

A Distributed Intelligent Automated Demand Response Building Management System

The goal of the 2.5 year Distributed Intelligent Automated Demand Response (DIADR) project was to reduce peak electricity load of Sutardja Dai Hall at UC Berkeley by 30% while maintaining a healthy, comfortable, and productive environment for the occupants. We sought to bring together both central and distributed control to provide “deep” demand response1 at the appliance level of the building as well as typical lighting and HVAC applications. This project brought together Siemens Corporate Research and Siemens Building Technology (the building has a Siemens Apogee Building Automation System (BAS)), Lawrence Berkeley National Laboratory (leveraging their Open Automated Demand Response (openADR), Auto-­Demand Response, and building modeling expertise), and UC Berkeley (related demand response research including distributed wireless control, and grid-­to-­building gateway development). Sutardja Dai Hall houses the Center for Information Technology Research in the Interest of Society (CITRIS), which fosters collaboration among industry and faculty and students of four UC campuses (Berkeley, Davis, Merced, and Santa Cruz). The 141,000 square foot building, occupied in 2009, includes typical office spaces and a nanofabrication laboratory. Heating is provided by a district heating system (steam from campus as a byproduct of the campus cogeneration plant); cooling is provided by one of two chillers: a more typical electric centrifugal compressor chiller designed for the cool months (Nov-­ March) and a steam absorption chiller for use in the warm months (April-­October). Lighting in the open office areas is provided by direct-­indirect luminaries with Building Management System-­based scheduling for open areas, and occupancy sensors for private office areas. For the purposes of this project, we focused on the office portion of the building. Annual energy consumption is approximately 8053 MWh; the office portion is estimated as 1924 MWh. The maximum peak load during the study period was 1175 kW. Several new tools facilitated this work, such as the Smart Energy Box, the distributed load controller or Energy Information Gateway, the web-­based DR controller (dubbed the Central Load-­Shed Coordinator or CLSC), and the Demand Response Capacity Assessment & Operation Assistance Tool (DRCAOT). In addition, an innovative data aggregator called sMAP (simple Measurement and Actuation Profile) allowed data from different sources collected in a compact form and facilitated detailed analysis of the building systems operation. A smart phone application (RAP or Rapid Audit Protocol) facilitated an inventory of the building’s plug loads. Carbon dioxide sensors located in conference rooms and classrooms allowed demand controlled ventilation. The extensive submetering and nimble access to this data provided great insight into the details of the building operation as well as quick diagnostics and analyses of tests. For example, students discovered a short-­cycling chiller, a stuck damper, and a leaking cooling coil in the first field tests. For our final field tests, we were able to see how each zone was affected by the DR strategies (e.g., the offices on the 7th floor grew very warm quickly) and fine-­tune the strategies accordingly.

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Computational Bayesian Framework for Quantification and Reduction of Predictive Uncertainty in Subsurface Environmental Modeling

Subsurface environmental systems are open and complex, in which intricate hydrologic, microbiologic, and geochemical processes occur and interact at multiple scales. Understanding and predicting system responses to natural forces (e.g., climate changes) and human activities (e.g., contaminant remediation and CO 2 sequestration) is indispensable for managing water resources, cleaning subsurface contamination at many sites of the Department of Energy (DOE), and providing expert analysis to inform policy-making on long-term stewardship of nuclear waste disposal and CO 2 storage sites. Groundwater reactive transport modeling is necessary for understanding and predicting the complex subsurface environmental system. However, as complex systems are never completely predictable, model predictions of the subsurface system are inherently uncertain, and uncertainty is one of the greatest obstacles in simulating the subsurface environment. Quantifying predictive uncertainty of the complex system is critical to test model predictive power, support decision-making, and guide experimental design and data collection for uncertainty reduction. This project tackled two major obstacles to efficient and effective quantification and reduction of predictive uncertainty in simulating the complex subsurface environment. One obstacle is that existing methods of uncertainty quantification are too fragmented and incomplete for understanding and predicting the complex subsurface environment as a whole. The other obstacle is that existing methods of uncertainty quantification are computationally demanding and may not be applicable to groundwater reactive transport modeling that is always computationally expensive. The above two obstacles to uncertainty quantification directly affect the design of data collection schemes for uncertainty reduction. In this project, we developed a comprehensive Bayesian framework to remove the first obstacle. The second obstacle was tackled by using the sparse grid methods, which were originally developed and analyzed for numerical integration in the field of applied mathematics. We integrated the sparse grid methods into the Bayesian framework seamlessly, which led to a sparse-grid-based method of Bayesian uncertainty analysis. The developed computational Bayesian framework has been applied to a number of subsurface environmental problems through collaborating with scientists at the Pacific Northwest National Laboratory and Oak Ridge National Laboratory. The applications demonstrated that the computational Bayesian framework is general and compatible with any models and numerical codes of subsurface modeling. It is thus can be applied to gain insights for subsurface environmental modeling. This project helped the PI achieve his career goal to advance the state-of-the-art computational methods in uncertainty quantification for subsurface environmental modeling. This project supported two doctoral students, two master students, and one post-doc. The two doctoral students, after their graduation, worked as post-docs at the Pacific Northwest National Laboratory and the Oak Ridge National Laboratory. The project produced a total of 29 journal articles (four under review), one book chapter, and a number of conference proceedings and abstracts.

54 ENVIRONMENTAL SCIENCES↗

Acquire and Test IDAES Framework Components

The cooperation under the Grid Modernization Initiative and the Applied Energy Tri-Laboratory umbrellas requires mutual understanding of capabilities and a common effort to identify gaps existing in the available computational modeling and analysis tools. In this work, we report acquisition and testing of the National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) framework, particularly including both electric power systems production cost model simulator Prescient as well as system optimization IDAES itself. Further, we consider the methods in which developments in Prescient and IDAES for grid-energy simulation and optimization may be included in the Framework for Optimization of ResourCes and Economics (FORCE) ecosystem that has been under collaborative development by Idaho National Laboratory, Argonne National Laboratory, and Oak Ridge National Laboratory. We propose two integration methods to introduce Prescient and IDAES into existing FORCE automated workflows. One integration involves using Prescient as a market reduced-order model and IDAES models similar to how existing Modelica models are used. The other integration involves wrapping the Prescient-IDAES dispatch optimization process with the stochastic capacity optimization workflow in FORCE.

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Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗

Developing Metrics to Evaluate the Skill and Credibility of Downscaling

In this project, our overarching goal was to evaluate the skill and credibility of statistical and dynamical downscaling techniques for reconstructing the historical climate record and projecting future climate change. This report summarizes our approach and accomplishments. In the first year of the project, the priority was to generate new data sets. For Year 2, the overall goal was to focus comparisons during the historical period and for a subset of variables, especially temperature and precipitation. In Year 3 and beyond, the focus was mainly on comparisons and metrics for future climate change simulations. To quantify the uncertainty associated with gridded dataset choice, the UCLA group compared eight gridded temperature datasets, examining climatologies, variability, and trends. The Scripps group completed statistical downscaling of NARR with the LOCA method, and UCLA and Scripps collaborated on a comparison of historical and end-of-century temperature and precipitation patterns over California from WRF, LOCA-WRF, and LOCA-Livneh. In addition to downscaling temperature and precipitation, the Scripps group has spent considerable time working on near-surface wind and humidity downscaling. The Santa Clara group assembled the Variable Infiltration Capacity (VIC) for nine snow-dominated river basins draining the western slopes of the Sierra Nevada range and assessed the role of snow albedo feedback in their VIC simulations. The results will help inform future downscaling studies.

54 ENVIRONMENTAL SCIENCES↗

Developing Metrics to Evaluate the Skill and Credibility of Downscaling (Final Report)

In this project, our overarching goal was to evaluate the skill and credibility of statistical and dynamical downscaling techniques for reconstructing the historical climate record and projecting future climate change. This report summarizes our approach and accomplishments. In the first year of the project, the priority was to generate new data sets. For Year 2, the overall goal was to focus comparisons during the historical period and for a subset of variables, especially temperature and precipitation. In Year 3 and beyond, the focus was mainly on comparisons and metrics for future climate change simulations. To quantify the uncertainty associated with gridded dataset choice, the UCLA group compared eight gridded temperature datasets, examining climatologies, variability, and trends. The Scripps group completed statistical downscaling of NARR with the LOCA method, and UCLA and Scripps collaborated on a comparison of historical and end-of-century temperature and precipitation patterns over California from WRF, LOCA-WRF, and LOCA-Livneh. In addition to downscaling temperature and precipitation, the Scripps group has spent considerable time working on near-surface wind and humidity downscaling. The Santa Clara group assembled the Variable Infiltration Capacity (VIC) for nine snow-dominated river basins draining the western slopes of the Sierra Nevada range and assessed the role of snow albedo feedback in their VIC simulations. The results will help inform future downscaling studies.

54 ENVIRONMENTAL SCIENCES↗

Young Leaders Workforce Training Program Overview and Impact

To support the Government of Colombia's plans to transform its power sector, the U.S. Agency for International Development (USAID) has assembled a cross-organizational team to develop and deliver a comprehensive workforce training program for young energy sector leaders in Colombia designed to enhance the efficient integration of growing volumes of variable renewable energy (VRE) to the energy sector. The team - which includes USAID's Colombia Mission, the National Renewable Energy Laboratory (NREL), USAID's Scaling Up Renewable Energy (SURE) program implemented by Tetra Tech, and the U.S. Energy Association (USEA) - collaboratively developed a series of seven capacity building modules designed to ready Colombia's energy sector workforce to participate in the construction, operation, and grid integration of VRE projects, such as wind and solar. This brochure highlights the program's objectives, results, and impacts to date.

Colombia↗

Understanding Cognitive and Collaborative Work: Observations in an Electric Transmission Operations Control Center

This paper describes research that is part of an ongoing project to design tools to assist in the integration of renewable energy into the electric grid. These tools will support control room dispatchers in real-time system operations of the electric power transmission system which serves much of the Western United States. Field observations comprise the first phase of this research in which 15 operators have been observed over various shifts and times of day for approximately 90 hours. Findings describing some of the cognitive and environmental challenges of managing the dynamically changing electric grid are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling of GE Appliances: Final Presentation

The Energy Information Administration (EIA) estimates that electricity use will increase by more than 30 percent by 2035, and that residential electricity usage will increase by 23 percent. During this time, peak electricity demand is expected grow at an even greater rate, requiring significant investment in system capacity. In addition, increased penetration of intermittent renewable resources will increase system variability, requiring additional resources to mitigate the variability associated with generator output. Widespread adoption of demand response (DR) enabled appliances, thermostats, and other demand-side resources can result in significant reduction to peak electrical demand and provide potential grid stabilization benefits. The key to adoption is to provide this resource at a cost commensurate with traditional grid capabilities, and to appropriately share both the costs and the benefits between the consumer and the service provider (i.e., the utility). However, the business model for investing in demand-side resources cannot be determined without an estimation of the possible technical benefits and how those benefits translate to monetary value in current electrical market structures. GE Appliances has developed a line of appliances that will have the capability of offering several levels of demand reduction actions based on information received from the utility grid, often in the form of price or grid status. However due to a number of factors, including the number of DR-enabled appliances available at any given time, the reduction of diversity factor due to the synchronizing control signal, and the percentage of consumers who may override the utility signal, it can be difficult to predict the aggregate response of a large number of residences. The effects of these behaviors have been modeled and simulated in the Pacific Northwest National Laboratory (PNNL) developed open-source software, GridLAB-D™, including evaluation of appliance controls, improvement to current algorithms, and development of aggregate control methodologies. The results of these simulations provide an estimation of the possible technical benefits (e.g., peak load reduction) attributable to smart appliances, but do not describe the monetary value of these services. This report is the final in a series of three reports funded by U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) in collaboration with GE Appliances’ through a Cooperative Research and Development Agreement (CRADA) to describe the potential of GE Appliances’ DR-enabled appliances to provide benefits to the utility grid.

Demand Response↗

Chance-Constrained System of Systems Based Operation of Power Systems

In this paper, a chance-constrained system of systems (SoS) based decision-making approach is presented for stochastic scheduling of power systems encompassing active distribution grids. Based on the concept of SoS, the independent system operator (ISO) and distribution companies (DISCOs) are modeled as self-governing systems. These systems collaborate with each other to run the entire power system in a secure and economic manner. Each self-governing system accounts for its local reserve requirements and line flow constraints with respect to the uncertainties of load and renewable energy resources. A set of chance constraints are formulated to model the interactions between the ISO and DISCOs. The proposed model is solved by using analytical target cascading (ATC) method, a distributed optimization algorithm in which only a limited amount of information is exchanged between collaborative ISO and DISCOs. In this paper, a 6-bus and a modified IEEE 118-bus power systems are studied to show the effectiveness of the proposed algorithm.

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PNNL’s Shared Perspectives Technology

Shared Perspectives, one of the technologies within the PNNL-developed GridOPTICS capability suite, enables neighboring organizations, such as different electric utilities, to more effectively partner to solve outages and other grid problems. Shared Perspectives provides a means for organizations to safely stream information from different organizational service areas; the technology then combines and aligns this information into a common, global view, enhancing global situation awareness that can reduce the time it takes to talk through a problem and identify solutions. The technology potentially offers applications in other areas, such as disaster response; collaboration in the monitoring/assessment of real-time events (e.g., hurricanes, earthquakes, and tornadoes); as well as military uses.

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EVs@Scale Lab Consortium Bi-Annual Stakeholder Meeting, 17 August 2022, Golden, Colorado [Slides]

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Lab Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. This network will be critical to support tens of millions of light-, medium-, and heavy-duty EVs on American roads by 2030. The EVs@Scale Lab Consortium brings together national laboratories and key stakeholders to conduct infrastructure research and development (R&D) that advances innovations in, and sets unified standards for, high-power and wireless charging. The effort will also develop technologies to integrate vehicle charging with the power grid, and develop cybersecurity measures to protect drivers, vehicles, equipment, and the grid. The first hybrid EVs@Scale Lab Consortium Biannual Stakeholder Meeting was held at NREL on August 17, 2022, to identify research, development, and deployment needs to accelerate technology development for electric vehicles at scale and explore opportunities for collaboration across government, academia, and industry.

33 ADVANCED PROPULSION SYSTEMS↗

Final Report to the National Energy Technology Laboratory on FY14- FY15 Cooperative Research with the Consortium for Electric Reliability Technology Solutions

The Power System Engineering Research Center (PSERC) engages in technological, market, and policy research for an efficient, secure, resilient, adaptable, and economic U.S. electric power system. PSERC, as a founding partner of the Consortium for Electric Reliability Technology Solutions (CERTS), conducted a multi-year program of research for U.S. Department of Energy (DOE) Office of Electricity Delivery and Energy Reliability (OE) to develop new methods, tools, and technologies to protect and enhance the reliability and efficiency of the U.S. electric power system as competitive electricity market structures evolve, and as the grid moves toward wide-scale use of decentralized generation (such as renewable energy sources) and demand-response programs. Phase I of OE’s funding for PSERC, under cooperative agreement DE-FC26-09NT43321, started in fiscal year (FY) 2009 and ended in FY2013. It was administered by DOE’s National Energy Technology Laboratory (NETL) through a cooperative agreement with Arizona State University (ASU). ASU provided sub-awards to the participating PSERC universities. This document is PSERC’s final report to NETL on the activities for OE, conducted through CERTS, from September 2015 through September 2017 utilizing FY 2014 to FY 2015 funding under cooperative agreement DE-OE0000670. PSERC is a thirteen-university consortium with over 30 industry members. Since 1996, PSERC has been engaged in research and education efforts with the mission of “empowering minds to engineer the future electric energy system.” Its work is focused on achieving: • An efficient, secure, resilient, adaptable, and economic electric power infrastructure serving society • A new generation of educated technical professionals in electric power • Knowledgeable decision-makers on critical energy policy issues • Sustained, quality university programs in electric power engineering. PSERC core research is funded by industry, with a budget supporting approximately 30 principal investigators and some 70 graduate students and other researchers. Its researchers are multi-disciplinary, conducting research in three principal areas: power systems, power markets and policy, and transmission and distribution technologies. The research is collaborative; each project involves researchers typically at two universities working with industry advisors who have expressed interest in the project. Examples of topics for recent PSERC research projects include grid integration of renewables and energy storage, new tools for taking advantage of increased penetration of real-time system measurements, advanced system protection methods to maintain grid reliability, and risk and reliability assessment of increasingly complex cyber-enabled power systems. A PSERC’s objective is to proactively address the technical and policy challenges of U.S. electric power systems. To achieve this objective, PSERC works with CERTS to conduct technical research on advanced applications and investigate the design of fair and transparent electricity markets; these research topics align with CERTS research areas 1 and 2: Real-time Grid Reliability Management (Area 1), and Reliability and Markets (Area 2). The CERTS research areas overlap with the PSERC research stems: Power Systems, Power Markets, and Transmission and Distribution Technologies, as described on the PSERC website (see http://www.pserc.org/research/research_program.aspx). The performers were with Arizona State University (ASU), Cornell University (CU), University of California at Berkeley (UCB), and University of Illinois at Urbana-Champaign (UIUC). PSERC research activities in the area of reliability and markets focused on electric market and power policy analyses. The resulting studies suggest ways to frame best practices using organized markets for managing U.S. grid assets reliably and to identify highest priority areas for improvement. PSERC research activities in the area of advanced applications focused on mid- to long-term software research and development, with anticipated outcomes that move innovative ideas toward real-world application. Under the CERTS research area of Real-time Grid Reliability Management, PSERC has been focused on Advanced Applications Research and Development (AARD), a subgroup of activities that works to develop advanced applications and tools to more effectively operate the electricity delivery system, by enabling advanced analysis, visualization, monitoring and alarming, and decision support capabilities for grid operators.

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Physics-Based GOES Satellite Product for Use in NREL's National Solar Radiation Database: Preprint

The National Renewable Energy Laboratory (NREL), University of Wisconsin, and National Oceanic Atmospheric Administration are collaborating to investigate the integration of the Satellite Algorithm for Shortwave Radiation Budget (SASRAB) products into future versions of NREL's 4-km by 4-km gridded National Solar Radiation Database (NSRDB). This paper describes a method to select an improved clear-sky model that could replace the current SASRAB global horizontal irradiance and direct normal irradiances reported during clear-sky conditions.

14 SOLAR ENERGY↗

U.S. Department of Energy (DOE) Enabling Extreme Real-Time Grid Integration of Solar Energy (ENERGISE) Project: Multiday and Intraday Energy Availability Product [Slides]

This presentation will provide an overview of the development of a Multi-Day Energy Availability Product under the DOE ENERGISE project, conducted in collaboration with Southwest Power Pool (SPP), the National Laboratory of the Rockies, Polaris, and the Electric Power Research Institute (EPRI). Existing market clearing processes are limited to day-ahead and real-time horizons, which may result in insufficient pricing signals and compensation for resource availability over multi-day timeframes (e.g., incentives for fuel procurement and energy-limited resource preparedness). This effort aims to develop a new market product and associated clearing process to value and procure resource energy availability over a multi-day horizon. The team will present progress to date and solicit advisory group feedback on proposed methodologies and preliminary findings.

14 SOLAR ENERGY↗