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DOE OSTI2015

An Assessment of the Impact of Stochastic Day-Ahead SCUC on Economic and Reliability Metrics at Multiple Timescales

This paper incorporates the stochastic day-ahead security-constrained unit commitment (DASCUC) within a multi-timescale, multi-scheduling application with commitment, dispatch, and automatic generation control. The stochastic DASCUC is solved using a progressive hedging algorithm with constrained ordinal optimization to accelerate the individual scenario solution. Sensitivity studies are performed in the RTS-96 system, and the results show how this new scheduling application would impact costs and reliability with a closer representation of timescales of system operations in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Enhancing the Flexibility of Generation of Run-Of-the-River Hydro Power Plants

Run-of-the-River Hydro Power Plants (ROR HPPs) output can be characterized as fixed and predictable output with low cost of both installation and operation. ROR HPP generation is proportional to the water flow and cannot be adjusted to provide inertia to the grid, which is critical to power systems stability. Hence ROR HPP can only participate in low profit energy markets and not in the high profit ancillary service market. With the advances in energy storage, they can help build a synthetic energy reservoir. The combined operation of ROR HPPs and energy storage are capable of both ramping and variable power output, allowing participation in the ancillary service markets. However, energy storage technologies such as supercapacitors and flywheels, which are power dense can quickly charge/discharge within a short duration. Energy dense storage technologies such as batteries can provide long duration energy injection while the maximum ramping rate is much lower than power dense energy storage. In order to provide long duration fast ramping capability, Hybrid Energy Storage Systems (HESSs) including both power and energy dense energy storage are proposed to be integrated to enable the flexible operation of ROR HPP. Power dense energy storage with quick burst of energy can assist in regulation, whereas energy dense storage can provide energy balance over larger time. In this paper, the properties of different types of energy storage including the ramping rate, affordable energy storage capacity, thermal management, etc. are analyzed. The size of each type of energy storage is determined to ensure optimal combination of HESS and ROR HPP. A generic Front End Controller (FEC) is developed and customized for ROR HPP to provide real time control and cohesive operation of multiple units. FEC serves as the interface between utility management systems and ROR HPPs to ensure their integration with the centralized controls. Using the Automatic Generation Control (AGC) signal received from grid operator, FEC optimizes the ROR HPP turbine and HESS so that the aggregated generation can satisfy the market needs. Based on the study, system operator can acquire extra inertia support for system stability, and the ROR HPP operators can enhance their revenues by participating in wider market avenues.

13 HYDRO ENERGY↗

DOE OSTI2013

Variable Renewable Generation can Provide Balancing Control to the Electric Power System (Fact Sheet)

As wind and solar plants become more common in the electric power system, they may be called on to provide grid support services to help maintain system reliability. For example, through the use of inertial response, primary frequency response, and automatic generation control (also called secondary frequency response), wind power can provide assistance in balancing the generation and load on the system. These active power (i.e., real power) control services have the potential to assist the electric power system in times of disturbances and during normal conditions while also potentially providing economic value to consumers and variable renewable generation owners. This one-page, two-sided fact sheet discusses the grid-friendly support and benefits renewables can provide to the electric power system.

14 SOLAR ENERGY↗

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 OSTI2017

Demonstration of Essential Reliability Services by a 300-MW Solar Photovoltaic Power Plant

The California Independent System Operator (CAISO), First Solar, and the National Renewable Energy Laboratory (NREL) conducted a demonstration project on a large utility-scale photovoltaic (PV) power plant in California to test its ability to provide essential ancillary services to the electric grid. With increasing shares of solar- and wind-generated energy on the electric grid, traditional generation resources equipped with automatic governor control (AGC) and automatic voltage regulation controls -- specifically, fossil thermal -- are being displaced. The deployment of utility-scale, grid-friendly PV power plants that incorporate advanced capabilities to support grid stability and reliability is essential for the large-scale integration of PV generation into the electric power grid, among other technical requirements. A typical PV power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. In this way, PV power plants can be used to mitigate the impact of variability on the grid, a role typically reserved for conventional generators. In August 2016, testing was completed on First Solar's 300-MW PV power plant, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to use grid-friendly controls to provide essential reliability services. These data showed how the development of advanced power controls can enable PV to become a provider of a wide range of grid services, including spinning reserves, load following, voltage support, ramping, frequency response, variability smoothing, and frequency regulation to power quality. Specifically, the tests conducted included various forms of active power control such as AGC and frequency regulation; droop response; and reactive power, voltage, and power factor controls. This project demonstrated that advanced power electronics and solar generation can be controlled to contribute to system-wide reliability. It was shown that the First Solar plant can provide essential reliability services related to different forms of active and reactive power controls, including plant participation in AGC, primary frequency control, ramp rate control, and voltage regulation. For AGC participation in particular, by comparing the PV plant testing results to the typical performance of individual conventional technologies, we showed that regulation accuracy by the PV plant is 24-30 points better than fast gas turbine technologies. The plant's ability to provide volt-ampere reactive control during periods of extremely low power generation was demonstrated as well. The project team developed a pioneering demonstration concept and test plan to show how various types of active and reactive power controls can leverage PV generation's value from being a simple variable energy resource to a resource that provides a wide range of ancillary services. With this project's approach to a holistic demonstration on an actual, large, utility-scale, operational PV power plant and dissemination of the obtained results, the team sought to close some gaps in perspectives that exist among various stakeholders in California and nationwide by providing real test data.

14 SOLAR ENERGY↗

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 OSTI2020

Attack-resilient algorithms and testbed federation for wide-area protection and control in smart grid

Today’s energy infrastructure is undergoing a massive transformation across all generation, transmission, and distribution systems to provide reliability, efficiency, and sustainability to the power system network. During the past 10 years, there has been a remarkable enhancement in developing close-loop wide-area protection and control (WAPAC) applications, such as automatic generation control (AGC), wide-area protection scheme (WAPS), synchrophasor-based wide-area voltage control system (WAVCS), etc., in the energy management system (EMS) to provide an adequate situational awareness to control center operators during physical disturbances and natural events. The rapid digitalization, unencrypted communication, and numerous data-sharing devices have increased digital access points that have exposed the grid network to countless cyberattacks pertinent to the WAPAC cybersecurity. Given the amount of complex grid network coupled with legacy infrastructures, it is untrustworthy to completely rely on information technology (IT)-based conventional security measures to defend against evolving cyberattacks. Hence, there is a compelling need to go beyond the traditional paradigm of ‘security by obscurity’ and ‘bolt-on’ security measures, and develop a suite of innovative security solutions at multiple layers to transform the current “fault-resilient” grid into “fault and attack-resilient” grid of the future. This dissertation specifically focuses on developing application-specific attack-resilient solutions for critical WAPAC applications in the smart grid. The first part of the study, Attack-Resilient Wide-Area Protection Scheme, presents a cyber-physical attack-resilient system (CPARS) for WAPS, where two anomaly detection methods are proposed to detect multi-level cyberattacks followed by the rules-based intrusion mitigation system (RIMS) to initiate effective mitigation strategies, tailored to these attacks, to restore the normal grid operation after disturbances. The first anomaly detection component, Machine learning-based Anomaly Detection for Centralized WAPS, discusses a novel architecture and methodology for developing a machine-learning-based anomaly detection system (ADS) for the centralized wide-area protection system (CWAPS) by applying the variational mode decomposition (VMD) technique and decision tree (DT) algorithms using cyber logs and synchrophasor measurements. The second component, Multi-Agent-based Anomaly Detection for Decentralized WAPS, presents a two-level hierarchical multi-agent-based decentralized WAPS against the system-aware stealthy cyber-attacks. Finally, for the RIMS, the state transition diagram-based mitigation measures are defined based on the grid operation states and experimental testing and evaluation are presented in a cyber-physical testbed environment. The second part of the study, Attack-Resilient Wide-Area Voltage Control System, addresses the existing vulnerabilities in the wide-area voltage control system (WAVCS), presents the methodology for performing an impact analysis during data integrity attacks, and proposes a data-driven attackresilient system (DARS) by incorporating machine learning-based ADS and rules-based anomaly mitigation system (RAMS) to detect these attacks and provide necessary mitigation actions to maintain the transient voltage stability after disturbances. Finally, the third part, Networked Federation Testbed (NEFTSec) for Smart Grid Cybersecurity, focuses on developing an interconnected federated testbed through a common network like the internet, describes its conceptual architectures, and also presents its design components for experimental testing, validation, and evaluation. Further, it presents the co-simulation interface algorithm (CIA) to facilitate the geographically-dispersed real-time distributed simulation (GD-RTDS) during the cyber-physical federation. In general, this dissertation presents innovative attack-resilient solutions for WAPAC applications that are experimentally tested and evaluated using the PowerCyber testbed and NEFTSec platform to accelerate the transition of state-of-the-art research works to the real-field deployments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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 OSTI2020

Coordinated frequency regulation among asynchronous AC grids with an MTDC system

With the increasing penetration level of renewable power, the power systems’ inertias are decreasing. To ensure that the frequency is above the threshold of the under frequency load shedding, one effective way is to share the spinning reserves among asynchronous AC grids through HVDC systems. In this paper, a coordinated frequency regulation scheme that enables spinning reserves sharing is proposed for such hybrid AC/DC grids. This scheme is a communication-free method that consists of the droop control, the inertia emulation control and the frequency safety control. The combined response of the three controls can increase not only the frequency nadir but also the settled frequency of the disturbed grid. In addition, the hysteresis comparators and the power injection limits are adopted in the frequency regulation scheme to reduce the coupling effect among AC grids. Thus, under small and harmless disturbance, the frequency regulation scheme will be inactive; the disturbance in strong AC grids would not affect the weak AC systems. The frequency regulation scheme coordinates well with the automatic generation control of the grids. Furthermore, the feasibility and effectiveness of the proposed frequency regulation scheme are verified through simulation studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Probability Density Function Control of Frequency Fluctuations in Renewable-Rich Power Systems

The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Here, based upon the stochastic distribution control theory originated by the second author, this paper proposes a novel stochastic controller to improve the frequency PDF in power grids when integrating a large amount of RESs, thereby minimizing the effects of uncertainties and enhancing overall system stability. The key idea is to manipulate the controllable power generation resources so that the frequency PDF is make to follow a target PDF by using the stochastic distribution control theory originated by the second author. The proposed method can easily be plugged into existing automatic generation controls for multi-area transmission grids. The proposed method is validated via a modified Kundar's two area system and 240-bus Western Electricity Coordinating Council systems. The simulation results show that the proposed control shapes the frequency PDF narrower and sharper, leading to a notable improvement toward minimizing the effects of randomness and uncertainty during grid operation.

frequency↗

DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs' commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible and thus reduce the size and extend the lifetime of the BESS. In conclusion, the effectiveness of the control strategy is validated with an innovative, multi-area, interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators' dynamic response.

25 ENERGY STORAGE↗

DOE OSTI2023

Secondary Frequency Control for Reconfigurable Interconnecting Microgrids

Microgrids and microgrid technologies offer an operations and control framework for realizing the needed aggregation of a growing share of distributed energy resources. As the number of microgrids increases, so will the incentive to interconnect them, leading to a combinatorial growth of potential operating states. At the same time, their growing complexity nudges interconnected microgrids conceptually closer to balancing authorities in the bulk power system. This paper focuses on secondary frequency control and leverages the conceptual similarity between balancing authorities and interconnected microgrids to adopt an automatic generation control design with some adaptations. Frequency control and restoration is demonstrated via several use-cases with switching and reconfiguration events.

Schweitzer, Eran↗

DOE OSTI2018

Optimal Regulation of Virtual Power Plants

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence and tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Secondary Frequency Regulation from Variable Generation through Uncertainty Decomposition: An Economic and Reliability Perspective

The rapid integration of variable generation (VG), such as photovoltaics (PV), necessitates an increase in the secondary frequency regulation (SFR) to handle the system intra-dispatch interval imbalance because of VG's variation. Although PV has the control capability to provide SFR, the main challenge is in guaranteeing the delivery of PV's energy and SFRs capacities in the automatic generation control (AGC) within each dispatch interval considering its uncertainty. This paper proposes a deliverable VG SFR provision model with endogenous VG's power uncertainty decomposition. First, the uncertainty of VG is decomposed using distributionally robust chance constraints through which the deliverable SFR provision is guaranteed. Next, the intra-interval frequency response of PV's SFR is validated with a user defined AGC model including the PV power plant. Finally, the economic benefits and the reliability improvements such as the frequency deviation reduction with PV providing SFRcan be integrated and evaluated. The proposed model is tested in a modified 18-bus system and in the Western Electricity Coordinating Council test system. Results demonstrate that with the deliverable SFR from PV, the system cost and the frequency reliability can be improved simultaneously. PV's SFR performance can be guaranteed with the proposed model.

14 SOLAR ENERGY↗

DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

closed-loop validation↗

DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗