Energy Grid | Kalyan Perumalla

DarkNet Cyber Resilience

Tue, 22 Mar 2022 00:00:00 +0000

DarkNet Cyber Resilience investigates the impacts of cyber stress and its thresholds of impact on alternative timing signals for the US national energy grid.

Cyber Resilience of Alternative Timing for Energy Grids

Overview

This project is focused on performing a systematic evaluation of the impacts of cyber stress on the system. It is developing tools that enable early detection of performance issues and rapid recovery from cyber-related events. A unique advancement of the project lies in going beyond general cybersecurity vulnerabilities and exposures (CVE). This is achieved by evaluating their implications to the cyber resilience specifically with regard to precise effects on the transmission and receipt of timing signals over the complex networks connecting the timing sources to the geographically-distant subscribers.

Key Links

DarkNet Website

Gallery

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program: DarkNet
Prime: Oak Ridge National Laboratory (ORNL)

Selected Publications

DarkNet Cyber Resilience

Two key cyber elements affecting the grid’s timing capability are Cyber Resilience and Cyber Trust. The timing services of DarkNet are systematically subjected to a range of cyber phenomena that stress four key performance factors, namely: Accuracy, Manageability, Telemetry, and Visibility. This analysis is designed to provide insights into four important categories of undesirable cyber phenomena: Loss of View (LoV), Loss of Control (LoC), Manipulation of View (MoV), and Manipulation of Control (MoC).

Kalyan Perumalla, Juan Lopez

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Exascale Computing for the National Energy Grid

Sat, 01 Jan 2022 00:00:00 +0000

Exascale Computing for the Stochastic Grid Dynamics of the US national energy transmission network is a part of the Exascale Computing Project to tap the world’s largest supercomputer to solve the nation’s energy grid problems.

Exascale Computing Project

Overview

The Exascale Computing Project that enables US revolutions in technology development: scientific Discovery; health care; and energy, economic, and national security. Exascale computing will provide the capability to tackle challenges at levels of complexity and performance that previously were out of reach.

The Problem

How can we secure the national energy transmission network despite unexpected cyber attacks, natural disasters, and unpredictable load fluctuations?
How fast and far into the future can we make it resilient?
How can we ultimately achieve this at the least cost to everyone?

The Solution

Enter Exascale computing and Global Optimization.

This project attacks this nationally important problem with an unprecedented high-technology approach that relies on supercomputing to work out the very best global solutions on-the-fly, rapidly examining millions of configurations involving all the energy generators, transmission lines, event contingencies, and complex physical constraints. Very high-end algorithms implemented with sophisticated parallel processing software is designed for the state-of-the-art supercomputing hardware, combining the know-how of some of the very best minds across the US national laboratory systems, tapping a range of experts in energy domain sciences, computational optimization, numerical algorithms, high-end computing hardware, and advanced software stack organization techniques.

Organization

Sponsor: US Department of Energy (DOE)
- Office: Advanced Scientific Computing Research (ASCR)
- Program: Exascale Computing Project (ECP)
Institutions: PNNL, ORNL, ANL, LLNL, NREL
Period: 2019-2023/24

Abbreviations

PNNL = Pacific Northwest National Laboratory
ORNL = Oak Ridge National Laboratory
ANL = Argonne National Laboratory
LLNL = Lawrence Livermore National Laboratory
NREL = National Renewable Energy Laboratory
PI = Principal Investigator

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NAERM

Sat, 01 Jan 2022 00:00:00 +0000

North American Energy Resilience Model provides the next generation planning infrastructure for the US national energy grid using a cloud-based real-time, interoperable, and federated modeling, simulation, and visualization technology.

Overview

NAERM dependencies across energy infrastructure layers

Interactive Contingency Selection

Contributions

As ORNL lead for the NAERM Software Architecture Group, my efforts were focused on enabling cloud-based federated simulations executing in a distributed fashion across PNNL, ORNL and ANL servers. In particular, a dynamically configured and launched network of virtual machines via Amazon Web Services (AWS), coordinated using AWS Step Functions. Automated launches of electric transmission grid scenarios can be triggered in a highly responsive fashion. The software architecture was designed to evaluated using the Siemens PSS/E simulator instances that were licensed to execute in on-premise mode only at ORNL. Additionally, PowerWorld simulations were dynamically interoperated with other instances using federated simulation interfaces of the HELICS system for interfacing with gas network outage models simulated at ANL.

A contingency visualization, selection and launch tool was developed with one of my team members (Dr. Maksudul Alam).

Architecture

Cloud-based Software Architecture for Federated Simulation

Demo Videos

Description

The NAERM will ultimately provide real-time situational awareness and analysis capabilities for emergency events for optimal operations and recovery, so that the Federal Government can quickly and effectively prepare and respond, for example, providing recommendations in coordination with State and local governments, Federal Emergency Management Agency (FEMA), and the National Guard. While the primary focus is on the energy sector, the NAERM will further assist industry in assessing the resilience implications of energy planning decisions on associated infrastructure. NAERM capabilities will also be leveraged by DOE’s National Nuclear Security Administration (NNSA), the Department of Defense (DoD), and the Department of Homeland Security (DHS) in support of their national security missions.
– NAERM Report

The North American Energy Resilience Model project is focused on developing the next generation planning infrastructure for the US national energy grid using a cloud-based real-time, interoperable, and federated modeling, simulation, and visualization technology

Ultimately, NAERM will enable DOE’s provision of situational assessment advice to industry and government to ameliorate the risk of and consequence associated with large- scale service disruptions across infrastructure sectors—and geographic and organizational boundaries—and the lengthy restoration and recovery operations following an extreme event. The NAERM will advance the state-of-science in planning and operations of energy supply in extreme events and provide rigorous resilience and associated economics metrics for these sectors.
– NAERM Report

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program: North American Energy Resilience Model (NAERM)
Team: ORNL, PNNL, LLNL, ANL, and others

DES Grid

Sat, 01 Jan 2022 00:00:00 +0000

Discrete Event Modeling of the Electric Grid is a new non-equilibrium, transient analysis model and solver that is indispensable for new advancements in grids with high renewable penetration.

Novel Discrete Event Modeling and Simulation of Energy Grids

Overview

This project is aimed at creating and demonstrating a new approach to transient analysis for power systems that has three key advantages over existing methods. These advantages are:

an accurate, physically plausible model that creates signals perceived by sensors throughout the transmission and distribution networks;
enabling a natural and accurate representation of modern electrical loads, such as power electronics devices, within the distribution system, and
a computationally tractable method of simulating these models at large scales.

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Approach

Grid modeling and simulation requires accurate capture of physics combined with internal and external behavioral elements. The physics includes movement of electricity at multiple scales broadly classified as transmission, distribution, and sub-distribution. This is driven by internal behaviors: generation is dictated by physics of power generators plus sophisticated controls to maintain voltage, and by consumption loads driven by a wide variety of traditional energy sinks as well as increasingly sophisticated sensors and controllers introduced by smart grid technologies. In light of advances in distributed energy resources and renewables, most aspects of transport, generation, consumption and responses are also greatly controlled by rich internal behaviors. Our approach provides support in one form or another to modeling and simulating all the aforementioned grid elements.

We approach the grid modeling and simulation problem with a first principles-based, fully generalized, transient simulation view of the grid. Our starting point is that of a new three-phase model that is equally applicable at multiple levels, spanning transmission, distribution and sub-distribution.

Our three-phase model is designed to produce voltage and current wave forms at scales in time and geographical spaces sufficient to understand system-wide dynamics resulting from localized-yet-interconnected behaviors of:

signal processing algorithms and logic in inverters, protection devices, and other equipment that act on millisecond time scales;
electrical and mechanical dynamics of conventional and new solar, fossil fuel, nuclear, and other power generators that evolve over tens of seconds; and
detailed dynamics of loads that may contribute to large-scale distributed controls that counterbalance the volatility of distributed/renewable generation.

We create a new type of power system model that integrates dynamic load and generation models with a dynamic, rather than quasi-equilibrium, model of the transmission and distribution network. This new model enables relevant, simulation-based performance assessments of new sensors, such as next generation phasor measurement units and distribution-based frequency sensors, and provide an unprecedented, indispensable understanding of how sensor characteristics impact wide area control strategies.

The new model developed through this research replaces pseudo equilibrium models of transmissions and loads with dynamic elements that properly resolve the physics that transmit electrical power. With these new models it becomes possible in simulation to measure physically plausible voltage signals throughout a large power system during a transient, and to do so with complete knowledge of the events within the modeled power system that produced the observed signal. This new insight will propel advancing sensing and control technologies that would be infeasible to engineer with present, inadequate models and experimental test beds.

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
- Program:
  - Grid Modernization Laboratory Consortium (GMLC)
  - Advanced Grid Modeling (AGM)
Prime: Oak Ridge National Laboratory (ORNL)

Additional Motivation

Current methods for electromechanical transient analysis of electrical power systems predate the significant, recent advances in sensing technology that allow measurements of frequency to be made through the transmission and distribution systems. Consequently, current methods of analysis make no attempt to accurately calculate the signals that these sensors are designed to monitor. This creates considerable difficulties when current methods, models, and simulation tools are used to assess how a new device that relies on measures of frequency will affect the response of the power system to a disturbance,

This problem has been widely recognized in recent years, and numerous, essentially ad hoc, solutions have been proposed. While these ad hoc techniques can, and have, been easily integrated into existing tools, they generally lack a fundamental basis in the physics of an electrical power system, are prone to large numerical errors, or both. At best, these proposals must be viewed as a stop gap measure until models become available that properly resolve dynamical effects in the transmission network that, in conjunction with the generator dynamics, ultimately determine how a signal is perceived by a sensor within the transmission and distribution systems.

Selected Publications

A Case Study in Simulation Methods for Power Electronic Circuits

A simplified circuit is used as a case study to uncover and highlight key considerations in the use of traditional numerical simulation methods and compare them with those obtained from alternative methods that are discrete event-based from the outset. Results show the regimes where the traditional numerical methods and the alternative discrete event methods are applicable, and the need for discrete event approaches that precisely and efficiently resolve switching dynamics produced by power electronics systems that are important in emerging grid scenarios, such as large scale renewable energy.

James Nutaro, Suman Debnath, Kalyan Perumalla

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Digital Twin Framework

Sat, 01 Jan 2022 00:00:00 +0000

Our novel Digital Twin Framework (DTF) is designed to improve resilience of critical infrastructure systems by continuously comparing the infrastructure state with automatically generated, AI/ML-based, real-time digital-twin simulation of the system.

Team

Digital Twin Framework Software Architecture

Overview

As the level of automation in critical infrastructure increases, the ability to detect cyber intrusions becomes more crucial and extremely challenging. Recent cyber attacks demonstrate the devastating and widespread affects they can have on critical infrastructure.

DTF is designed specifically to detect and eventually prevent such attacks, with models validated against experimental data from two critical infrastructure experimental emulators – a canal lock system and an electric distribution system – exhibiting very different dynamics. The canal lock system’s digital twin uses a recurrent neural network trained from the experimental data collected via the DTF. A digital twin of the transmission system is created using a commercial real-time power systems simulator and integrated into our DTF along with the hardware, embedded controllers, and live sensor data using the Open Field Message Bus data model, and publish/subscribe communication protocols. A cyber attack is used on both systems to demonstrate the DTF’s detection capability.

Organization

Sponsor: Lab Directed Research and Development, Oak Ridge National Laboratory
Period: 2018-2020

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On the Effectiveness of Recurrent Neural Networks for Live Modeling of Cyber-Physical Systems

We empirically study the effectiveness of Recurrent Neural Network (RNN)-based models as the basis of DT-based resilience and uncover the important characteristics of an RNN-based solution with experimentation on a lab-scale Canal Lock CPS emulator with live validations and attack scenarios. For the first time, we demonstrate actual, real-time use of a RNN-based model as a DT for performing live analysis on an operational CPS.

Srikanth Yoginath, Varisara Tansakul, Supriya Chinthavali, Curtis Taylor, Joshua Hambrick, Philip Irminger, Kalyan Perumalla

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A Digital Twin Framework for Testing, Evaluation and Deployment of Resilient Cyber-physical Systems

We describe an approach to detecting and preventing cyber attacks by continuously comparing the infrastructure state with a real-time digital-twin simulation of it. Specifically, we describe and demonstrate a Digital Twin Framework (DTF) designed specifically to detect and eventually prevent such attacks. The canal lock system’s digital twin uses a recurrent neural network trained from the experimental data collected via the DTF.

Raymond Hink, Mark Buckner, Supriya Chinthavali, Chris Craig, Timothy Daniel, Joel Dawson, Milton Ericson, Joshua Hambrick, Philip Irminger, Ryan Kerekes, Juan Lopez, Kalyan Perumalla, Nicholas Peters, Stacy Prowell, Varisara Tansakul, Curtis Taylor, Bailu Xiao, Srikanth Yoginath

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Visualizing the National Energy Grid

Sat, 01 Jan 2022 00:00:00 +0000

EGIVAC, System for Electric Grid Interactive Visualization, Animation, and Control, is one of the ground-breaking, feature-rich, large-scale visualizations of the US national energy grid.

Visualization on the wall

Overview

In 2006-07, developed the first grid visualization system from the ground up, scaling to the full national grid sizes, 100KV to 700KV+.

The system opened up, for the first time ever, the ability to dynamically customize geophysical layers and icons together with grid network buses and lines, shown with accurate latitude and longitude coordinates synchronized with rich geographical layers.

Gallery

Interactive, visual differentiation based on voltage ratings was achieved for the first time at the national scale incorporating large interconnects including ERCOT and Eastern Interconnect.

The capability for the rendering to scale even from smaller personal desktop displays up to the largest, wall-sized multi-monitor systems was achieved for the first time for national energy grids.

Dynamic, interactive animation capabilities provided a natural, visual evaluation of contingencies to decisionmaking teams, with the potential to tie real-time weather data streams with grid state.

Impact

This visualization system went onto inspire large investments by the US Department of Energy and other agencies in grid monitoring centers and the development of next generation systems such as VERDE and EAGLE-I.

My work also featured prominently in the research highlights of the Computational Sciences and Engineering Division across multiple years, and won the laboratory director’s award among all the lab-directed research and development projects in 2007.

Organization

Sponsor: US Department of Energy (DOE)
- Office: Office of Electricity (OE)
Prime: Oak Ridge National Laboratory (ORNL)

Features

EGIVAC is a graphical user interface designed to help electric grid operators to visualize, animate and control the operation of the grid in a highly interactive fashion. The system has been designed with the objectives of interactivity of display/control and of reflecting geographical correspondence of electrical elements. The tool is also intended to serve as an intelligent front-end to control, such as for rapid contingency analysis using parallel/distributed execution of multiple future scenarios.

Visualization

Rendering tuned to minimize clutter at nation-scale display
Color coded buses/lines for high contrast in multitude
Large screen display on Power Wall
Interactive display filters based on voltages (KV)
Population/customer coverage & reach (work in progress)
Hands-off panning
Zoom in/out

Animation

Time-driven animation
Pause/Resume
Interactive slow/fast speed control
Phasor Measurement Units (PMU) animation (planned)
Morphing geographical topology into electrical circuit (series/parallel) (work in progress)
Dynamic graphs of affected operational measures (work in progress)

Control

Visual alert effects (blinking, color changes)
Event impact analysis (e.g., population affected by hurricanes)
Parallel targeted contingency analysis (work in progress)

Resolution

Tested with 45,000 buses and 60,000 lines
Smooth animation (1 to 30 frames per second)

Platform

Java (portable to Mac, Windows, Linux, and other platforms)

Fact Sheet

A Flexible OT Testbed for Evaluating On-Device Implementations of IEC-61850 GOOSE

Fri, 01 Sep 2023 00:00:00 +0000

Open Access:
- Journal: https://www.sciencedirect.com/science/article/pii/S1874548223000318.
- PDF: https://www.sciencedirect.com/science/article/pii/S1874548223000318/pdfft?md5=4606c01cd9fbd3efc0e6b73a074b8910&pid=1-s2.0-S1874548223000318-main.pdf.

Survey of Cybersecurity Governance, Threats, and Countermeasures for the Power Grid

Thu, 20 Oct 2022 00:00:00 +0000

Design of a Novel Information System for Semi-Automated Management of Cybersecurity in Industrial Control Systems

Wed, 22 Jun 2022 00:00:00 +0000

Article is available as Open Access

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

Wed, 15 Jun 2022 00:00:00 +0000

Open Access: https://www.mdpi.com/2624-800X/1/4/31.

DarkNet Cyber Resilience

Tue, 22 Mar 2022 00:00:00 +0000

CyBERT: Cybersecurity Claim Classification by Fine-Tuning the BERT Language Model

Thu, 04 Nov 2021 00:00:00 +0000

Open Access: https://www.mdpi.com/2624-800X/1/4/31.
This article belongs to the Special Issue Machine Learning and Data Analytics for Cyber Security.

A Case Study in Simulation Methods for Power Electronic Circuits

Mon, 19 Jul 2021 00:00:00 +0000

https://ieeexplore.ieee.org/abstract/document/9552085

Trust-but-Verify in Cyber-Physical Systems

Wed, 28 Apr 2021 00:00:00 +0000

https://dl.acm.org/doi/abs/10.1145/3445969.3450434

Smart Semi-Supervised Accumulation of Large Repositories for Industrial Control Systems Device Information

Mon, 01 Feb 2021 00:00:00 +0000

A Novel Vetting Approach to Cybersecurity Verification in Energy Grid Systems

Mon, 13 Jul 2020 00:00:00 +0000

https://www.osti.gov/servlets/purl/1661247

https://ieeexplore.ieee.org/abstract/document/9167562

RL-HEMS: Reinforcement Learning-Based Home Energy Management System for HVAC Energy Optimization (OR-20-C051)

Tue, 04 Feb 2020 00:00:00 +0000

https://ashraem.confex.com/ashraem/w20/meetingapp.cgi/Paper/26352

A Digital Twin Framework for Testing, Evaluation and Deployment of Resilient Cyber-physical Systems

Wed, 01 Jan 2020 00:00:00 +0000

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization.

Wed, 01 Jan 2020 00:00:00 +0000

Design of A High-Fidelity Testing Framework for Secure Electric Grid Control

Wed, 01 Jan 2014 00:00:00 +0000

[Pub 144]

http://wintersim.org

Towards High Performance Discrete Event Simulations of Smart Electric Grids

Sat, 01 Jan 2011 00:00:00 +0000

[Pub 130]

Energy Grid | Kalyan Perumalla

DarkNet Cyber Resilience

Overview

Key Links

Gallery

Organization

Selected Publications

Exascale Computing for the National Energy Grid

Overview

The Problem

The Solution

Organization

Gallery

Related Publications

NAERM

Overview

Contributions

Architecture

Demo Videos

Description

Organization

DES Grid

Overview

Gallery

Approach

Organization

Additional Motivation

Selected Publications

Digital Twin Framework

Overview

Organization

Gallery

Related Publications

Visualizing the National Energy Grid

Overview

Gallery

Impact

Organization

Features

Visualization

Animation

Control

Resolution

Platform

A Flexible OT Testbed for Evaluating On-Device Implementations of IEC-61850 GOOSE

Survey of Cybersecurity Governance, Threats, and Countermeasures for the Power Grid

Design of a Novel Information System for Semi-Automated Management of Cybersecurity in Industrial Control Systems

An Accuracy-Maximization Approach for Claims Classifiers in Document Content Analytics for Cybersecurity

DarkNet Cyber Resilience

CyBERT: Cybersecurity Claim Classification by Fine-Tuning the BERT Language Model

A Case Study in Simulation Methods for Power Electronic Circuits

Trust-but-Verify in Cyber-Physical Systems

Smart Semi-Supervised Accumulation of Large Repositories for Industrial Control Systems Device Information

A Novel Vetting Approach to Cybersecurity Verification in Energy Grid Systems

RL-HEMS: Reinforcement Learning-Based Home Energy Management System for HVAC Energy Optimization (OR-20-C051)

A Digital Twin Framework for Testing, Evaluation and Deployment of Resilient Cyber-physical Systems

RL-HEMS: Reinforcement Learning Based Home Energy Management System for HVAC Energy Optimization.

Design of A High-Fidelity Testing Framework for Secure Electric Grid Control

Towards High Performance Discrete Event Simulations of Smart Electric Grids