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At least 217 records · Page 12

Start-up of Silo 130 Waste Retrieval at La Hague: first Step Towards Reducing Legacy Inventory - 20020

On June 25, 2019, the first grapple of waste and debris was lifted from Silo 130, one of the most challenging legacy waste storage silos at La Hague. This was the achievement of more than ten years of studies and efforts focused on solving some very unique technical and safety challenges, and on designing an innovative, efficient solution. The waste is from de-cladding materials from past Gas-Cooled Reactor fuel reprocessing operations. It is an unsorted mixture of magnesium cladding pieces, graphite debris, and various other metallic waste types. These materials can be chemically reactive and therefore need specific dispositions for handling and storing. The building is more than 40 years old and does not meet modern standards. French safety authorities have required the silo to be emptied. After about three years of operation, the bulk of this waste will be removed and placed in safe storage, pending the selection of a final conditioning solution. Removal of bottom debris will then be possible. When finished, this operation will bring a conclusion to a significant legacy-related hazard on the site. The silo will then be available for final cleaning and de-activation. This paper will describe the technical, safety, and economical challenges, and the various decisions and optimizations that led to the definition of the process and technology to be implemented. Several innovative features were developed and implemented, in all sections of the project: project organization, progressive approach for the waste disposition strategy, light building design, customized and robust retrieval technology, processing technologies involving the most modern robotic and sorting techniques, storage method... Several of these first-of-a-kind innovative features have been developed and qualified specifically for this application, using the detailed qualification procedure specified for all La Hague projects. The facility was built in less than five years, overcoming various difficulties along the line. Commissioning is now finished with the combined efforts of the project, engineering, start-up, and operating teams assisted by dedicated suppliers. The facility is now ramping-up. The paper will also report on the commissioning and start-up of the facility and describe the first operational results. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Microgrid Fast Charging Station (MFCS) Design Platform Project (Summary Report)

This report documents the important steps and outcomes of the Microgrid Fast Charging Station (MFCS) Design Platform project, executed by XENDEE Corporation and its testing and validation by Idaho National Laboratory (INL). This final summary report builds on the first summary released on April 30th, 2021 and adds the final results from the Hardware in the Loop (HIL) simulations and tests, which have been completed July 14th 2021. With this report XENDEE Corporation and Idaho National Laboratory conclude the first version of the Microgrid Fast Charging Station (MFCS) Design Platform as well as all related tests and validations for two in-depth case studies for islanded and non-islanded operation. The platform itself utilizes XENDEE’s advanced modeling systems and INL’s HIL system to ensure project viability and technical feasibility. It also intelligently maps all cables, transformers, and distributed technology interactions to anticipate and mitigate problems during peak usage or adverse conditions. Finally, the system is designed to optimize dispatch and generation at each time step of the day allowing the Microgrid to take advantage of energy sales to the utility and best manage the charging of an electrical fleet. This allows operators to reliably build bankable Microgrid systems and to operate them to reach the maximum efficiency even under the dynamic needs of electric vehicle fast charging

24 POWER TRANSMISSION AND DISTRIBUTION↗

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Collaborative Decision Approach for Electricity Pricing-demand Response Stackelberg Game

Demand response programs are considered as a valuable resource in smart grids that provide several advantages of load shifting, peak load reduction, mediating intermittency of renewable energy integration, etc. Flexible price-based incentives have been recognized as a critical strategy in motivating and compensating consumers' load adjustment actions for successful implementation of demand response. Game theoretical approaches, especially Stackelberg games are popularly adopted to model the relationship between electricity price and customers' demand response and solved by the classical centralized backward induction (BI) method. However, the BI method generally requires convexity of the follower's model for necessary optimality conditions, and the computational time of any centralized approach increases sharply with larger problem instances. In this paper, the Stackelberg game of electricity pricing-demand response between a distribution system operator (DSO) and load aggregators (LAs) is decomposed based on a collaborative optimization (CO) framework, where each LA is treated as a discipline with its own domain constraints (e.g. building temperature control), while the DSO at the system level tries to reduce the solution discrepancy and guide the searching towards optimality. Several groups of comparison experiments have demonstrated the effectiveness of the proposed collaborative decision approach in solving the demand response game.

Chen, Yang↗

Development of process parameters and post-build conditions for qualification of LPBF 316 SS

To harness the potential of laser powder bed fusion (LPBF) 316H stainless steel (SS) for use in advanced nuclear reactors, extensive research efforts are needed to develop optimal laser processing parameters and appropriate heat treatments, taking into account various manufacturing platforms and locations. Furthermore, it is crucial to assess the material properties in environments relevant to reactor operating conditions. In collaboration with Oak Ridge National Laboratory (ORNL) and Los Alamos National Laboratory (LANL), Argonne National Laboratory (ANL) is dedicated to gaining insights into how the manufacturing process and post-build treatments impact the performance of LPBF 316H SS. This report provides an overview of ANL's research findings for FY23, focusing on LPBF 316H SS produced using a Renishaw AM400 laser system. Specifically, our research has concentrated on three key areas: 1) Optimum laser processing parameters: Leveraging the high-throughput printing technology, we systematically varied the laser power, exposure time and point distance within the same build. By measuring the as-printed porosity, we identified an optimum printing parameter window that produced materials with near-complete density; 2) Post-built treatment development: Materials printed with the optimum laser parameters underwent treatments including stress relief, solution annealing, and hot isostatic pressing. Subsequently, we fabricated tension, creep, and fatigue specimens from materials subjected to these different conditions. Over the next year, a series of scoping tests will be conducted to facilitate the selection of the most suitable post-build treatment condition; 3) Thermal aging effects on microstructure and properties: thermal aging at 550°C, 650°C and 750°C was conducted on LPBF 316H SS specimens up to 2500 h. Microstructural characterization was performed with electron microscopy, and the evolution of the dislocation cell structures and secondary phases was studied. Microhardness tests and tension tests were conducted to quantify changes in mechanical properties. The results revealed that the aged LPBF 316H SS exhibited a high density of Cr-rich and Mo-rich fine precipitates within grains due to the presence of a high density of dislocations and the globally distributed dislocation cell structures, which served as heterogeneous nucleation sites for secondary phases. Along grain boundaries, a Mo-Cr-rich phase, observed in 750°C-aged conditions, displayed significant thermal coarsening. Throughout the aging process, various mechanisms, including stress relaxation, dislocation cell structure recovery, solution hardening, and precipitation hardening, competed to influence materials strength. These results contribute towards establishing the technical basis for qualifying LPBF 316H SS for advanced nuclear reactor applications.

36 MATERIALS SCIENCE↗

Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications

With building electric demand becoming increasingly dynamic, and a growing percentage of intermittent renewable power generation from solar photovoltaics and wind turbines, the power grid is facing increasing challenge to manage the real time balance between the supply and demand. With advancements in smart sensing and metering, smart appliances, electric vehicles, and energy storage technologies, demand side management of residential buildings can help the grid to improve stability by optimizing flexible loads. This paper reviews recent studies on residential building demand side management, with a focus on characterization and quantification of energy flexibility covering various types of flexible loads, metrics, methods, and applications. The reviewed studies showed four levels of applications: building level (45%), district or community level (29%), system level (19%), and building sector level (7%). Shifting loads is the dominant flexibility type in 60% of applications, followed by shedding (19%), generation (16%), and modulating (6%). Depending on the technology and application scope, flexible operations have a wide range of performance, with peak power reductions of 1%~65%, energy savings up to 60%, operational cost reduction of 1%~48%, and greenhouse gas emission reductions of up to29%. More than half (51%) of the studies employed control strategies to achieve flexibility; among those 72% used optimal controls, while 28% used rule-based controls. About 58% of the studies used mathematical formulation to quantify energy flexibility. Most studies were based on simulation, while less than 15% of the studies had measurements from experiments or field tests. The review reveals research opportunities to address significant gaps in the existing literature: (1) establishing a common definition and performance metrics for energy flexibility of buildings that are technology and application agnostic, (2) developing an ontology to standardize representation of flexibility resources for interoperability, (3) integrating occupant impacts into the quantification and optimization of energy flexibility, and (4) developing requirements and credits of energy flexibility in building energy codes and standards. Findings from the review can inform future research and development of energy flexible buildings which are essential to a reliable and resilient power grid.

Li, H↗

Modeling and Validation of a Residential Multi-Functional Variable Refrigerant Flow Heat Pump System with Heat Recovery

To bridge the existing gap in modeling the variable refrigerant flow heat pump systems with heat recovery (VRFHR), we developed a suite of dynamic VRFHR system models in Modelica. These models are specifically tailored for residential multi-functional VRFHR (MF-VRFHR) applications, including space conditioning and domestic hot water (DHW) heating, utilizing both the TIL library for HVAC equipment and the Buildings library for thermal load calculations. The development comprises essential component models, including the newly developed heat recovery unit (HRU), along with system models that integrate the heat pump system and building envelope. These system models accommodate various operational modes such as heating-only, cooling-only, and heating-recovery (including heating-dominant and cooling-dominant) modes. Furthermore, we propose an efficient optimization-based model calibration method that identifies critical model parameters while utilizing a small amount of data obtained from either real systems or manufacturer's specifications. We demonstrate the effectiveness of these models and the proposed calibration method for a MF-VRFHR system installed in Richland, WA. The developed models are calibrated and validated using data collected under different operational modes during both heating and cooling seasons. The results show that the models capture the system dynamics and achieve high accuracy, with the coefficient of the variation of the root-mean-square-error less than 15% for variables such as outdoor unit power consumption, compressor speed, space temperature and DHW temperature. The validated models serve as a reliable representation of the MF-VRFHR system, facilitating the development and validation of optimized controls needed to realize the full benefits of integrated heat pump systems. Future research will utilize these models to develop advanced controls and optimize system performance for improved energy efficiency and demand flexibility.

Modeling, Variable refrigerant flow (VRF) systems,↗

Network Optimization of the Electrosynthesis of Chemicals from CO2

Carbon dioxide electroreduction (ECO2R) is gaining attention due to its capacity to mitigate CO2 emissions while using electricity that would otherwise be curtailed. Its foreseeable industrial implementation requires of holistic methods to assess the technological and economic performance of ECO2R processes and integrate them in current chemical supply chains and power systems. Here, we combine techno-economic assessment and mathematical programming to find the optimal paths to electroreduce CO2 into valuable chemicals under variable electricity prices. The proposed approach is tested with a case study addressing the CO2 capture from flue gas or direct air and its electricity-powered reduction into carbon monoxide, formic acid or multi-carbon compounds. The results obtained demonstrate the ability of the framework to build ECO2R networks and provide operation profiles that respond to fluctuating electricity prices.

carbon dioxide↗

Seamlessly Fuel Flexible Heat Pump with Optimal Model-based Control Strategies to Reduce Peak Demand, Utility Cost and CO2 Emission

This research develops a novel hybrid fuel heat pump system for space heating of residential and small commercial buildings with built-in optimization and control. Whereas conventional dual fuel systems either run on gas or electricity at any given moment, the proposed seamlessly fuel flexible heat pump (SFFHP) simultaneously consumes gas and electricity and continuously optimizes the proportion of each. The building air flows across the heat pump condenser first and then flows across the furnace coil, and this reduces the heat pump temperature lift. The SFFHP delivers energy savings by allowing each subsystem (gas furnace and electric heat pump) to operate where it performs best to improve energy efficiency, minimize energy cost, and minimize carbon footprint. The capacities of the electric heat pump and gas furnace are continuously adjusted based on ambient conditions, utility price signals, and marginal grid emission signals. An optimal model predictive control strategy was developed with the goal of minimizing utility cost and minimizing CO2 emission. Two case studies were conducted to simulate the performance of SFFHP during the heating season in Chicago and Los Angeles, respectively. Compared with a conventional electric heat pump, SFFHP yields 33% utility cost reduction and 49% CO2 emission reduction in Chicago. Similarly, it achieves 23% utility cost reduction and 17% CO2 emission reduction in Los Angeles. Case studies demonstrate that SFFHP can deliver significant reductions in peak demand, utility cost, and CO2 emission. Due to the hybrid fuel nature of this novel equipment, user comfort will always be maintained. The fuel flexibility makes it an attractive option for demand response programs.

Li, Zhenning↗

Nodal capacity expansion planning with flexible large-scale load siting

We propose explicitly incorporating large-scale load siting into a stochastic nodal power system capacity expansion planning model that concurrently co-optimizes generation, transmission, and storage expansion. The potential operational flexibility of some of these large loads is also taken into account by considering them as consisting of a set of tranches with different reliability requirements, which are modeled as a constraint on expected served energy across operational scenarios. We implement our model as a two-stage stochastic mixed-integer optimization problem with cross-scenario expectation constraints. To overcome the challenge of scalability, we build upon existing work to implement this model on a high performance computing platform and exploit scenario parallelization using an augmented Progressive Hedging Algorithm. The algorithm is implemented using the bounding features of mpisppy, which have shown to provide satisfactory provable optimality gaps despite the absence of theoretical guarantees of convergence. We test our approach and assess the value of this proactive planning framework on total system cost and reliability metrics using realistic testcases geographically assigned to San Diego and South Carolina, with datacenter and direct air capture facilities as large loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Game Theoretic Orchestration for Cooperation among Power Distribution System Applications

The evolving transformation with the proliferation of distributed energy resources and advanced metering, necessitates advanced distribution systems to integrate and orchestrate a large number of grid-edge devices while also serving multiple system-level objectives such as resilience, decarbonization, equity and other system mandates. The parallel deployment and control of resources towards achieving diverse objectives may lead to conflicts between applications that want to control overlapping sets of device setpoints, potentially leading to oscillatory behavior and suboptimal performance. This work aims at leveraging game theoretic framework to drive cooperative behavior among competitive applications. The work proposes a weighted-consensus based game design to facilitate conflict resolution through consensus-building iterations for modular platform. Simulation-based evaluation on a sample test system demonstrates the performance the proposed deconfliction strategy in resolving operational conflicts and achieving close-to-optimal trade off among the applications. Results also compare the proposed strategy with a distribution optimization approach and illustrate it effectiveness in diverse apps regardless of their design while also incentivizing apps with flexible design.

Advanced distribution operations, cooperation, app↗

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Sensor impacts on building and HVAC controls: A critical review for building energy performance

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

Building control↗

Operation and performance of VRF systems: Mining a large-scale dataset

The energy consumption of air-conditioning systems has gained increasing attention as it contributes significantly to the global building energy use. The variable refrigerant flow (VRF) system is a common air-conditioning system applied widely in residential and office buildings in China. Understanding the actual operation and performance of VRF systems is fundamental for the energy-efficient design and operation of VRF systems. Previous research on VRF system operation used either limited field data covering certain building types and climate zones or used a questionnaire to obtain a larger dataset. However, they did not capture the wide applications of VRF systems quantitatively across all building types, climate zones, and operating conditions. To fill this gap, statistical and clustering analysis was conducted on the newly proposed key performance indicators of approximately 287,000 VRF systems for residential and commercial buildings in all five climate zones in China. In this work, the main findings are: (1) VRF systems are mainly used for cooling in all climate zones in China; (2) among all building types, the duration of use is lowest in residential buildings and highest in hotels and medical buildings; (3) the distribution of the ideal VRF cooling coefficient of performance (COP) is similar across all climate zones and building types; whereas the COPs of ideal VRF heating in the Severe Cold region and Cold regions are lower than those in other climate zones; and (4) partial load operations for VRF systems are common in residential buildings and office buildings due to the part-time-part-space operation mode. These findings can inform the actual application of VRF systems in China, supporting the design, operation, industry standard development, and performance optimization of VRF systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal environmental and economic performance trade-offs for fifth generation district heating and cooling network topologies with waste heat recovery

Network topology greatly influences both the economic and environmental performance of fifth generation district heating and cooling (5GDHC) systems. In this study the optimal trade-offs between the environmental and economic performance of 5GDHC network topologies for a five-building district with waste heat recovery were explored. A life cycle assessment method was used to calculate the total life cycle CO 2 emissions (LCCO2) associated with the installation and operation of various network topologies. Twelve months of empirical data from a data center cooling system were analyzed to assess its suitability for integration into a 5GDHC system. The most suitable method for utilizing this waste heat was selected based on the ambient loop warm pipe setpoint, waste heat temperature, and district energy system configuration. A multi-objective optimization algorithm was used to select the 5GDHC network topology that provided the optimal trade-off between LCCO2 and life cycle cost (LCC). A trade-off parameter was employed to weigh the importance of each objective in the selection process. The results showed waste heat from the data center was suitable for integration into the 5GDHC system due to its availability and consistent temperature profile. When return temperatures of 25 °C or higher were available from the liquid-cooled system, direct pre-heating of the ambient loop warm pipe was found to be the most effective waste heat integration method. The selection of the network topology that provided the optimal trade-off between LCCO2 and LCC (optimal trade-off topology) was highly dependent on factors such as fuel prices, CO 2 prices, electricity CO 2 emissions factors, availability of waste heat, embodied CO 2 emissions associated with network installation and network infrastructure costs. Optimal trade-off topologies produced substantial LCCO2 reductions relative to corresponding LCC increases. LCCO2 reduction to LCC increase ratios from 5.78 to 117.79 were identified with CO 2 offset costs ranging from 4.77 to 60.08 ($/tCO 2 e).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Simon, Donald L.↗

Grid-interactive Efficient Buildings Projects Summary

Through its grid-interactive efficient building (GEB) research, DOE’s Building Technologies Office seeks to build on existing energy-efficiency efforts to optimize the interplay among energy efficiency, demand response, behind-the-meter generation and energy storage to increase the flexibility of demand-side management. BTO envisions a future where buildings dynamically operate as part of a low cost, reliable electricity grid while meeting the needs and expectations of building occupants.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Low-Cost, Easy-To-Integrate and Reliable Grid Energy Storage System with 2 nd Life Lithium Batteries

Batteries retired from electric vehicles have the potential to extend their service as low-cost stationary energy storage systems. However, disperse battery state of health (SOH) and nonuniform battery characters often lead to compromised battery performance and reliability, which greatly hinder their adoption. A Heterogenous Unifying Battery (HUB) system is proposed to stage 2 nd life battery bricks for a period, and enable them to attain improved SOH uniformity, performance, and reliability before being sold for 2 nd life applications, while simultaneously providing grid services. It may offer a technically and economically advantageous solution for the broad utilization of 2 nd use batteries. The goal of this project was to develop the hardware and software that enables the key functions of the HUB system. The first achievement of the project was the development of a 1kW scale proof-of-concept (POC) system, which comprises (i) a modular plug-n-play DC-DC power converter matrix with isolated series output connections to achieve fully independent control of energy flow to each of the connected battery units at low voltage; (ii) enhanced model based control that drives each batteries’ SOH towards uniformity while collectively providing grid energy storage services; and (iii) comprehensive procedures to perform battery diagnostics and prognostics. The second achievement was the development of a 100kW scale HUB system and demonstrated its performance of re-establishing battery SOH uniformity through a period of battery cycling operation. The final HUB system incorporates six DC-DC power converter matrices paired with six battery bricks. Hot swapping of a single battery brick while maintaining consistent system power was demonstrated and system operation was validated to be capable of implementing the approved grid duty cycle and of balancing and conditioning the battery bricks. Through the course of the project, the team optimized the building-block design, form-factors, and adjusted life balancing control. An up-sized 250kW Scale was developed and deployed in October 2022 with pack-level battery form factors, see photo in Figure 1 The third achievement of the project was to perform a techno-economic analysis in order to better understand the cost and revenue potentials in this new “recondition-then-resell" value proposition. The final TEA quantified the economics of new Li-ion batteries as well as second-life batteries processed via reconditioning and traditional binning. Results showed the reconditioned second-life batteries in this project to be economically favorable and viable in grid energy storage markets. The TEA results were published in the Applied Energy journal. The fourth achievement of the project was to deliver a tech-to-market plan for the HUB system that includes funding, IP, and manufacturing strategies. The final T2M plan outlines a business strategy in which the HUB provides a B2B service to EV companies as an alternative to battery recycling that can prepare batteries for 2nd life applications. A company named Smartville Inc. was founded to carry on the commercialization, funding, and technical IP licensing activities of the OPEN project.

25 ENERGY STORAGE↗