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At least 1,171 records · Page 65

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↗

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗

Understanding Regional Inertia Dynamics in CAISO from Real Grid Disturbances

The shift from synchronous generators to inverter-based resources has caused power system inertia to be unevenly distributed across power grids. As a result, certain grid regions are more vulnerable to high rate-of-change of frequency (RoCoF) during disturbances. This paper presents a measurement-based framework for estimating grid inertia in CAISO (California Independent System Operator) region using real disturbance-driven frequency data from the Frequency Monitoring Network (FNET/GridEye). By analyzing confirmed disturbances from 2013 to 2024, we identify trends in regional inertia and frequency dynamics, highlighting their relationship with renewable generation and the evolving duck curve. Regional RoCoF values were up to six times higher than interconnection-wide values, coinciding with declining inertia. Recent recovery in inertia is attributed to the increased deployment of battery energy storage systems with synthetic inertia capabilities. These findings underscore the importance of regional inertia monitoring, strategic resource planning, and adaptive operational practices to ensure grid reliability amid growing renewable integration.

Dulal, Saurav [University of Tennessee, Knoxville ↗

Blackstart Capability and Survivability of Wind Turbines with Fully Rated Converters

We report the blackstart capability of wind turbines is critical for the recovery of wind-dominant power systems from blackouts. If wind power plants are not able to restore a power system, the incorporation of wind resources into electric grids could be limited by blackstart capability. This paper tackles this problem by setting forth a grid-forming controller for Type 4 wind turbines which employ fully rated power converters. To this end, we engineer two-axis anti-windup proportional-integral regulators that serve to ride through restoration disturbances. We also design an active protection system to prevent wind turbines from stalling during recovery from blackouts. We demonstrate in a high-fidelity simulation environment that Type 4 wind turbines with the developed controllers and protection subsystem can: (i) re-energize a notional wind-dominant grid; (ii) ride through asymmetrical faults; and (iii) survive low wind speed events.

17 WIND ENERGY↗

Synchronized Waveforms – A Frontier of Data-Based Power System and Apparatus Monitoring, Protection, and Control

Voltage and current waveforms contain the most authentic and granular information on the behaviors of power systems. In recent years, it has become possible to synchronize waveform data measured from different locations. Thus large-scale coordinated analyses of multiple waveforms over a wide area are within our reach. This development could unleash a set of new concepts, strategies, and tools for monitoring, protecting, and controlling power systems and apparatuses. This paper presents an in-depth review and analysis of the advancements in synchronized waveform data, including measurement devices, data characteristics, use cases, and comparisons with synchrophasor data. Based on the findings, five strategies are proposed to discover and develop synchronized waveform based applications over multiple application areas. The paper also presents three complementary measurement platforms and two data screening algorithms for application implementation. It further discusses committee activities and standard developments useful to explore the full potential of the data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Barrier-Certificated Reinforcement Learning Approach for Enhancing Power System Transient Stability

Increasing integration of renewable resources brings more flexibility and poses new challenges to modern power systems, leading to highly nonlinear and complex dynamics. Here, this paper aims to provide a general solution framework to traditional control problems, such as frequency control and voltage control, which attempt to maintain the stability of either synchronous generators-governed or inverter-governed systems when subjected to a disturbance and simultaneously guarantee operational constraints, providing a complete complement to existing works on control design. Building on reinforcement learning (RL) and control barrier functions, the framework includes two subsystems, i.e., a model-free controller and a barrier-certification system, which discover RL-based control actions and sequentially filter them using a barrier certificate to satisfy operational constraints. Calculating a barrier function is generally challenging for a complex power system. This is addressed by representing the barrier function using neural networks (NNs) and data-based approaches. An adaptive method is introduced to certify the neural barrier function that perseveres barrier conditions, which is more compatible with online implementation. The proposed framework synthesizes a stabilizing controller that satisfies predefined safety regions. The effectiveness of the proposed framework is demonstrated via several comparative case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Pricing and Energy Trading in Peer-to-Peer Zero Marginal-Cost Microgrids

Efforts to utilize 100% renewable energy in community microgrids require new approaches to energy markets and transactions to efficiently address periods of scarce energy supply. In this paper we contribute to the promising approach of peer-to-peer (P2P) energy trading in two main ways: analysis of a centralized, welfare-maximizing economic dispatch that characterizes optimal price and allocations, and a novel P2P system for negotiating energy trades that yields physically feasible and at least weakly Pareto-optimal outcomes. Our main results are 1) that optimal pricing is insufficient to induce agents with batteries to take optimal actions, 2) a novel P2P algorithm to addresses this while keeping private information, 3) a formal proof that this algorithm converges to the centralized solution in the case of two agents negotiating for a single period, and 4) numerical simulations of the P2P algorithm performance with up to 10 agents and 24 periods that show it converges on average to total welfare within 0.1% of the social optimum in on the order of 10s to 100s of iterations, increasing with the number of agents, time periods, and total storage capacity.

batteries↗

A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller (Final Report)

This report contains information regarding the activities carried out in the project "A Smart and Flexible Microgrid with a Low-cost Scalable Open-source Controller. The project aims at developing a community-based flexible microgrid (FMG) with smart grid features, including multiple utility feeders and dynamic boundaries that utilize intelligent switches and ultra-high-speed communication links already in a smart grid. The project also aims at developing a corresponding controller for such an FMG with low cost and high scalability. With distributed renewable energy resources (DERs) and the intelligent microgrid controller, the FMG will achieve aggressive emission reduction, increased energy use efficiency, and reliability improvement goals. The FMG and its controller design will be scalable for different geographic areas, load sizes, distributed generation source number and types, and even multiple MGs within a distribution electric power system. In order to achieve these project objectives, three main development tasks were carried out: FMG design, FMG controller development, and FMG controller testing. The fourth task was technology to market.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Grid Expansion Optimal Planning Tools (GridEO): Manual for Users and Developers

This report describes Grid Expansion Optimal Planning Tools (GridEO). GridEO is a Python package for electric power grid capacity expansion modeling. With GridEO, the user can build and solve instances of the Capacity Expansion Planning (CEP) problem to determine an optimal plan of investment in capacity of various types of power grid equipment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

OEDI—Solar Grid Integration Data and Analytics Library

As a part of the Open Energy Data Initiative, this effort aims to develop and demonstrate novel distribution state estimation, control optimization, and transient analysis as well as provide access to data, data integration, and mapping information. More specifically, the focus of the effort will be on physics-based distribution system state estimation, hybrid (physics-based and machine learning) distribution optimal power flow, and event detection/analysis for solar integration and analytics. This work will enable reproducible, robust, replicable, and generalizable R&D in simulation and emulation of solar system integration. These test models and datasets will provide an integrated library for developing and testing power system operation technologies. To make the library user-friendly, this project will provide data curation tools such as data translators, mapping scripts and APIs, database schemas and metadata, interfaces and user dashboard, source code for the reference algorithms, description of the use-cases/scenarios, and comprehensive information on all the assumptions.

14 SOLAR ENERGY↗

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A modular Space Station/Base electrical power system - Requirements and design study.

The requirements and procedures necessary for definition and specification of an electrical power system (EPS) for the future space station are discussed herein. The considered space station EPS consists of a replaceable main power module with self-contained auxiliary power, guidance, control, and communication subsystems. This independent power source may 'plug into' a space station module which has its own electrical distribution, control, power conditioning, and auxiliary power subsystems. Integration problems are discussed, and a transmission system selected with local floor-by-floor power conditioning and distribution in the station module. This technique eliminates the need for an immediate long range decision on the ultimate space base power sources by providing capability for almost any currently considered option.

Eliason, J. T.↗

Plasma waves in a relativistic, strongly anisotropic plasma propagated along a strong magnetic field

The dispersion properties of plasma waves in a relativistic homogeneous plasma propagated along a strong magnetic field are studied. It is shown that the non-damping plasma waves exist in the frequency range omega sub p or = omega or = omega sub L. The values of omega sub p and omega sub L are calculated for an arbitrary homogeneous relativistic function of the particle distribution. In the case of a power ultrarelativistic distribution, it is shown that, if the ultrarelativistic tail of the distribution drops very rapidly, slightly damping plasma waves are possible with the phase velocity (omega/K)c.

Onishchenko, O. G.↗

Analysis of a Mars-stationary orbiting microwave power transmission system

To determine the feasibility of providing efficient RF power transmission from a Mars-stationary orbit to the surface of the planet, an assessment was made focussing on RF propagation in the 2.45- to 300-GHz range. The proposed orbiting system configuration provides for power generation by either photovoltaic array or nuclear reactor, the conversion of the dc output to RF, and subsequent propagation of RF energy from the orbiting array to the Martian surface. On the planet, a rectenna array will convert RF to dc power to be distributed for planetary power needs. Total efficiency of the energy conversion chain from dc to RF in orbit through RF to dc on the planetary surface was derived for several representative frequencies in the range of study. Tradeoffs between component efficiency and transmitting antenna requirements were considered for each of these frequencies. Rectenna element power density thresholds and desired received power levels were used to determine receiving antenna criteria. Recommendations are presented for research into developing technologies which may afford enhanced viability of the proposed microwave power transmission system.

Long, Kenwyn J.↗

High power GaInAs lasers with distributed Bragg reflectors

Single-mode strained-layer lasers have been fabricated which use buried second-order gratings for distributed Bragg reflectors. The lasers contain a strained GaInAs quantum well in the active region and operate in an edge emitting fashion with CW powers in excess of 110 mW. Single longitudinal and transverse mode operation is maintained at about 971.9 nm up to 42 mW. Total power conversion efficiencies as high as 28 percent have been observed. The longitudinal and transverse mode behavior is stable under 90 percent amplitude modulation with 50 percent duty cycle pulses at 10 kHz and 10 MHz. Preliminary life-test data at 40 C also indicate room temperature lifetimes in excess of 45,000 hours.

O'Brien, S.↗

User interface design principles for the SSM/PMAD automated power system

Martin Marietta has developed a user interface for the space station module power management and distribution (SSM/PMAD) automated power system testbed which provides human access to the functionality of the power system, as well as exemplifying current techniques in user interface design. The testbed user interface was designed to enable an engineer to operate the system easily without having significant knowledge of computer systems, as well as provide an environment in which the engineer can monitor and interact with the SSM/PMAD system hardware. The design of the interface supports a global view of the most important data from the various hardware and software components, as well as enabling the user to obtain additional or more detailed data when needed. The components and representations of the SSM/PMAD testbed user interface are examined. An engineer's interactions with the system are also described.

Jakstas, Laura M.↗

Collisional and dynamical history of Gaspra

Interpretation of the impact record on Gaspra requires understanding of the effects of collisions on a target body of Gaspra's size and shape, recognition of impact features that may have different morphologies from craters on larger planets, and models of the geological processes that erase and modify impact features. Crater counts on the 140 sq km of Gaspra imaged at highest resolution by the Galileo spacecraft show a steep size-frequency distribution (cumulative power-law index near -3.5) from the smallest resolvable size (150 m diameter) up through the large feature (1.5 km diameter crater) of familiar crater-like morphology. In addition, there appear to be as many as eight roughly circular concavities with diameters greater than 3 km visible on the asteroid. If we restrict our crater counts to features with traditionally recognized crater morphologies, these concavities would not be included. However, if we define craters to include any concave structures that may represent local or regional damage at an impact size, then the larger features on Gaspra are candidates for consideration. Acceptance of the multi-km features as craters has been cautious for several reasons. First, scaling laws (the physically plausible algorithms for extrapolating from experimental data) indicate that Gaspra could not have sustained such large-crater-forming impacts without being disrupted; second, aside from concavity, the larger structures have no other features (e.g. rims) that can be identified with known impact craters; and third, extrapolation of the power-law size distribution for smaller craters predicts no craters larger than 3 km over the entire surface. On the other hand, recent hydrocode modeling of impacts shows that for given impact (albeit into a sphere), the crater size is much larger than given by scaling laws. Gaspra-size bodies can sustain formation of up to 8-km craters without disruption. Besides allowing larger impact craters, this result doubles the lifetime since the last catastrophic fragmentation event up to one billion years. Events that create multi-km craters also globally damage the material structure, such that regolith is produced, whether or not Gaspra 'initially' had a regolith, contrary to other models in which initial regolith is required in order to allow current regolith. Because the globally destructive shock wave precedes basin formation, crater size is closer to the large size extrapolated from gravity-scaling rather than the strength-scaling that had earlier been assumed for such small bodies. This mechanism may also help explain the existence of Stickney on Phobos. Moreover, rejection of the large concavities as craters based on unfamiliar morphology would be premature, because (aside from Stickney) we have no other data on such large impact structures on such a small, irregular body. The eight candidate concavities cover an area greater than that counted for smaller craters, because they are most apparent where small craters cannot be seen: on low resolution images and at the limb on high resolution images. We estimate that there are at least two with diameter greater than 4 km per 140 sq km, which would have to be accounted for in any model that claims these are impact craters.

Greenberg, R.↗