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At least 163 records · Page 9

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

Induced Markov chain for wind farm generation forecasting

Systems and methods for forecasting power generation in a wind farm are disclosed. The systems and methods utilize an induced Markov chain model to generate a forecast of power generation of the wind farm. The forecast is at least one of a point forecast or a distributional forecast. Additionally, the systems and methods modify at least one of: (i) a generation of electricity at a power plant coupled to a common power grid as the wind farm; or (ii) a distribution of electricity in the common power grid based on the forecast of power generation of the wind farm. In an exemplary approach, utilizing the induced Markov chain model to generate the forecast may include determining a series of time adjacent power output measurements based on historical wind power measurements and calculating a time series of difference values based on the series of time adjacent power output measurements.

17 WIND ENERGY↗

Electric Grid Supply Chain Review: Large Power Transformers and High Voltage Direct Current Systems

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. The need to modernize and increase the capacity of the U.S. power grid is increasing due to growing population, aging infrastructure, grid resilience requirements, operational flexibility needs, and a growing portfolio of renewable energy. As part of the Paris Climate Agreement the United States has committed to reducing its net greenhouse gas emissions by 50 to 52 percent below 2005 levels in 2030 and has set a goal of 100 percent carbon pollution free electricity by 2035 (The United States of America Nationally Determined Contribution, 2021). Meeting these targets will require a significant expansion of the power system to integrate a large amount of new renewable resources (United States Department of State & United States Executive Office of the President, 2021). However, many critical components supporting the power grid have limited to no domestic manufacturing capacity and face complex challenges in supporting a rapid expansion of the grid to meet multiple objectives, including decarbonization goals. This report focuses on two key grid components: large power transformers (LPTs) and high-voltage direct current (HVDC) transmission.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Seasonal Reconfiguration of Electrical Distribution Systems to Mitigate the Impact of Electric Vehicle Charging

Power grids face challenges in their infrastructure related to the integration of electric vehicles (EV). In particular, EV charging stations may induce instability in key system parameters such as substantial voltage drops, active power losses, and transformer overload due to high demand during charging periods. This article presents a seasonal reconfiguration strategy based on the differential evolution (DE) algorithm, aimed at enhancing system performance under highly variable and stochastic load profiles, particularly those driven by EV charging. The DEA algorithm is hybridized with the find-union (FU) algorithm to efficiently ensure network radiality throughout the optimization process. The proposed methodology is validated on a hybrid distribution system composed of the IEEE 33-bus network, a modified IEEE 13-bus system, and a specific 13-bus microgrid. Results have demonstrated that seasonal reconfiguration significantly reduces active power losses and mitigates transformer loading during critical demand hours, thereby quantifiably increasing the system’s performance. As an integral component of the proposed approach, an analysis of CO2 emissions associated with energy losses is included, allowing a contextualized assessment of the environmental benefits of seasonal reconfiguration in various geographical areas.

24 POWER TRANSMISSION AND DISTRIBUTION↗

E-transit-bench: simulation platform for analyzing electric public transit bus fleet operations

When electrified transit systems make grid aware choices, improved social welfare is achieved by reducing grid stress, reducing system loss, and minimizing power quality issues. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs and so on, that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid's power flow and therefore cannot account for the power grid's needs in its day-to-day operation. In this paper we propose a framework of transportation-grid co-simulation, analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day's traffic from Chattanooga city's transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of transit electrification that further necessitates such an integrated transportation-grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.

Sen, Rishav↗

Interconnection Standards for Combined Heat and Power (CHP) - State Standards that Impact Interconnection to the Electric Distribution Grid

This Issue Brief examines state interconnection policies that apply to CHP throughout the United States. It discusses barriers to CHP interconnection and describes elements of effective interconnection standards. The information in this document is intended to help inform state regulators, policy makers, utility personnel, electricity customers, and other stakeholders about the current status of CHP interconnection requirements, and how the interconnection process could be improved to accelerate the adoption of CHP.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Phasor-Based Control for Scalable Integration of Variable Energy Resources

We propose an innovative framework termed phasor-based control (PBC) to facilitate the integration of heterogeneous and intermittent distributed energy resources (DER) on the electric grid. PBC presents a unified approach that is agnostic to optimization criteria and to the particular characteristics of participating resources. It is enabled by synchronized, high-precision voltage phasor measurements that allow stating control objectives in grid-specific, rather than resource-specific, terms. We present qualitative justification and examine the general feasibility of this control approach, including the behavior of candidate control algorithms in simulation. Initial results suggest that PBC has significant potential to support stable and resilient grid operations in the presence of arbitrarily high penetrations of DER.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Systematic Study to Determine 5G Baseline Performance for Scientific Computing

The fifth-generation (5G) cellular networks envisions achieving higher data rates, improved connectivity, reduced latency, and better quality of service (QoS) than the fourthgeneration (4G) cellular networks. Such improved performance can be utilized to address the challenges in applications such as electricity generation in power systems. The traditional power grids responsible for electricity generation suffer from drawbacks such as life-threatening blackout crises, and energy storage proliferation as they are not robust to extreme climatic conditions. A recent study proposed the idea of extending the capabilities of advanced wireless technologies such as the current 5G to develop a robust, energy-efficient, and secure smart grids. However there are two main challenges associated with the integration of power systems and wireless technologies. First, it is imperative to understand the architecture and the enabling technologies of 5G to ensure that the performance requirements of the smart grids are met. Second, an end-to-end testbed is required to determine if the performance requirements are met by estimating the 5G characteristics such as latency, and throughput. Our proposed alleviates the aforementioned concerns in the following manner. To begin with, a systematic study of the 5G architecture including both the StandAlone (SA) and Non-Standalone (NSA) operations is presented. Furthermore, a detailed survey of the possible 5G enabling technologies is elicited. In addition to these, an end-toend testbed that can estimate the 5G characteristics is explained in detail with appropriate preliminary results.

5G, 5G Communication↗

Risk Retirement—Decreasing Uncertainty and Informing Consenting Processes for Marine Renewable Energy Development

Marine renewable energy (MRE) is under development in many coastal nations, adding to the portfolio of low carbon energy sources that power national electricity grids as well as off-grid uses in isolated areas and at sea. Progress in establishing the MRE industry, largely wave and tidal energy, has been slowed in part due to uncertainty about environmental risks of these devices, including harm to marine animals and habitats, and the associated concerns of regulators and stakeholders. A process for risk retirement was developed to organize and apply knowledge in a strategic manner that considered whether specific environmental effects are likely to cause harm. The risk retirement process was tested against two key MRE stressors: effects of underwater noise from operational MRE devices on marine animals, and effects of electromagnetic fields from MRE electrical export cables on marine animals. The effects of installation of MRE devices were not accounted for in this analysis. Applying the risk retirement process could decrease the need for costly investigations of each potential effect at every new MRE project site and help move the industry beyond current barriers.

16 TIDAL AND WAVE POWER↗

Co-design optimization of combined heat and power-based microgrids

With the emergent need for clean and reliable energy resources, hybrid energy systems, such as the microgrid, are widely adopted in the United States. A microgrid can consist of various distributed energy resources, for instance, combined heat and power (CHP) systems. Here, the CHP module is a distributed cogeneration technology that produces electricity and recaptures heat generated as a by-product. It is an energy-efficient technology converting heat that would otherwise be wasted to valuable thermal energy. For an optimal system configuration, this study develops a novel co-design optimization framework for CHP-based cogeneration microgrids. The framework provides the stakeholder with a method to optimize investments and attain resilient operations. The proposed co-design framework has a mixed integer programming (MIP) model that outputs decisions for both plant designs and operating controls. The microgrid considered in this study contains six components: the CHP, boiler, heat recovery unit, thermal storage system, power storage system, and photovoltaic plant. After solving the MIP model, the optimal design parameters of each component can be found to minimize the total installation cost of all components in the microgrid. Furthermore, the online costs from energy production, operation, maintenance, machine startup, and disruption-induced unsatisfied loads are minimized by solving the optimal control decisions for operations. Case studies based on designing a CHP-based microgrid with empirical data are conducted. Moreover, we consider both nominal and disruptive operational scenarios to validate the performance of the proposed co-design framework in terms of a cost-effective, resilient system.

42 ENGINEERING↗

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗

Elucidating Sodium-Sulfur Battery Chemistry using Operando Transmission X-ray Microscopy and X-ray Absorption Spectroscopy

Room-temperature sodium-sulfur (Na-S) batteries offer a beneficial and cost-effective solution for powering modern electric grids and devices. However, Na-S batteries suffer from performance decay during battery cycling due to the sluggish kinetics and polysulfide shuttling. Revealing the conversion mechanism of the Na-S chemistry is critical to designing high-capacity and stable Na-S batteries. In this study, we employed operando X-ray microscopy and operando X-ray absorption spectroscopy to elucidate the sulfur conversion in a carbon host using an ether-based electrolyte. We reveal the structural and chemical evolution of the sulfur cathode during cycling, which results in volume expansion and the dissolution of active material, ultimately affecting the battery performance. Our work provides fundamental insight into the sulfur reaction scheme, addressing the lingering challenges before establishing inexpensive Na-S batteries for broad applications, including portable electronics and large-scale energy storage.

Jagadeesan, Sathya Narayanan [SLAC National Accele↗

Electromagnetic Field Simulation Utilizing VERTEX

The understanding of electromagnetic fields is essential for many core applications at Oak Ridge National Laboratory (ORNL). Electromagnetic fields play an important role in particle accelerators, antennas, electric motors, power grids, and are principal part of nuclear fusion. We develop a numerical solver called able to treat the Maxwell system utilizing ORNL's VERTEX framework.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

IDAES-PSE Software Tools for Optimizing Energy Systems and Market Interactions

Modern power grids coordinate electricity production and consumption via multi-scale wholesale energy markets. Historically, levelized cost metrics were the de facto standard for techno-eco-nomic analyses of energy systems and comparison of technology options. However, these metrics neglect the complexity of energy infrastructure including the time-varying value of electricity. An emerging alternative is multi-period optimization, which considers the locational marginal price of electricity as input data (parameters). In this work, we present a general interface for multi-period optimization with time-varying energy prices to facilitate rapid analysis and comparison of potential energy systems models. The PriceTakerModel class is written in the IDAES-PSE platform and allows users to generate a multi-period, price-taker model instance, as well as automatically generate common operational constraints for their model, such as start-up and shutdown. We show this interface successfully generates multi-period price-taker models, facilitates model discrimination, and aids in analyzing various technologies for deployment in unique energy markets.

Laky, Daniel↗

Communication enabled fast-acting imbalance reserve

A system and method for control of dispatchable resources on an electrical power distribution grid is disclosed. The disclosed method provides improved response to power imbalance based on a communications signal independent of system frequency. The communication signal provides a feed-forward control of dispatchable power resources. A communications network is employed to generate a signal to dispatchable resources that a power imbalance has occurred. Due to fast response power transmission network interfaces associated with the dispatchable resources, the respective resources respond in significantly less time than feedback controlled conventional generators which depend on line frequency sensing. The rapid response mitigates the impact of power imbalances and enables greater penetrations of converter-interfaced power generation units such as renewable energy sources to be connected to the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Model based co-simulation platform for integrated building system control and design optimization

Both steady-state and dynamic simulations have been widely used by HVAC&R industry to support product/equipment development for decades. Steady-state simulation focuses on the system mass, energy and momentum balance of an equilibrium state. It is based on high-fidelity components models, and thus is suitable for system and component design optimization. Dynamic simulation studies the system transient response and is generally used for controls development and verification. It usually does not require rigorous component models of high accuracy because 1) the commonly used PID control is feedback control whose control performance evaluation doesn’t require high fidelity system/plant model; 2) high-fidelity dynamic model significantly increases the number of equations and variables and creates tremendous challenge for math solver. For supervisory control, transactive control or optimization of an integrated building system, the HVAC&R equipment is often one of the sub-components to be controlled. High-fidelity equipment models are required for accurately evaluating control strategies. In addition, building equipment manufacturers have developed a lot of high-fidelity steady-state equipment/component models per their expertise. Thus, a platform that can integrate OEM high-fidelity steady-state model with dynamic building simulation and/or electric power system & grid simulation to support the development and verification of supervisory control for integrated building systems is necessary. In this study, ORNL’s heat pump design tool (HPDM) is utilized to develop a co-simulation platform for supervisory control and optimization in integrated building systems. It is based on a model that integrates high-fidelity steady-state simulation equipment models with dynamic building simulation. A practical case of using the proposed co-simulation platform to develop and evaluate the supervisory control and optimization is presented and discussed.

Sun, Jian↗

Biochemical Conversion of Herbaceous Biomass to Renewable Diesel: Net Greenhouse Gas and Air Pollutant Trade-offs

This study examines greenhouse gas (GHG) and criteria air pollutant (CAP) emissions trade-offs for renewable diesel across 12 scenarios, involving different biochemical conversion designs, biorefinery scales, and feedstocks. A conventional design uses lignin for on-site heat and power, which exports excess power to the grid. An alternative design exports lignin pellets, offsetting other pellet production methods but requiring grid electricity to meet biorefinery power demands. Net emissions were quantified in Iowa and Georgia, selected considering feedstock availability, coproduct displacement, and regional power grids, assuming grid-exported power avoids coal or low-carbon electricity. Results for the conventional design remained consistent across the electricity displacement scenarios. When comparing lignin utilization strategies, pelletizing lignin reduces sulfur dioxide, carbon monoxide, nitrogen oxides, and volatile organic compounds (net emissions –0.66 mg MJ –1 , 25 mg MJ –1 , 25 mg MJ –1 , 7.8 mg MJ –1 , respectively). However, lignin pelletization increases net particulate matter (fine and coarse) and ammonia (net emissions of 4.7 mg MJ –1 , 13 mg MJ –1 , and 0.26 mg MJ –1 , respectively), alongside indirect GHG emissions due to grid electricity dependence. Additionally, processing 2000 tonnes corn stover daily minimizes emissions for both designs. Only lignin pelletization with renewable electricity and additional particulate matter and ammonia controls reduces all CAP and GHG emissions simultaneously.

09 BIOMASS FUELS↗