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At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Multi-fluid, earth battery energy systems and methods

The present disclosure relates to a system for storing and time shifting at least one of excess electrical power from an electrical power grid, excess electrical power from the power plant itself, or heat from a heat generating source, in the form of pressure and heat, for future use in assisting with a production of electricity. An oxy-combustion furnace is powered by a combustible fuel source, plus excess electricity, during a charge operation to heat a reservoir system containing a quantity of a thermal storage medium. During a discharge operation, a discharge subsystem has a heat exchanger which receives heated CO 2 from the reservoir system and uses this to heat a quantity of high-pressure, supercritical CO 2 (sCO 2 ) to form very-high-temperature, high-pressure sCO 2 at a first output thereof. The very-high-temperature, high-pressure sCO 2 is used to drive a Brayton-cycle turbine, which generates electricity at a first output thereof for transmission to a power grid. The Brayton-cycle turbine also outputs a quantity of sCO 2 which is reduced in temperature and pressure to a heat recuperator subsystem. The heat recuperator subsystem circulates the sCO 2 and re-heats and re-pressurizes the sCO 2 before feeding it back to the heat exchanger to be even further reheated, and then output to the Brayton-cycle turbine as a new quantity of very-high-temperature, high-pressure sCO 2 , to assist in powering the Brayton-cycle turbine.

Buschek, Thomas A.↗

DOE OSTI2019

HEMP Transformer Defense Through Power Electronics

High altitude electromagnetic pulse (HEMP) generated by exoatmospheric nuclear burst has the ability to affect the electric power grid. The main power grid components, cables and transformers, act as large antennas that have current induced in them from the HEMP. These currents are called geomagneticallyinduced currents (GIC), and they can occur during geomagnetic disturbances from HEMP or solar flares. HEMPs produce pulses with high electric field strengths that breakdown the dielectric of most electronics and, it is broken into three stages: E1 pulse with a microsecond width, E2 the falling trail of the pulse, and E3 a constant DC component. Oak Ridge National Laboratory has proven that transformers fitted with lightning arrestors do not receive damage from E1 and E2 pulses. However, the DC component of the E3 causes the transformer’s core to saturate and induce rapid heating that damages the transformer. SRNL is developing a power electronic system that is connected to the neutral of the high voltage side of large power transformers (LPT). This system will inject the inverse of the DC effect from the HEMP into the primary side of the transformer canceling out the E3 waveform and protecting the transformer from half-cycle-saturation. This year SRNL successfully simulated removing the DC injected and accurately simulated saturation on the transformer.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado: Preprint

The past decade has witnessed the rapid adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from the government and industry. Rapid EV adoption brings significant charging demand to the power grid, causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of EV home charging on the grid and identify risk factors, this study presents a data-driven residential charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

A Review on Artificial Intelligence for Grid Stability Assessment

Artificial intelligence provides a convenient route for power grid stability assessment. Compared with simulation-based approaches, artificial intelligence can potentially save time on model development and numerical computation in stability assessment. This paper first reviewed existing literature on using artificial intelligence for power grid stability assessment. Then a machine-leaning-based tool is presented and developed to assess power grid transient stability, frequency stability, and small signals stability. Test results verified the accuracy and effectiveness of the AI tool for power grid stability assessment.

You, Shutang↗

DOE OSTI2017

R&D 100 Winner 2017: Control System for Active Damping of Inter-Area Oscillations

Researchers at Sandia National Labs have developed a control system to improve damping of inter-area oscillations to improve power grid reliability. Current grids operate will below transmission capacity to avoid widespread outages due to inter-area oscillations. This control system is the first successful grid demonstration of feedback control making it a game changer for the smart grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Hydropower Flexibility and Environmental Tradeoffs Analysis

The importance of hydropower increases as the power grid evolves with the higher variable renewable contribution. As conventional thermal power plants are retired, the importance of hydropower contribution increases to balance the variability of solar and wind generation. However, reservoir water resources are constrained by multiple constraints, and variability of water inflow to the reservoirs creates limitations to dam water releases for power grid needs. Coordinating multiple tools, including water resources, ecological, and technical and economic power grid modeling, informs dam water releases. The case study, the Columbia River Basin multipurpose reservoir project, is operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. We integrated a production cost model, a water resource model, and decades of tribal knowledge to analyze the fish-friendly way of operating Columbia hydropower scheduling and grid impacts. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

Columbia River↗

DOE OSTI2013

3-Port Single-Stage PV & Battery Converter Improves Efficiency and Cost in Combined PV/Battery Systems

Due to impressive cost reductions in recent years, photovoltaic (PV) generation is now able to produce electricity at highly competitive prices, but PV’s inherent intermittency reduces the potential value of this energy. The integration of battery storage with PV will be transformational by increasing the value of solar. Utility scale systems will benefit by firming intermittency including PV ramp smoothing, grid support and load shifting, allowing PV to compete directly with conventional generation. For distributed grid-tied PV adding storage will reduce peak demand utility charges, as well as providing backup power during power grid failures. The largest long term impact of combined PV and battery systems may be for delivering reliable off-grid power to the billions of individuals globally without access to conventional power grids, or for billions more that suffer from daily power outages. PV module costs no longer dominate installed PV system costs. Balance-of-System (BOS) costs including the PV inverter and installation now contribute the majority of installed system costs. Battery costs are also dropping faster than installation and battery power converter systems. In each of these separate systems power converters have become a bottleneck for efficiency, cost and reliability. These bottlenecks are compounded in hybrid power conversion systems that combine separate PV and battery converters. Hybrid power conversion systems have required multiple power converters hardware units and multiple power conversion steps adding to efficiency losses, product and installation costs, and reliability issues. Ideal Power Converters has developed and patented a completely new theory of operation for electronic power converters using its indirect EnergyPacket Switching™ topology. It has established successful power converter products for both PV and battery systems, and its 3-Port Hybrid Converter is the first product to exploit the topology’s capability for the industry’s first single-stage multi-port hybrid power converter. This unique low cost approach eliminates the hybrid power conversion bottlenecks when integrating batteries into PV systems. As result this product will significantly accelerate market adoption of these systems.

14 SOLAR ENERGY↗

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 OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids: Preprint

Increase in the proliferation of DERs requires real-time situational awareness for efficient grid operations. State estimation plays an important role for real time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hierarchical spectral clustering-based network partition algorithm followed by a decentralized compressive sensing (DCS) based state estimation. The applicability of the proposed network partitioning algorithm is tested on IEEE-123 bus, IEEE-8500 node, and a 6204-node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6204-node distribution network after dividing the network into 18 optimal partitions. Simulation results show that DCS-based state estimation recovers the system states with high accuracy and low complexity.

ADMM↗

DOE OSTI2017

Hiding Critical Targets in Smart Grid Networks

With the integration of advanced communication technologies, the power grid is expected to greatly enhance efficiency and reliability of future power systems. However, since most electrical devices in power grid substations are connected via communication networks, cyber security of these communication networks becomes a critical issue. Real-World incidents such as Stuxnet have shown the feasibility of compromising a device in the power grid network to further launch more sophisticated attacks. To deal with security attacks of this spirit, this paper aims to hide critical targets from compromised internal nodes and hence protect them from further attacks launched by those compromised nodes. In particular, we consider substation networks and propose to add carefully-controlled dummy traffic to a substation network to make critical target nodes indistinguishable from other nodes in network traffic patterns. This paper describes the design and evaluation of such a scheme. Evaluations show that the scheme can effectively protect critical nodes with acceptable communication cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗

DOE OSTI2019

On the Need for Communication for Voltage Regulation of Power Distribution Grids

We consider the problem of regulating the voltage profile of a power distribution grid by controlling the reactive power injection of distributed microgenerators. We define a very general class of purely local feedback controllers in which reactive power injection is adjusted based on the local voltage measurements. This class includes most of the solutions proposed in the literature and in the latest grid codes. We show that these strategies do not guarantee the desired regulation, as each of them can have an equilibrium that is not feasible with respect to the desired voltage and power constraints. We then propose a networked feedback law to show that, by adding short-range communication between microgenerators, it is possible to design control strategies that provably converge to the feasible set. This fundamental performance gap between local and networked strategies is finally illustrated via simulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity

The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However, the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.

big data↗

DOE OSTI2023

AI-Based Faster-Than-Real-Time Stability Assessment of Large Power Systems with Applications on WECC System

Achieving clean energy goals will require significant advances in regard to addressing the computational needs for next-generation renewable-dominated power grids. One critical obstacle that lies in the way of transitioning today’s power grid to a renewable-dominated power grid is the lack of a faster-than-real-time stability assessment technology for operating a fast-changing power grid. This paper proposes an artificial intelligence (AI) -based method that predicts the system’s stability margin information (e.g., the frequency nadir in the frequency stability assessment and the critical clearing time (CCT) value in the transient stability assessment) directly from the system operating conditions without performing the conventional time-consuming time-domain simulations over detailed dynamic models. Since the AI method shifts the majority of the computational burden to offline training, the online evaluation is extremely fast. This paper has tested the AI-based stability assessment method using multiple dispatch cases that are converted and tuned from actual dispatch cases of the Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. The results show that the AI-based method could accurately predict the stability margin of such a large power system in less than 0.2 milliseconds using the offline-trained AI agent. Therefore, the proposed method has great potential to achieve faster-than-real-time stability assessment for practical large power systems while preserving sufficient accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

2024.03.13 Bushing Subcommittee presentation on Transformer Bushing Seismic Resilience: Design, Hazard, & Prevention Analysis [Slides]

Presents results from power grid simulations on synthetic grids that estimate the impact from power transformer failures due to earthquakes. In the best-case scenario, there is an 82.9% likelihood of load loss greater or equal to 51 MW. Methodologies are described as well as path forward to improving transformer resilience and, consequently, the resilience of the bulk power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Modeling Primary Frequency Response for Grid Studies

For the electric power grid, maintaining nearly constant frequency is important measure of system reliability and stability. Primary frequency response (PFR) is one of the important reserve services used by grid operators to uphold steady frequency. Modeling PFR is historically rare in grid integration and planning studies, but could become more importantly with greater deployment of non-synchronous generators. In this work, we illustrate how a PFR constraint can be implemented into production cost models, which are a key component of grid planning studies. We also discuss the complexities and nuances associated with PFR modeling and provide results of a case study implementing PFR in a section of the western U.S. power grid.

14 SOLAR ENERGY↗

DOE OSTI2018

A generative graph model for electrical infrastructure networks

We propose a generative graph model for electrical infrastructure networks that accounts for heterogeneity in both node and edge type. To inform the design of this model, we analyze the properties of power grid graphs derived from the U.S. Eastern Interconnection, Texas Interconnection, and Poland transmission system power grids. Across these datasets, we find subgraphs induced by nodes of the same voltage level exhibit shared structural properties atypical to small-world networks, including low local clustering, large diameter and large average distance. On the other hand, we find subgraphs induced by transformer edges linking nodes of different voltage types contain a more limited structure, consisting mainly of small, disjoint star graphs. The goal of our proposed model is to match both these inter and intra-network properties by proceeding in two phases: we first generate subgraphs for each voltage level and then generate transformer edges that connect these subgraphs. The first phase of the model adapts the Chung-Lu random graph model, taking desired vertex degrees and desired diameter as inputs, while the second phase of the model is based on a simpler random star graph generation process. We test the performance of our model by comparing its output across many runs to the aforementioned real data. In nearly all categories tested, we find our model is more accurate in reproducing the unusual mixture of properties apparent in the data than the Chung-Lu model. We also include graph visualization comparisons, as well as a brief analysis of edge-deletion resiliency. Ultimately, our model may be used to generate synthetic graph data, test hypotheses and algorithms at different scales, and serve as a baseline model on top of which further electrical network properties, device models, and interdependencies to other networks, may be appended.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Integrating Renewable Generation into Grid Operations: Four International Experiences

International experiences with power sector restructuring and the resultant impacts on bulk power grid operations and planning may provide insight into policy questions for the evolving United States power grid as resource mixes are changing in response to fuel prices, an aging generation fleet and to meet climate goals. Australia, Germany, Japan and the UK were selected to represent a range in the level and attributes of electricity industry liberalization in order to draw comparisons across a variety of regions in the United States such as California, ERCOT, the Southwest Power Pool and the Southeast Reliability Region. The study draws conclusions through a literature review of the four case study countries with regards to the changing resource mix and the electricity industry sector structure and their impact on grid operations and planning. This paper derives lessons learned and synthesizes implications for the United States based on answers to the above questions and the challenges faced by the four selected countries. Each country was examined to determine the challenges to their bulk power sector based on their changing resource mix, market structure, policies driving the changing resource mix, and policies driving restructuring. Each countries’ approach to solving those changes was examined, as well as how each country’s market structure either exacerbated or mitigated the approaches to solving the challenges to their bulk power grid operations and planning. All countries’ policies encourage renewable energy generation. One significant finding included the low- to zero-marginal cost of intermittent renewables and its potential negative impact on long-term resource adequacy. No dominant solution has emerged although a capacity market was introduced in the UK and is being contemplated in Japan. Germany has proposed the Energy Market 2.0 to encourage flexible generation investment. The grid operator in Australia proposed several approaches to maintaining synchronous generation. Interconnections to other regions provides added opportunities for balancing that would not be available otherwise, and at this point, has allowed for integration of renewables.

24 POWER TRANSMISSION AND DISTRIBUTION↗