Dynamic Programming Method to Optimally Select Power Distribution System Reliability Upgrades
Not Available
42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “electric grid systems”
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.
Multi-timescale operations of nuclear-renewable hybrid energy systems for reserve and thermal product provision
In this paper, an optimal operation strategy of a nuclear-renewable hybrid energy system (N-R HES), in conjunction with a district heating network, is developed within a comprehensive multi-timescale electricity market framework. The grid-connected N-R HES is simulated to explore the capabilities and benefits of N-R HES of providing energy products, different reserve products, and thermal products. An N-R HES optimization and control strategy is formulated to exploit the benefits from the hybrid energy system in terms of both energy and ancillary services. A case study is performed on the customized NREL-118 bus test system with high renewable penetrations, based on a multi-timescale (i.e., three-cycle) production cost model. Both day-ahead and real-time market clearing prices are determined from the market model simulation. In conclusion, the results show that the N-R HES can contribute to the reserve requirements and also meet the thermal load, thereby increasing the economic efficiency of N-R HES (with increased revenue ranging from 1.55% to 35.25% at certain cases) compared to the baseline case where reserve and thermal power exports are not optimized.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Best Practices for Resilience in Smart Grid-Interactive Efficient Buildings
The Federal Energy Management Program (FEMP) supports federal agencies' energy decisions with information and guidance on design, funding, and operations to ensure federal buildings are efficient and resilient. The modernization of building infrastructure and the evolution of buildings to support decarbonization involves complex implementation of multiple components across several systems. This includes energy-efficient equipment, on-site energy generation and storage systems, and control systems. These systems have operational modes that can operate more efficiently if they are able to behave responsively to the conditions of the electrical grid. These grid-interactive efficient buildings (GEB) allow facilities to manage power demand according to operational constraints and market signals issued by grid operators. With proper design and planning, these same capabilities have the potential to enable building and facility resilience - coordinating with microgrids, maintaining power on critical circuits to sustain essential operations, and monitoring building health and safety status during an outage. By managing the load of buildings, GEBs can also reduce the cost of backup generation and make better use of renewable power sources on site. This document outlines some of the processes and considerations to guide the design and operation of GEBs in ways that promote facility resilience.
building decarbonization↗
Model Predictive Control for a Grid-interactive Efficient Thermal Storage-integrated Heat Pump System
Building heating and cooling systems can be used to overcome the mismatch between the intermittent supply of renewable power and the fluctuating demand for electricity. A novel underground thermal energy storage integrated with a dual-source heat pump has been proposed to mitigate the mismatch while meeting the thermal demand of buildings efficiently. Conventional thermostat control with heuristic rules cannot provide intelligent decisions to maximize the thermal efficiency and flexibility of the proposed system. Advanced control strategies like model predictive control (MPC) have provided a new paradigm for grid-interactive efficient building operation with the advancement of computation and sensing. This study developed an MPC for the proposed system to provide grid service for Demand Side Management and minimize the operating cost of building owners. A control-oriented dynamic model of the proposed system has been developed. Given an objective function and proper constraints, an optimization problem is formulated to determine the optimal control strategy of the system. Dynamic Programming is adopted to solve the optimization problem. A rule-based control (RBC) is also developed to achieve similar goals. Short-term simulations are conducted to compare the system performance resulting from the two controls. The simulation results indicate that the MPC performs more intelligently than the RBC in charging thermal energy storage and selecting heat pump sources by taking advantage of the predicted cooling demands of the building and the performance of the integrated system. As a result, the MPC could save energy and reduce operating costs compared with the RBC. A case study shows that, for a 3-day operation, the MPC saves 36.9% energy and reduces 38.5% operating cost compared with the RBC.
Shi, Liang↗
Analyzing Risks and Vulnerabilities of Various Computer Systems and Undergoing Exploitation using Embedded Devices
Security is one of the most if not the most important areas today. After the several attacks on the United States, security everywhere has heightened from airports to communication among the military branches legionnaires. With advanced persistent threats (APTs) on the rise following Stuxnet, government branches and agencies are required, more than ever, to follow several standards, policies and procedures to reduce the likelihood of a breach. Attack vectors today are very advanced and are going to continue to get more and more advanced as security controls advance. This creates a need for networks and systems to be in an updated, patched and secured state in a launch control system environment. Attacks on critical systems are becoming more and more relevant and frequent. Nation states are hacking into critical networks that might control electrical power grids or water dams as well as carrying out advanced persistent threat (APTs) attacks on government entities. NASA, as an organization, must protect its self from attacks from all different types of attackers with different motives. Although the International Space Station was created, there is still competition between the different space programs. With that in mind, NASA might get attacked and breached for various reasons such as espionage or sabotage. My project will provide a way for NASA to complete an in house penetration test which includes: asset discovery, vulnerability scans, exploit vulnerabilities and also provide forensic information to harden systems. Completing penetration testing is a part of the compliance requirements of the Federal Information Security Act (FISMA) and NASA NPR 2810.1 and related NASA Handbooks. This project is to demonstrate how in house penetration testing can be conducted that will satisfy all of the compliance requirements of the National Institute of Standards and Technology (NIST), as outlined in FISMA. By the end of this project, I hope to have carried out the tasks stated above as well as gain an immense knowledge about compliance, security tools, networks and network devices, as well as policies and procedures.
Penetration Testing↗
Grid Modeling and Hosting Capacity Analysis
An interface with the OpenDSS distribution grid simulator, facilitating users in calibrating and validating models. Additionally, three distinct tools have been developed: PV Hosting Capacity: This tool allows users to determine the additional amount of photovoltaic (PV) generation that can be integrated into the system without breaching operational constraints. EV Hosting Capacity: This tool focuses on identifying the capacity for incorporating extra electric vehicle (EV) load into the system without surpassing operational limitations. Project Impact Analysis Tool: This tool is designed to assess and report all potential grid violations associated with a specific project, providing valuable insights into its impact on the distribution grid.
Poudel, Shiva↗
An Integrated Paradigm for the Management of Delivery Risk in Electricity Markets: From Batteries to Insurance and Beyond
If power systems transition to integrate higher amounts of variable renewable energy sources, storage technologies, and distributed energy resources (DERs), new risk management frameworks are necessary to ensure cost-effective and reliable power system operations. Projects funded by the Advanced Research Projects Agency-Energy (ARPA-E) Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program aim to contribute new risk management frameworks by developing methods to quantify and manage risk at grid asset and system levels. The National Renewable Energy Laboratory (NREL) led a PERFORM project in collaboration with the Johns Hopkins University, the Electric Power Research Institute (EPRI), kWh Analytics, Packetized Energy, and Imperial Consultants (ICON). The project addressed two challenges related to risk management in electricity markets: managing net load imbalances and flexibility from DERs. This final technical report presents a list of project accomplishments, activities, and outputs.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Summary of a Workshop on Integrating Energy Equity into Power System Planning and Operation
On November 29 and 30, 2023, the Energy Systems Integration Group convened a one-and-a-half-day workshop in Arlington, Virginia, to improve knowledge and practices for integrating energy equity considerations into power system planning and operation. Workshop participants were invited to discuss approaches for integrating energy equity aspects into models and tools and to explore possible pathways for enhanced technical practices. Participants included utility planning and modeling practitioners, social science and energy justice academics, representatives from energy and environmental justice nongovernmental organizations, non-profits, consumer advocates, and representatives from the U.S. Department of Energy, national labs, and other government agencies. This report summarizes the discussion points and outcomes of the workshop, which prioritized the technical aspects of incorporating the challenges and solutions identified by electricity-futures stakeholders and communities. These technical activities include the fundamental grid structure and hardware, detailed modeling approaches that benchmark energy system performance and justify future investments, and engineering designs and limitations for potential solutions to meet energy equity goals in communities.
energy equity↗
A Path to 100 Percent Renewable Energy: Grid-Forming Inverters will Give Us the Grid We Need Now
This is a more urgent problem than it might sound. The westernmost Hawaiian island of significant size, Kauai is home to around 70,000 residents and 30,000 tourists at any given time. Renewable energy accounts for 70 percent of the energy produced in a typical year - a proportion that's among the highest in the world and that can be hard to sustain for such a small and isolated grid. During the day, the local system operator, the Kauai Island Utility Cooperative, sometimes reaches levels of 90 percent from solar alone. But on 2 April, the 26-MW generator was running near its peak output, to compensate for the drop in solar output as the sun set. At the moment when it failed, that single generator had been supplying 60 percent of the load for the entire island, with the rest being met by a mix of smaller generators and several utility-scale solar-and-battery systems.
battery management systems↗
A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms
There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.
Lee, Jangjae [Texas A & M Univ., College Station, ↗
Self-powered Heating: Efficiency Analysis
Conventional fuel-fired heating devices such as furnaces, boilers, and water heaters have fuel efficiency less than 100% on the basis of higher heating value. They also require electricity from the electric grid to power parasitic loads such as blowers, pumps, fans, and ignitors. The primary energy efficiency of the device accounts for both fuel used on-site and primary energy used off-site to produce electric power used by the device. This work compares conventional fuel-fired heating devices to two types of self-powered devices. A self-powered device (SPD) integrates a power cycle onboard to eliminate consumption of grid electricity. We assume that all heat rejected by the onboard power cycle is added to the process fluid, so that, compared with a conventional device, the same amount of heat is provided to the process fluid and the same amount of fuel is consumed, but grid electricity consumption is eliminated. The first SPD type is the basic one: exactly the electricity required is generated. The second type considered is the SPD with heat pump (SPD-HP), in which the power cycle generates more electricity than needed for parasitic loads, and the excess electricity is used to power a heat pump. The heat pump extracts additional heat from the ambient to boost efficiency. Both SPD and SPD-HP self-consume all the generated electricity, in contrast to combined heat and power (CHP) systems that export electricity. In this work, equations are derived to express the efficiency of three classes of heating devices: conventional (consuming grid electricity), self-powered (consuming no grid electricity), and self-powered with heat pump. The efficiency of each is derived as a function of up to six factors: (1) the fraction of combustion heat captured, (2) the rate of parasitic power consumption, (3) the fraction of electric energy dissipated as useful heat, (4) the power cycle conversion efficiency, (5) the grid efficiency, when applicable, and (6) the heat pump COP, when applicable. Scenarios are identified in which it is possible to achieve efficiency greater than 100% on a higher heating value basis. Plausible configurations using existing technology options are outlined.
Gluesenkamp, Kyle↗
Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022
Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.
Array↗
Preliminary Component Design and Cost Estimation of a Novel Electric-Thermal Energy Storage System Using Solid Particles
Energy storage will become indispensable to complement the uncertainty of intermittent renewable resources and to firm the electricity supply as renewable power generation becomes the mainstream new-built energy source and fossil fuel power plants are phased out to meet carbon-neutral utility targets. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system is projected to have promising cost and performance characteristics to meet the future growing energy storage needs. This paper introduces the system and components required for particle TES to become technically and economically competitive. The system integrates electric particle heaters, particle TES within insulated concrete silos, and an efficient air-Brayton combined-cycle power system to provide power for storage durations up to several days via low-cost, high-performance storage cycles. Design specifications and cost estimation of major components in a commercial-scale system are presented in this paper. A techno-economic analysis based on preliminary component designs and performance indicates that particle TES integrated with an air-Brayton combined-cycle power system has a path to achieve the targeted levelized cost of storage of 5 ¢/kWh-cycle at a round-trip efficiency of 50% when taking low-cost energy-specific components and leveraging basic assets from existing thermal power plants. The cost model provides insights for further development and economic potentials for long-duration energy storage.
14 SOLAR ENERGY↗
Modelling and analysis of nuclear reactor system coupled with a liquid metal battery
Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.
25 ENERGY STORAGE↗
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↗
Validating Protection System Behavior with Machine Learning in a Master State Overseer
As power system protection devices continue the widespread transition from analog to digital, they become increasingly intricate. The internal functions and communication between critical grid components must now be significantly more complex to keep up with the demands of the modern smart grid. This brings increased difficulty in maintenance and monitoring, making it harder to identify potential misoperation, power anomalies, and cyber threats. Such issues are often only pinpointed after an exhaustive and costly post-mortem analysis, when a major outage or damage has already occurred. A solution is needed for validating protection systems as they operate, independently evaluating grid state and confirming whether the protection system is behaving accordingly. As opposed to incident response, this acts as a constant verification mechanism that raises a flag when subtler issues are noticed, catching them earlier and preventing larger incidents. This work presents the implementation of such a system, expanding on the prototype developed by the authors in a previous paper. This is accomplished with a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. Additionally, this system is contextualized within a larger, modular Master State awareness Overseer (MSO) framework, responsible for monitoring, analyzing, and managing an electric grid.
24 - POWER TRANSMISSION AND DISTRIBUTION↗
Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection
The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak demand, increasingly diverse generating resources, and fast-growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification. Projecting where future generation may be developed is critical to maintaining a robust and resilient electric grid under this mounting uncertainty and variability. Using an integrated multisectoral, multiscale modeling framework that links a human-Earth systems model, an hourly load model, a geospatial power plant siting model, and an hourly grid operations model, we evaluate the power plant landscape evolution under eight alternative futures between 2020 and 2055. These futures represent a wide but plausible range of atmospheric conditions, emissions constraints, and economic, technological, and population growth assumptions. We find that local-level development can vary substantially both by generation type and capacity buildout across these futures. Specific regions of the Western Interconnection are projected to see large amounts of capacity development regardless of the future scenario. We additionally determine that projected power plant locations are more heavily influenced by the cost to interconnect to the electric grid than the locational energy value.
Mongird, Kendall↗
A Review of Current Research Trends in Power-Electronic Innovations in Cyber–Physical Systems
Here, in this article, a broad overview of the current research trends in power-electronic innovations in cyber–physical systems (CPSs) is presented. The recent advances in semiconductor device technologies, control architectures, and communication methodologies have enabled researchers to develop integrated smart CPSs that can cater to the emerging requirements of smart grids, renewable energy, electric vehicles, trains, ships, the Internet of Things (IoT), and so on. The topics presented in this article include novel power-distribution architectures, protection techniques considering large renewable integration in smart grids, wireless charging in electric vehicles, simultaneous power and information transmission, multihop network-based coordination, power technologies for renewable energy and smart transformer, CPS reliability, transactive smart railway grid, and real-time simulation of shipboard power systems. It is anticipated that the research trends presented in this article will provide a timely and useful overview to the power-electronics researchers with broad applications in CPSs.
24 POWER TRANSMISSION AND DISTRIBUTION↗