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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High-Penetration Microgrids Providing Grid Stability Using Frequency Watt Control

The U.S. grid is rapidly transitioning towards utilizing inverter-based renewable energy resources such as solar, wind, and batteries, reducing the carbon emission footprint. Inverter-based microgrid control architectures remain a critical focus to address power system stability issues in future high penetration markets lacking spinning generation assets. Idaho National Laboratory (INL) is researching an active layered inverter based frequency-Watt control scheme that provides distribution level stability in high-penetration markets where grid inertia is lacking. Hardware in the loop case study was implemented using INL’s Microgrid Testbed to combat scalable frequency deviations ranging from 60 Hz down to 50 Hz initialized by a hydropower model implementing step loads using a 540-kW grid emulator. Our research findings demonstrate the importance of distribution level, inverter-based active frequency-Watt controls utilizing a battery energy storage system (BESS) to provide adequate frequency support at the point of common coupling without major power infrastructure upgrades.

14 SOLAR ENERGY↗
DOE OSTI2025

Distributed Coordination of Demand-side Flexible Resources in Microgrid with All-Time Feasibility

The prevalence of distributed renewable generators motivates microgrid operators to exploit demand-side flexible resources (DFRs). Due to their dispersed nature, distributed DFR coordination has been a vibrant research area, while there are several issues awaiting to be addressed. On one hand, DFR power is internally coupled through power flow, while DFR usually cannot access grid information. On the other hand, in time-restricted scenarios, solution feasibility cannot be guaranteed by conventional dual-based algorithms. To fill these gaps, we propose a distributed DFR coordination framework with all-time feasibility. The proposed framework accounts for the distinct access of microgrid entities to grid information. A distributed and all-time feasible algorithm is proposed for optimal DFR coordination, which allows DFRs to make local decisions without violating constraints throughout iterations. The effectiveness of the proposed algorithm is demonstrated through case studies. The impact of peer-to-peer communication links on algorithm convergence is also investigated, which emphasizes the balance between communication investment and algorithm performance.

Li, Hongyi [Iowa State Univ., Ames, IA (United Sta↗
DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗
DOE OSTI2021

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking: Preprint

As distributed energy resources play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. The comparison of a distribution system run with fixed feed-in voltage is compared to the closely tied distribution-transmission co-simulation. It is determined that even without advanced voltage controls, the feed-in voltage response of the transmission system shows a lower level of voltage excursions. Therefore, control methods for voltage stability should be benchmarked on realistic transmission and distribution co-simulations for more accurate assessment of voltage profiles.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2020

Operationalizing Synchrophasors for Enhanced Grid Reliability and Asset Utilization

The report discusses the development of production-grade synchrophasor software applications. The objective is to improve system reliability and asset utilization for offline as well as real-time considerations, as per the Department of Energy (DOE) guidelines specified by Funding Opportunity Announcement (FOA) DE-FOA-0001492. On the one hand, we have developed grid management applications on how to transform synchrophasor-based monitoring into operator guidance, and commercial grade tools addressing industry needs such as NERC Reliability Standards (MOD 26, MOD 27 and MOD 33). On the other hand, with the wide industrial adoption in mind, the developed applications have been fully discussed with utility partners and installed in the utility partners site including 6 field tests. The Model Validation and Calibration software module has been integrated into GE’s PhasorAnalyticsTM. The first commercial contract has been signed even before the close date of this project. The Angle-based Grid Management (AGM), Fast Voltage Security Assessment (FastVSA), Enhanced Islanding Monitoring(EIM) and Enhanced Disturbance Management (EDM) have been integrated into GE’s Grid Stability Assessment line of applications in e-terra Suite of EMS product.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Optimal operational controls for power grid

Power grid operation is facing increased penetration of renewables and distributed energy resources at both transmission and distribution levels. This presents an increased level of randomness and uncertainty for its operational quality, where the challenges are mainly how controls and optimizations can be performed so that the operational quality of the power grid can be maintained. An interesting feature is also that we need to make a good use of uncertainties embedded in the swing equation from the renewable contributions rather than simply trying to minimize the impact of uncertainties. Furthermore, this requires effective solutions on system estimation, control, and optimization. Indeed, in past decades, work has been carried out on the development of advanced controls and optimization for such complicated dynamic systems. Examples are optimal operational control for both performance and stability enhancement considering random renewables penetration, frequency, and active power control for microgrids and parameter estimation for various parts of the power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Numerical Study of Hypoxia in Chesapeake Bay Using an Unstructured Grid Model: Validation and Sensitivity to Bathymetry Representation

A three-dimensional unstructured-grid hydrodynamic and water quality model (Semi-implicit Cross-scale Hydroscience Intergrated System Model-Integrated Compartment Model) is applied successfully for Chesapeake Bay. The model is validated with observations of salinity, chlorophyll-a, dissolved oxygen, nutrients, and phytoplankton productions from the year 1991 to 1995 for the mainstem and some major tributaries, based on multiple model skill scores. Model experiments are conducted to test the importance of having (1) an accurate representation of bathymetry to correctly predict hypoxia and other processes and (2) a high-resolution model grid for tributaries to correctly simulate water quality variables. Further, comparison with the model experiment results with bathymetry smoothing indicates that bathymetry smoothing, as commonly used for many systems, changes the stratification and lateral circulation pattern, resulting in more salt intrusion into shallow water regions, and an increase in the freshwater age. Consequently, a model with bathymetry smoothing can lead to an unrealistic prediction of the distribution of hypoxia and phytoplankton production. Local grid refinement shows significant improvement of model simulations on local stratification and water quality variables. Overall, the use of high-resolution unstructured grid model leads to a faithful representation of the complex geometry, and thus a seamless cross-scale capability for simulating water quality processes in the Bay including tributaries and tidal creeks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Robust Adaptive Control for Large-scale Inverter-based Resources with Partial and Complete Loss of Inverters

This article proposes an approach to address the current and the aggregated active power control challenge for large-scale inverter-based resources subjected to partially or completely loss of inverters and grid voltage variations. To address this problem, a distributed active power mechanism is proposed which generates desired inverters current. Then an adaptive mechanism distributes the voltage control input automatically between inverters in response to the partial or complete loss of inverters. An L2-gain-based controller is designed for each inverter to track the desired current and rejects the grid voltage disturbance. Here, simulation results show a significant robust tracking for collective active power and current.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Community Resilience Through Rapid Restoration Leveraging Distributed Energy Resources (DERs) and Low-Cost Sensors

Equitable and automated bottoms-up power restoration following an extreme event will be demonstrated at a site in Puerto Rico. To do so, the team will develop enhanced grid situational awareness techniques integrating behind-the-meter (BTM) distributed energy resources (DER) discovery, impedance sweeping based outage boundary detection, and feasible restoration path identification algorithms. Resilience metric will be developed and incorporated along with situational awareness information in a distributed Model Predictive Control (MPC)-based restoration optimization algorithm to control and mobilize grid assets. These algorithms will be validated through power hardware-in-the-loop experiments and ultimately, a site demonstration to show that outage recovery time and total recovered load could be improved by >20% over the baseline.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

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

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

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Demonstrating the Transient System Impact of Cyber-Physical Events Through Scalable Transmission and Distribution (T&D) Co-Simulation

Modern power systems become more vulnerable to cyber threats due to their growing interconnectivity, interdependence, and complexity. Widespread deployment of distributed energy resources (DERs) further expands the threat landscape to the grid edge, where fewer cybersecurity protections exist. In this article, a systematic cyber-physical events demonstration, enabled by an integrated transmission, distribution, and communication co-simulation framework, is performed. It analyzes cyber risks to power grid under DER-enabled automatic generation control from different angles. Unlike existing works, the simulation captures millisecond-to-minutes frequency and voltage transient dynamics at a cross-region system scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Supply Chain Management in Cyber Grid Guard Framework

Grid modernization has impeded innovative power grid applications and energy resources that are increasingly distributed. Blockchain/distributed ledger technology (DLT) has the potential to enhance the resilience of the electric infrastructure, particularly in a decentralized and distributed environment. The benefits of blockchain are to ensure asset information and lifecycle events are secure and traceable and identify potential malicious modification of data. Oak Ridge National Laboratory (ORNL) has developed a framework, Cyber Grid Guard (CGG), incorporating blockchain. The system implements a low-energy, fast, and robust enhancement to system trustworthiness within and across electric grid systems, including substations, control centers, and metering infrastructures. Currently, one of the major concerns is supply chain attacks. There have been several recent attacks that have significantly impacted critical infrastructures and organizations around the world. This document focuses on how CGG can be used to address the supply chain issue.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Integrating Resilience Planning in Distribution System Planning

Electric utilities, regulators, and stakeholders face increasing risks of severe storms, freezes, floods, and heat waves damaging grid infrastructure and causing power outages—and increasing risks of utility equipment igniting wildfires. At the same time, customer electricity rates have risen substantially in recent years, due in part to replacing aging infrastructure and improving resilience to natural hazards and physical threats. To address these challenges, utilities are beginning to move beyond traditional, siloed planning processes to balance resilience with other fundamental grid objectives such as affordability, reliability, safety, and serving new loads. This study presents a framework for states and utilities that want to advance integration of resilience and distribution planning processes to improve planning efficiency, better prioritize cost-effective grid expenditures, and balance planning objectives. The framework includes 7 key integration points between these planning processes: -Strategy process -Data -Threat assessments -Solution identification and prioritization -Optimization opportunities -Consideration of other grid needs -Metrics Lawrence Berkeley National Laboratory reviewed utility distribution system plans and interviewed subject matter experts to identify emerging practices for each of the 7 integration points. This report presents these practices, which can be used as a guide toward more holistic planning and cohesive investment strategies. It also includes 3 case studies to provide practical examples of how utilities apply such integrated planning processes: two pole hardening programs and one microgrid planning effort. The report concludes by identifying opportunities for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

An economic assessment of behind-the-meter photovoltaics paired with batteries on the Hawaiian Islands.

Due to natural variability and uncertainty, the ever-increasing penetration of solar generation in Hawaii presents challenges to power grid operators to maintain reliable system operation. Demand response (DR) has the potential to be a cost-effective tool for Hawaii to reach its aggressive renewable energy goals while maintaining the reliability of power grids. The Hawaii Public Utilities Commission has approved the Hawaiian Electric Company's revised portfolio of DR programs. The companies have released a grid services purchase agreement and subscribed an initial tranche of load into their DR programs. This paper presents innovative analytical methods and comprehensive economic assessment for distributed photovoltaics (PV) paired with battery energy storage systems (BESSs) for two new DR programs, including fast frequency response and capacity grid service. Optimal dispatch and sizing methods are proposed for the paired system considering different tariff schedules and PV compensation programs across five islands. It was found that while the best resource configuration and potential economic benefits vary with tariff structure, a BESS paired with PV can be optimally dispatched to generate multiple value streams simultaneously. Compensation from DR programs is an important value stream to help increase the cost-effectiveness of the integrated system.

Battery energy storage system↗
DOE OSTI2023

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗