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At least 379 records · Page 21

Frequency-Nadir-Constrained Unit Commitment for Low-Inertia, High-IBR Island Power Systems [Slides]

The process of energy decarbonization in island power systems is accelerated due to the swift integration of inverter-based renewable energy resources (IBRs). The unique features of such systems, including rapid frequency changes resulting from potential generation outages or imbalances due to the unpredictability of renewable power, pose a significant challenge in maintaining the frequency nadir without external support. This paper presents a unit commitment (UC) model with data-driven frequency nadir constraints, including either frequency nadir or minimum inertia requirements, helping to limit frequency deviations after significant generator outages. The constraints are formulated using a linear regression model that takes advantage of real-world, year-long generation scheduling and dynamic simulation data. The efficacy of the proposed UC model is verified through a year-long simulation in an actual island power system using historical weather data. The alternative minimum inertia constraint, derived from actual system operation assumptions, is also evaluated. Findings demonstrate that the proposed frequency nadir constraint notably improves the system's frequency nadir under high photovoltaic (PV) penetration levels, albeit with a slight increase in generation costs, when compared to the alternative minimum inertia constraint.

14 SOLAR ENERGY↗

Continuous-time look-ahead flexible ramp scheduling in real-time operation

This paper develops a novel continuous-time look-ahead optimization model for co-optimizing balancing energy and flexible ramp products in real-time power systems operation. In addition, a continuous-time day-ahead operation model is developed to commit and schedule an adequate subset of generating units for providing balancing energy and ramping requirements in real-time operation. The up and down flexible ramp products are defined as continuous-time decision trajectories that continuously supply the real-time up and down ramping requirements of the system. The deliverability of flexible ramp products is secured through reserving the respective power requirements in generation capacity constraints of generating units. A function space solution method is proposed to reduce the dimensionality of day-ahead and real-time models through projecting them into finite-dimensional function spaces spanned by Bernstein polynomials, where the real-time operation decisions are modeled with a higher accuracy level than day-ahead decisions. Simulations are conducted on the IEEE-RTS system using CAISO load data, and the numerical results showcase the effectiveness of the proposed model in supplying the energy and flexible ramp requirements and avoiding ramping scarcity in the system, while reducing the operation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-layered Energy Management Framework for Extreme Fast Charging Stations Considering Demand Charges, Battery Degradation, and Forecast Uncertainties

To achieve a cost-effective and expeditious charging experience for extreme fast charging station (XFCS) owners and electric vehicle (EV) users, the optimal operation of XFCS is crucial. It is however challenging to simultaneously manage the profit from energy arbitrage, the cost of demand charges, and the degradation of a battery energy storage system (BESS) under uncertainties. This paper, therefore, proposes a multi-layered multi-time scale energy flow management framework for an XFCS by considering long- and short-term forecast uncertainties, monthly demand charges reduction, and BESS life degradation. In the proposed approach, an upper scheduling layer (USL) ensures the overall operation economy and yields optimal scheduling of the energy resources on a rolling horizon basis, thereby considering the long-term forecast errors. A lower dispatch layer (LDL) takes the short-term forecast errors into account during the real-time operation of the XFCS. Per the latest research, monthly demand charges can be as high as 90% of the total monthly bills for EV fast charging stations; to this end, this paper takes the first attempt at the reduction of demand charges cost by considering the trade-off between the energy cost and monthly demand charges. Contrasting literature, this work allocates an energy reserve in the BESS stored energy to deal with the impact of short-term forecast errors on the optimized real-time operation of the XFCS. Moreover, degradation modeling considers the trade-off between short-term benefits and long-term BESS life degradation. As a result, case studies and a comparative analysis prove the efficacy of the proposed framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The ABCs of On-Demand Transit (ODT)

On-demand mobility - also referred to as on-demand transit (ODT) - is a form of public mobility that is flexible with respect to where and when service is provided, and ODT deployments have increased significantly in recent years. Transit agencies are becoming increasingly interested in ODT, and due to differing definitions and various service design and business model options, it can be difficult to learn about the emerging industry. This work provides an overview of the definitions of ODT, recent trends internationally and in the U.S., ODT's benefits and challenges (particularly compared to fixed-route transit), three primary service design options, system costs and funding considerations, and a metrics framework for evaluating ODT systems to ensure continued successful performance. Identified benefits include increased service areas, short ride and wait times, increased user flexibility, potential to reduce energy consumption and emissions through shared trips and smaller, right-sized vehicles, increased safety and comfort through door-to-door service, and rich data streams including granular spatio-temporal data that can be analyzed to continuously improve the service. Challenges include scaling ODT service up as small increases in ridership require additional supply to keep service quality high, serving peak times including keeping low wait times, the lack of fixed schedule being challenging for commuters, integrating ODT services with nearby transit systems, and equity for riders without smartphones who cannot track the vehicle in a mobile app. Finally, an overview of seven ODT case studies (in Texas, Missouri, New York, and Ontario, Canada) performed by NREL and related analysis of travel time, energy and emissions, costs, and equity are presented. Initial key findings include: ODT can be cost- and energy-effective compared to fixed-route transit, ODT serves more people than other transit options, and ODT system deployments can be followed by rapid growth.

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PORFLOW modeling of Vadose zone flow and transport for the E-area intermediate level vault

In support of the E-Area Performance Assessment, a two-dimensional model of water flow and radionuclide transport through the E-Area Intermediate Level Vault (ILV) and local vadose zone has been developed using the PORFLOWTM software. The purpose of the model is to calculate flux to the water table for radionuclides eluted from the ILV during its operational life, the period of institutional control, and times following site closure. Results of model calculations will be used by a three-dimensional PORFLOW model of transport through the aquifer to determine radionuclide concentrations at a hypothetical 100 meter well and at the site boundary where contaminated groundwater could be assessed by members of the public following site closure. While newly developed, the model structure closely follows that used in the 2008 PA while incorporating a refined computational mesh, updated material properties for the vadose zone soil and vault concrete, revised infiltration rates, and new solid-liquid distribution coefficients. The model also addresses degradation of concrete hydraulic properties by blending soil and concrete water retention curves over a 500 year period. That is, the hydraulic properties of ILV concrete start out as fresh concrete at the time of site closure and degrade to soil properties over a 500 year time period. This approach has not been used previously in E-Area PA’s. The model has been used to calculate water flow through the ILV vadose zone and, on a trial basis, transport of a limited number of radionuclides from the waste region inside the ILV to the water table. Figure ES-1 provides a view of the model and an example of water flow after the concrete has substantially degraded. Figure dimensions are in centimeters. The red area in the left hand side figure is the waste disposal region within the ILV. Colored bands in the figures indicate different soil and concrete regions. Figure ES-2 shows a calculation of flux to the water table (mol/yr) for U-234 and its one-year half-life decay chain (U-234 → Th-230 → Ra-226 → Pb-210). Pb-210 flux is too small to show on the same scale used for Th-230 and Ra-226 in Figure ES-2. The model has also been used to make a preliminary evaluation of the release of tritium from TPBAR disposal containers that will be place in the ILV. A separately calculated tritium release rate as a function of time was used as a source in the PORFLOW model. The TPBAR disposal schedule and tritium release rate differ from the values used in the 2008 PA. Results from these initial trial runs are compared to calculations made for the 2008 PA ILV analysis. In brief, a new PORFLOW model of flow and transport through the ILV vadose zone has been developed and tested. The model is ready to be used for PA calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Assessment of wind power scenario creation methods for stochastic power systems operations

Probabilistic scenarios of renewable energy production, such as wind, have been gaining popularity for use in stochastic variants of power systems operations scheduling problems, allowing for optimal decision-making under uncertainty. The quality of the scenarios has a direct impact on the value of the resulting decisions, but until now, methods for creating scenarios have not been compared under realistic operational conditions. Here, we compare the quality of scenario sets created using three different methods, based on a simulated re-enactment of stochastic day-ahead unit commitment and subsequent dispatch for a realistic test system. We create scenarios using a dataset of forecasted and actual wind power values, scaled to evaluate the effects of increasing wind penetration levels. We show that the choice of scenario set can significantly impact system operating cost, renewable energy use, and the ability of the system to meet demand. This result has implications for the ability of system operators to efficiently integrate renewable production into their day-ahead planning, highlighting the need for the use of performance-based assessments for scenario evaluation.

17 WIND ENERGY↗

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

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Utility Sector Impacts of Reduced Electricity Demand: Updates to Methodology and Results

This report presents revisions to the methodology for estimating the utility sector impacts associated with electricity demand reductions, first published in our 2014 study. The earlier report described how to calculate utility impact factors based on data from the Energy Information Agency's Annual Energy Outlook (AEO) projections of electricity supply and demand. The 2014 methodology relied on data from the AEO Reference case, and side cases implementing demand-side policies with a substantial impact on total demand. Beginning in 2015, the AEO publication schedule was revised to limit the number of side cases published with each AEO, and no suitable demand-focused side cases have been released since 2014. Hence, this paper presents a generalization of the methodology that allows a uniform approach irrespective of the nature of the side cases published with the AEO. The impact factors we calculate represent coeffcients of variation between a unit reduction to site electricity demand and corresponding supply-side changes, including reductions to electric power generation and primary fuel consumption by fuel type, emissions of criteria pollutants (Hg, NO x and SO 2 ) and greenhouse gases (CO 2 , N 2 O and CH 4 ), and total installed capacity by plant type. The impact factors are time-dependent, and also depend on the demand sector and end use. In this report, we apply the methodology to all AEO publications from 2014-2019, and all scenarios. We quantify the variation in factors across different side cases within each AEO, and across different AEO publications, and compare this to the variation due to changes in methodology.

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Measuring Societal Infrastructure Service Burden

Social Infrastructure Service Burden (abbr. Social Burden) is defined as the burden to a population for attaining services needed from infrastructure. Infrastructure services represent opportunities to acquire things that people need, such as food, water, healthcare, financial services, etc. Accessing services requires effort, disruption to schedules, expenditure of money, etc. Social Burden represents the relative hardship people experience in the process of acquiring needed services. Social Burden is comprised of several components. One component is the effort associated with travel to a facility that provides a needed service. Another component of burden is the financial impact of acquiring resources once at the providing location. We are applying Social Burden as a resilience metric by quantifying it following a major disruption to infrastructure. Specifically, we are most interested in quantifying this metric for events in which energy systems are a major component of the disruption. We do not believe this is the only such use of the Social Burden metric, and therefore we will also be exploring its use to describe blue-sky conditions of a society in the future. Furthermore, while the construct can be applied to a dynamically changing situation, we are applying it statically, directly following a disruption. This notably ignores recovery dynamics that are a key capability of resilient systems. This too will be explored in future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the operational characteristics and economic value of pumped thermal energy storage

Pumped thermal energy storage (PTES) systems use an electrically-driven heat pump to store electricity in the form of thermal energy, and subsequently dispatch the stored thermal energy to generate electricity using a thermodynamic heat engine. Optimal day-ahead operational scheduling and annual value of a PTES system based on Joule-Brayton thermodynamic cycles and two-tank molten salt hot thermal storage is evaluated in this work. Production cost models, which simultaneously optimize commitment and dispatch schedules for an entire set of generators to minimize the cost of satisfying electricity demand, are employed to determine system-optimal operation and day-ahead energy value of the PTES system within each of six hypothetical near-future grid scenarios intended to approximately represent the U.S. Western Interconnection or the Texas Interconnection. Sensitivity to grid scenario (including the contribution of variable renewable energy sources), thermal storage capacity, relative heat pump and heat engine capacities, and startup/shutdown cycling costs are evaluated. PTES energy value and heat engine annual capacity factor increase strongly as the contribution of variable renewable resources increases, heat pump capacity increases relative to heat engine capacity, or PTES cycling costs decrease. Grid scenarios in which the contribution of variable renewable energy is dominated by solar photovoltaics (PV) vs. wind produce inherently different PTES operational patterns. Annual PTES energy value within PV-dominated scenarios increased with storage capacity only up to approximately seven hours of full-load discharge capacity, whereas that within wind-dominated scenarios exhibited a continual increase with storage duration up to at least 16 hours.

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Design and implementation of I/O performance prediction scheme on HPC systems through large-scale log analysis

Abstract Large-scale high performance computing (HPC) systems typically consist of many thousands of CPUs and storage units used by hundreds to thousands of users simultaneously. Applications from large numbers of users have diverse characteristics, such as varying computation, communication, memory, and I/O intensity. A good understanding of the performance characteristics of each user application is important for job scheduling and resource provisioning. Among these performance characteristics, I/O performance is becoming increasingly important as data sizes rapidly increase and large-scale applications, such as simulation and model training, are widely adopted. However, predicting I/O performance is difficult because I/O systems are shared among all users and involve many layers of software and hardware stack, including the application, network interconnect, operating system, file system, and storage devices. Furthermore, updates to these layers and changes in system management policy can significantly alter the I/O behavior of applications and the entire system. To improve the prediction of the I/O performance on HPC systems, we propose integrating information from several different system logs and developing a regression-based approach to predict the I/O performance. Our proposed scheme can dynamically select the most relevant features from the log entries using various feature selection algorithms and scoring functions, and can automatically select the regression algorithm with the best accuracy for the prediction task. The evaluation results show that our proposed scheme can predict the write performance with up to 90% prediction accuracy and the read performance with up to 99% prediction accuracy using the real logs from the Cori supercomputer system at NERSC.

97 MATHEMATICS AND COMPUTING↗

Automated electrical demand peak leveling in a manufacturing facility with short term energy storage for smart grid participation

Demand side management of energy is a vital function in the smart grid that allows for greater integration of renewable energy resources, and is facilitated with economic incentives in energy and demand pricing schedules. Manufacturing systems can take advantage of these incentives to reduce their energy costs through active energy management. This paper is a simulation analysis on the implementation of a novel algorithm that levelizes the maximum power load of an industrial bakery that operates under an on-peak demand price structure. The algorithm takes advantage of an untapped thermal energy storage resource in the facility, a chilled glycol buffer tank, to level the short intra-day power oscillations that the facility experiences. One of the key advantages of the algorithm is that it does not require precise demand forecasting or complex control algorithms, such as model predictive control. Even with substantial error in peak power estimates (5%), the algorithm is expected to result in at least a 2% peak reduction. Under ideal prediction, the algorithm reduces the on-peak facility power maximum by 7.3% of the possible 9.0% reduction the storage can provide. Further, the algorithm uses very few facility specific inputs, and can readily be adapted for any facility with short intra-day oscillatory power profiles and untapped storage capacity. The key insight of the paper is the employment of a novel algorithm to leverage untapped energy storage in manufacturing facilities to transform them into smart grid participants with no major capital investment.

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University Coalition for Fossil Fuel Energy Research

Following a nationwide open competition, the University Coalition for Fossil Energy Research (UCFER) was established in October 2015 through a cooperative agreement between Penn State and the Department of Energy (DOE) National Energy Technology Laboratory (NETL). Penn State lead UCFER with the objective of advancing basic and applied research for clean and low-carbon energy based on fossil fuels in support of the DOE’s mission. UCFER focused on research that improves the efficiency of production and use of fossil energy resources, while minimizing the environmental impacts and reducing greenhouse gas emissions. Penn State lead a team of nine universities (Massachusetts Institute of Technology, The Pennsylvania State University, Princeton University, Texas A&M University, University of Kentucky, University of Southern California, The University of Tulsa, University of Wyoming, and Virginia Polytechnic and State University) during the competition stage, adding seven more universities in 2017 (Carnegie Mellon University, Louisiana State University, The Ohio State University, University of North Dakota, University of Pittsburgh, University of Utah, and West Virginia University). This Coalition exhibited a wide geographical distribution across the U.S. bringing a wide variety of fossil energy expertise. This national university alliance was a major collaborative effort with NETL to address specific topics of R&D in NETL’s mission area, which involved one or more of NETL’s five core competencies (Geologic and Environmental Systems, Materials Engineering and Manufacturing, Energy Conversion Engineering, Systems Engineering and Analysis, and Computational Science and Engineering). The first five to six months of the project was the definitization stage. During this period, Penn State worked closely with NETL to finalize the Coalition organizational structure and By- Laws, prepare a statement of substantial involvement and a statement of project objectives, and develop operations and membership plans. A major component of this stage included preparing an execution plan to solicit research, evaluate proposals, recommend selected projects to NETL, and award projects. In addition, a plan was prepared to monitor projects, review projects, disseminate knowledge from research projects and develop an online system for Coalition research portfolio management. This included developing a website and several databases. The first of six rounds of solicitations started in mid-2016. Projects from the sixth solicitation started February 1, 2021, and ended January 31, 2023. Projects that were selected represented twelve technology lines. Approximately $16.6 million in funding was available for the six solicitations. Most of the funding was provided by DOE, Office of Fossil Energy (DOEFE) with the DOE Fuel Cells Technologies Office (DOE-FCTO) providing funding for a few projects. Coalition universities submitted 259 proposals in response to the solicitations, requesting approximately $67.0 million in funding, and forty-three projects were selected. However, one project withdrew after the principal investigator left the university. The management of the Coalition projects was a major activity by Penn State. Managing the Coalition projects consisted of monitoring the projects, reviewing the projects through annual technical review meetings, disseminating knowledge from the research projects, and developing an online system for Coalition research portfolio management. Penn State’s OMT monitored projects to ensure that all milestones (technical, schedule, budget) were met, expenditures were allowable, cost share (when applicable) were reported, and all technical reports were submitted. The OMT also posted the technical reports electronically on a secure members-only website for access and review by the Coalition members. Disseminating knowledge from the research projects was done through a website, newsletters, various meetings, conferences, journal articles, publicity/press releases, and project summaries that were prepared after each project was completed. Penn State kept NETL apprised of UCFER progress through quarterly reports (thirtyone were submitted by Penn State), verbal and written communications, yearly updates at the annual technical review meetings, and cost accrual reports. The UCFER project had a significant impacty. The UCFER program established the first national university alliance in fossil energy research with a major collaboration effort with DOE NETL that addressed specific topics in NETL’s research and development mission areas. It generated inter-university collaborations, which was another program interest. Twenty-two out of 259 proposals contained collaborations (≈8.5%) and three of forty-two funded projects involved inter-university collaborations (≈7.0%). The forty-two funded projects provided support at fourteen universities involving 269 personnel. Research was conducted by 106 faculty, 115 graduate and undergraduate students, forty-six research staff and post-doctoral scholars, and two visiting scholars. Students and post-doctoral scholars were also on-site at NETL through CRADAs. In addition, non-Coalition participants included six universities and sixteen companies and national laboratories. The non-Coalition participants were involved as subcontractors, providers of cost share, performed unpaid consultation and sample analysis, served as advisory board members, or were providers of samples and materials for testing. UCFER also produced visibility in that fifty-six refereed journal articles were published, fifty-seven conference papers and twenty-three posters were prepared, 190 presentations were given, eight patent applications were filed, two books/book chapters were written, and ten software codes were developed. Collaboration between NETL and the individual projects was a major requirement for all funded projects. This included NETL staff time to support collaboration, consultation, technical guidance, sample preparation and analysis, internships at NETL, on-site testing and equipment usage by Coalition participants at NETL, co-mentoring students, and coauthoring journal articles and conference papers. Collaboration was impacted by COVID-19 in that not all on-site activities could be performed. NETL personnel were coauthors on eight of the conference papers (fourteen percent of the conference papers that were prepared) and seventeen of the journal articles (thirty percent of the journal articles that were prepared). A website was developed for an online proposal solicitation and review process and to provide exposure to UCFER. A website analysis highlighted the large amount of member and general public interest in UCFER by interpreting access statistics from March 2016 through June 2023. Visitors to the site originated from many different organizations, businesses, and countries. The website provided a means to disseminate information to both the general public and the UCFER members and was successfully used for outreach activities. In addition, NETL required that RFP release, proposal submission, and proposal reviews all be performed online. Penn State successfully developed these capabilities in a secure section of the website, which were used throughout the UCFER project. It is recognized that each project had its technical successes. In addition, highlighted successes were compiled and summarized from the research projects. Information was requested from the PIs of completed projects. In addition, Penn State’s Operations Management Team reviewed subcontract reports to identify project successes. Examples of information requested from PIs included (not all-inclusive): new projects that have been funded as a result of UCFER funding; new commercial products; establishment of a new center; new patent; new software; best paper awards; highly-cited work; and graduate student successes. A total of forty-eight highlighted successes were reported.

01 COAL, LIGNITE, AND PEAT↗

Impact of Transport Electrification Demand and Charging Schedules on Electricity Markets and Nuclear Generators

As the U.S. pursues deep decarbonization targets, electric vehicles (EVs) are likely to become a major driver of demand growth and a major determinant of daily demand patterns. This study analyzes a possible future ERCOT-like electricity grid, and examines the impact of different types of EV charging schedules on grid and market outcomes. This analysis demonstrates the significant impact of EV charging patterns on capacity expansion simulations. Even without EVs, the overall daily demand profile in a market can have significant impacts on prices and grid stability in that system, especially if non-dispatchable renewable generators (e.g. wind and solar) make up a significant fraction of the generation mix. EV demand will not necessarily follow this preexisting demand profile, so its daily trends may significantly change what generation portfolio would optimally serve the system. Furthermore, the effects of EV demand can alter the profitability of different types of units, by altering the frequency of market events like extreme-demand hours or zero-price hours. These effects are explored in this study. The EV demand levels were derived from MARKAL simulations of the West-South-Central North American Electric Reliability Corporation (NERC) region for the year 2050, using a carbon tax of $100/ton. The baseline MARKAL simulation forecasted that 23% of the region’s annual electricity demand in 2050 would be attributable to EVs, and broke out demand projections for EV and non-EV end-use in that year. To model lower EV penetration into the system, an additional case was explored which assumed that EVs only achieved 75% of the demand level projected by MARKAL.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Gasification Combined Heat and Power from Coal Fines

The goal of this final project report is to comprehensively summarize the work for public domain conducted on project DE-FE 0031520. In accordance with the Statement of Project Objectives (SOPO), the University of Kentucky Center for Applied Energy Research (UKy-CAER) (Recipient) has completed a Front End Engineering Design (FEED) study 5 MWe polygeneration unit using the Coal Fields Regional Industrial Park in Hazard, Kentucky (KY) as a model location and using coal recovered from the adjacent Pads Branch Impoundment as feed. The scope of work is a thorough study that can be used as a template for the application of the proposed technology throughout Eastern KY and other coal communities nationwide. The Technology Design Basis was developed based on three elements: basic site characteristics; fuel feedstock; and environmental health and safety requirements. The Basic Engineering Design Elements include the preliminary process design (the process area descriptions; the Block Flow Diagram (BFD), Process Flow Diagrams (PFDs) and Piping and Instrumentation Diagrams (P&IDs), process simulation outputs and Heat and Mass Balance (H&MB) stream tables, the major process equipment and instrumentation lists which includes specifications and materials of construction); the cost estimate (capital cost estimate, operational cost estimate, and comparison with state-of-the-art commercial scale similar technologies, options to lower cost, construction cost and schedule estimate); and other supporting elements (guidelines for execution and management of the project), logistical summary, and balance of plant summary, the Environmental Health and Safety (EH&S) assessment; and a Social and Economic Impact (S&EI) assessment. All project milestones, deliverables and success criteria were met. The proposed 5 MWe polygeneration facility being fed from impoundment recovered coal has been shown to be technically feasible. Annual revenues are estimated at $\$ $2.4M from electricity, steam and hydrocarbon production; annual operating expenses are $\$ $5.2M ($\$ $2.9 M in operating expenses, and $\$ $2.4M in indirect expenses). The gasifier facility, as configured during the FEED, will lose money when operating under commercial operating conditions and terms. However, eight options improving the economics can be considered during the detailed design phase to make the facility profitable by taking advantage of the positive differential of revenue to variable operating costs, and reducing the influence of fixed operating costs. Coupled with the findings from the S&EI assessment estimating a total economic impact of $\$ $374M for the proposed polygeneration facility at >$\$ $1.5B, if three additional such projects are implemented, clearly positive economics are demonstrated. No EH&S issues are identified that would prohibit proceeding with the project, although permitting efforts are estimated to take 3-5 years.

01 COAL, LIGNITE, AND PEAT↗

Demonstration of Utility Managed Smart Charging for Multiple Benefit Streams (Final Report)

In the summer of 2020, the U.S. Department of Energy (DOE) awarded funding to Exelon’s Maryland utilities—Baltimore Gas and Electric (BGE), Delmarva Power & Light (DPL), and Potomac Electric Power Company (Pepco)—to implement the Smart Charge Management (SCM) pilot. This initiative aimed to design and implement managed electric vehicle (EV) charging strategies, evaluate the grid impacts of EV charging, and assess the utilities' ability to control EV load based on real-time grid conditions. The SCM pilot explored four aspects for continued improvement: (1) cybersecurity and managed charging functionality testing of two vendor platforms—WeaveGrid (telematics-based) and Shell Recharge Solutions (network-based)—which pursued charge scheduling and optimization through distinct approaches; (2) an analysis by Argonne National Laboratory (ANL) modeling team of three potential SCM enrollment scenarios within BGE and Pepco service territories over the next decade to assess future scalability; (3) employing customer engagement strategies, including surveys and a responsive pricing approach; and (4) the launch and implementation of pilots in Exelon’s Maryland territories in collaboration with WeaveGrid.

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Evidence of Completion of Milestone 3: Experimental Testbed

Construction and deployment of the experimental testbed encountered scheduling delays, and completion was subsequently further delayed by curtailment of LANL operations due to the COVID-19 pandemic. Between March and October, LANL was in a state of “Limited Operations” such that only certain “mission-critical” work was performed with approximately 25% on-site staffing. In spite of this, much of the lab space preparation was executed and the five initial model house” units were constructed and installed during this period. Still, the pace of construction was impacted by difficulty in coordinating personnel and minimizing contact between workers. Currently, LANL is in the mode of “Normal Operations with Maximum Telework,” which continues to limit the availability of on-site personnel. Nevertheless, Milestone 3 is now complete. This document describes the experiment as it is deployed and provides status for each task for this milestone.

99 GENERAL AND MISCELLANEOUS↗