Multiscale Optimization of Integrated Energy Systems Using Machine Learning Models for Market Interactions
The presentation was delivered at the 2022 American Institute of Chemical Engineers (AIChE) annual meeting.
Ghouse, Jaffer↗
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Integrated energy harvesting transceivers and transmitters with dual-antenna architecture for miniaturized implants and electrochemical sensors
Systems and methods for utilizing a small form-factor, wirelessly powered transceiver are disclosed. In one embodiment, a wireless powered transceiver includes a receive antenna configured to receive a receive signal, a transmit antenna configured to transmit a transmit signal, a power harvesting system including a rectifier circuit configured convert radio frequency energy from the receive signal into DC (direct current) voltage, and a power management unit (PMU) configured to set the operating mode and biasing condition of the receive and transmit circuitry blocks and provide DC voltage from the receive circuitry block to the transmit circuitry block to maintain a minimum voltage, a receiver circuitry block configured to provide energy from the receive signal to the power harvesting system, and a transmitter circuitry block including a data modulator circuit, the data modulator circuit configured to generate the transmit signal using DC voltage received from the power management unit.
Babakhani, Aydin↗
Advanced Research on Integrated Energy Systems (ARIES)
ARIES is the nation's most advanced research platform to support the transition to a clean energy future. This presentation, part of the PEGI Industry Workshop, 24-25 May 2023, discusses ARIES.
ARIES↗
Multiperiod Conceptual Design of Integrated Energy Systems with Market Interaction Surrogate Models
The presentation highlights the market analysis capabilities, both price-taker analysis and the novel market surrogate models approach, applied to optimal design of electricity and hydrogen co-production systems. The research findings were presented at the 2023 AIChE Annual Meeting.
Chen, Xinhe↗
Integrated Energy Systems Modeling and Simulation
This presentation covers IES modeling and simulation tools, with a specific focus on how physical modeling is linked to technoeconomic analysis.
08 HYDROGEN↗
Integrated energy harvesting transceivers and transmitters with dual-antenna architecture for miniaturized implants and electrochemical sensors
Systems and methods for utilizing a small form-factor, wirelessly powered transceiver are disclosed. In one embodiment, a wireless powered transceiver includes a receive antenna configured to receive a receive signal, a transmit antenna configured to transmit a transmit signal, a power harvesting system including a rectifier circuit configured convert radio frequency energy from the receive signal into DC (direct current) voltage, and a power management unit (PMU) configured to set the operating mode and biasing condition of the receive and transmit circuitry blocks and provide DC voltage from the receive circuitry block to the transmit circuitry block to maintain a minimum voltage, a receiver circuitry block configured to provide energy from the receive signal to the power harvesting system, and a transmitter circuitry block including a data modulator circuit, the data modulator circuit configured to generate the transmit signal using DC voltage received from the power management unit.
Babakhani, Aydin↗
Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems
Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
INL’s Integrated Energy Systems – Supporting Scaling R&D from kW to MW
ARPA-E Nuclear Heat for Chemical Process Industry Day - Lightening Introduction
42 - ENGINEERING↗
A reduced order sulfuric acid decomposition model for a nuclear-powered hybrid sulfur cycle
A reduced order model of sulfuric acid decomposition within a bayonet chemical reactor was developed to support the U. S. Department of Energy Integrated Energy System program, and address the lack of knowledge in scaling and integration for joint chemical and nuclear processes. Sulfuric acid decomposition within a bayonet reactor was modeled to provide chemical and thermodynamic data relevant to advanced nuclear reactor-driven integrated energy systems based on desired operational scale and operational conditions. The temperature range required for high-temperature advanced nuclear reactor integrated energy systems, 750-850 °C, was shown to produce reasonable agreement (within a few percent relative error) with past models and experimental data, and yielded good efficiency results for bayonet reactor operations. The results of the reduced order model agreed with previous work from Savannah River National Labs within a maximum of 3.4% error on the decomposition of sulfur trioxide, and on previous Hybrid Sulfur flowsheets from Gorensek and Summers that showed operational temperature, pressure, and composition ranges for efficiency which made the Hybrid Sulfur cycle competitive with water electrolysis. Here, the agreement with previous high-fidelity models provided a framework for future Integrated Energy System grid evaluations with an advanced nuclear reactor and large-scale hydrogen production using a mathematical model to represent chemical operations.
08 HYDROGEN↗
Combining total energy and energy industrial center concepts to increase utilization efficiency of geothermal energy
Integrating energy production and energy consumption to produce a total energy system within an energy industrial center which would result in more power production from a given energy source and less pollution of the environment is discussed. Strong governmental support would be required for the crash drilling program necessary to implement these concepts. Cooperation among the federal agencies, power producers, and private industry would be essential in avoiding redundant and fruitless projects, and in exploiting most efficiently our geothermal resources.
Bayliss, B. P.↗
Integrated North American energy markets under different futures of cross-border energy infrastructure
Not Available
Siddiqui, Sauleh↗
Simultaneous Design and Operation of a Coal-Fired Hybrid Energy System with Integrated Thermal Energy Storage
This final report describes novel capabilities developed as part of DISPATCHES, Design Integration and Synthesis Platform to Advance Tightly Coupled Hybrid Energy Systems, for designing hybrid energy systems (HES) a.k.a. integrated energy systems (IES) in the context of a larger electricity market. Capabilities are demonstrated on a case study with fossil-based power coupled to a molten salt thermal energy storage system.
20 FOSSIL-FUELED POWER PLANTS↗
FY22 Economic Impact Summary
In 2022, Idaho National Laboratory was one of the state’s top employers (sixth overall). INL directly employed a total of 5,460 positions, a 4% growth from the previous year. The large growth of Idaho’s economy between 2021 and 2022 means INL’s economic impact on the state has also deepened. Dollars that INL has brought into the state tend to stay and circulate longer, facilitating increased impacts and growth rates for the state. INL, along with the other 16 national labs housed under the Department of Energy (DOE), perform research focused on: nuclear energy, integrated energy systems (such Summary Results as microgrid, battery and environmental research), and national security. This study evaluates the economic activity of INL within the economy of Idaho. This study estimates the total economic impact generated by INL apart from any other DOE or Department of Defense operations within the state. Total operational impacts of INL in 2022 amounted to $\$ $3.38 billion in output, $\$ $2.42 billion in gross state product (GSP), and 16,445 jobs throughout Idaho.
99 GENERAL AND MISCELLANEOUS↗
HIGH-LOW FIDELITY THERMAL HYDRAULIC COUPLING USING AI/MACHINE LEARNING ALGORITHMS
The primary goal of the US Department of Energy (DOE) office of Nuclear Energy Integrated Energy Systems (IES) program is to develop the tools and framework for coupling multi-scale and multi-physical thermal and electrical energy usage and storage systems. High- and low-fidelity (high–low) coupling is a key feature of multi-scale, multi-component systems and has been an important focus of research in the nuclear energy community for the past two decades. An essential feature of demonstrating the capability to couple high-fidelity and low-fidelity systems for real-time applications are surrogate/reduced order models (ROM). For the purposes of this study, surrogate models are essentially Blackbox models, typically developed using supervised Machine learning (ML) algorithms. The surrogate models can be used to mimic the response of high-fidelity models to represent large historical datasets and coupled with more general low-fidelity system models distributed as Functional Mock-up Interface (FMI) or Functional Mock-up Units (FMU) modules. The example is demonstrated with Spallation Neutron Source (SNS) First Target Station flow loop data. The flow loop is a liquid mercury loop with a pump, piping, heat exchange, and internal heat generation in the target window. This work elucidates some of the potential benefits and future needs of developing tools for high–low system coupling of energy systems.
Williams, Wesley↗
Report on Coastal Structure Integrated Wave Energy Converters (CSI-WECs)
This report investigates a largely underexplored, and underexploited, application for wave energy: coastal structure integrated wave energy converters (CSI-WECs). These WEC types have significant potential to rapidly advance the wave energy industry while addressing the challenges of coastal community resiliency and marine energy integration and application, and the urgent need for increased coastal protection. To further support the value proposition investigation of this work, three wave energy developers agreed to conduct an energy production analysis of their technology for the four sites identified. Additionally, a geographic information system-based tool was developed that supports efficient and comprehensive site assessment for optimal and high-value deployments.
16 TIDAL AND WAVE POWER↗
Data Projection of the High Temperature Electrolysis System in the Dynamic Energy Transport and Integration Laboratory using Dynamic System Scaling
For nuclear power to be flexible in a functioning Integrated Energy System (IES), excess produced heat must be stored or utilized during times of low power demand to ensure a load factor of 1 while load balancing. The Dynamic Energy Transport and Integration Laboratory (DETAIL) is one facility that is under development to emulate IES conditions on the engineering-scale, planned to conduct virtual real time operations with industry-scale facilities, and is currently testing thermal storage and high temperature electrolysis. As part of the study to develop a method to preprocess input signals or postprocess output signals between systems of different scales via Dynamical System Scaling (DSS), the current research is one of the continued efforts branching from the data projection activity conducted for the Thermal Energy Distribution System and currently engages the High Temperature Electrolysis (HTE) System in DETAIL. The HTE SOEC electrical, fluid, and thermal dynamics Figure of Merits (FOM) were identified, governing equations and closure relations were successfully scaled, and relations between FOM scaling ratios were determined. Setting the scaling objectives to reform existing data to project a data set that doubly accelerated the electrolysis process while preserving the produced amount of hydrogen was generated for the full transient. The calculated boundary conditions were inlet temperature, stack current, and inlet steam mass flow rate at 1470 K, 121.1 A, and 1.886 g/s, respectively. The research outcomes demonstrated an output signal postprocessing case accelerating the hydrogen production without changing geometry, number of cells, and partial pressures.
08 HYDROGEN↗
Integrated Hydrogen Energy Storage System (IHESS) for Power Generation (Final Report)
GTI Energy partnered with Praxair Inc., a subsidiary of Linde PLC (Praxair), the Center for Electromechanics at the University of Texas at Austin (CEM), Entergy Corporation (Entergy), Quanta Services (Quanta) and Mitsubishi Heavy Industries (MHI) to perform a feasibility study that determines the economic and technical feasibility of low-carbon hydrogen energy storage integrated with a site-specific fossil fuel asset to decarbonize electricity production using the Integrated Hydrogen Energy Storage System (IHESS). The proposed IHESS concept is novel, as it sought to leverage the existing natural gas infrastructure, hydrogen production and pipelines, existing underground hydrogen storage system and power plants in the Gulf Coast region to reduce carbon emissions and generate lowcarbon electricity. This study has shown that IHESS has a promising commercial outlook as the concept leverages existing natural gas infrastructure assets and hydrogen production and storage that are unique to the Texas gulf coast region. A key hurdle with hydrogen supply and transportation has been capital investment. By storing hydrogen in underground storage and delivering it as a fuel source during peak demand using the existing infrastructure minimizes the capital investment. Regional petrochemical producers who are actively seeking opportunities to reduce costs and lower emissions should find the IHESS concept very appealing.
03 NATURAL GAS↗
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↗