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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions

Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.

Jiang, Sufan [The University of North Carolina at ↗
DOE OSTI2024

Distributed Automatic Generation Control Considering DPV Using T&D Dynamic Co-Simulation

The increasing adoption of distributed energy resources (DERs) over the last decade warrants a reconsideration of control of generation resources. This paper proposes a distributed Automatic Generation Control (AGC) using transmission-and-distribution (T&D) dynamic co-simulation framework for the efficient DPV frequency regulation services. The co-simulation framework allows AGC units to exchange the information for distributed AGC, based on their adopted communication network topology. As a result, a cost-effective automatic generation control is achieved with DPV and conventional generators. The proposed distributed AGC is based on the gossip algorithm in which the neighboring AGC units share the relevant local information with each other and updates their share of AGC regulation signal. Distributed photovoltaics (DPV) unit contribute to AGC response based on their headroom capacity via DER aggregators. The algorithm is tested on IEEE-14 bus transmission system under conditions of generation failure and random load variation to observe effective frequency regulations service offered by DPVs and other AGC units. The study shows that DPV can effectively participate in AGC with the proposed distributed control framework.

automatic generation control↗
DOE OSTI2019

Grid-Friendly Renewable Energy: Solar and Wind Participation in Automatic Generation Control Systems

This paper focuses on emerging technological and regulatory considerations of using solar and wind generators to provide essential reliability services through participation in area-wide automatic generation control (AGC) systems. AGC systems enable a grid operator to centrally and automatically manage the output of interconnected generators, storage devices, and controllable loads to maintain reliable and safe system operations. The paper highlights recent experiences of solar and wind on AGC, as well as recent developments that may enable VRE to participate in AGC in the near future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Controlling Wind Turbines for Secondary Frequency Regulation: An Analysis of AGC Capabilities Under New Performance Based Compensation Policy

As wind energy becomes a larger portion of the world's energy portfolio there has been an increased interest for wind turbines to control their active power output to provide ancillary services which support grid reliability. One of these ancillary services is the provision of frequency regulation, also referred to as secondary frequency control or automatic generation control (AGC), which is often procured through markets which recently adopted performance-based compensation. A wind turbine with a control system developed to provide active power ancillary services can be used to provide frequency regulation services. Simulations have been performed to determine the AGC tracking performance at various power schedule set-points, participation levels, and wind conditions. The performance metrics used in this study are based on those used by several system operators in the US. Another metric that is analyzed is the damage equivalent loads (DELs) on turbine structural components, though the impacts on the turbine electrical components are not considered. The results of these single-turbine simulations show that high performance scores can be achieved when there are insufficient wind resources available. The capability of a wind turbine to rapidly and accurately follow power commands allows for high performance even when tracking rapidly changing AGC signals. As the turbine de-rates to meet decreased power schedule set-points there is a reduction in the DELs, and the participation in frequency regulation has a negligible impact on these loads.

17 WIND ENERGY↗
DOE OSTI2015

Controlling Wind Turbines for Secondary Frequency Regulation: An Analysis of AGC Capabilities Under New Performance Based Compensation Policy: Preprint

As wind energy becomes a larger portion of the world's energy portfolio there has been an increased interest for wind turbines to control their active power output to provide ancillary services which support grid reliability. One of these ancillary services is the provision of frequency regulation, also referred to as secondary frequency control or automatic generation control (AGC), which is often procured through markets which recently adopted performance-based compensation. A wind turbine with a control system developed to provide active power ancillary services can be used to provide frequency regulation services. Simulations have been performed to determine the AGC tracking performance at various power schedule set-points, participation levels, and wind conditions. The performance metrics used in this study are based on those used by several system operators in the US. Another metric that is analyzed is the damage equivalent loads (DELs) on turbine structural components, though the impacts on the turbine electrical components are not considered. The results of these single-turbine simulations show that high performance scores can be achieved when there is sufficient wind resource available. The capability of a wind turbine to rapidly and accurately follow power commands allows for high performance even when tracking rapidly changing AGC signals. As the turbine de-rates to meet decreased power schedule set-points there is a reduction in the DELs, and the participation in frequency regulation has a negligible impact on these loads.

17 WIND ENERGY↗
DOE OSTI2016

Testbed-based Performance Evaluation of Attack Resilient Control for AGC

The modern electric power grid is a complex cyber-physical system whose reliable operation is enabled by a wide-area monitoring and control infrastructure. This infrastructure, supported by an extensive communication backbone, enables several control applications functioning at multiple time scales to ensure the grid is maintained within stable operating limits. Recent events have shown that vulnerabilities in this infrastructure may be exploited to manipulate the data being exchanged. Such a scenario could cause the associated control application to mis-operate, potentially causing system-wide instabilities. There is a growing emphasis on looking beyond traditional cybersecurity solutions to mitigate such threats. In this paper we perform a testbed-based validation of one such solution - Attack Resilient Control (ARC) - on Iowa State University's \textit{PowerCyber} testbed. ARC is a cyber-physical security solution that combines domain-specific anomaly detection and model-based mitigation to detect stealthy attacks on Automatic Generation Control (AGC). In this paper, we first describe the implementation architecture of the experiment on the testbed. Next, we demonstrate the capability of stealthy attack templates to cause forced under-frequency load shedding in a 3-area test system. We then validate the performance of ARC by measuring its ability to detect and mitigate these attacks. Our results reveal that ARC is efficient in detecting stealthy attacks and enables AGC to maintain system operating frequency close to its nominal value during an attack. Our studies also highlight the importance of testbed-based experimentation for evaluating the performance of cyber-physical security and control applications.

attack resilience↗
DOE OSTI2021

Examining the Economic Optimality of Automatic Generation Control

The automatic generation control (AGC) system is temporally situated between economic dispatch and synchronous generator dynamics, and its primary role is to regulate frequency within and tie-line flows between control areas. Given appropriate choice of participation factors (feed-forward controller gains that govern the disaggregation of the area-level power requirement to individual generators), the AGC can be engineered to nudge system dynamics toward a steady-state operating point corresponding to economic optimality. This paper establishes necessary and sufficient conditions under which a widely accepted choice of participation factors guarantees the alignment of steady-state synchronous generator outputs with a global minimum of a prototypical economic dispatch problem. In so doing, it resolves several ambiguities and formalizes technical assumptions governing the role of the standard AGC architecture in the context of economic dispatch and steady-state operation. Numerical case studies tailored to a modified version of the New England 39-bus 10-machine test system validate the theoretical results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Improving Deployment Availability of Energy Storage With Data-Driven AGC Signal Models

Energy Storage (ES) provides great flexibility and large benefits to power system operations and control. When providing ancillary services (e.g., regulation, reserve, etc.), the real-time (RT) deployment of ES is uncertain, and it is important to manage state of charge accordingly. Aiming to improve the ES performance for providing energy and regulation service in the electricity market, we propose two data-driven Automatic Generation Control (AGC) signal models. The first one is a historical-data-driven AGC signal model, which is based on the analysis of the historical AGC signals, and is designed for ES participation in the day-ahead (DA) market. The second one is a prediction-data-driven AGC signal model, which is based on the prediction of the AGC signals, and is designed for ES participation in the RT market. We also develop a deployment availability check model and solution algorithm. The proposed framework is applied to an ES bidding problem in the DA and RT markets. The results indicate that deployment availability and operational performance of the ES are improved with the proposed data-driven AGC models compared to traditional benchmarks.

AGC signal model↗
DOE OSTI2013

NV Energy Large-Scale Photovoltaic Integration Study: Intra-Hour Dispatch and AGC Simulation

The uncertainty and variability with photovoltaic (PV) generation make it very challenging to balance power system generation and load, especially under high penetration cases. Higher reserve requirements and more cycling of conventional generators are generally anticipated for large-scale PV integration. However, whether the existing generation fleet is flexible enough to handle the variations and how well the system can maintain its control performance are difficult to predict. The goal of this project is to develop a software program that can perform intra-hour dispatch and automatic generation control (AGC) simulation, by which the balancing operations of a system can be simulated to answer the questions posed above. The simulator, named Electric System Intra-Hour Operation Simulator (ESIOS), uses the NV Energy southern system as a study case, and models the system’s generator configurations, AGC functions, and operator actions to balance system generation and load. Actual dispatch of AGC generators and control performance under various PV penetration levels can be predicted by running ESIOS. With data about the load, generation, and generator characteristics, ESIOS can perform similar simulations and assess variable generation integration impacts for other systems as well. This report describes the design of the simulator and presents the study results showing the PV impacts on NV Energy real-time operations.

Energy↗
DOE OSTI2021

Man‐in‐the‐middle attacks and defence in a power system cyber‐physical testbed

Abstract Man‐in‐The‐Middle (MiTM) attacks present numerous threats to a smart grid. In a MiTM attack, an intruder embeds itself within a conversation between two devices to either eavesdrop or impersonate one of the devices, making it appear to be a normal exchange of information. Thus, the intruder can perform false data injection (FDI) and false command injection (FCI) attacks that can compromise power system operations, such as state estimation, economic dispatch, and automatic generation control (AGC). Very few researchers have focused on MiTM methods that are difficult to detect within a smart grid. To address this, we are designing and implementing multi‐stage MiTM intrusions in an emulation‐based cyber‐physical power system testbed against a large‐scale synthetic grid model to demonstrate how such attacks can cause physical contingencies such as misguided operation and false measurements. MiTM intrusions create FCI, FDI, and replay attacks in this synthetic power grid. This work enables stakeholders to defend against these stealthy attacks, and we present detection mechanisms that are developed using multiple alerts from intrusion detection systems and network monitoring tools. Our contribution will enable other smart grid security researchers and industry to develop further detection mechanisms for inconspicuous MiTM attacks.

Wlazlo, Patrick↗
DOE OSTI2016

Active Power Control of Wind Turbines for Ancillary Services: A Comparison of Pitch and Torque Control Methodologies

As wind energy generation becomes more prevalent in some regions, there is increased demand for wind power plants to provide ancillary services, which are essential for grid reliability. This paper compares two different wind turbine control methodologies to provide active power control (APC) ancillary services, which include derating or curtailing power generation, providing automatic generation control (AGC), and providing primary frequency control (PFC). The torque APC controller provides all power control through the power electronics whereas the pitch APC controller uses the blade pitch actuators as the primary means of power control. These controllers are simulated under various wind conditions with different derating set points and AGC participation levels. The metrics used to compare their performance are the damage equivalent loads (DELs) induced on the structural components and AGC performance metrics, which are used to determine the payments for AGC services by system operators in the United States. The simulation results show that derating the turbine reduces structural loads for both control methods, with the APC pitch control providing larger reductions in DELs, lower AGC performance scores, and higher root-mean-square pitch rates. Providing AGC increases the structural loads when compared to only derating the turbine, but even the AGC DELs are generally lower than those of the baseline control system. The torque APC control methodology also allows for more sustained PFC responses under certain derating conditions.

17 WIND ENERGY↗
DOE OSTI2017

Dissipativity-based design of local and wide-area DER controls for large-scale power systems with high penetration of renewables

In this paper, an integrated and modular control design is developed for distributed energy resources (DERs) to stabilize power systems and minimize effects of load variations and intermittent generation. Traditionally, the droop control of each generator (or virtual power plant) works as a local feedback loop to track frequency during load disturbance, whereas automatic generation control (AGC) calculates control signals and sends them to each generator with the goal of matching the total generation and load in the overall system. The droop control and the AGC work separately, therefore the two controls often conflict each other. The proposed design enables us to modularly synthesize an integrated control for each of the DERs by using both local and wide-area measurements so that the controls work together in enhancing stability and performance of the power system. The design methodology admits the full nonlinear power flow equations, and it results in a data-driven control that in real-time takes into account the nonlinear power flow interactions (in terms of current angle measurements) and adaptively adjusts parameters of the controls that operate the DERs. The design framework uses the concept of passivity-short systems to analyze individual DERs and quantify their dynamic responses in such a way that the resulting system-wide implementation becomes plug-and-play. Simulations are done to demonstrate the effectiveness of the proposed methodology and design.

Harvey, Roland↗
DOE OSTI2017

Deep Learning-Based Data Forgery Detection in Automatic Generation Control

Automatic Generation Control (AGC) is a key control system in the power grid. It is used to calculate the Area Control Error (ACE) based on frequency and tie-line power flow between balancing areas, and then adjust power generation to maintain the power system frequency in an acceptable range. However, attackers might inject malicious frequency or tie-line power flow measurements to mislead AGC to do false generation correction which will harm the power grid operation. Such attacks are hard to be detected since they do not violate physical power system models. In this work, we propose algorithms based on Neural Network and Fourier Transform to detect data forgery attacks in AGC. Different from the few previous work that rely on accurate load prediction to detect data forgery, our solution only uses the ACE data already available in existing AGC systems. In particular, our solution learns the normal patterns of ACE time series and detects abnormal patterns caused by artificial attacks. Evaluations on the real ACE dataset show that our methods have high detection accuracy.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Anomaly Detection for Power System Generation Control based on Hierarchical DBSCAN

The generation level of a generator in power grid is under control of multiple control loops such as governor action, Automatic Generation Control (AGC), and manual control. These control loops are vulnerable to cyber attacks and could become potential targets for the malicious adversary. In this paper, we investigated the detection of abnormal generation controls induced by cyber attacks. One data-driven anomaly detection methodology is presented based on the behavior conformity of generation units located in the same balancing authority. A semi-supervised clustering algorithm with Hierarchical Density based Spatial Clustering of Application with Noise (HDBSCAN) is proposed for the detection model training. In our previous work, we obtained a synthetic dataset that covers scenarios including normal operation, generation control under ramp attack, switching attack, AGC integrity attacks, etc. and it is used to evaluate the proposed clustering algorithm. Experimental results show that the proposed algorithm provides better detection accuracy than K-means clustering and can distinguish not only between normal and abnormal generation controls but also among various anomaly scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Distributed Hierarchical Control Architecture for Transient Dynamics Improvement in Power Systems

In this paper, a novel distributed hierarchical coordinated control architecture is proposed for large scale power systems. The newly considered architecture facilitates frequency restoration and power balancing functions to be decoupled and implemented at different levels. At the local level, decentralized robust generator controllers are designed to quickly restore frequency after large faults and disturbances in the system. The controllers presented herein are shown to improve transient stability performance, as compared to conventional governor and excitation control. At the area level, Automatic Generation Control (AGC) is modified and coordinates with the decentralized robust controllers to reach the interchange schedule in the tie lines. The interaction of local and zonal controllers is validated through detailed simulations.

Marinovici, Laurentiu D.↗
DOE OSTI2017

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

This paper describes a novel set of stochastic unit commitment and economic dispatch models that consider stochastic loads and variable generation at multiple operational timescales. The stochastic model includes four distinct stages: stochastic day-ahead security-constrained unit commitment (SCUC), stochastic real-time SCUC, stochastic real-time security-constrained economic dispatch (SCED), and deterministic automatic generation control (AGC). These sub-models are integrated together such that they are continually updated with decisions passed from one to another. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies with deterministic approaches are conducted in low wind and high wind penetration scenarios to highlight the advantages of the proposed methodology, one with perfect forecasts and the other with current state-of-the-art but imperfect deterministic forecasts. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and reliability metrics to provide a broader view of its impact.

17 WIND ENERGY↗
DOE OSTI2017

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

Real-time charging strategies, in the context of vehicle to grid (V2G) technology, are needed to enable the use of electric vehicle (EV) fleets batteries to provide ancillary services (AS). Here, we develop tools to manage charging and discharging in a fleet to track an Automatic Generation Control (AGC) signal when aggregated. We also propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing Model Predictive Control (MPC). Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations

Solar power forecasting improvements are mainly evaluated by statistical and economic metrics, and the practical reliability benefits of these forecasting enhancements have not yet been well quantified. This paper aims to quantify reliability benefits from solar power forecasting improvements. To systematically analyze the relationship between solar power forecasting improvements and reliability performance in power system operations, an expected synthetic reliability (ESR) metric is proposed to integrate state-of-the-art independent reliability metrics. The absolute value and standard deviation of area control errors (ACE), and the North American Electric Reliability Corporation Control Performance Standard 2 (CPS2) score are calculated through the multi-timescale scheduling simulation, including the day-ahead unit commitment (DU), real-time unit commitment (RU), real-time economic dispatch (RE), automatic generation control (AGC) sub-models. The absolute area control error in energy (AACEE), CPS2 violations, CPS2 score, and standard deviation of the raw ACE are all calculated and combined as the ESR metric. Numerical simulations show that the reliability benefits of multi-timescale power system operations are significantly increased due to the improved solar power forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗