Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “GRIDS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Identifying emerging smart grid impacts to upstream and midstream natural gas operations.

The Smart Grid has come to describe a next-generation electrical power system that is typified by the increased use of communications and information technology in the generation, delivery and consumption of electrical energy. Much of the present Smart Grid analysis focuses on utility and consumer interaction. i.e. smart appliances, home automation systems, rate structures, consumer demand response, etc. An identified need is to assess the upstream and midstream operations of natural gas as a result of the smart grid. The nature of Smart Grid, including the demand response and role of information, may require changes in upstream and midstream natural gas operations to ensure availability and efficiency. Utility reliance on natural gas will continue and likely increase, given the backup requirements for intermittent renewable energy sources. Efficient generation and delivery of electricity on Smart Grid could affect how natural gas is utilized. Things that we already know about Smart Grid are: (1) The role of information and data integrity is increasingly important. (2) Smart Grid includes a fully distributed system with two-way communication. (3) Smart Grid, a complex network, may change the way energy is supplied, stored, and in demand. (4) Smart Grid has evolved through consumer driven decisions. (5) Smart Grid and the US critical infrastructure will include many intermittent renewables.

03 NATURAL GAS↗
DOE OSTI2016

CFD-Informed Spacer Grid Models in the Subchannel Code CTF

Data from computational fluid dynamics (CFD) simulations can be utilized to improve the predictive capabilities of the subchannel code CTF. Past work incorporating CFD results into CTF has included accounting for directed crossflow and turbulent mixing between adjacent subchannels. Spacer grids impact fluid flow in various ways, and this work focuses on four spacer grid effects, namely: 1. Directed crossflow; 2. Turbulent mixing; 3. Enhanced downstream heat transfer; 4. Pressure drop correlation. Heat transfer augmentation occurs partially due to the disturbances in the developed flow and from the additional turbulence generated by the presence of obstructions in the fluid flow's path. The boundary layer disruption is caused in part by the newly-directed flow just downstream of the spacer grid vanes. This effect lessens as the distance from the grid increases and the flow returns to its developed state, closer to what would be expected in a bare subchannel. Current plans of this work are to develop a method for incorporating the effects of spacer grids on the heat transfer calculation within CTF. Proposed techniques include the addition of an enhancement factor to the local heat transfer coefficient. The inclusion of CFD data from properly-designed simulations will allow CTF to better predict parameters such as fluid temperatures near spacer grids. Improved pressure loss coefficients for each grid can also be generated using CFD simulations. The heat transfer modification has been studied, with other authors noting correlations which are dependent on grid properties such as the blockage ratio. Parameters considered in this study are the turbulent kinetic energy (TKE) and vorticity. There are currently no models to calculate or store either of these parameters within CTF. When accounting for spacer grid effects in CTF, it is important to not double-count the effects towards two different CTF models. This requires carefully designing CFD simulations around capturing specific phenomena from the grids and being able to apply these CFD results to all appropriate flow conditions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments

Although machine learning (ML) has emerged as a powerful tool for rapidly assessing grid contingencies, prior studies have largely considered a static grid topology in their analyses. This limits their application, since they need to be re-trained for every new topology. Here, this paper explores the development of generalizable graph convolutional network (GCN) models by pre-training them across a range of grid topologies and contingency types. We found that a GCN model with auto-regressive moving average (ARMA) layers with a line graph representation of the grid offered the best predictive performance in predicting voltage magnitudes (VM) and voltage angles (VA). We introduced the concept of phantom nodes to consider disparate grid topologies with a varying number of nodes and lines. For pre-training the GCN ARMA model across a variety of topologies, distributed graphics processing unit (GPU) computing afforded us significant training scalability. The predictive performance of this model on grid topologies that were part of the training data is substantially better than the direct current (DC) approximation. Although direct application of the pre-trained model to topologies that are not part of the grid is not particularly satisfactory, fine-tuning with small amounts of data from a specific topology of interest significantly improves predictive performance. In general, this paper highlights the feasibility of training large-scale GNN models to assess the reliability of power grids by considering a wide variety of grid topologies and contingency types. With the advent of foundational models in ML and the exponential increase in GPU computing clusters, generalizable ML models will significantly enhance how utilities manage power systems and make decisions in real-time or near-real-time.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

A gating grid driver for time projection chambers

A simple but novel driver system has been developed to operate the wire gating grid of a Time Projection Chamber (TPC). This system connects the wires of the gating grid to its driver via low impedance transmission lines. When the gating grid is open, all wires have the same voltage allowing drift electrons, produced by the ionization of the detector gas molecules, to pass through to the anode wires. When the grid is closed, the wires have alternating higher and lower voltages causing the drift electrons to terminate at the more positive wires. Rapid opening of the gating grid with low pickup noise is achieved by quickly shorting the positive and negative wires to attain the average bias potential with N-type and P-type MOSFET switches. The circuit analysis and simulation software SPICE shows that the driver restores the gating grid voltage to 90% of the opening voltage in less than 0.20 µs, for small values of the termination resistors. When tested in the experimental environment of a time projection chamber larger termination resistors were chosen so that the driver opens the gating grid in 0.35 µs. In each case, opening time is basically characterized by the RC constant given by the resistance of the switches and terminating resistors and the capacitance of the gating grid and its transmission line. By adding a second pair of N-type and P-type MOSFET switches, the gating grid is closed by restoring 99% of the original charges to the wires within 3 µs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Future grid mix impacts on whole-building life cycle assessment

Building construction and operation are a significant contribution to global greenhouse gas emissions, so understanding and mitigating emissions is crucial for reliable and realistic emissions accounting. Whole-building Life Cycle Assessment (WBLCA) is an emissions accounting method that considers lifetime environmental impacts of a building during its construction, operation, and eventual end-of-life. When performing WBLCAs, emission calculations from the building's operation over the entire building lifespan are typically based on today's energy grid mixes. This method does not consider changes or advancements in the clean energy proportion within the grid mix and can over or under-inflate results, skewing the ratio of embodied vs. operational environmental impacts. While a variety of prediction tools estimate what future grid emissions might be, predictions can vary widely. To predict the clean energy ratio within future grid mixes and the potential impact these changes might have on WBLCA, annual data from several existing U.S. grid models was averaged and probabilistic modeling was used to extend the usable projections of shorter forecasts. Results show that clean energy sources will likely continue to increase over time, although the rate of growth varies by model. On average, by 2085, the clean energy penetration of the grid is projected to reach ~81% and renewable energy is projected to reach ~71%, although no widespread consensus is reached. To understand how the future grid mix impacts lifetime building emissions within a WBLCA context, the team analyzed two 2021 IECC-compliant all-electric residential buildings: one built from traditional materials and construction processes and the other built with carbon sequestering materials and modular assembly, with a portion of energy generated on site. The results indicate that a moderate estimate of future electricity grid mixes shows a reduction of yearly operational emissions for traditional residential buildings of 55% between 2025 and 2085, and a corresponding reduction of 48% of total emissions over a 60 year building lifespan. This study offers a nuanced approach to account for the variability of future grid mix models and provides an average trend-line based on a robust collection of scenarios.

Life Cycle Assessment (LCA)↗
DOE OSTI2018

Financial and Operational Bundling Strategies for Sustainable Micro-Grid Business Models

One of the biggest barriers to the scale up of mini-grids in Sub Sahara Africa ('SSA') is access to finance. While there are plenty of government and donor-led initiatives, private investment in the mini-grid sector has been slow to take off because of the high level of risk to reward and the relatively high transaction costs compared to larger grid-tied projects. Specific challenges for mini-grids include policy and regulatory risk, a lack of proven business models, and uncertainty about demand and the ability and willingness of customers to pay. Bundling or aggregation of mini-grids is one potential solution to these challenges. At its simplest, bundling means combining projects or different aspects of projects (eg. financial, operational and service) into a portfolio to create economies of scale (eg. lower costs, mitigation of risks, reaching an investment size that is attractive to more financiers.) There are two main types of bundling: Operational bundling - aggregation of similar projects (eg. similar business model, geographical area, technology or customer type) in order to reduce development and operating costs, - Financial bundling - aggregation of projects into a portfolio in order to attract more private investors through the larger ticket size and portfolio de-risking. This report looks at the different mini-grid business and financing models, and the opportunities and challenges around financial bundling. It looks at techniques for bundling through donors and national governments such as tenders, auctions and results based financing. It considers financial pooling mechanisms, including funds for mini-grid growth and end user financing, and financial products for de-risking mini-grid investments. Finally, there are three developer case studies of financial bundling of mini-grids.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

U.S. Department of Energy-National Lab Equity Summit: Grid Planning and Operations (Workshop Report)

This report summarizes the U.S. DOE and national laboratories equity summit that was held on February 5, 2024, and focused on grid planning and operations. The objectives of the summit were to connect DOE and lab researchers working on grid-related equity issues, share information on current and planned grid-related equity projects and initiatives, and inspire and educate participants by hearing from our panelists about solutions and challenges to integrating equity in grid planning and operations. The summit included two panels of industry leaders. The first was a state and community perspectives panel that included representatives from a state public utility commission (Oregon Public Utility Commission), a state energy office (Washington Department of Commerce), a state utility consumer advocate (Connecticut Consumer Counsel), and industry consultants (Elevated Engagement and ArkSpring Consulting). Panelists shared successes they have seen, critical challenges related to equity and grid planning and operations, and other considerations. The second panel addressed utility perspectives and included representatives from two utilities (Commonwealth Edison and Tacoma Power), the National Rural Electric Cooperative (NRECA), and a former utility employee and legal consultant. Panelists discussed the role of the utility concerning equity, the most significant technical and data modeling needs and opportunities, and the role the labs could help advance equity in grid planning and operations. There was also a session on partner organization presentations. Argonne National Laboratory made a short presentation on the Grid Modernization Laboratory Consortium (GMLC) project they are leading on equity-informed power system planning. NARUC, NASEO, and the Clean Energy States Alliance, as partners of the GMLC project also shared updates on relevant activities and resources. During the summit, there were two rounds of lightning presentations by national labs and DOE highlighting research that addresses equity and grid planning and operations (Tables 5 and 6 and slides in the Appendix). The goal of the lightning rounds was to share information between participants to encourage collaboration and leverage ongoing research at labs and DOE. The summit included two interactive exercises where summit participants shared their perspectives on relevant equity projects and initiatives (Table 2), key challenges regarding equity and grid planning and operations (Table 3), and promising innovations or progress (Table 4). At the end of the session, participants were asked to share essential insights from the event (Table 7) and an action they plan to take as a result of the event. Participants agreed that the event was useful in helping them share and learn from each other. The project team plans to use the information from the summit as a starting point to help inform future research and technical assistance. In 2026, another Equity Summit will be held (virtually or in person) as part of the same project to help raise awareness and disseminate research and resources completed during the project's duration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Ten questions concerning integrating smart buildings into the smart grid

Recent advances in information and communications technology (ICT) have initiated development of a smart electrical grid and smart buildings. Buildings consume a large portion of the total electricity production worldwide, and to fully develop a smart grid they must be integrated with that grid. Buildings can now be 'prosumers' on the grid (both producers and consumers), and the continued growth of distributed renewable energy generation is raising new challenges in terms of grid stability over various time scales. Buildings can contribute to grid stability by managing their overall electrical demand in response to current conditions. Facility managers must balance demand response requests by grid operators with energy needed to maintain smooth building operations. For example, maintaining thermal comfort within an occupied building requires energy and, thus an optimized solution balancing energy use with indoor environmental quality (adequate thermal comfort, lighting, etc.) is needed. Successful integration of buildings and their systems with the grid also requires interoperable data exchange. However, the adoption and integration of newer control and communication technologies into buildings can be problematic with older legacy HVAC and building control systems. Public policy and economic structures have not kept up with the technical developments that have given rise to the budding smart grid, and further developments are needed in both technical and non-technical areas.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Demonstrating the data center as a flexible grid asset using a C-HIL setup

Increasing data center demand is outpacing grid infrastructure development. Artificial intelligence workloads and hyperscale cloud growth are creating unprecedented demand for power, while traditional grid expansion faces multiyear development timelines. Verrus is developing an innovative datacenter solution for this challenge, data centers that act as active grid-supportive assets rather than passive loads. Our approach integrates a novel grid-aware power flow management system with battery energy storage systems(BESS) into a microgrid-controlled, medium-voltage power distribution architecture that delivers critical capabilities, such as: * Fast response to grid disturbances such over/ under voltage or over/ under frequency * Demand flexibility that can service requests from the utility within 10 s * Uninterrupted transition to islanded operation during grid outages * Continuous uptime assurance for compute loads while maintaining all customer service level agreements. Through Verrus' strategic partnership with the National Renewable Energy Laboratory (NREL), these capabilities were validated using NREL's Advanced Research on Integrated Energy Systems (ARIES) virtual emulation environment to model a 70-MW grid-interactive data center. This paper outlines the design, methodology, and results of this emulated deployment, demonstrating that data centers can provide both critical load resilience and ancillary grid support without compromising uptime requirements. Specifically, we present a digital real time simulation of a 70 MW data center integrated with a physical microgrid controller, and demonstrate the data center response in the event of a grid voltage and frequency event, utility demand response request and utility outage.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Impact of network topology on synchrony of oscillatory power grids

Replacing conventional power sources by renewable sources in current power grids drastically alters their structure and functionality. In particular, power generation in the resulting grid will be far more decentralized, with a distinctly different topology. Here, we analyze the impact of grid topologies on spontaneous synchronization, considering regular, random, and small-world topologies and focusing on the influence of decentralization. We model the consumers and sources of the power grid as second order oscillators. First, we analyze the global dynamics of the simplest non-trivial (two-node) network that exhibit a synchronous (normal operation) state, a limit cycle (power outage), and coexistence of both. Second, we estimate stability thresholds for the collective dynamics of small network motifs, in particular, star-like networks and regular grid motifs. For larger networks, we numerically investigate decentralization scenarios finding that decentralization itself may support power grids in exhibiting a stable state for lower transmission line capacities. Decentralization may thus be beneficial for power grids, regardless of the details of their resulting topology. Regular grids show a specific sharper transition not found for random or small-world grids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Development of a smart DC grid model

Smart grid and distributed generation should be the solution of the global climate change and the crisis energy of the main source of electrical power generation which is fossil fuel. In order to meet the rising electrical power demand and increasing service quality demands, as well as reduce pollution, the existing power grid infrastructure should be developed into a smart grid and distributed power generation which provide a great opportunity to address issues related to energy efficiency, energy security, power quality and aging infrastructure systems. The conventional of the existing distributed generation system is an AC grid while for a renewable resources requires a DC grid system. This paper explores the model of smart DC grid by introducing a model of smart DC grid with the stable power generation give a minimal and compressed circuitry that can be implemented very cost-effectively with simple components. The PC based application software for controlling was developed to show the condition of the grid and to control the grid become ‘smart’. The model is then subjected to a severe system perturbation, such as incremental change in loads to test the performance of the system again stability. It is concluded that the system able to detect and controlled the voltage stability which indicating the ability of power system to maintain steady voltage within permissible rangers in normal condition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Using a Grid-Forming Inverter to Stabilize a Low-Inertia Power System - Maui Hawaiian Island

As power systems around the world integrate greater amounts of wind and solar photovoltaic power, periods of very high instantaneous power shares of inverters, the primary interfacing technology for these generation sources, are complicating system stability and control. The contemporary, primary mode of inverter operation, grid-following, which explicitly assumes the presence of a local, stable voltage waveform, yields operational inadequacy at high instantaneous power shares potentially leading to instability due to the low-inertia conditions, as well as the correlated reduced voltage forming capacity on the respective system. Parallel connected grid-forming inverters, which directly regulate the local voltage, are a solution that is expected to bolster system stability and mitigate the shortcomings of the grid-following technology. In this paper, grid-following and two types of grid-forming inverter control, the traditional linear droop and the recently introduced nonlinear exponential droop (Droop-e), are simulated on a low-inertia, H = 0.48s, high inverter-based resource scenario, 97%, with a validated electromagentic transient domain model of the Hawaiian island of Maui power system. The benefit of a single grid-forming device over its grid-following counterpart is significant, both in terms frequency deviation and voltage stability. Further, the superiority of the Droop-e and the associated secondary power sharing control over both grid-following and linear droop grid-forming technologies is displayed, with improved nadir and rate of change of frequency over the linear droop control.

droop control↗
DOE OSTI2023

Developing a Disaster-Ready Power Grid Agent Through Geophysically-Informed Fault Event Scenarios

Management of the nation’s power grid over the coming decades will need to factor multiple climate-driven threats to the power system that can be stressful or even detrimental to its operations. During disasters, grid operators suffer from cognitive overload where the electric grid is severely impacted by the weather, yet grid operators have limited awareness of these factors. Meanwhile, the electric grid is facing an explosion of data coming from a variety of sources which can enable the operator to evaluate the risks and develop mitigation strategies against hazardous events. In this work, we processed heterogeneous environmental and power grid data to learn and model grid behavior caused by extreme weather events. In this study, we focused on two weather-driven hazards, hurricanes and wildfires, which were analysed for the electric grid of Texas. We the used this data to train a Reinforcement Learning (RL) agent by analysing and predicting future behaviour of the grid during those hazard events. All these parts are incorporated in one framework to have a geophysically informed power simulators that can be used to train RL agents.

electic grid, reinforcement learning, climate adap↗
DOE OSTI2018

Tariff Considerations for Micro-Grids in Sub-Saharan Africa

This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the name of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance This report examines some of the key drivers and considerations policymakers and decision makers face when deciding if and how to regulate electricity tariffs for micro-grids. Presenting a range of tariff options, from mandating some variety of national (uniform) tariff to allowing micro-grid developers and operators to set fully cost-reflective tariffs, it examines various benefits and drawbacks of each. In addition, the report and explores various types of cross-subsidies and other transitional forms of regulation that may offer a regulatory middle ground that can help balance the often competing goals of providing price control on electricity service in the name of social good while still providing a means for investors to ensure high enough returns on their investment to attract the necessary capital financing to the market. Using the REopt tool developed by the U.S. Department of Energy's National Renewable Energy Laboratory to inform their study, the authors modeled a few representative micro-grid systems and the resultant levelized cost of electricity, lending context and scale to the consideration of these tariff questions. This simple analysis provides an estimate of the gap between current tariff regimes and the tariffs that would be necessary for developers to recover costs and attract investment, offering further insight into the potential scale of subsidies or other grants that may be required to enable micro-grid development under current regulatory structures. It explores potential options for addressing this gap while trying to balance stakeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.takeholder needs, from subsidized national tariffs to lightly regulated cost-reflective tariffs to more of a compromise approach, such as different standards of regulation based on the size of a micro-grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Ultra-Large-Scale Power System Control and Coordination Architecture: A Strategic Framework for Integrating Advanced Grid Functionality

Electric power grids are being stressed by integration of intermittent renewable resources and significant adoption of distributed energy resources. The complexity of the grid is growing rapidly as we attempt to support technical, business, and societal goals for which power grids were not originally designed. Today, we largely take stability of the grid for granted. Stability could significantly degrade or collapse because of new dynamics introduced to the grid, and because the emerging extreme complexity makes traditional control analysis intractable, so that grid behavior is more unpredictable than in the past. This paper describes emerging issues in grid control and provides reasons why the present path of grid control evolution is problematic and presents an ultra-large scale framework for grid control that can solve today’s problems and those expected over the next 30 years. Failure to address these issues in the short term will result in rapidly escalating system deployment and maintenance costs, potential stranded assets related to replacement of the “ad hoc” systems, along with substantial operational risks that are unacceptable under current utility and regulatory practices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Roles and Responsibilities for Distribution Grids: DER Sensing and Communication Networks

Traditional distribution grids require sensing and communications for grid operations. In many cases the communications networks are owned by the Distribution Operator (DO); in some cases, carrier services such as leased telephone land lines or cellular services are used. In recent years, wireless mesh field area networks and optical fiber have become viable options for distribution. Fiber in particular has improved in cost to the point where its high performance (large bandwidth, low latency, and low packet loss) has become practical for distribution systems where geographic circumstances permit. As grid modernization proceeds, utilities find a need to improve or upgrade distribution communications; this represents a significant investment and it is natural that both utilities and regulators would seek both to future-proof and minimize their costs. Given the development and rising penetration of smart grid edge devices such as Distributed Energy Resources (DER) that have local sensing and intelligence and can communicate via the internet or other non-utility communications channels to cloud-based services, the idea of using such devices for grid sensing and communications to support grid operations has emerged as a potential means to avoid utility investment. To a great extent, however, these DER and communication channels will be owned and operated not by the DO but by end-use customers, aggregators and other third parties pursuing their own energy needs and business models. The question of whether such devices and systems can effectively substitute for DO grid modernization investment can be assessed and resolved using grid architecture methods and by considering the appropriate roles and responsibilities of the entities and systems involved in distribution grid operations. This approach reveals that there are several compelling reasons to dismiss the idea of eliminating DO owned and operated sensing and communication entirely and relying on DER-based sensing and third party communications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗
DOE OSTI2019

Modeling Electrolysis-based H2 Production for Grid Service Assessment

Hydrogen is a promising clean and renewable source of energy. Its high energy density offers a unique and effective means to store energy. The integration of hydrogen production devices with the power grid could lead to a cleaner and more reliable grid operation at reasonable costs. In this work, the capability of Proton Exchange Membrane (PEM) electrolyzers to perform grid services is assessed using a battery equivalent model approach. The Battery Equivalent Model (BEM) has been developed to represent the physics and operation of a fleet of PEM electrolyzers. The BEM model has been designed to be modular and readily incorporated into grid planning studies. This application of PEM electrolyzers can be integrated with other power generation and consumption devices, aggregating capabilities of each device to enhance the ability of the integrated system to provide grid services and improves grid stability. The developed model is evaluated using ancillary support services including peak management, frequency regulation, voltage regulation, artificial inertia, spinning reserve, and wholesale market price response using a representative price and power system profiles. The BEM model has also been evaluated to provide frequency regulation service that conforms to the IEEE 1547-2018 standard. Metrics such as energy efficiency, charging efficiency, hydrogen production rate, and service efficacy have been incorporated into the model to quantify the performance of the fleet while responding to grid services. Results show the electrolyzer fleet's effectiveness in quickly adjusting its real power consumption based on grid service requests. The energy efficiency of the fleet is maintained relatively high – in the range of 78% and 90% during the service operation. These results demonstrate the ability of PEM electrolyzers to effectively provide fast dispatch capability through storing off-peak hour energy while regulating power consumption during peak hours. The BEM model can assist in quantifying the stability and variability impacts from integration of PEM electrolyzers with intermittent renewable resources in grid integration studies.

08 HYDROGEN↗