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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Hybrid Reinforcement Learning-MPC Approach for Distribution System Critical Load Restoration

This paper proposes a hybrid control approach for distribution system critical load restoration, combining deep reinforcement learning (RL) and model predictive control (MPC) aiming at maximizing total restored load following an extreme event. RL determines a policy for quantifying operating reserve requirements, thereby hedging against uncertainty, while MPC models grid operations incorporating RL policy actions (i.e., reserve requirements), renewable (wind and solar) power predictions, and load demand forecasts. We formulate the reserve requirement determination problem as a sequential decision-making problem based on the Markov Decision Process (MDP) and design an RL learning environment based on the OpenAI Gym framework and MPC simulation. The RL agent reward and MPC objective function aim to maximize and monotonically increase total restored load and minimize load shedding and renewable power curtailment. The RL algorithm is trained offline using a historical forecast of renewable generation and load demand. The method is tested using a modified IEEE 13-bus distribution test feeder containing wind turbine, photovoltaic, microturbine, and battery. Case studies demonstrated that the proposed method outperforms other policies with static operating reserves.

distribution system↗
DOE OSTI2022

Natural Gas-Electric Interdependency Through 2030

Presentation to IEEE Power and Engineering Society 2022 General Meeting on natural-gas electric interdependency results from Grid Modernization Initiative Near-Term Reliability and Resilience project.

Brewer, John↗
DOE OSTI2022

Soft Actor Critic Based Volt-VAR Co-optimization in Active Distribution Grids

Modern distribution networks are undergoing several technical challenges, such as voltage fluctuations, because of high penetration of distributed energy resources (DERs). This paper proposes a deep reinforcement learning (DRL)-based Volt VAR co-optimization technique for reducing voltage fluctuations as well as power loss under high penetration of DERs. In addition, the proposed approach minimizes the operational cost of the grid. A stochastic policy optimization based soft actor critic (SAC) agent is proposed to configure the optimal set-points of the reactive power outputs of the inverters. The performance of the proposed model is verified on the modified IEEE 34- and 123-bus systems and compared with a base case scenario with no reactive supply by inverters, and a local droop control approach. The results demonstrate that the proposed framework outperforms the conventional droop control method in improving the voltage profile, minimizing the network power loss, and reducing grid operational cost.

—Distribution grids, deep reinforcement learning, ↗
DOE OSTI2022

Assessing the Optimality of LinDist3Flow for Optimal Tap Selection of Step Voltage Regulators in Unbalanced Distribution Networks: Preprint

The adoption of distributed energy resources such as photovoltaics (PVs) has increased dramatically during the previous decade. The increased penetration of PVs into distribution networks (DNs) can cause voltage fluctuations that have to be mitigated. One of the key utility assets employed to this end are step-voltage regulators (SVRs). It is desirable to include tap selection of SVRs in optimal power flow (OPF) routines, a task that turns out to be challenging because the resultant OPF problem is nonconvex with added complexities stemming from accurate SVR modeling. While several convex relaxations based on semi-definite programming (SDP) have been presented in the literature for optimal tap selection, SDP based schemes do not scale well and are challenging to implement in large-scale planning or operational frameworks. This paper deals with the optimal tap selection (OPTS) problem for wye-connected SVRs using linear approximations of power flow equations. Specifically, the LinDist3Flow model is adopted and the effective SVR ratio is assumed to be continuous–enabling the formulation of a problem called LinDist3Flow-OPTS, which amounts to a linear program. The scalability and optimality gap of LinDist3Flow-OPTS are evaluated with respect to existing SDP-based and nonlinear programming techniques for optimal tap selection in three standard feeders, namely, the IEEE 13-bus, 123-bus, and 8500-node DNs. For all DNs considered, LinDist3Flow-OPTS achieves an optimality gap of approximately 1% or less while significantly lowering the computational burden.

linear approximations↗
DOE OSTI2023

Synchronous Wind: Evaluating the Grid Impact of Inverterless Grid-Forming Wind Power Plants: Preprint

Grid-forming (GFM) control of Type-3 and Type-4 wind turbine generators have attracted substantial attention in power system research. However, the limited over-current capability of power electronics converters continues to deteriorate the grid strength of the evolving power systems. This paper developed the generic model of synchronous wind power generators, also known as Type-5 wind turbines, for the power system integration studies. The Type-5 wind turbine interface to the grid through a synchronous generator; hence, its operation and consequent grid impacts are similar to a conventional power plant. Based on the developed model, a Type-5 wind power plant is integrated into IEEE 14-bus testbed to evaluate its control and operation with a bulk power system. Finally, the stability properties of Type-5 wind turbine generators are compared with Type-3 wind turbines in GFM control mode through impedance characterization.

grid strength↗
DOE OSTI2023

5G Security and AI/ML

Invited talk to IEEE Communication Society's SIG for AI and Machine Learning in Security.

5G Security↗
DOE OSTI2022

Assessing Cybersecurity Resilience of Distributed Ledger Technology in Energy Sector Using the MITRE ATT&CK® ICS Framework

Digitization in the power industry enables wide connectivity among multiple new entrants such as DERs, prosumers, and P2P counterparts within or outside the Distributed Ledger Technology (DLT). The use of DLT to improve resilience in the power grid has growing support, but new technology provides new opportunities for adversaries to cause harm. This work completed by the Cybersecurity- focused task force of IEEE SA P2418.5 evaluates the potential risks by applying the MITRE ATT&CK® ICS matrix to the DLT Engineering and Cybersecurity Stack designed for power systems applications

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2019

Data-driven cyber attack detection and mitigation for decentralized wide-area protection and control in smart grids

Modern power systems have already evolved into complicated cyber physical systems (CPS), often referred to as smart grids, due to the continuous expansion of the electrical infrastructure, the augmentation of the number of heterogeneous system components and players, and the consequential application of a diversity of information and telecommunication technologies to facilitate the Wide Area Monitoring, Protection and Control (WAMPAC) of the day-to-day power system operation. Because of the reliance on cyber technologies, WAMPAC, among other critical functions, is prone to various malicious cyber attacks. Successful cyber attacks, especially those sabotage the operation of Bulk Electric System (BES), can cause great financial losses and social panics. Application of conventional IT security solutions is indispensable, but it often turns out to be insufficient to mitigate sophisticated attacks that deploy zero-day vulnerabilities or social engineering tactics. To further improve the resilience of the operation of smart grids when facing cyber attacks, it is desirable to make the WAMPAC functions per se capable of detecting various anomalies automatically, carrying out adaptive activity adjustments in time and thus staying unimpaired even under attack. Most of the existing research efforts attempt to achieve this by adding novel functional modules, such as model-based anomaly detectors, to the legacy centralized WAMPAC functions. In contrast, this dissertation investigates the application of data-driven algorithms in cyber attack detection and mitigation within a decentralized architecture aiming at improving the situational awareness and self-adaptiveness of WAMPAC. First part of the research focuses on the decentralization of System Integrity Protection Scheme (SIPS) with Multi-Agent System (MAS), within which the data-driven anomaly detection and optimal adaptive load shedding are further explored. An algorithm named as Support Vector Machine embedded Layered Decision Tree (SVMLDT) is proposed for the anomaly detection, which provides satisfactory detection accuracy as well as decision-making interpretability. The adaptive load shedding is carried out by every agent individually with dynamic programming. The load shedding relies on the load profile propagation among peer agents and the attack adaptiveness is accomplished by maintaining the historical mean of load shedding proportion. Load shedding only takes place after the consensus pertaining to the anomaly detection is achieved among all interconnected agents and it serves the purpose of mitigating certain cyber attacks. The attack resilience of the decentralized SIPS is evaluated using IEEE 39 bus model. It is shown that, unlike the traditional centralized SIPS, the proposed solution is able to carry out the remedial actions under most Denial of Service (DoS) attacks. The second part investigates the clustering based anomalous behavior detection and peer-assisted mitigation for power system generation control. To reduce the dimensionality of the data, three metrics are designed to interpret the behavior conformity of generator within the same balancing area. Semi-supervised K-means clustering and a density sensitive clustering algorithm based on Hierarchical DBSCAN (HDBSCAN) are both applied in clustering in the 3D feature space. Aiming to mitigate the cyber attacks targeting the generation control commands, a peer-assisted strategy is proposed. When the control commands from control center is detected as anomalous, i.e. either missing or the payload of which have been manipulated, the generating unit utilizes the peer data to infer and estimate a new generation adjustment value as replacement. Linear regression is utilized to obtain the relation of control values received by different generating units, Moving Target Defense (MTD) is adopted during the peer selection and 1-dimensional clustering is performed with the inferred control values, which are followed by the final control value estimation. The mitigation strategy proposed requires that generating units can communicate with each other in a peer-to-peer manner. Evaluation results suggest the efficacy of the proposed solution in counteracting data availability and data integrity attacks targeting the generation controls. However, the strategy stays effective only if less than half of the generating units are compromised and it is not able to mitigate cyber attacks targeting the measurements involved in the generation control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Developing VSC-HVDC Oscillation Damping Control Constraints in Unit Commitment

High-voltage direct current (HVDC) systems within the existing power grids will play a pivotal role in enabling high share of renewable power integration and transportation electrification. There is a need for transmission planning models to accurately capture the impact of VSC-HVDC oscillation damping control on the system planning and model the constraints in the security constrained unit commitment (SCUC) problem. In this paper, the SCUC problem in a hybrid DC-AC grid considering damping on electromechanical inter-area oscillation is studied. An electromechanical oscillation-driven transmission capability constraints are derived from system swing equation and incorporated into the SCUC. Multiple system damping control scenarios are set based on the extracted plausible bounds of damping coefficient and inertia constant to linearize the nonlinear expressions. The SCUC problem with proposed constraints is tested on the IEEE 73-bus reliability test system (RTS) case via PLEXOS. The impact of the proposed constraints on regional generation, inertia, power flow, annual system cost, and renewable energy curtailment are fully assessed.

damping control↗
DOE OSTI2023

Are System Baselines within OT Environments Feasible?

Critical infrastructure stakeholders need to baseline their systems to understand expected protocol communications.Baseline behaviors may vary based on operational context.Expected operations during a maintenance window, for example, may be different from normal operations.Furthermore, constructing system baselines for Industrial Control Systems (ICS) is difficult and time-consuming.ICS processes generate artifacts expressed across heterogeneous data sources such as network and device logs. There needs to be a corpus of data in order to develop and compare methods that evaluate the feasibility, performance, and generality of approaches to construct baselines for ICS events. Standalone repositories of network packet captures are insufficient to develop methods to classify or recognize operational events expressed across multiple data sources. Moreover, static data corpora do not enable researchers to compare the impact of changing the underlying system for which a baseline is being constructed and this limits the ability to evaluate the performance of system baselines given system changes (e.g. patches, configuration, maintenance events). In order to address these limitations within the community, this talk intends to promote discussion about the state of the practice of constructing baselines. In this manner, we can continue to understand requirements within industry that are not being met by current approaches to baseline construction. This talk builds on two previous talks on the topic of system baselines for OT environments. First, Weaver co-presented at the RSA Conference ICS Sandbox with Dan Gunter. The talk confirmed the need within industry to construct baselines across multiple types of data sources relative to the semantics of specific business processes. Second, Weaver presented at IEEE Security and Privacy Workshop on Language-Theoretic Security.

02 PETROLEUM↗
DOE OSTI2023

A Privacy Preserving Distributed Model Identification Algorithm for Power Distribution Systems: Preprint

Distributed control/optimization is a promising approach for network systems due to its advantages over centralized schemes, such as robustness, cost-effectiveness, and improved privacy. However, distributed methods can have drawbacks, such as slower convergence rates due to limited knowledge of the overall network model. Additionally, ensuring privacy in the communication of sensitive information can pose implementation challenges. To address this issue, we propose a distributed model identification algorithm that enables each agent to identify the sub-model that characterizes the relationship between its local control and the overall system outputs. The proposed algorithm maintains the privacy of local agents by only communicating through dummy variables. We demonstrate the efficacy of our algorithm in the context of power distribution systems by applying it to the voltage regulation of a modified IEEE distribution system. The proposed algorithm is well-suited to the needs of power distribution controls and offers an effective solution to the challenges of distributed model identification in network systems.

data-driven modeling↗
DOE OSTI2020

Radiation Simulation using Wi-Fi Signal Strength and Frequency

For routine radiological operations, lost radioactive sources, decommissioning and cleanup of nuclear facilities, and radiological terrorist events such as Radioactive Dispersive Devices (RDDs) or Radiological Exposure Devices (REDs), individuals are tasked with accurately locating both point and distributed sources of radiation. Radiation workers must often practice these tasks, whether part of initial training or periodically as part of formal or informal exercises or drills. In such circumstances, it is desirable to have an accurate recreation of a radioactive source, including a method of detecting it, which does not include dangerous amounts of radiation. The goal of this research was to develop a radiation simulation technology that uses IEEE 802.11x W-LAN protocol, i.e. Wi-Fi sources and detectors for these, as an inexpensive, precise and accurate method of replicating sources of gamma radiation. For this work, existing 802.11x sources were used. Software was developed for use with an Android smartphone to detect the presence of these sources. The measurements followed the expected behavior as a function of distance from the sources, mimicking that of gamma radiation, thus demonstrating the fundamental principle of operation. The ultimate system will be used in an outreach program to interest students in the radiation protection field.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

An Electromagnetic Transient and Three-Phase Phasor Co-Simulation Platform for Studying Distribution System Transients with High Pentration of DERs

Inverter vendors usually have electro-magnetic transient (EMT) models of distributed energy resources (DERs) for validation purposes and these types of models are usually black-boxed considering intellectual property (IP) protection. Limited by small simulation time step for the entire power system network, studying the system-level responses of DERs in EMT simulators is more time-consuming as the network size increases. Meanwhile, vendors usually do not have inverter models that can be used in three-phase phasor-domain simulators. This paper proposes a platform that can dynamically co-simulate the EMT inverter models and three-phase phasor-domain distribution networks considering high penetration of inverter-based DERs. This platform is very useful for evaluating the impacts of vendor-provided black-box DER model on distribution system dynamics. The co-simulation platform is validated against the full EMT model using a simple two-inverter test system and tested using IEEE 34-node test feeder.

Liu, Yuan↗
DOE OSTI2018

Direct Current Arc-Flash Hazards of Solar Photovoltaic Systems

An arc-flash is a rapid release of thermal energy, pressure waves, and electromagnetic interference from a high-power electrical system, caused by such events as unintentional shorting or equipment malfunction. Arc-flashes are hazardous to people and equipment. Incident energy (IE) is a means of quantifying the degree of thermal hazard posed by an arc-flash event. The calculated IE value dictates what level of personal protective equipment (PPE) workers are required to wear when servicing equipment. Overly burdensome PPE may increase a worker’s discomfort and decrease dexterity, which could lead to unintentional shorting, while inadequate PPE also comes with increased safety risks. The majority of arc-flash research to date has focused on alternating current (ac) systems. For example, IE calculations and PPE for ac systems are relatively well understood and have been applied across many equipment types and voltages. IE calculation methodologies in ac systems are backed by a wide range of industry tests and are included in Institute of Electrical and Electronics Engineers (IEEE) and National Fire Protection Association (NFPA) standards. However, very little is known about direct current (dc) arc-flash and its hazards. This is a significant knowledge gap, as an increasing number of dc systems are being deployed: solar photovoltaic (PV) plants, battery storage, and electric vehicles and their charging infrastructure. The dc arc-flash hazard publications are rooted primarily in theory, and their IE calculation methods contradict each other. Insufficient knowledge and data are preventing the formation of industry consensus and standards around dc arc-flash hazard assessment. Here, this white paper highlights the current status and research opportunities for assessing arc-flash hazards in dc systems, with a focus on PV plants. The nonlinear current-voltage characteristics of PV modules make them unique in comparison to other linear dc sources, such as batteries. Also, PV equipment has rapidly evolved from 600 Vdc to 1,500 Vdc (in the United States), increasing potential arc-flash hazards. The operating regime of a PV-array within its I-V characteristic curve during an arc-flash event and the sustainability of arc-flash events in a utility-scale PV plant need to be investigated. Arc-flash experiments on a 1-MWdc nameplate capacity utility-owned ground-mount photovoltaic plant suggest that the PV array acts as a constant-current supply with currents near the short-circuit portion of the I-V characteristic curve of the array, with median arc voltage as 1/3 of the rated voltage. Various engineering software packages (CYME7 by EATON, PTW by SKM, ArcFlash™ by EasyPower, ETAP, and so on) have started offering dc arc-flash calculation features to estimate the risk of arc-flash in dc and PV systems. However, they are reliant on the same simplified arc-flash models, which contradict each other due to differences in assumptions such as characteristics of the power source, arc current, voltage and impedance, arc-operating regime, and so on. Physical arc-flash testing and improved physics-based modeling with correct assumptions representing practical scenarios are two methods to improve understanding and quantify the risks associated with dc arc-flash hazards. The results would inform development of a more accurate calculation procedure for IE and proper PPE levels.

14 SOLAR ENERGY↗