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Development of Intelligent Energy Management System Using Natural Computing

Yang, Cheng
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203

Abstract Details

2012, Master of Science in Engineering, University of Toledo, College of Engineering.
In this thesis an Intelligent Energy Management System (EMS) for end consumer has been proposed. This system develops an algorithm for smart meter which is integrated between distribution grid and end consumers. The smart meter determines when to draw the energy from the grid or the storage unit for consumption. The first objective of the intelligent EMS is to save the cost for consumers by shifting the power drawn from the grid from high cost period to low cost period. The second objective of the intelligent EMS is to avoid grid overload by shifting the power drawn from the grid from high demand period to low demand period. The algorithm takes into consideration the hourly price and load demand of the grid. The algorithm was tested with the real data collected by ISO New England for the six states of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island and Vermont, during the period of Jan 1, 2011 to Dec 31, 2011. Two approaches based on Fuzzy Logic and Genetic Algorithm (GA) were used. It was demonstrated the GA based approach outperformed the Fuzzy Logic based approach. The intelligent approach based on GA resulted in more cost saving as compared to what was theoretically foreseen and predicted.
Dr. Devinder Kaur, PhD (Committee Chair)
Dr. Ezzatollah Salari, PhD (Committee Member)
Dr. Mansoor Alam, PhD (Committee Member)
Computer Engineering; Computer Science; Electrical Engineering; Energy; Engineering
smart grid; energy management system; smart meter; fuzzy logic; genetic algorithm

Recommended Citations

Citations

  • Yang, C. (2012). Development of Intelligent Energy Management System Using Natural Computing [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203

    APA Style (7th edition)

  • Yang, Cheng. Development of Intelligent Energy Management System Using Natural Computing. 2012. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203.

    MLA Style (8th edition)

  • Yang, Cheng. "Development of Intelligent Energy Management System Using Natural Computing." Master's thesis, University of Toledo, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1341375203

    Chicago Manual of Style (17th edition)

toledo1341375203
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© 2012, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.