Masters Theses


"With development in wind turbine technology, wind energy has become an important contestant in the utility market. However, wind energy has the intrinsic property of variations which causes fluctuations in the power grid.

Plug-in electric vehicles are drawing the attention of researchers and the electric power industry because of its need for charging from the grid and its ability to store energy. With increase in the numbers of plug-in electric vehicles, there will be significant penetration of distributed energy resources and hence plug-in electric vehicles connected to the grid in parking lots (SmartParks) can be used as energy storage sink or source devices in order to function as shock absorbers in a smart grid.

The objective of this thesis is threefold, namely:

  • Tuning approach for development of optimal proportional integral controllers for a doubly fed induction generator based wind farm is presented. The tuning is carried out online at various wind speed conditions using a recently introduced heuristic optimization technique called the mean variance optimization (MVO).
  • A fuzzy logic coordinating controller for wind farms and SmartParks is presented to improve the performance during grid faults at different locations in a smart grid. The parameters of the fuzzy logic controller are optimized to enhance performance.
  • An adaptive critic design (ACD) based optimal controller design is developed to dispatch the SmartPark charge/discharge power commands based on forecasted wind power fluctuations. This facilitates effective and continuous utilization of SmartParks to mitigate power fluctuations while maintaining an optimal state of charge (SOC) at the SmartParks"--Abstract, page iv.


Venayagamoorthy, Ganesh K.

Committee Member(s)

Corzine, Keith, 1968-
Kimball, Jonathan W.


Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering


National Science Foundation (U.S.)
Missouri University of Science and Technology. Real-Time Power and Intelligent Systems Laboratory


Financial support provided by Real-Time Power and Intelligent Systems (RTPIS) Laboratory and the National Science Foundation (NSF) (CAREER ECCS # 0348221, GO ALI ECCS #080204 7 and EFRI # 08360 17)


Missouri University of Science and Technology

Publication Date


Journal article titles appearing in thesis/dissertation

  • Development of optimal controllers for DFIG based wind farm in a smart grid under variable wind speed conditions
  • Optimal controllers for improved transient stability in a smart grid
  • Mitigation of power fluctuations in transmission lines connected to a wind farm-energy storage bus


xii, 83 pages

Note about bibliography

Includes bibliographical references.


© 2011 Priyam Chakravarty, All rights reserved.

Document Type

Thesis - Open Access

File Type




Subject Headings

Smart power grids
Intelligent control systems
Wind power plants
Parking lots
Electric vehicles

Thesis Number

T 10254

Print OCLC #


Electronic OCLC #