webinar series NM SMART Grid Center Student Research Spotlight - - PowerPoint PPT Presentation

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webinar series NM SMART Grid Center Student Research Spotlight - - PowerPoint PPT Presentation

May 29, 2023 14 likes •428 views

webinar series NM SMART Grid Center Student Research Spotlight Presenters: Jeewon Choi (UNM), Jacob Marks (New Mexico Tech), Adnan Bashir (UNM), Shubhasmita Pati & Rusty Nail (NMSU) webinar series Next Webinar CURENT NSF/DOE

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webinar series

NM SMART Grid Center Student Research Spotlight

Presenters: Jeewon Choi (UNM), Jacob Marks (New Mexico Tech), Adnan Bashir (UNM), Shubhasmita Pati & Rusty Nail (NMSU)

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webinar series Next Webinar – CURENT NSF/DOE Engineering Research Center Overview

Presenter: Kevin Tomsovic, Director of CURENT, CTI Professor in the Department of Electrical Engineering & Computer Science at the University of Tennessee

April 22, 2020 Noon–1PM

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The NM SMART Grid Center Overview

Sustainable, Modular, Adaptive, Resilient, Transactive

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NM SMART Grid Center Research Goals

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  • RG1: Create a comprehensive

framework for distribution feeders to evolve into managed distribution feeder microgrids (DFMs)

  • RG2: Design a network architecture for

DFM infrastructure that is scalable, resilient, secure, and protects user privacy

  • RG3: Integrate machine intelligence into

decision making for the DFM

  • RG4: Develop realistic scenarios for
  • peration of DFMs in various stress

conditions

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NM SMART Grid Center Team

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Faculty

34

Graduate Students

57

Undergraduate Students

19

Staff/Other

24

Post Docs

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  • 1. Smart meter privacy issues
  • 2. Privacy preserving solutions
  • 3. What is differential privacy?
  • 4. How can differential privacy be used

in the smart grid?

Differential Privacy in the Smart Grid

Jacob Marks

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What Are The Privacy Concerns?

  • Household occupancy
  • Economic status
  • Appliance usage
  • Even what you’re

watching on TV

Multimedia Content Identification Through Smart Meter Power Usage Profiles

by Ulrich Greveler, Benjamin Justus, Dennis Löhr https://www.semanticscholar.org/paper/Multimedia-Content-Identification-Through-Smart-Greveler-Justus/75b9a34cb6a0268ae7acaad34c7fcdedb450f160

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Two Types of Privacy

Cryptographic Privacy

Sender Receiver Interceptor

Statistical Privacy

Database Data Analyst Legitimate Receiver = Adversary

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Differential Privacy

Goal: It should be very unlikely that an attacker can identify if you are in a dataset. Plausible deniability. VS

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Differential Privacy

Definition: P(A(D1) ∈ S) ≤ e" P(A(D2) ∈ S) “the modification of any single user’s data in the dataset (including its removal or addition) changes the probability of any output only up to a multiplicative factor eε.” (I have a DREAM!)

P : Probability A : Mechanism D1 : Database 1 D2 : Database 2 S : ⊆ Range(A) " : Privacy budget

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Differential Privacy

Laplacian mechanism Added noise maintains differential privacy. However your data is now less good.

“Laplace distribution,” Wikipedia. 20-Mar-2020, Accessed: 24-Mar-2020. [Online]. Available: https://en.wikipedia.org/w/index.php?title=Laplace_distribution&oldid=946537954.

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Differential Privacy

I Have a DREAM! (DiffeRentially privatE smArt Metering)

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Problems?

  • Will data be accurate enough for use?
  • Who will be trusted with the original data?
  • Speed
  • Accuracy
  • Privacy
  • Out of all DP solutions which are best?
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Conclusion

  • There are many privacy concerns associated

with smart meters

  • Cryptographic or statistical solutions could be

used

  • Differential privacy is especially promising
  • Need more data on which differential privacy

solutions work best

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References

  • R. Lu, X. Liang, X. Li, X. Lin, and X. Shen, “EPPA: An Efficient and Privacy-Preserving Aggregation

Scheme for Secure Smart Grid Communications,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 9, pp. 1621–1631, Sep. 2012. Clement, Jana & Ploennigs, Joern & Kabitzsch, Klaus. (2013). Detecting Activities of Daily Living with Smart Meters. 10.1007/978-3-642-37988-8_10.

  • G. Ács and C. Castelluccia, “I Have a DREAM! (DiffeRentially privatE smArt Metering),” in Information

Hiding, Berlin, Heidelberg, 2011, pp. 118–132.

  • S. Thorve, L. Kotut, and M. Semaan, “Privacy Preserving Smart Meter Data,” p. 5, 2018.
  • M. R. Asghar, G. Dán, D. Miorandi, and I. Chlamtac, “Smart Meter Data Privacy: A Survey,” IEEE

Communications Surveys Tutorials, vol. 19, no. 4, pp. 2820–2835, Fourthquarter 2017.

  • C. Dwork and A. Roth, “The Algorithmic Foundations of Differential Privacy,” FNT in Theoretical

Computer Science, vol. 9, no. 3–4, pp. 211–407, 2013.

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Conclusion

  • There are many privacy concerns associated

with smart meters

  • Cryptographic or statistical solutions could be

used

  • Differential privacy is especially promising
  • Need more data on which differential privacy

solutions work best

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Smart Grid Data Generation

Presenter: Adnan Bashir Advisor: Trilce P. Estrada

March 25, 2020

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  • 1. Smart grid is still in evolution phase
  • 2. Researchers don’t often share their data
  • 3. A lot of data needed to incorporate decision support
  • 4. Mathematical modeling can be put to a good use

Why synthesize smart grid data ?

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  • 1. Generative Adversarial Networks
  • We still need real data to generate new data
  • 1. Mosaik
  • Combines simulators and models
  • 1. MATPOWER
  • Steady-state power system simulation
  • 1. PYPOWER
  • Power flow and Optimal Power Flow solver

What are available tools ?

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  • 1. Open-source power simulation and optimization
  • 2. Runs on MATLAB & GNU
  • 3. > 4000 citations since 2010
  • 4. > 22,000 downloads / year

Image Source: Google Scholar

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in action

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CKAN Data Repository

DEMO by Adnan Bashir

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Power System Resiliency

Shubhasmita Pati & Rusty Nail

Graduate Students Klipsch School Of Electrical & Computer Engineering

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Resilience

  • [1] D. E. Alexander, “Resilience and disaster risk reduction: an etymological journey,”Natural hazards and earth system sciences,
  • vol. 13, no. 11, pp.2707–2716, 2013.
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Resilience VS Reliability

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Research Challenge

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Applying Resiliency and Contingency Planning

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Applying Resiliency and Contingency Planning

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Recognizing the Realities

  • f Resiliency
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Future directions

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Contact Information

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Q&A

Use Zoom Q&A Feature!

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webinar series Next Webinar – CURENT NSF/DOE Engineering Research Center Overview

Presenter: Kevin Tomsovic, Director of CURENT, CTI Professor in the Department of Electrical Engineering & Computer Science at the University of Tennessee

April 22, 2020 Noon–1PM