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Smart Grid REsiliency and Analytics Lab

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SG-REAL (Smart Grid Resiliency and Analytics Lab)

Research Goals

Develop cybersecure and resilient power system operation and control algorithms utilizing smart grid data and real time validation of these developed
algorithms.
 
 
 
 
 

Teaching Goals

Smart grid education targeted towards middle school, high school, undergraduate and graduate students using hardware-in-the-loop demonstration of smart grid devices and operations.
 
 
 
 
 

Motivation

The electric power system is moving towards the Smart Grid (SG) development for improved reliable, secure, resilient, and economic operation. Implementation of such a system requires development, enhanced testing, and validation of smart grid technologies. The Objective of SG-REAL is focused on development and validation of power system operation and control algorithms.

RESEARCH INTERESTS AND GRANTS

The research goal of SG-REAL is developing ‘Power System Operation and Control’ algorithms in the context of the evolving smart grid. Availability of the smart grid data such as synchrophasor data, smart meter data, distribution automation data, cyber logs provide opportunities for better control and optimization algorithms for power system operation and control precisely towards resiliency. The approach developed by my research group includes physics-driven machine learning for power grid operation and control. My existing research projects with external and internal collaborators relate to the following.

Power System Operation and Control

Data-Driven Computational Algorithms to enable security, resiliency, sustainability and voltage stability of the power grid (Transmission Systems with Microgrid and Active Distribution Systems)

Real-Time, Multi-Layer Cyber–Power Testbed for Resiliency Analysis

Real-Time Modeling and Analysis of Cyber-Power Systems for quality-aware synchrophasor applications and resiliency analysis

Industrial Grade Tools

Industry-grade tool development for electric grid resiliency, smart grid data analytics

List of Existing Research Projects

 

WVU Project

 

  1. Lead-PI, Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency, NSF, $1.378M (Total: $2.01M) (08/18-08/23)
  2. Lead-PI, CPS: DFG Joint: Medium: Collaborative Research: Data-Driven Secure Holonic control and Optimization for the Networked CPS (aDaptioN), NSF/ DFG, $810K (01/20-12/22)
  3. WVU PI, Efficient UltRa Endpoint IoT-enabled Coordinated Architecture (EUREICA), DOE, $279K (07/20-06/23)
  4. Co-Lead PI, UI-ASSIST: US-India collAborative for smart diStribution System wIthSTorage, DOE/DST/Washington State University, $1.5M (Total: $39M) (09/17-09/22)
  5. WVU PI, SolarSTARTS: Solar-Assisted State-Aware and ResilienT infrastructure System, DOE/ University of Utah, $450,000 (Total: $3.5M) (01/20-12/22)

 

WSU Project

 

  1. Co-PI, Grid Ready Energy Analytics Training with Data, DOE/ Electric Power Research Institute, $244K (04/19-03/24)
  2. WSU PI, Tools for keeping your power ON during extreme events, WSU OC Commercialization Gap Funding (CGF), $37,948 (01/21-12/21)
  3. WSU PI, Data-driven Control of DERs & Hybrid PV Plants for Enhancing Voltage Stability Over Multiple Timescales, NSF I/UCRC PSERC, $220K (07/21-07/23)
  4. WSU PI, Federated Predictive Analysis For Power Grid Using Multi Agent Models, PNNL DGRP, $103,562 (01/21-12/22)

 

Previous Research Project

 

  1. WSU PI, AGI Grid SandBox, Pacific Northwest National Lab, $190,000 (08/19-09/21)
  2. WSU PI, NOMARS, Siemens / DARPA, $45,000 (12/20-03/21)
  3. Lead-PI, AGGREGATE: dAta-driven modelinGpreservinGcontRollabledErfor outaGemAnagemenT and rEsiliency, DOE, $900K (Total: $2.29M) (10/17-06/21)
  4. WSU PI, Resilient Alaskan Distribution system Improvements using Automation, Network analysis, Control, and Energy storage (RADIANCE), INL/DOE, $400K (Total: $6.2M) (11/17-12/20)
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PUBLICATIONS

Resiliency of Power Distribution Systems

Resiliency of Power Distribution Systems: Concepts, Implementation and Management

Cyber Infrastructure for the Smart Electric Grid

This book provides a comprehensive overview of fundamental principles of smart grid operation and control. It describes smart grid technologies including sensors, communication networks, computation, data management, and cyber security.

Real-time Synchrophasor Data Anomaly Detection and Classification using Isolation Forest, KMeans and LoOP

Power grid operators assess situational awareness using time-tagged measurements from phasor measurement units (PMUs) placed at multiple locations in a network.

CP-TRAM: Cyber-Physical Transmission Resiliency Assessment Metric

Natural disasters and cyber intrusions threaten the normal operation of the critical electric grid infrastructure. There is still no widely accepted methodology to quantify the resilience in power systems. In this work, power system resiliency refers to the ability of the system to keep provide ener
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RESEARCH GROUP

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Dr Anurag K Srivastava

Director

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Dr. Subir Majumder

Engineering Scientist

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Dr. Sagnik Basumallik

Engineering Scientist

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Partha Sarathi Sarker

Ph.D. Student

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Mohammed M. Hussain

Ph.D. Student

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NEWS

April 20, 2022

 

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Dr. Srivastava to give webinar at MIT LIDS/ EESG

The talk focuses on real time physics-aware data analytics to enhance situational awareness and decision support for enabling operational resiliency of the power grid and associated challenges and opportunities.

March 9, 2022

 

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Partha Sarker, Graduate student in SG-REAL won the first-place award in LCSEE graduate student poster presentations

Poster title: Metrics and tools for measuring cyber-physical resiliency of electric grids.

January 12, 2022

 

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Dr. Srivastava to give IEEE PES talk on distributed optimization for power grid, January 2022

The talk focuses on algorithms for distributed optimization, classification, use cases, and discusses current limitations and future research needs.
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  • Dr. Anurag K Srivastava,
    Raymond J. Lane Professor and Chairperson Lane Department of Computer Science and Electrical Engineering AERB 363B,
    1220 Evansdale Drive, PO Box 6109 West Virginia University,
    Morgantown, WV 26506

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