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DOE OSTI2022

Dynamic Economic Dispatch Considering Transmission–Distribution Coordination and Automatic Regulation Effect

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately; the transmission–distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission–distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Pumped Storage Hydropower (PSH) FAST Commissioning Prize Technical Analysis

The US energy landscape has undergone major changes over the past 10 years and will continue to see significant changes in future decades as the power grid increases its reliance on variable renewable energy resources. Because of the inherent variability of these resources, renewable energy growth may require additional energy storage capacity to provide flexible load-following capabilities and other grid services that can quickly adjust to changes in energy demand and generation. Pumped storage hydropower (PSH)—one such energy storage technology—uses pumps to convey water from a lower reservoir to an upper reservoir for energy storage and releases water back to the lower reservoir via a powerhouse for hydropower generation. PSH facility pump and generation cycling often follows economic and energy demand conditions. Across the United States, 43 PSH facilities are in operation and 55 projects are in various permitting or licensing stages. Altogether, the 43 operational projects provide the wide majority (95%) of utility-scale electricity storage in the United States. These facilities also provide significant power and nonpower grid benefits, including large-scale electrical system reserve capacity, grid reliability support, and electricity supply-demand balancing through quick-response capabilities and operational flexibility. PSH systems can accomplish these at a scale (e.g., size) and cost that makes these systems highly attractive from a technical standpoint. Although these research concepts are still in their infancy, they demonstrate promising potential as future PSH energy storage technologies. Although PSH has many advantages, development in the United States has effectively stalled since the 1990s, partially because of the magnitude of project costs and financing interest during development and construction, the length of time from project investment until project revenue begins, permitting challenges, construction risks, competition from other storage technologies (e.g., batteries, hydrogen storage), and electricity market evolution and uncertainty. In short, the time, cost, and risk associated with modern PSH development have resulted in limited growth in the United States recently, despite the growing energy storage demand stemming from increased wind and solar power deployment. Technology innovation is needed to help reduce PSH commissioning time, cost, and risk, particularly during the post-licensing phase of project development. To address challenges facing the PSH industry and to improve PSH commissioning timelines, the US Department of Energy (DOE) Water Power Technologies Office (WPTO) initiated the PSH Furthering Advancements to Shorten Time to (FAST) Commissioning Prize project.

13 HYDRO ENERGY↗

DOE OSTI2021

Exploring filamentous fungi depolymerization of corn stover in the context bioenergy queuing operations

Recalcitrance of lignocellulosic feedstocks to depolymerization is a significant barrier for bioenergy production approaches that require conversion of monomeric carbohydrates to renewable energy sources. This study assesses how low-cost modifications in the feedstock supply chain can be transformed into targeted pretreatments in the context of the entire bioenergy supply chain. The aim of this research is to overcome the physiochemical barriers in corn stover that necessitate increased severity in conversion in terms of chemical loading, temperature, and residence time. Corn stover samples were inoculated with a selective (Ceriporiopsis subvermispora) and non-selective (Phaenarochaete chrysosporium) lignin degrading filamentous fungal strains, then stored aerobically to determine the working envelope for fungal pretreatment to achieve lignin degradation. Dry matter loss and gross chemical makeup of corn stover varied by the length of treatment (2 and 4 weeks) and by the moisture content of the treated corn stover samples (40 and 60%, wet basis). Dry matter loss in P. chrysosporium inoculated biomass was elevated compared to the C. subvermispora inoculated biomass; however, treatment also induced additional chemical composition changes suggestive of depolymerization. Scanning electron microscope images reveal hyphae attached within cell lumen and suggest structural changes within P. chrysosporium treated corn stover after 60% moisture storage. These results highlight that fungal treatment approaches must balance loss of convertible material with the potential for reduction in recalcitrance. Techno-economic assessment (TEA) of fungal pretreatment in a short-term queuing system indicated the viability of this approach compared to conventional queuing operations. The total queuing system cost was estimated at $\$$1.65/tonne of biomass stored. After applying the credit of $\$$1.48/tonne from energy savings in the conversion phase using fungal pretreated biomass, the total system cost was $0.80 lower than traditional biomass queueing approach. While the TEA results suggested that treating biomass with C. subvermispora is the most economically viable storage method in the designed fungal-assisted queuing system, future research should focus on additional fungal depolymerization such as those observed in the P. chrysosporium inoculated biomass.

09 BIOMASS FUELS↗

DOE OSTI2023

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Heat Loss Characteristics and Energy Use of Piperazine with the Advanced Stripper (PZAS) at the UT-SRP Pilot Plant

Heat duty and heat loss were measured at the pilot plant at UT Austin. Heat loss was measured with energy balances using water. Heat loss was studied using surface temperature measurements over 68 different locations at the pilot plant. Surface temperature measurements indicated that bare metal surfaces were the primary source of heat loss from the pilot plant. Heat loss from bare metal surfaces was at least 50% controlled by natural convection and in many cases was as high as 75% natural convection controlled. Measured heat loss at the pilot plant was 20100 BTU/hr and overall heat loss did not show any dependence on the heat rate of the plant. Compared to PZAS™ at the National Carbon Capture Center, heat loss relative to heat rate was higher at 38%. The relative heat loss at the pilot plants was found to decrease by 20% per MW of added capacity. Measured net heat duty was found to be dependent on measured lean loading and cold rich bypass flow rate. Measured net heat duty was between 2.2 and 2.4 GJ/tonne at an optimum lean loading of 0.2–0.21 mol/mol. Data reconciliation by Aspen Plus® Data Fit™ underpredicted CO2 flow rate by 20% due to an overprediction of lean loading by 19%, indicating a necessary change in thermodynamic parameters in the model. This resulted in an over prediction of heat duty by 33% on average.

Amine scrubbing, stripper, energy requirement, hea↗

DOE OSTI2025

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma: Preprint

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of a conceptual microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

DOE OSTI2024

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

Solar energy has the potential to be a core energy resource for the southeastern United States. To better understand the implications of higher levels of solar PV (27%-43% of total generation capacity) and electricity storage (13%-49% of peak load) would affect electricity system reliability, costs, and operations in the U.S. Southeast, this study sought to address two main questions. First, how would higher levels of solar PV and electricity storage impact the costs, reliability, and operations of electricity systems in the Southeast in 2035? Second, at different levels of solar PV and electricity storage, what are the benefits of operational coordination among utilities in the Southeast, through more efficient regional dispatch and sharing operating reserves? To answer these questions, the study used detailed capacity expansion and dispatch modeling to develop and examine 15 scenarios with different levels of solar PV, electricity storage, and operational coordination, focusing on the year 2035. The study also evaluates the benefits of operational coordination among utilities through more efficient regional dispatch and reserve sharing, at different levels of solar and storage. The study focuses on five balancing regions that cover Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, and parts of Mississippi and Missouri.

14 SOLAR ENERGY↗

DOE OSTI2024

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

14 SOLAR ENERGY↗

DOE OSTI2020

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗

DOE OSTI2023

Bat Smart Curtailment: Efficacy and Operational Testing

Curtailment, or blanket curtailment, is a leading method to mitigate the impacts to bats from operating wind turbines. Although this strategy results in considerable decreases in bat fatalities, it also results in decreased energy production. In 2019, Natural Power was awarded funding by the Department of Energy to assess the readiness of the informed smart curtailment technology, EchoSense (formerly referred to as Detection and Active Response Curtailment, [DARC]). The research undertaken by this project expands the understanding of alternative methods, known as smart curtailment, to maintain a reduction in bat fatalities while simultaneously recovering lost energy associated with blanket curtailment. The overall project was composed of three major tasks; Task 1 was focused on cybersecurity compliance of the EchoSense system in accordance with the North American Electric Reliability Corporation Critical Infrastructure Protection (“NERC CIP”) standards, Task 2 assessed the mechanical loads exerted on turbines when operating under a smart curtailment regime, and Task 3 assessed the efficacy of the EchoSense system at an operational wind farm. Regarding Task 1, an external review by the National Renewable Energy Laboratory determined that the EchoSense system did not create any new cybersecurity weaknesses and was compliant with the NERC CIP standards. As a result of this process, Natural Power developed some best practices (10.1) for wind- wildlife technology developers. In conjunction with the National Renewable Energy Laboratory, the results (10.2) of the loads testing demonstrated that the periodic curtailment and release of turbines by the EchoSense system did not have any detrimental impact on the mechanical components of a wind turbine (Task 2). During the late summer to fall of 2020 and 2021, Natural Power demonstrated that the use of the EchoSense smart curtailment system resulted in no significant difference in bat fatalities compared to blanket curtailment with cut-in speeds at 6.9 m/s (2020) and 5.0 m/s (2021) while resulting in a significant difference in decreased lost energy (Task 3). This translates to an average of 41% (2020) and 56% (2021) reduction in per turbine energy loss compared to blanket curtailment. The reduction in energy loss that would have been achieved by EchoSense curtailment compared to blanket curtailment, if applied across all 69 turbines, is roughly equivalent to having an additional turbine on site. These results are notable for finding a balance between the environmental impact of wind energy and the economic feasibility in energy production associated with mitigating that impact. https://www.naturalpower.com/us/expertise/service/engineering-operations/echosense

17 WIND ENERGY↗

DOE OSTI2022

Uranium Oxide Elutriation at Higher Flow Rates and Longer Times

This work supports the recovery of high-assay low-enriched uranium (i.e., U enriched in 235 U to >5% and <20%) from used nuclear fuel. One step includes elutriating triuranium octoxide (U 3 O 8 ) from a fluidized bed of alumina (Al 2 O 3 ) that fills the main reaction chamber. The experiments outlined in this report assessed the effects of the time and flow rate on the elutriation of U 3 O 8 powder from the reaction vessel. Testing at Oak Ridge National Laboratory (ORNL) was performed in a one-fourth scale experimental apparatus based on a pilot-scale system, which is the Material Recovery Pilot Plant (MRPP) at Idaho National Laboratory (INL). The experimental system comprises a supply of pressurized nitrogen (N 2 ), a gas heater, the reaction vessel, a knock-out pot, and a water trap where elutriated particles are collected for sampling. An Al 2 O 3 fluidized bed is contained within the reaction vessel. A bed of Al 2 O 3 with a nominal size of 180 µm and U 3 O 8 with a nominal size of 7 µm was fluidized at 2 different flow rates so the U 3 O 8 physically separated from the bed. The apparatus was simple and had no valves or sharp bends downstream from the reactor. The flow exited the reactor through a side port at the top. The flow passed through a knock-out vessel before the flow was passed through a bubbler to capture the U 3 O 8 . Seven tests were completed with U 3 O 8 using an elutriating gas of N 2 heated to 200°C. Tests were performed with bed loadings that comprise 25.0 g of U 3 O 8 , or 3.6 wt% of the bed mass. Except for one test performed at 12 SLPM, the gas flow rate through the bed for the other experiments was set at 10 SLPM as measured by the mass flow meter. Linear velocities through the bed were calculated as 28 and 34 cm/s, or 0.9 and 1.1 ft·s -1 . The duration of the tests ranged from 20 to 180 min, and one test had a flow cycled between 0 and 5 SLPM every 5 min for 40 min. The testing successfully demonstrated elutriation of U 3 O 8 from the fluidized bed as up to a 100% of the U 3 O 8 was transferred out of the bed. The removal of U 3 O 8 had a logarithmic dependence on flow rate. The design changes made the apparatus easier to clean, and the mass balances were better than those used in previous studies. Some elutriated Al 2 O 3 collected in the tubing that connected the reactor to the knock-out pot, but the amount of Al 2 O 3 was minimal for 10 SLPM. The flow at 12 SLPM showed considerable transport of Al 2 O 3 bed material into the reaction-vessel headspace and the transfer line to the knock-out pot.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Floating Offshore Wind US Manufacturing and Commercialization (CRADA Final Report)

Create a detailed manufacturing, assembly, load-out, transportation, upending, turbine integration, and offshore transportation plan for a hypothetical project in one of the California lease areas off the central coast. Develop a detailed schedule and cost estimation for each step of the process and compare with conventional floating platform designs.

17 WIND ENERGY↗

DOE OSTI2020

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Shape Matters: Understanding the Effect of Electrode Geometry on Cell Resistance and Chemo-Mechanical Stress

Rechargeable batteries that incorporate shaped three-dimensional electrodes have been shown to have increased power and energy densities when compared to a conventional geometry, i.e. a planar cathode and anode that sandwich an electrolyte. Electrodes can be shaped to enable a higher active material loading, while keeping ion transport distances small. However, the relationship between electrical and mechanical performance of shaped electrodes remains poorly understood. Many electrode designs have been explored, where the electrodes are individually shaped or intertwined, and advances in manufacturing and shape/topology optimization have made such designs a reality. Here, we explore sinusoidal half cells and interdigitated full cells. First, we use a simple electrostatics model to understand the cell resistance as a function of shape. Here we focus on low-temperature conditions, where the electrolyte conductivity decreases relative to that of the electrode; here, LiPF 6 EC:DMC electrolyte and MnO 2 electrode are considered. Next, we use a chemo-mechanics model to examine the stress that arises due to intercalation-driven volume expansion. We show that shaped electrodes provide a significant reduction in resistance in low-temperature conditions, however, they exhibit unfavorable stress concentrations. Overall, we find that the fully interdigitated electrodes may provide the best balance with respect to this resistance-stress trade-off.

25 ENERGY STORAGE↗