Power Conversion and Control Systems for a Modern Electric Grid
Explore the source record for details and available documents.
SEARCH · Engineering Papers
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.
Explore the source record for details and available documents.
Energy storage, at various scales, will be required to maintain reliable power supply from variable renewable resources, and improve grid resilience. Long-duration energy storage (10-100 h) can substitute baseload coal power generation and increase levels of renewable power supply. Thermal energy storage (TES) has siting flexibility and the ability to store a large capacity of energy, and thus it has the potential to meet the needs of long-duration energy storage. Here, a novel TES system was developed by using solid particles as storage media and charging/discharging electricity from renewable power connected via the electric grid. The particle TES uses low-cost silica sand at 30-40$/Ton that is stable at high temperatures of >1,000 degrees C. Thus, the particle TES system has an overall low storage cost and high thermal-power efficiency. Key components of the system were conceptually designed and modeled for their performance. Conversion of electricity to thermal energy using electric heating can achieve a >98% charging efficiency, and the conversion of thermal energy back to electricity uses an air-Brayton combined power cycle with >52% thermal-to-electricity efficiency at >1,170 degrees C to achieve a >50% roundtrip efficiency after subtracting estimated plant parasitic losses. Laboratory-scale prototypes were fabricated and tested to verify their design approaches and operations relevant to product-scale components.
China is actively promoting vehicle electrification, which is deemed to help achieve its ambitious carbon neutrality goal by 2060. Here we show that vehicle electrification in China leads to an increase in automotive emissions of mercury, a persistent, global hazardous pollutant regulated in the United Nations’ Minamata Convention. We found that with current technologies, life-cycle mercury emissions of battery electric vehicles of 300 miles of all-electric range are 92% higher than conventional gasoline internal combustion engine vehicles, primarily due to the high mercury emissions from coal-based electricity generation. Notably different from greenhouse gases, mercury emissions are mainly embedded in vehicular material production and vehicle manufacturing, accounting for 50–60% for electric vehicles and ~90% for gasoline vehicles of their life-cycle mercury emissions. Even with a deeply decarbonized power grid, mercury footprints of electric vehicles would still be higher than those of gasoline vehicles, implying a potential increase in automotive mercury emissions in any countries that promote vehicle electrification. Measures including decarbonizing electric grid, implementing mercury-specific emission control through vehicle supply chain, and increasing metal recycling in electric vehicle batteries will help mitigate the unintended mercury emission increase caused by vehicle electrification.
In this talk, we give an overview of the field of convex optimization and work through four canonical problems that relate to electrical power systems and smart grids. The purpose of these examples is to demonstrate the breadth of applications of convex optimization in energy research and to show that toy versions of these problems can be solved in just a few lines of code, indicating the scale and complexity of problems that can be tackled with a more detailed treatment. We emphasize the cvxpy modeling language as a foundational technology that enables rapid development and prototyping of convex optimization problems, allowing researchers to focus on model development rather than get caught in the weeds of numerical and code implementation.
NASA Glenn Research Center, in collaboration with the aerospace industry and academia, has begun the development of technology for a future hybrid-wing body electric airplane with a turboelectric distributed propulsion (TeDP) system. It is essential to design a subscale system to emulate the TeDP power grid, which would enable rapid analysis and demonstration of the proof-of-concept of the TeDP electrical system. This paper describes how small electrical machines with their controllers can emulate all the components in a TeDP power train. The whole system model in Matlab/Simulink was first developed and tested in simulation, and the simulation results showed that system dynamic characteristics could be implemented by using the closed-loop control of the electric motor drive systems. Then we designed a subscale experimental system to emulate the entire power system from the turbine engine to the propulsive fans. Firstly, we built a system to emulate a gas turbine engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft. We programmed the first motor and its drive to mimic the speed-torque characteristic of the gas turbine engine, while the second motor and drive act as a generator and produce a torque load on the first motor. Secondly, we built another system of two PM motors and drives to emulate a motor driving a propulsive fan. We programmed the first motor and drive to emulate a wound-rotor synchronous motor. The propulsive fan was emulated by implementing fan maps and flight conditions into the fourth motor and drive, which produce a torque load on the driving motor. The stator of each PM motor is designed to travel axially to change the coupling between rotor and stator. This feature allows the PM motor to more closely emulate a wound-rotor synchronous machine. These techniques can convert the plain motor system into a unique TeDP power grid emulator that enables real-time simulation performance using hardware-in-the-loop (HIL).
A large fraction of the world's population lacks access to the electric grid. Standard photovoltaic (PV) cells can provide a renewable off-grid source of electricity but only produce power from daytime solar irradiance and do not produce power at night. While there have been several theoretical proposals and experimental demonstrations of energy harvesting from the radiative cooling of a PV cell at night, the achieved power density is very low. Here, we construct a device, which incorporates a thermoelectric generator that harvests electricity from the temperature difference between the PV cell and the ambient surrounding. We achieve 50 mW/m 2 nighttime power generation with a clear night sky, with an open-circuit voltage of 100 mV, which is orders of magnitude higher as compared with previous demonstrations. During the daytime, the thermoelectric generator also provides additional power on top of the electric power generated directly from the PV cells. Our system can be used as a continuous renewable power source for both day- and nighttime in off-grid locations.
During fiscal year 2021 (FY 2021), the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO) funded early-stage research, development, demonstration, & deployment (RDD&D) projects that address Batteries and Electrification of the U.S. transportation sector. The VTO Electrification Sub-Program is composed of Electric Drive Technologies, and Grid Integration activities. The Electric Drive Technologies group conducts R&D projects that advance electric motors and power electronics technologies. The Grid and Charging Infrastructure group conducts R&D projects that advance grid modernization and electric vehicle charging technologies. This document presents a brief overview of the Electrification Sub-Program and progress reports for its R&D projects. Each of the progress reports provide a project overview and highlights of the technical results that were accomplished in fiscal year (FY) 2021.
Maintaining reliability of the bulk power system, which supplies and transmits electricity, is a constant focus of electric grid planners, operators, and regulators. Based on the standards set by power system reliability entities, the U.S. grid has been and continues to be very reliable. Over the past decade the average U.S. customer has only experienced about 15 minutes of outages per year due to supply limitations, with most of those outages occurring due to failures on the distribution system. However, there have been a few notable incidents in recent years tied to extreme weather events. The fact sheet provides and introduction to reliability of the bulk power system in the U.S.
Increased renewables penetration to electrical grid is necessary to reduce overall emissions from the electrical power generation sector. Nonetheless, its integration creates challenges to grid operators who must match the power being generated by intermittent renewables and other traditional energy sources with the demand from consumers, while ensuring the reliability and power quality for the entire system. Energy storage has been proposed as an alternative to natural gas peaking plants and a form to deliver excess renewable energy generation at times of peak demand. For energy storage to provide benefits to end customers (energy consumers), it must be reliable, efficient, and cost effective. The Illinois Sustainable Technology Center (ISTC), one of the surveys that integrate the Prairie Research Institute (PRI), aims to develop a Center for Energy Storage at Existing Assets (CESEA) at UIUC with the participation of Waste Pressure Corp and Ecotek Engineering USA LLC. CESEA will focus on LDES systems that can integrate to existing infrastructure in a manner that reduces the initial capital expenditure and demonstrates the ability to repurpose fossil assets that would otherwise become stranded, to serve the energy transition. CESEA aims to leverage UIUC’s unique facilities to validate LDES systems performance at a relevant operating environment. UIUC’s facilities include a 85-MW combined heat and power (CHP) power plant, two (2) solar PV plants totaling over 18 MWdc of installed capacity, an electrical grid along with a substation at transmission and distribution voltages, a 22-mile gas pipeline network operating at two pressure levels, along with steam and chilled water distribution networks. The new LDES systems will connect to the existing UIUC grid through a new test electrical station, which will have the capacity to accommodate additional connections to test new devices and technologies as part of future CESEA R&D activities. The test electrical station will contain meters, instrumentation, and controls to accurately capture data and allow optimization of control algorithms. CESEA will initially focus on technologies that: i) utilize existing equipment or facilities to perform at least one of the process steps in LDES (charging, storage, or discharging), ii) leverage mature or commercially available components or controls, iii) show potential for cost-leadership in 10+ hour storage at a commercial scale. Initial technologies that were identified to meet these criteria include Compressed Gas Energy Storage (CGES), and TES. CGES stores electricity by raising the pressure of a compressible gas inside a control volume and converting the stored energy to electricity via expansion-generation. CGES is a generalization of CAES that covers any working gas (not just air). A successful CGES demo will help to circumvent many challenges faced by CAES (long development times due to site prospecting, high cost of compression and storage, heat recovery management, etc.) by: 1) utilizing existing infrastructure (compressors, pipelines, underground storage or pressure vessels) used in the transportation and storage of industrial gases for LDES charging and storage; 2) deploying over sites already-developed for industrial applications with minor additional work; 3) leveraging the price structure of commercial industrial gas to cover the costs of electricity used during charging. A previous DOE-sponsored conceptual study (DE-FE-0032018) estimated the levelized cost of energy of a 1.1 MW / 17 MWh CGES system at $0.08/kWh, with a commercial 10x scale system cost estimated at <$0.04/kWh (Giardinella, 2022). The pilot-sized system was estimated to avoid up to 2693 tons of CO2/year.
There has been a buzz around increased grid modernization for more than a decade. Grid modernization includes, but is not limited to, upgrades to the grid to enhance reliability, resilience, security, and access to clean energy sources. One significant change that has been happening in this context is the increased penetration of computing power and controlled devices like power electronics in the power grid. As this change happens, the operation and characteristics of the power grid are set to undergo a significant change. The power grid moves from an older electric machine dominated grid that used analog electronics for controls to a power electronics dominated grid that uses digital computing for controls. As this transition happens, there are significant problems of applied mathematics that will need to be resolved in power electronics and power grid. The problems include the ability to simulate in different timescales, while also leveraging the significantly improved computing capabilities available today. In this paper, the challenges related to simulation of power electronics are discussed and the challenge problems laid down that applied mathematics may help resolve in future.
This report summarizes the design and application of an outdoor power line sensor testbed (OPLST) with a real-time simulator and power meter to compare a potential transformer (PT) and current transformer (CT) versus an advanced line-post sensor. The OPLST was created to validate advanced medium-voltage (20/34.5 kV) outdoor power line sensors used in electrical distribution systems. Electrical utilities have installed metering and relay-protection transformers like PTs and CTs for several decades. The PTs/CTs are iron core measurement transformers based on the electromagnetic induction principle and provide reliable data in normal grid operation. However, new outdoor power line sensors (OPLS) using other technologies like voltage divider, Rogowski coil and optical principles have become available and may have favorable performance and costs compared to PTs/CTs. Therefore, the importance of testing these technologies with the PT/CT, to compare the measured phase voltage/current at different power grid scenarios is crucial to understand the performance of these new OPLS. For this study a G&W Electric Model CVS-36-O power line sensor was chosen as the OPLS to test with voltage/current signals. An OPAL-RT Technologies Model OP4510 real-time simulator and Schweitzer Engineering Laboratories Model SEL-735 power meter were installed with the 20/34.5 kV OPLST to compare the measured transient events collected from an advanced OPLS and the PT/CT. This system is installed at the Distributed Energy Communications and Control (DECC) lab, Oak Ridge National Laboratory (ORNL). The simulator generated different power grid scenarios (electrical faults, capacitor bank operation, service restoration, etc.), and its analog-output signals were connected to the voltage/current amplifiers that feed the 20/34.5 kV aerial cable loop through the PT/CT devices. Additional PT/CT devices were also wired with the medium voltage aerial cable loop to measure the phase current/voltage signals and server as references. After each test, common format for transient data exchange (COMTRADE) files were collected from the SEL-735 power meter and used to compare the performance of the OPLS with the PT/CT. The behavior of analog signals, harmonic components, total harmonic distortion and crest factors were assessed and found favorable for the G&W sensor as compared to the reference PT/CT.
Disclosed herein are representative embodiments of methods, apparatus, and systems for charging and discharging an energy storage device connected to an electrical power distribution system. In one exemplary embodiment, a controller monitors electrical characteristics of an electrical power distribution system and provides an output to a bi-directional charger causing the charger to charge or discharge an energy storage device (e.g., a battery in a plug-in hybrid electric vehicle (PHEV)). The controller can help stabilize the electrical power distribution system by increasing the charging rate when there is excess power in the electrical power distribution system (e.g., when the frequency of an AC power grid exceeds an average value), or by discharging power from the energy storage device to stabilize the grid when there is a shortage of power in the electrical power distribution system (e.g., when the frequency of an AC power grid is below an average value).
This was a collaborative effort between Lawrence Livermore National Security, LLC ("LLNS"), as manager and operator of Lawrence Livermore National Laboratory ("LLNL") and ECCO International Inc. ("Participant"). The team designed and implemented a new approach for the Security-Constrained Alternating-Current Unit Commitment (SCACUC) problem. The SCACUC problem is a mathematical optimization problem that decides which generating units should be online and how much power should be produced (and consumed) at each point of the power grid. The decisions are made so as to minimize the total cost of supplying electricity while respecting technical constraints of the power grid, both under normal and emergency conditions. The team developed a solution for SCACUC as specified in the ARPA-E Grid Optimization Competition (GOC) Challenge 3, which put forth a forward-looking version of the problem, which many features not present in today’s electricity market specifications for SCACUC.
The modern power grid has seen a rise in the integration of non-linear loads, presenting a significant concern for operators. These loads introduce unwanted harmonics, leading to potential issues such as overheating and improper functioning of circuit breakers. In pursuing a more sustainable grid, the adoption of electric vehicles (EVs) and photovoltaic (PV) systems in residential networks has increased. Understanding and examining the effects of high-order harmonic frequencies beyond $1.5$ kHz is crucial to understanding their impact on the operation and planning of electrical distribution systems under varying nonlinear loading conditions. This study investigates a diverse set of critical power electronic loads within a household modeled using PSCAD/EMTdc, analyzing their unique harmonic spectra. This information is utilized to run the time-series harmonic analysis program in OpenDSS on a modified IEEE 34 bus test system model. The impact of high-order harmonics is quantified using metrics that evaluate total harmonic distortion (THD), transformer harmonic-driven eddy current loss component, and propagation of harmonics from the source to the substation transformer.
Resilience hazards for electric power systems are on the rise, exacerbated by both a rise in extreme weather events and manmade physical and cyber attacks. At the same time, grid modernization challenges plague the United States, covering everything from increased electrification and ambitious renewable energy targets to aging infrastructure and regulation that lags behind today’s challenges. This talk will cover an all-hazards risk based approach that addresses both rising resilience and grid modernization challenges. Examples of this approach taken for national laboratory research projects will be discussed, including a deep dive into a project that addressed black start, resynchronization, distributed control, and cybersecurity challenges for an operational microgrid up to sub-transmission voltages. As takeaways from this project are translated from demonstration scale to real-world exercises, key lessons are noted on the translation from research into practice and how this can inform risk-based research moving forward
Electricity production currently generates approximately 25% of greenhouse gas emissions in the USA. Thus, increasing the amount of renewable energy is a key step to carbon neutrality. However, integrating a large amount of fluctuating renewable generation is a significant challenge for power grid operating and planning. Grid reliability, i.e., an ability to meet operational constraints under power fluctuations, is probably the most important of them. In this letter, we propose computationally efficient and accurate methods to estimate the probability of line overflow, i.e., reliability constraints violation, under a known distribution of renewable energy generation. To this end, we investigate an importance sampling approach, a flexible extension of Monte-Carlo methods, which adaptively changes the sampling distribution to generate more samples near the reliability boundary. The approach allows to estimate overload probability in real-time based only on a few dozens of random samples, compared to thousands required by the plain Monte-Carlo. Our study focuses on high voltage direct current power transmission grids with linear reliability constraints on power injections and line currents. Herein, we propose a novel theoretically justified physics-informed adaptive importance sampling algorithm and compare its performance to state-of-the-art methods on multiple IEEE power grid test cases.
Bangladesh has experienced significant economic growth and poverty reduction over the past several decades. Recognizing the central role electricity plays in economic development, the Government of Bangladesh (GOB) has established policies to accelerate the growth of the electric power sector. The Bangladesh power grid is transforming into one marked by declining reliance on domestic natural gas reserves and oil-based rental power plants, increasing renewable energy contribution, and shifting demand patterns. The GOB is now reconsidering its prior plans to increase the share of coal capacity in the generation mix to meet demand, shifting its focus instead to electricity imports from neighboring countries, nuclear generation, liquified natural gas imports, and domestic renewable resources such as wind and solar. However, investments in the transmission and distribution system, as well as ancillary services, have not kept pace with investments in generation resources over the past decade. Thus, Bangladesh electricity consumers still experience outages and poor power quality despite adequate installed capacity. On the demand side, population growth and industrialization have fueled steady growth in electricity consumption as efforts to expand access to electricity enabled near-universal electricity access by mid-2020. The combined changes in the mix of generation resources and patterns of electricity demand present new challenges and opportunities in operating and maintaining a reliable power system. Energy storage has the potential to help meet these challenges and accelerate Bangladesh’s energy transition. Declining costs for some energy storage technologies make them increasingly cost-effective solutions to provide a wide range of grid services. Previous analyses of energy storage in the region have identified several potential applications for storage at the bulk system level, including energy arbitrage, ancillary services, and transmission network support. The potential for storage to meet these needs depends on many factors, including physical characteristics of the power system and the policy and regulatory environments in which these energy storage assets would operate. This report applies an Energy Storage Readiness Assessment the National Renewable Energy Laboratory developed for policy makers and regulators to identify priority areas of focus as they continue to develop the appropriate suite of policies, programs, and regulations to enable storage deployment. This assessment uses a simple evaluation scheme to identify the barriers and opportunities for utility-scale energy storage within Bangladesh’s policy and regulatory environment.
A demand bidding mechanism for engaging large industrial electricity users in the operation of the power grid is presented. Demand bidding is formulated as an optimization problem based on a modified version of the alternating current optimal power flow problem, and can be interpreted as a tâtonnement process between the grid operator and electricity users. Here, the work provides the first – to the authors’ knowledge – grid-scale case study of demand bidding, using a synthetic grid structure in the footprint of the grid of Texas. Results reveal that the demand bidding lowers overall power generation costs, but economic benefits plateau as the number of participants increases. Transmission line and transformer capacity constraints become the limiting factors, revealing that expanding and fortifying the transmission infrastructure is key to expanding demand-side participation. Demand bidding does not substantially alter the optimal operation of existing bidding entities when the number of bidders increases, thereby supporting existing bidders to stay in the system and encouraging new ones to join.