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At least 1,243 records · Page 69

Reactor Subsystem Simulation for Nuclear Hybrid Energy Systems

Nuclear Hybrid Energy Systems (NHES) could be a key part of the solution to achieving energy security, may provide reliable power availability even with increasing renewable energy penetration into the power grid, and may allow repurposing excess electricity in times of low demand. Incorporating a fission-based power source in a multi-output system (electricity and process heat) can offer significant advantages over carbon-based production sources, such as coal or natural gas, including reduction in atmospheric carbon emissions. In an integrated multi-output system, thermal energy from the nuclear reactor subsystem can be diverted to industrial applications in times of low electricity demand. High temperature, high quality heat from advanced reactor designs might be used for hydrogen production or synthetic fuel production (coal-to-liquid or natural gas-to-liquid processes). Low temperature heat from advanced reactor designs or the current and future fleet of light water reactors (LWRs) might be applied to desalination processes or be stored for later use in low temperature ammonia or hydrocarbon-based thermal cycles. The NHES research team is currently developing a dynamic simulation of an integrated hybrid energy system. A detailed simulation of proposed NHES architectures will allow initial computational demonstration of a tightly coupled NHES to identify key reactor subsystem requirements, identify candidate reactor technologies for a hybrid system, and identify key challenges to operation of the coupled system. This work will provide a baseline for later coupling of design-specific reactor models through industry collaboration. The modeling capability addressed in this report focuses on the reactor subsystem simulation. Many computational tools and methods are available for modeling a nuclear reactor, power conversion systems and associated process applications. One method is to develop a single program capable of modeling the entire system. Another is to combine two or more existing computer programs, each modeling a portion of the system for which it is validated, where the programs exchange information to compute the solution. The former method requires a lengthy development and verification and validation process. The latter method leverages industry standard software to reduce development and funding requirements. Preliminary system models have been developed by Idaho National Laboratory researchers and are currently being enhanced to assess integrated system performance given multiple sources (e.g., nuclear + wind) and multiple applications (i.e., electricity + process heat). Initial efforts to integrate a Fortran-based simulation of a small modular reactor (SMR) with the balance of plant model have been completed in FY12. This initial effort takes advantage of an existing SMR model developed at North Carolina State University to provide initial integrated system simulation for a relatively low cost. The SMR subsystem simulation details are discussed in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Powering the Blue Economy: Foundational Research and Development

With increased use of the oceans for transportation, extraction of food, fibre, and minerals, recreation and tourism, and other blue economy industries, there is a need for additional power at sea. In the face of climate change, the increased power must come from renewable sources; often marine energy is the most energy-dense power source available. But we have little experience with adapting wave and tidal devices from large scale grid power to the specialized and small devices needed to power blue economy applications, nor the engineering solutions to support codesign of emerging marine industries. As directed by the U.S. Department of Energy (DOE), two DOE national laboratories have developed foundational research and development projects to replace conventional power or batteries at sea (ocean observation platforms), emerging industry power needs (offshore aquaculture operations), as well as examining common challenges for using marine power (efficient power systems, minimizing interference, optimizing materials and manufacturing).

marine energy↗

Energy Storage for DC Fast Chargers Development and Demonstration of Operating Protocols for 20-kWh and 200-kWh Field Sites

Many of the currently available and future electric vehicles can be fast charged, and, typically, at least 50% of the battery capacity can be returned in 15 to 20 minutes. This charge rate requires a power of at least 50 kilowatts, which can be expensive in terms of both infrastructure and electric utility demand charges. One potential way of minimizing this cost is to charge the electric vehicle with combined battery and grid power, thereby reducing the peak load on the grid. Many sizes and configurations are possible for such a battery. This study examines two possibilities: (1) a 20-kilowatt hour (kWh) battery energy storage (BES) system and (2) a 200-kWh BES system, as well as developing standard test procedures for assessing the suitability of battery technologies for use in such systems.

25 ENERGY STORAGE↗

Considerations for Distributed Energy Resource Integration in Puerto Rico: DOE Multi-Lab Grid Modeling Support for Puerto Rico; Analytical Support for Interconnection and IEEE Std 1547-2018 National Renewable Energy Laboratory (Task 3.0)

To ensure the sustainable long-term recovery of Puerto Rico's electric power grid from hurricanes María and Irma and to build capacity to manage future potential natural disasters in the most secure and resilient way, the U.S. Department of Energy (DOE) convened experts from multiple national laboratories to develop a comprehensive set of data, models, analytic tools, and studies, considering inputs from a wide variety of stakeholder groups, to support technically sound recommendations for Puerto Rico's energy investment decisions. A resilient electric grid is vital to Puerto Rico's security, economy, and way of life, and it will provide the foundation for essential services that people and businesses on the island rely on every day. This report shows progress for a grid modeling task under the DOE-sponsored project that is a collaboration among the National Renewable Energy Laboratory (NREL) and other national laboratories. In Phase 1 of the multilab effort to support Puerto Rico's recovery, NREL provided the utility company Puerto Rico Electric Power Authority (PREPA) recommendations for a new framework of interconnection standards to accelerate the integration of utility-scale, transmission-connected renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliably, safety, or security. This Phase 2 report focuses on the interconnection of distributed energy resources (DERs) to the electric distribution system in Puerto Rico. This report is intended to familiarize the reader with Puerto Rico's distribution infrastructure and operational practices and procedures that are relevant to DER interconnection. The report also provides considerations for streamlining the interconnection process given the expected increase in deployments resulting from Puerto Rico's renewable portfolio standard (RPS) goal of 100% renewables by 2050. Accordingly, the report identifies considerations and concerns associated with the increase in intermittent generation, strategies for DER interconnection best practices, and the potential use of the latest technological solutions identified in the latest revision of the Institute of Electrical and Electronics Engineers (IEEE) 1547-2018 interconnection standard.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Grid Resilient, Self-Powered, Fuel Flexible, High Efficiency Heating System (Final Report)

The Grid Independent High Efficiency System (GIHES) delivers a heating system that operates free from the power grid and provides ultra-low emissions and high efficiency heating for residential and commercial buildings. The project demonstrated two weeks of continuous grid independent operation of a storage water heater equipped with a powered damper. The Thermoelectric Generator (TEG) integrated GIHES technology revolutionizes heating systems to provide grid resilient hot water production, while delivering significant value to the end user by eliminating impacts of power interruption and enhancing comfort, convenience and productivity. The system maximizes the thermal-to-electric conversion efficiency by optimizing location and orientation of the TEGs and durability while lowering system costs. The TEGs generate enough power to charge a battery and run the storage water heater unit with a powered damper uninterrupted by providing the required parasitic electrical power for start-up, shutdown and during idling. Several TEGs were analytically and experimentally evaluated based on the size, surface area and the power being generated before designing and fabricating a complete multi-TEG assembly for integration with the water heater. The GIHES technology can be extended to boilers, furnaces and tankless water heaters and integrated with heat pump to further increase the overall equipment efficiency. The technology has the potential to reduce the amount of dispatch power and peak power plant operation. An advanced burner was designed, developed and 3D printed for fuel flexible operation. The burner was designed to enable tighter integration with TEGs for potentially higher TEG output, should this be necessary. A bench-scale test rig to perform testing of a 200,000 Btu/h burner and capable of handling up to 10% H2 (by volume) was setup at GTI’s laboratory with appropriate safety and controls to ensure smooth and safe operation. Testing of the 3D burner showed < 5 ppm NOx emissions can be achieved for the entire firing range and with different levels of hydrogen blends with natural gas. The burner will enable a more integrated TEG-burner module design for improved system performance, should this be required in the future. Techno-economic analysis (TEA) of the TEG integrated with the water heaters was performed. The testing data and the power output were used to develop the TEA. The analysis for the storage unit with damper showed that the TEG integrated system costs $95. This is much lower than a one-time charge needed to wire and install dedicated power. Discussions with TEG manufacturers and OEM’s will provide more detailed information and methods to further lower these costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hierarchical Control and Stability Analysis for a Nonisolated Grid-Tied DC Energy Router Integrating Energy Storage and Partial Distributed Generation

This article proposes a nonisolated dc converter-based energy router (dc-ER) and its operating strategy. Here, the intent is to integrate energy storage (ES), distributed generation (DG), local load, and dc power grid in an autonomous and more efficient way. The ES/DG power ports are coupled with each other in partial-type connections, which obtains higher voltage supply gain and direct input–output power transmission. High-voltage supply gain allows a wide solar power tracking range and the possibility of optimal battery charging/discharging. Direct input–output power transmission improves the energy conversion efficiency. In this article, the operating modes of dc-ER are first analyzed, followed by the optimal hardware design counting the DG current ripple minimization and the limitation caused by the power flow direction. Second, the mathematical model of dc-ER is deduced. The hierarchical control is then proposed to manage port energy in a flexible manner. The stability is analyzed by using impedance modeling. Finally, experimental and simulation results verify the superiorities of the proposed topology in terms of flexible operating mode transition and high-power conversion efficiency.

25 ENERGY STORAGE↗

Capturing Infrastructure Interdependencies for Power Outages Prediction During Extreme Events

As extreme weather events such as hurricanes, severe thunderstorms, and floods grow in frequency and intensity, the disruption of power grid systems poses significant challenges, including widespread electrical outages, economic losses, and threats to public safety. This paper presents a forward-looking approach that leverages geographical graph-based machine learning models to predict county-level maximum power outages during such events. By capturing the intricate interdependencies within power system networks, our approach aims to provide precise and actionable predictions that can optimize emergency response efforts and enhance grid resilience. Through the integration of real-world data, including hurricane advisories and power outage records, we have trained and benchmarked multiple machine learning models, demonstrating the feasibility and potential of this method. While our initial results are promising, this paper also charts a course for advancing these models, addressing the remaining challenges, and ultimately transforming how we anticipate and respond to the impacts of extreme weather on power systems.

Lee, Sangkeun (Matt) [ORNL] (ORCID:000000021317511↗

Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India’s Electric Grid, Vol. I. National Study. Executive Summary

The use of renewable energy (RE) sources, primarily wind and solar generation, is poised to grow significantly within the Indian power system. The Government of India has established an installed capacity target of 175 gigawatts (GW) RE by 2022 that includes 60 GW of wind and 100 GW of solar, up from current capacities of 29 GW wind and 9 GW solar. India’s contribution to global efforts on climate mitigation extends this ambition to 40% non-fossil-based generation capacity by 2030. Global experience demonstrates that power systems can integrate wind and solar at this scale; however, evidence-based planning is important to achieve wind and solar integration at least cost. The purpose of this analysis is to evaluate the operation of India’s power grid with 175 GW of RE in order to identify potential cost and operational concerns and actions needed to efficiently integrate this level of wind and solar generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Grid Operational Technology Edge-Level Threat Detection

This report presents a deployable solution to improve the cybersecurity situational awareness of the legacy SCADA system infrastructure in power grids. The main goal of this project is to provide system owners and operators a highly trusted, intelligent alarm system and comprehensive situational awareness of ongoing or potential cybersecurity threats on the grid network. The key contributions of this project include: (1) the development of software, the Intrusion Detection Visualizer for the Operational Technology Network (IViz-OT), to visualize and locate intrusions on the grid network; (2) testing the signature-based Hybrid Intrusion Detection for Energy Systems (HIDES) for different types of intrusions; (3) the integration of HIDES and IViz-OT into the visualization dashboard; and (4) real-time testing using a hardware-in-the-loop test bed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗

Photovoltaic (PV) System Levelized Cost of Energy (LCOE) Evaluation with Grid Support Function Valuation and Service Lifetime Estimation

Photovoltaic (PV) systems play a critical role in renewable energy resource grid integration, and levelized cost of energy (LCOE) is commonly used to evaluate PV system feasibility in modern power grids. In this work, a revised PV system LCOE calculation model is derived to quantify the potential of LCOE reduction. Particularly, the grid support functions are valuated to offset the investment and operation costs of PV systems, which thereby reduces the LCOE. Meanwhile, PV system service lifetime is also estimated with the derived PV inverter reliability model, considering the critical components (i.e., semiconductor devices and capacitors). The case studies with field datasets are conducted to validate the effectiveness of the developed LCOE calculation model.

Zhao, Shijia↗

A Clarke Transformation-Based DFT Phasor and Frequency Algorithm for Wide Frequency Range

Despite its wide applications in power grid monitoring, the classic discrete Fourier transform (DFT)-based synchrophasor estimation algorithms suffer from significant errors when the power system operates under off-nominal frequency conditions. This phenomenon is caused by spectral leakage of DFT and becomes even more severe for single-phase synchrophasor estimation. To address this issue, a theory to eliminate the spectral leakage-caused errors is proposed and a Clarke transformation-based DFT synchrophasor estimation algorithm is proposed to implement the theory in this paper. The Clarke transformation constructs a second signal that has exactly 90° phase angle difference from the original single-phase input signal and helps eliminate the estimation errors for a wide frequency range. The proposed algorithm is tested under the conditions required in the phasor measurement unit standard C37.118.1-2011 and C37.118.1a-2014, as well as the harmonic and noise conditions not required in the standard to verify its performance. More importantly, the idea of using Clarke transformation can be used for other DFT-based synchrophasor algorithms in order to achieve higher synchrophasor measurement accuracy under dynamic conditions. An example is presented at last to demonstrate the expandability of the proposed idea.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Graph modeling systems and methods

An apparatus and a method for vulnerability and reliability modeling are provided. The method generally includes constructing a graph model of a physical network using a computer, the graph model including a plurality of terminating vertices to represent nodes in the physical network, a plurality of edges to represent transmission paths in the physical network, and a non-terminating vertex to represent a non-nodal vulnerability along a transmission path in the physical network. The method additionally includes evaluating the vulnerability and reliability of the physical network using the constructed graph model, wherein the vulnerability and reliability evaluation includes a determination of whether each terminating and non-terminating vertex represents a critical point of failure. The method can be utilized to evaluate wide variety of networks, including power grid infrastructures, communication network topologies, and fluid distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evolution of Scenario Generation Capabilities in the ExaSGD Project

High-fidelity renewable energy scenarios and rare-event high-impact contingencies are essential for modeling operations and infrastructure expansion of the next generation power grids using exascale computing resources. As the ExaSGD project progressed, our capabilities for generating scenarios for modeling wind power output at multiple wind farms significantly improved, evolving from the use of independent random perturbations to importance sampling-based techniques capturing representative spatial-temporal relations. Contingency generation also improved, evolving from standard N-1 techniques to probabilistic models of infrastructure damage resulting from extreme weather events. We review the developments in the realistic intermittent-energy scenario forecasting and extreme-event contingency creation as the ExaSGD project progressed and discuss the future work in these areas.

economic dispatch↗

Fault Clearing Operation in Low-Frequency High-Voltage AC Systems

Abstract—Low-frequency high-voltage ac (LF-HVac) system has been proposed as an alternative to HVdc and HVac systems to reduce transmission losses and improve grid flexibility. LF-HVac system employs back-to-back (BTB) converters to interconnect and control the voltage and power interchange between two power grid operating at different frequencies. While there are multiple studies on LF-HVac system in the literature, the fault clearing method in the LF-HVac system has not been analyzed. Therefore, this paper focuses on fault clearing operation in LFHVac system and proposes a novel method to reduce fault current by changing operating frequency of power source and converter. The performance of the proposed method is validated using detailed models of BTB converters developed in PSCAD/EMTDC. The ability to change operating frequency at the onset of a fault condition allows breakers to rapidly clear the fault and recloses. The results obtained by using the proposed method substantially diminish the fault current.

Kim, Woosung↗

A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data

With the expected increase in the number of electric vehicles (EVs) on the road in the coming years, it is important that analysis tools are capable of modeling and predicting the expected load on the power grid due to both individual EV charging sessions as well as large populations of vehicles. To do this accurately, the power profile of an EV charge session must be accurately modeled, including for scenarios where the temperature is above or below the ideal, and also take into account the nuances of manufacturer charging preferences. This paper introduces a method that utilizes the data in the Next-Gen Profile (NGP) data collection project to build a model of EV charging that takes into account the variations in charging power that occur due to off-nominal battery temperature and manufacturer preferences that limit power due to cold temperatures or high battery state-of-charge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗