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Towards Efficient and Effective Smart Grid Control

By Michael Aiudi
Slide 1: Title slide for presentation on efficient and effective smart grid control by Michael Aiudi

Slide-1

Michael Aiudi

Ocean Engineering Student

University of Rhode Island Rising Senior

I-SENSE REU Final Presentation

08/04/17

Less CO2 emissions and a more reliably power system

Slide 2: Outline slide showing presentation structure with background information, methods, simulation results, and conclusion

Slide-2

Outline

  • Background Information
  • Method: PSO + Grid Search
  • Simulation and Results
  • Conclusion
Slide 3: Background information on smart grid definition and benefits including cost reduction and improved coordination

Slide-3

Background of Smart Grid

What is a Smart grid

"… an electricity supply network that uses digital communications technology to detect and react to local changes in usage…"

Why do we need it

Decrease cost, waste, and response time:

  • Easier add distributed generation and storage
  • Coordination and Communication
  • Detect errors
Slide 4: Smart grid optimization challenges including uncontrolled production and demand, and the need for smarter controllers

Slide-4

Challenges of Smart grid Optimization

  • Uncontrolled production and demand
  • New generation sources need to be able to be introduced easily
  • Transient surges of power

Need for smarter controllers

Slide 5: Introduction to Particle Swarm Optimization as a search method based on bird flocking behavior

Slide-5

What is: Particle Swarm Optimization

  • A way of searching for an optimal point
  • Originally based on a flock of birds
  • Searches for best "food" location through communication

5/14

Slide 6: Mathematical explanation of how Particle Swarm Optimization works with velocity and position update equations

Slide-6

How: Particle Swarm Optimization

Starts randomly and compares particles location to personal and global best

Moves toward best location at partially-random velocity, overshoots, repeats

Vi t+1 = W*Vi t + c1 * rand * (Pbest - xi t) + c2 * rand * (Gbest - xi t)

xi t+1 = xi t + Vi t+1

Slide 7: Smart grid simulation model diagram showing home loads, solar panels, generators and controllers

Slide-7

Smart Grid Simulation Model

Home Load, Cloud Shading and Solar Panels, Generator, Controllers…

Slide 8: Comparison between simplified and realistic models showing load patterns with and without distributed generation noise

Slide-8

Simplified vs Realistic Models

Simple:

Load put on the system

Realistic:

Load put on the system, with the noise from distributed generation

Slide 9: PSO fitness vs. iteration

Slide-9

PSO fitness vs. iteration

Two graphs are shown comparing the fitness performance over iterations:

Simplified Model

Graph showing fitness improvement over iterations for the simplified model.

Realistic Model

Graph showing fitness improvement over iterations for the realistic model with distributed generation noise.

Slide 10: Performance comparison table showing PSO is 26 times faster than Grid Search for simplified model

Slide-10

PSO vs Grid Search: Simplified Model

Grid Search: 525.5 min

PSO: 20.9 min (Over 26 times faster)

Time (min) P I Fitness
PSO 20.86 27.287 3.5184 96.098
Grid Search 525.5 27.3 3.5 96.1185
Slide 11: Performance comparison table showing PSO is 23 times faster than Grid Search for realistic model

Slide-11

PSO vs Grid Search: Realistic

Grid Search: 487.7 min

PSO: 21.1 min (23 times faster)

Time (min) P I Fitness
PSO 21.12 22.019 2.152 710.83
Grid Search 487.72 22 2.15 710.91
Slide 12: Conclusion summarizing smart grid as the future with PSO helping address frequency fluctuation challenges

Slide-12

Conclusion

  • Smart grid is the future of power systems
  • It brings new challenges, such as frequency fluctuations
  • Smart controllers can deal with these challenges through use of Particle Swarm Optimization
Slide 13: Acknowledgments slide thanking NSF, I-SENSE, FAU, professors and colleagues

Slide-13

Acknowledgments

National Science Foundation

I-SENSE

Â鶹¾«Æ·ÊÓƵ

Prof. Jason Hallstrom

Prof. Yufei Tang

Andrea Gonzalez and Mary Jo Jackson

The rest of the I-SENSE faculty, staff, and students

Slide 14: References slide with multiple IEEE and web sources used in the presentation

Slide-14

References

  • http://ieeexplore.ieee.org/document/5762913/
  • http://ieeexplore.ieee.org/document/6563367/
  • https://gradeup.co/p-pi-and-pid-controllers-i-ba51cc88-c453-11e5-8e45-0f580d23b1d8
  • http://www.eesi.org/briefings/view/smart-grid-how-does-it-work-and-why-do-we-need-it
  • http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=488968
  • https://www.google.com/search?q=florida+atlantic+university&rlz=1C1GGRV_enUS751US751&source=lnms&tbm=isch&sa=X&ved=0ahUKEwiMtLHSz7PVAhWCRCYKHVccCoYQ_AUIDCgD&biw=1920&bih=974#imgrc=LQqdZKYOMzkkWM
  • https://www.google.com/search?q=university+of+rhode+island&rlz=1C1GGRV_enUS751US751&source=lnms&tbm=isch&sa=X&ved=0ahUKEwjW1IuP0LPVAhXK5yYKHZdiA8EQ_AUICygC&biw=1920&bih=974#imgrc=5SKso2reApAgzM
  • https://www.google.com/search?q=smartgrid&rlz=1C1GGRV_enUS751US751&source=lnms&tbm=isch&sa=X&ved=0ahUKEwio-oya8bbVAhUGySYKHe6mBNUQ_AUICygC&biw=1745&bih=885#imgrc=eW24-XM-cGXDzM
  • https://www.google.com/search?q=what+is+a+smart+grid&rlz=1C1GGRV_enUS751US751&source=lnms&tbm=isch&sa=X&ved=0ahUKEwjx6ruk6LbVAhVBRyYKHboVDUwQ_AUIDCgD&biw=1745&bih=885#imgrc=Hfl--1BE1afn4M
  • https://www.google.com/search?q=pso+birds&rlz=1C1GGRV_enUS751US751&source=lnms&tbm=isch&sa=X&ved=0ahUKEwiUzoK57vTUAhUFNT4KHekyALkQ_AUICygC&biw=1920&bih=925#tbm=isch&q=bird+flock+and+school+of+fish&imgrc=goppaTBw5hs8iM
  • https://www.google.com/search?q=particle+swarm+optimization&rlz=1C1GGRV_enUS751US751&tbm=isch&source=lnms&sa=X&ved=0ahUKEwiYieWm7fTUAhUPET4KHWnZDn4Q_AUICCgD&biw=1920&bih=925#imgrc=uRrIlg0-kR7srM
  • https://www.google.com/search?q=particle+swarm+optimization&rlz=1C1GGRV_enUS751US751&tbm=isch&source=lnms&sa=X&ved=0ahUKEwiYieWm7fTUAhUPET4KHWnZDn4Q_AUICCgD&biw=1920&bih=974#imgrc=kCRSZSu86QgB9M
  • https://www.google.com/search?rlz=1C1GGRV_enUS751US751&biw=1745&bih=841&tbm=isch&sa=1&q=I+SENSE+fau&oq=I+SENSE+fau&gs_l=psy-ab.3...5042.6577.0.6992.4.4.0.0.0.0.66.233.4.4.0....0...1.1.64.psy-ab..0.2.118...0j0i8i30k1.yCAolKklOoY#imgrc=bWcbSAuAaaEVDM
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For a downloadable version of this presentation, email: I-SENSE@FAU.