Engineering topics

Myers, Kurt S.

Publications and source records attributed to Myers, Kurt S..

18 records

DOE OSTI2023

National Reactor Innovation Center (NRIC) Grid Connection Roadmap (Rev. 1)

In an effort to define the roadmap for establishing the necessary electrical infrastructure at the Idaho National Laboratory to fully support connection of NRIC reactors, this roadmap serves to identify the current forecasted reactors planned for installation at INL and provide a consolidated list of the identified infrastructure improvements that will be necessary to support testing of NRIC reactors. Additionally, the roadmap will leverage this information to establish an integrated timeline to support detailed planning and execution of system improvements. To drive this planning, requirements, as derived from authoritative sources, will be identified. A clear definition of impacted stakeholders will be established, as well as a list of risks that will need to be managed as the program moves forward.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

National Reactor Innovation Center (NRIC) Grid Connection Roadmap

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Energy management system, method of controlling one or more energy storage devices and control unit for one or more power storage units

Systems, methods and apparatuses are provided for reducing peak energy demand and to smooth intermittent energy profiles from onsite variable energy sources and loads. Some embodiments use system level and device level analysis and optimization to adaptively adjust the operation of a behind the meter energy storage (BMES) to smooth out energy generation variabilities and follow a reference load signal, including at short time resolutions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Big data analytics in smart grids: state-of-the-art, challenges, opportunities, and future directions

Big data has a potential to unlock novel groundbreaking opportunities in the power grid sector that enhances a multitude of technical, social, and economic gains. The currently untapped potential of applying the science of big data for better planning and operation of the power grid is a very challenging task and needs significant efforts all-around. As power grid technologies evolve in conjunction with measurement and communication technologies, this results in unprecedented amount of heterogeneous big data sets from diverse sources. In particular, computational complexity, data security, and operational integration of big data into utility decision frameworks are the key challenges to transform the heterogeneous large dataset into actionable outcomes. Moreover, due to the complex nature of power grids along with the need to balance power in real time, seamless integration of big data into utility operations is very critical. In this context, big data analytics combined with grid visualization can lead to better situational awareness and predictive decisions. This paper presents a comprehensive state-of-the-art review of big data analytics and its applications in power grids, and also identifies challenges and opportunities from utility, industry, and research perspectives. The paper analyzes research gaps and presents insights on future research directions to integrate big data analytics into electric utility decision framework. Detailed information for utilities looking to apply big data analytics and details insights on how utilities can enhance revenue streams and bring disruptive innovation in the industry are discussed. More importantly, general guidelines for utilities to make the right investment in the adoption of big data analytics by unveiling interdependencies among critical infrastructures and operations are also provided.

13 HYDRO ENERGY↗

DOE OSTI2018

Improvement of Transmission Line Ampacity Utilization by Weather-Based Dynamic Line Rating

Most of the existing overhead transmission lines (TLs) are assigned a static rating by considering the conservative environmental conditions (e.g., high ambient temperature and low wind speed). Such a conservative approach often results in underutilization of line ampacity because the worst conditions prevail only for a short period of time during the year. Dynamic line rating (DLR) utilizes local meteorological conditions and grid loadings to adaptively compute additional line ampacity headroom that may be available due to favorable local environmental conditions. This paper details Idaho National Laboratory-developed weather-based DLR, which utilizes a state-of-the-art general line ampacity state solver for real-time computation of thermal ratings of TLs. Performance of the proposed DLR solution is demonstrated in existing TL segments at AltaLink, Canada, and the potential benefits of the proposed DLR for enhanced transmission ampacity utilization are quantified. Moreover, we investigated a hypothetical case for emulating the impact of an additional wind plant near the test grid. Furthermore, the results for the given system and data configurations demonstrated that real-time ratings were above the seasonal static ratings for at least 76.6% of the time, with a mean increase of 22% over the static rating, thereby demonstrating huge potential for improvement on ampacity utilization.

17 WIND ENERGY↗

DOE OSTI2017

Transmission Line Ampacity Improvements of AltaLink Wind Plant Overhead Tie-Lines Using Weather-Based Dynamic Line Rating

Abstract—Overhead transmission lines (TLs) are conventionally given seasonal ratings based on conservative environmental assumptions. Such an approach often results in underutilization of the line ampacity as the worst conditions prevail only for a short period over a year/season. We presents dynamic line rating (DLR) as an enabling smart grid technology that adaptively computes ratings of TLs based on local weather conditions to utilize additional headroom of existing lines. In particular, general line ampacity state solver utilizes measured weather data for computing the real-time thermal rating of the TLs. The performance of the presented method is demonstrated from a field study of DLR technology implementation on four TL segments at AltaLink, Canada. The performance is evaluated and quantified by comparing the existing static and proposed dynamic line ratings, and the potential benefits of DLR for enhanced transmission assets utilization. For the given line segments, the proposed DLR results in real-time ratings above the seasonal static ratings for most of the time; up to 95.1% of the time, with a mean increase of 72% over static rating.

17 WIND ENERGY↗

DOE OSTI2017

Optimal Coordinated EV Charging with Reactive Power Support in Constrained Distribution Grids

Electric vehicle (EV) charging/discharging can take place in any P-Q quadrants, which means EVs could support reactive power to the grid while charging the battery. In controlled charging schemes, distribution system operator (DSO) coordinates with the charging of EV fleets to ensure grid’s operating constraints are not violated. In fact, this refers to DSO setting upper bounds on power limits for EV charging. In this work, we demonstrate that if EVs inject reactive power into the grid while charging, DSO could issue higher upper bounds on the active power limits for the EVs for the same set of grid constraints. We demonstrate the concept in an 33-node test feeder with 1,500 EVs. Case studies show that in constrained distribution grids in coordinated charging, average costs of EV charging could be reduced if the charging takes place in the fourth P-Q quadrant compared to charging with unity power factor.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Photovoltaic Hosting Capacity of Feeders with Reactive Power Control and Tap Changers

This paper proposes an algorithm to determine photovoltaic (PV) hosting capacity of power distribution networks as a function of number of PV injection nodes, reactive power support from the PVs, and the sub-station load tap changers (LTCs). In the proposed method, several minute by minute simulations are run based on randomly chosen PV injection nodes, daily PV output profiles, and daily load profiles from a pool of high-resolution realistic data set. The simulation setup is built using OpenDSS and MATLAB. The performance of the proposed method is investigated in the IEEE 123-node distribution feeder for multiple scenarios. The case studies are performed particularly for one, two, five and ten PV injection nodes, and looking at the maximum voltage deviations. Case studies show that the PV hosting capacity of the 123-node feeder greatly differs with the number of PV injection nodes. We have also observed that the PV hosting capacity increases with reactive power support and higher tap position of sub-station LTC.

14 SOLAR ENERGY↗

DOE OSTI2017

Optimum aggregation of geographically distributed flexible resources in strategic smart-grid/microgrid locations

This paper determines optimum aggregation areas for a given distribution network considering spatial distribution of loads and costs of aggregation. An elitist genetic algorithm combined with a hierarchical clustering and a Thevenin network reduction is implemented to compute strategic locations and aggregate demand within each area. The aggregation reduces large distribution networks having thousands of nodes to an equivalent network with few aggregated loads, thereby significantly reducing the computational burden. Furthermore, it not only helps distribution system operators in making faster operational decisions by understanding during which time of the day will be in need of flexibility, from which specific area, and in which amount, but also enables the flexibilities stemming from small distributed resources to be traded in various power/energy markets. A combination of central and local aggregation scheme where a central aggregator enables market participation, while local aggregators materialize the accepted bids, is implemented to realize this concept. The effectiveness of the proposed method is evaluated by comparing network performances with and without aggregation. Finally, for a given network configuration, steady-state performance of aggregated network is significantly accurate (≈ ±1.5% error) compared to very high errors associated with forecast of individual consumer demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Reducing Demand Charges and Onsite Generation Variability Using Behind-the-Meter Energy Storage

Electric utilities in the United States are increasingly employing demand charges and/or real-time pricing. This directive is bringing potential opportunities in deploying behindthe-meter energy storage (BMES) systems for various grid functionalities. This study quantifies techno-economic benefits of BMES in reducing demand charge and smoothing load/generation intermittencies, and determines how those benefits vary with onsite distributed photovoltaic. We proposed a two-stage control algorithm, whereby the first stage proactively determines costoptimal BMES configuration for reducing peak-demands and demand charges, and the second stage adaptively compensates intermittent generations and short load spikes that may otherwise increase the demand charges. The performance of the proposed algorithm is evaluated through a 24 hours time sweep simulation performed using data from smart microgrid testbed at Idaho National Laboratory (INL). The simulation results demonstrated that this research provides a simple but effective solution for peak shaving, demand charge reductions, and smoothing onsite PV variability.

25 ENERGY STORAGE↗

DOE OSTI2017

Optimum Aggregation and Control of Spatially Distributed Flexible Resources in Smart Grid

This paper presents an algorithm to optimally aggregate spatially distributed flexible resources at strategic microgrid/smart-grid locations. The aggregation reduces a distribution network having thousands of nodes to an equivalent network with a few aggregated nodes, thereby enabling distribution system operators (DSOs) to make faster operational decisions. Moreover, the aggregation enables flexibility from small distributed flexible resources to be traded to different power and energy markets. A hierarchical control architecture comprising a combination of centralized and decentralized control approaches is proposed to practically deploy the aggregated flexibility. The proposed method serves as a great operational tool for DSOs to decide the exact amount of required flexibilities from different network section(s) for solving grid constraint violations. The effectiveness of the proposed method is demonstrated through simulation of three operational scenarios in a real low voltage distribution system having high penetrations of electric vehicles and heat pumps. Finally, the simulation results demonstrated that the aggregation helps DSOs not only in taking faster operational decisions, but also in effectively utilizing the available flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Design and Cosimulation of Hierarchical Architecture for Demand Response Control and Coordination

Demand response (DR) plays a key role for optimum asset utilization and to avoid or delay the need of new infrastructure investment. However, coordinated execution of multiple DRs is desired to maximize the DR benefits. In this paper, we propose a hierarchical DR architecture (HDRA) to control and coordinate the performance of various DR categories such that the operation of every DR category is backed-up by time delayed action of the others. A reliable, cost-effective communication infrastructure based on ZigBee, WiMAX, and fibers is designed to facilitate the HDRA execution. The performance of the proposed HDRA is demonstrated from the power system and communication perspectives in a cosimulation environment applied to a 0.4 kV/400 kVA real distribution network considering electric vehicles as a potential DR resource (DRR). The power simulation is performed employing a real time digital simulator whereas the communication simulation is performed using OMNeT++. Finally, the HDRA performance demonstrated the maximum utilization of available DR potential by facilitating simultaneous execution of multiple DRs and enabling participation of single DRR for multiple grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Procter & Gamble Wind and Solar Analysis Summary

This LETTER REPORT has been prepared by Idaho National Laboratory (INL) as a basic summary of wind data, solar data, and energy production analyses for the Procter & Gamble (P&G) Box Elder Plant in Tremonton, UT. Along with this initial analysis report, future development studies/reports may go into more detail and be used to support the development of a renewable energy projects on P&G property. These summaries may also be used as supplemental material to support and accelerate further data analysis by other parties involved in the final development and construction of a renewable project.

14 SOLAR ENERGY↗

DOE OSTI2014

A Comparison of Real-Time Thermal Rating Systems in the U.S. and the U.K.

Real-time thermal rating is a smart-grid technology that allows the rating of electrical conductors to be increased based on local weather conditions. Overhead lines are conventionally given a conservative, constant seasonal rating based on seasonal and regional worst case scenarios rather than actual, say, local hourly weather predictions. This paper provides a report of two pioneering schemes-one in the U.S. and one in the U.K.-where real-time thermal ratings have been applied. Thereby, we demonstrate that observing the local weather conditions in real time leads to additional capacity and safer operation. Second, we critically compare both approaches and discuss their limitations. In doing so, we arrive at novel insights which will inform and improve future real-time thermal rating projects.

17 WIND ENERGY↗

DOE OSTI2014

Dynamic Line Rating: Research and Policy Evaluation

Dynamic Line Rating (DLR) is a smart grid technology that allows the rating of electrical conductors to be increased based on local weather conditions. Overhead lines are conventionally given a conservative rating based on worst case scenarios. We demonstrate that observing the conditions in real time leads to additional capacity and safer operation. This paper provides a report of a pioneering scheme in the United States of America in which DLR has been applied. Thereby, we demonstrate that observing the local weather conditions in real time leads to additional capacity and safer operation. Secondly, we discuss limitations involved. In doing so, we arrive at novel insights which will inform and improve future DLR projects. Third, we provide a policy background and discussion to clarify the technology’s potential and identifies barriers to the imminent adoption of dynamic line rating systems. We provide suggestions for regulatory bodies about possible improvements in policy to encourage adoption of this beneficial technology.

17 WIND ENERGY↗

DOE OSTI2013

Malmstrom Air Force Base Wind Farm Economic Analysis

The Air Force’s Civil Engineer Support Agency and Global Strike Command (AFCESA and AFGSC) retained Idaho National Laboratory (INL) to perform an Economic Feasibility Study for a potential Malmstrom Air Force Base (MAFB) third party developed wind energy project in Great Falls, MT.

17 WIND ENERGY↗

DOE OSTI2012

Technical Assessment for the CPC FD-7x-1500 Wind Turbine located at Tooele Army Base, Tooele Utah

The CPC FD-7x-1500 Wind Turbine was installed with funding from the Energy Conservation Investment Program (ECIP). Since its installation, the turbine has been plagued with multiple operational upsets causing unacceptable down time. In an effort to reduce down time, the Army Corps of Engineers requested the Idaho National Laboratory conduct an assessment of the turbine to determine its viability as an operational turbine.

17 WIND ENERGY↗

DOE OSTI2012

Developing Government Renewable Energy Projects

The US Army Corps of Engineers has retained Idaho National Laboratory (INL) to conduct a study of past INL experiences and complete a report that identifies the processes that are needed for the development of renewable energy projects on government properties. The INL has always maintained expertise in power systems and applied engineering and INL’s renewable energy experiences date back to the 1980’s when our engineers began performing US Air Force wind energy feasibility studies and development projects. Over the last 20+ years of working with Department of Defense and other government agencies to study, design, and build government renewable projects, INL has experienced the do’s and don’ts for being successful with a project. These compiled guidelines for government renewable energy projects could include wind, hydro, geothermal, solar, biomass, or a variety of hybrid systems; however, for the purpose of narrowing the focus of this report, wind projects are the main topic discussed throughout this report. It is our thought that a lot of what is discussed could be applied, possibly with some modifications, to other areas of renewable energy. It is also important to note that individual projects (regardless the type) vary to some degree depending on location, size, and need but in general these concepts and directions can be carried over to the majority of government renewable energy projects. This report focuses on the initial development that needs to occur for any project to be a successful government renewable energy project.

17 WIND ENERGY↗