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Modeling & Analysis of a Small Hydropower Plant and Battery Energy Storage System Connected as a Microgrid
Puget Sound Energy (PSE) is a utility with headquarters in Bellevue, WA that provides electric and gas service to customers in many regions of western Washington State. PSE is undertaking the implementation of a battery energy storage system pilot project in Glacier, WA, a small town located in the North Cascade Mountains near Mt. Baker Ski Area. Glacier experiences power outages that are both somewhat frequent and lengthy (roughly 2.8 outages per year with a duration of 7.5 hours average). The primary cause of the outages is faults on a long 55 kV transmission line that serves the town of Glacier from the Kendall substation. This approximately 10-mile long line is shown in the upper left of Figure 1 below. The Kendall-Glacier transmission line extends through an area of heavy forest with few reasonable options for increasing the line’s reliability. The substation in Glacier (also shown on figure below) serves over 1000 customers that are mostly residential but includes over 50 small businesses. The town has approximately 250 year-round residents, and a peak in visitors during the winter ski season when storms are also more likely to cause power outages. Figure 1: Proposed Microgrid in Glacier, WA Given the reliability challenges in Glacier, PSE is assessing the feasibility of a 2MW/4.4MWh battery energy storage system (BESS) that would allow for improved reliability. The BESS would also allow for the ability to investigate other applications for utility-scale energy 5 storage. This energy storage system is being considered for operation in “planned islanding” and “microgrid” mode. “Planned islanding” indicates use of the BESS to provide power to part or potentially all of the load in the town of Glacier during an outage. “Microgrid” indicates utilization (during an outage) of the BESS in parallel with Nooksack Falls Hydroelectric Power Plant, a small (nameplate 1.5 MW/2000 HP) hydro power plant less than 10 miles from the town of Glacier. Nooksack is a run-of river small hydro generation plant with a gross head of 226 ft. The site has a 5-foot diameter penstock which enters the powerhouse and goes into a pelton turbine with six runners on one shaft. It was originally constructed by Stone & Webster in 1906, which makes it the second oldest operating power generation facility in Western Washington. It was placed on the National Register of Historic places in December of 1988. The plant operated until 1997 when a fire destroyed the generator. The project continued operations in 2003 after the replacement of the generator and other updates.
Evaluating Safety Characteristics of Lithium-Ion Battery Systems Through Cascading Thermal Runaway Experiments and Modeling.
Abstract not provided.
Hierarchical Model-Free Transactional Control of Building Loads to Support Grid Services
A transition from generation on demand to consumption on demand is one of the solutions to overcome the many limitations associated with the higher penetration of renewable energy sources. Such a transition, however, requires a considerable amount of load flexibility in the demand side. Demand response (DR) programs can reveal and utilize this demand flexibility by enabling the participation of a large number of grid-interactive efficient buildings (GEB). Existing approaches on DR require significant modelling or training efforts, are computationally expensive, and do not guarantee the satisfaction of end users. To address the aforementioned limitations, this software code considers a scalable hierarchical model-free transactional control approach that incorporates elements of virtual battery, game theory, and model-free control (MFC) mechanisms. The developed approach separates the control mechanism into upper and lower levels. The MFC modulates the flexible GEB in the lower level with guaranteed thermal comfort of end users in response to the optimal pricing and power signals determined in the upper layer using a Stackelberg game integrated with aggregate virtual battery constraints. Additionally, the usage of MFC necessitates less burdensome computational and communication requirements, thus, it is easily deployable even on small, embedded devices. This software code enables the use of residential and small-size commercial buildings to offer a potentially substantial source of ancillary grid services that are currently underutilized. A hierarchical, model-free transactive building control provides a smooth interface between the grid service requests of utilities and the reliable control required by participating buildings. Model-free control, which supports distributed control architecture, will be a more scalable solution that can be deployed in neighborhood-size systems as well as individual buildings. The proposed approach contributes to the body of knowledge on two main aspects. First, it couples the MFC with the game-theoretic control and proposes a scalable model-free transactive control approach. MFC does not require any modeling effort or model training for the various building loads. This is very beneficial since deriving an accurate model for every single unit participating in DR programs and obtaining all the parameters about the units (e.g., thermal coefficients, standby losses) are infeasible. Also, MFC is computationally efficient, easily deployable even on small, embedded devices, and can be implemented in real time. Second, it integrates the concept of virtual battery into DR via the Stackelberg game. The concept of virtual battery enables efficient coordination and aggregation of a large number of flexible GEB with guaranteed thermal comfort of end users.
Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan
It has been shown that shared automated electric vehicles (SAEVs) hold great promise for improving transportation access in urban centers while drastically reducing transportation-related energy consumption and air pollution. Using taxi-trip data from New York City, we develop an agent-based model to predict the battery range and charging infrastructure requirements of a fleet of SAEVs operating on Manhattan Island. We also develop a model to estimate the cost and environmental impact of providing service and perform extensive sensitivity analysis to test the robustness of our predictions. We estimate that costs will be lowest with a battery range of 50-90 mi, with either 66 chargers per square mile, rated at 11 kW or 44 chargers per square mile, rated at 22 kW. We estimate that the cost of service provided by such an SAEV fleet will be $0.29-$0.61 per revenue mile, an order of magnitude lower than the cost of service of present-day Manhattan taxis and $0.05-$0.08/mi lower than that of an automated fleet composed of any currently available hybrid or internal combustion engine vehicle (ICEV). We estimate that such an SAEV fleet drawing power from the current NYC power grid would reduce GHG emissions by 73% and energy consumption by 58% compared to an automated fleet of ICEVs.
Probing lattice defects in crystalline battery cathode using hard X-ray nanoprobe with data-driven modeling
Lattice defects, e.g., dislocations and grain boundaries, critically impact the properties of crystalline battery cathode materials. A longstanding challenge is to probe the meso–scale heterogeneity and evolution of lattice defects with sensitivity to atomic-scale details. Herein, we tackle this issue with a unique combination of X-ray nanoprobe diffractive imaging and advanced machine learning techniques. The domains with different lattice defect configuration within a single-crystalline LiCoO2 cathode particle are faithfully revealed using our approach. We further visualize the rearrangement of grain boundaries and local crystallinity upon mild thermal annealing. Furthermore, these results pave a direct way to the understanding of crystalline battery materials’ response under external stimuli with high fidelity, which provides valuable empirical guidance to defect-engineering strategies for improving the cathode materials against aggressive battery operation.
Impact of automated battery sorting for mineral recovery from lithium-ion battery recycling in the United States
The United States has identified several lithium-ion battery materials as critical for reaching the national emission reduction targets that have been set in accordance with the 2015 Paris Agreement. However, with few natural resources available domestically, there is a rapidly growing focus on the development of a domestic recycling industry to recover these materials from end-of-life batteries. Here, we use the Lithium-Ion Battery Resources Assessment (LIBRA) system dynamics model to evaluate the impact of automated battery sorting technology in terms of the shares of cobalt and nickel that are recovered through recycling. Findings show that automated sorting has clear benefits over manual sorting methods by helping recyclers selectively process high-cobalt batteries. By maximizing cobalt recovery, recycling becomes more profitable and drives greater investment in recycling capacity, resulting in a higher share of nickel and cobalt recovered from EOL batteries over time.
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.
Optimal design and dispatch of a system of diesel generators, photovoltaics and batteries for remote locations
Renewable energy technologies, specifically, solar photovoltaic cells, combined with battery storage and diesel generators, form a hybrid system capable of independently powering remote locations, i.e., those isolated from larger grids. If sized correctly, hybrid systems reduce fuel consumption compared to diesel generator-only alternatives. We present an optimization model for establishing a hybrid power design and dispatch strategy for remote locations, such as a military forward operating base, that models the acquisition of different power technologies as integer variables and their operation using nonlinear expressions. Our cost-minimizing, nonconvex, mixed-integer, nonlinear program contains a detailed battery model. Due to its complexities, we present linearizations, which include exact and convex under-estimation techniques, and a heuristic, which determines an initial feasible solution to serve as a “warm start” for the solver. We determine, in a few hours at most, solutions within 5% of optimality for a candidate set of technologies; these solutions closely resemble those from the nonlinear model. Lastly, our instances contain real data spanning a yearly horizon at hour fidelity and demonstrate that a hybrid system could reduce fuel consumption by as much as 50% compared to a generator-only solution.
A Coupled Electrochemical-Thermal Failure Model for Predicting the Thermal Runaway Behavior of Lithium-Ion Batteries
Thermal runaway is always a troublesome problem that hinders the safe application of high energy lithium-ion batteries. There is an urgent need to interpret the voltage and temperature changes and their underlying mechanisms during thermal runaway, in order to guide the safe design of a battery system. This paper is dedicated to building a coupled electrochemical-thermal model that can well predict the voltage drop and temperature increase during thermal runaway. The model can capture the underlying mechanism of 1) the capacity degradation under high temperature; 2) the internal short circuit caused by the thermal failure of the separator; and 3) the chemical reactions of the cell components that release heat under extreme temperature. The model is validated using by experimental data, therefore the modeling analysis has high fidelity. We employ the model to analyze 1) the capacity degradation under extreme temperature; 2) the influence of the SEI decomposition and regeneration on the thermal runaway behavior; 3) the heat generation by internal short circuit in the thermal runaway process. In conclusion, the discussions presented here help extend the usage of lithium-ion batteries at extreme high temperature (>80 degrees C), and guide the safe design of lithium-ion batteries with less hazard level during thermal runaway.
Flow simulation and analysis of high-power flow batteries
The cost of a flow battery system can be reduced by increasing its power density and thereby reducing its stack area. If per-pass utilizations are held constant, higher battery power densities can only be achieved using higher flow rates. Here, a 3D computational fluid dynamics model of a flow battery flow field and electrode is used to analyze the implications of increasing flow rates to high power density operating conditions. Interdigitated and serpentine designs, and cell sizes ranging from 10 cm 2 to 400 cm 2 , are simulated. The results quantify the dependence of pressure loss on cell size and design, demonstrating that the details of the passages that distribute flow between individual channels and the inlet and outlet have a major impact on pressure losses in larger cells. Additionally, in-cell flow behavior is analyzed as a function of cell size and design. Flow structures are interrogated to show how and where electrode parameters influence pressure drops, and how regions where transport is slow are correlated with the presence of experimentally observed cell degradation.
In-line monitoring of Li-ion battery electrode porosity and areal loading using active thermal scanning - modeling and initial experiment
This work focuses on a new technique called active thermal scanning for in-line monitoring of porosity and areal loading of Li-ion battery electrodes. In this technique a moving battery electrode is subjected to thermal excitation and the induced temperature rise is monitored using an infra-red camera. Static and dynamic experiments with speeds up to 1.5 m min -1 are performed on both cathodes and anodes and a combined micro- and macro-scale finite element thermal model of the system is developed. It is shown experimentally and through simulations that during thermal scanning the temperature profile generated in an electrode depends on both coating porosity (or area loading) and thickness. Here, it is concluded that by inverting this relation the porosity (or areal loading) can be determined, if thermal response and thickness are simultaneously measured.
BATPAC--VERSION 5.0
Argonne National Laboratory has worked on electrochemical energy storage for several decades. The focus on lithium-ion chemistries started in the early 1990s, developing new materials, synthesis methods, and performance characterizations. Sponsored by the U.S. Department of Energy, Energy Efficiency and Renewable Energy, Vehicle Technologies Office (DOE-EERE-VTO), Argonne has led with many advances. The experimental activities were complemented with multi-scale modeling that ranged from the atomic to the system (manufacturing processes and automobiles) level. The Battery Performance and Cost (BatPaC) model is a calculation method based on Microsoft¿ Office Excel spreadsheets that have been developed at Argonne for estimating the performance and manufacturing cost of lithium-ion batteries for electric-drive vehicles including hybrid-electrics (HEV), plug-in hybrids (PHEV) and pure electrics. The effort is being funded by the Vehicle Technology Office (VTO), which is part of the Energy Efficiency and Renewable Energy (EERE) office of the U.S. Department of Energy (USDOE). BatPaC was first developed in 2007, was subsequently peer-reviewed, and it has served Argonne researchers and the greater battery community in studying the impact of material properties on performance at the pack level. With further developments, the model now allows the design of cells and battery packs for automotive applications, to meet performance requirements (power, energy, recharge time), and estimates the cost of manufacturing the designed batteries. Since the cost depends on the materials he design, and the manufacturing process, this bottom-up model/tool enables the user to study their effects. Designed or the lithium-ion cell and battery researcher, BatPaC helps answer many questions by being 1.Transparent in the assumptions made and the method of calculation 2.Capable of designing a battery specifically for the requirements of an application 3.Constrained by the physical limitations that govern battery performance 4. A bottom-up calculation approach to account for every cost factors. BatPaC predicts the impact of promising materials (and their properties) on the performance metrics relevant for the different applications. Researchers can use the specific capacities and the half-cell voltages of a particular set of electrode materials to calculate the mass and volume of a cell to develop a model incorporating the properties of all the other materials in the cell and the design of the cell enclosure. These calculations not only reveal the impact of an improved material but also enable researchers to calculate the material properties that would be needed to meet the performance criteria of a full battery pack. With this information, researchers can provide he battery industry with realistic expectations that will help it more successfully advance novel battery technologies an Applications.
Material and Energy Flows in the Production of Cathode and Anode Materials for Lithium Ion Batteries
The Greenhouse gases, Regulated Emissions and Energy use in Transportation (GREET) model has been expanded to include four new cathode materials that can be used in the analysis of battery-powered vehicles: lithium nickel cobalt manganese oxide (LiNi 0.4 Co 0.2 Mn 0.4 O 2 [NMC]), lithium iron phosphate (LiFePO 4 [LFP]), lithium cobalt oxide (LiCoO 2 [LCO]), and an advanced lithium cathode (0.5Li 2 MnO 3 ∙0.5LiNi 0.44 Co 0.25 Mn 0.31 O 2 [LMR-NMC]). In GREET, these cathode materials are incorporated into batteries with graphite anodes. In the case of the LMR-NMC cathode, the anode is either graphite or a graphite-silicon blend. Lithium metal is also an emerging anode material. This report documents the material and energy flows of producing each of these cathode and anode materials from raw material extraction through the preparation stage. For some cathode materials, we considered solid state and hydrothermal preparation methods. Further, we used Argonne National Laboratory’s Battery Performance and Cost (BatPaC) model to determine battery composition (e.g., masses of cathode, anode, electrolyte, housing materials) when different cathode materials were used in the battery. Our analysis concluded that cobalt- and nickel-containing compounds are the most energy intensive to produce.
Optimization of the lithium/thionyl chloride battery
The progress which has been made in modeling the lithium/thionyl chloride cell over the past year and proposed research for the coming year are discussed. A one-dimensional mathematical model for a lithium/thionyl chloride cell has been developed and used to investigate methods of improving cell performance. During the course of the work a problem was detected with the banded solver being used. It was replaced with one more reliable. Future work may take one of two directions. The one-dimensional model could be augmented to include additional features and to investigate in more detail the cell temperature behavior, or a simplified two-dimensional model for the spirally wound design of this battery could be developed to investigate the heat flow within the cell.
Modeling distributed energy resource aggregations in security constrained unit commitment and economic dispatch
The Federal Energy Regulatory Commission (FERC) recently issued Order 2222, which requires all wholesale electricity markets in the US to allow distributed energy resources (DERs) to participate in the market as aggregated resources. These DER aggregations may be composed of many individual resources that are offered and dispatched by the market as a single entity. We present here a model of a distributed energy resource aggregator (DERA) that is scheduled by a market operator’s security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED). The DERA model includes constraints for battery energy storage systems (BESSs), demand response resources (DRRs), and a simple distributed energy resource (DER). This paper describes a model for each resource type and presents two methods for the DERA to generate market offer curves: a profit-maximizing optimization to compute cost curves and a direct cost algorithm to determine dispatch costs for each resource and combine into cost curves. Once all participating DERAs are scheduled in SCUC/SCED, the model is then modified to dispatch individual DERs to maximize profit or minimize schedule deviation of the DERAs. A simulation of a representative day illustrates the DERA offers, the scheduled generation, and the DERA dispatch. Findings show the potential for unavoidable schedule deviations due to internal DER constraints and due to economic incentives to deviate from the SCUC/SCED schedules. This highlights the importance of DERA offer construction on market efficiency and system reliability. Novel aspects of our approach include: (1) We consider the asymmetry of price incentives impacting DERAs from the wholesale market compared to those impacting consumers from the retail market, as imposed by current regulations and laws. (2) We model aggregate consumer response through statistically parameterizable utility functions rather than a potentially impractical approach of modeling each individual consumer. (3) We show how to use the DERA operational dispatch model to create offers into the wholesale electricity market. (4) We show how DERAs may fail to meet their scheduled dispatch because the market offer format may not permit them to fully express their operational features such as intertemporal costs and constraints to the market.
Mechanical Modeling and Testing of Pouch Cells under Various Loading Conditions
Understanding the mechanical behaviors of batteries is critical to improve battery safety since mechanical failure may directly lead to short-circuits. Nevertheless, mechanical modeling of batteries is challenging since a cell usually contains multiple thin layers with drastically different material properties, and they exhibit different responses under different loading conditions. In this work, we developed a mechanical model for a large-format pouch cell, where the cell is represented by thick shell elements that are not only computationally efficient but also account for different thickness and material properties of individual components. Moreover, the mechanical properties of active materials in electrodes are described by a continuous surface cap model that can capture both compaction and shear deformation modes and can include strain rate effect and damage. Furthermore, to evaluate the model capabilities, we conducted abuse tests under various loading conditions (quasi-static compression, shear and impact). It is shown that the model prediction of load-displacement relationship and failure condition agree with experimental results, which demonstrates that the developed model can capture the mechanical behaviors of a cell in different abuse events. Details of element formulation, material parameters evaluation and test setup are presented. Capabilities, limitations and future directions of model development are also discussed.
Mathematical model of a lithium/polypyrrole cell
A mathematical model to simulate the charge/discharge behavior of a lithium/lithium perchlorate-propylene carbonate/polypyrrole secondary battery cell is presented. The model can be used to gain a better understanding of the behavior of this cell and to provide guidance toward the design of new secondary batteries which utilize an electronically conductive polymer such as polypyrrole as the cathode. The model includes the capability of handling charge and discharge behavior and is used to study the effect of various design parameters on the performance of the cell.