The objective of this research is to address a pressing need for techniques that control the power outputs of large-scale, grid-interconnected wind farms, so that wind energy may be utilized efficiently, reliably, and economically. The approach is based on a blend of advanced theories in nonlinear control, energy conversion, and power system reliability, which involves theoretical research and algorithm development, including modeling of wind farms for power system operation, seamless control of such farms so that they can operate in both the maximum power tracking and power regulation modes, and analysis of their dynamic power output characteristics.
This project bridges the gap between advanced control theory and power system engineering practice, by providing novel control technologies for enabling integration of large-scale uncertain wind generation into the power system. The research requires state-of-the-art modeling of electric machines, wind turbines, and power system reliability. In addition, the research supports nationwide development in wind energy and addresses a set of theoretical challenges in advanced nonlinear control.
This project promotes national policy on renewable energy, by providing solutions to several defining issues in reliable and economic utilization of wind resources. It also promotes integration of interdisciplinary research with education at state universities. The integration will be realized through incorporation of new topics in traditional energy conversion and power systems courses, field trips to actual wind farms, graduate research mentorship, design of a new graduate course, and involvement of underrepresented groups. The principal investigator is also currently a mentor at two high-school robotics teams.
This project is an undertaking that provides a set of solutions to several fundamental issues on the integration of large-scale uncertain wind generation into the power system. The increasing occurrence of reliability problems and the difficulties in power system operation due to wind power integration have created a pressing need to advance the theory and technology for the management of uncertainties arising from alternative energy resources. In particular, the problem of how to control and operate large-scale wind farms, in order to maximize wind energy utilization without compromising power system reliability, has largely been unexplored. Over the project duration, we have carried out a series of research and education activities. Specifically, we have addressed the problem of controlling variable-speed wind turbines with doubly fed induction generators (DFIG) using a blend of linear and nonlinear control strategies, so that the turbines can operate in both the maximum power tracking and power regulation modes, despite experiencing aerodynamic and mechanical uncertainties. We have developed for this problem a nonlinear dual-mode controller and demonstrated its effectiveness via theoretical analysis and computer simulation using realistic wind profiles from actual wind farms, provided by the OGE Energy Corporation. We have also developed an approximate model of wind turbine control systems, along with a wind farm wind speed model, for use in the design and analysis of wind farm power controllers. In addition, we have studied the impact of control, or lack thereof, on the transient and steady-state bifurcation characteristics of voltage at a bus that receives DFIG-based wind power, as well as the benefit of wind farm kinetic energy release for frequency control purposes. Finally, we have applied model predictive control, adaptive control, and quasilinear control theories to develop a comprehensive wind farm controller, which makes the wind farm power output accurately and smoothly track a desired reference from the power grid operator. Our results have been reported in four journal publications, one journal paper under review, eight conference presentations and publications, and one Ph.D. dissertation. On the education side, the project has supported one postdoc and seven graduate students, including two underrepresented minorities. We have also organized annual field trips for both graduate and undergraduate students to wind farms in Oklahoma, as well as multiple outreach activities including the Annual Frontiers of Power Conference and the Annual Energy Information Dissemination Program. This project has contributed toward realizing the "20% wind by 2020" vision put forth by DOE. Specifically, the project has produced scientific methods for designing sophisticated wind turbine and wind farm controllers, with which wind fluctuations can be optimally managed, so that the active and reactive power outputs of a large-scale wind farm can be either maximized or made sufficiently smooth, whichever is desired by the power grid operator. In addition, the project has produced scientific methods for understanding the behavior of the resulting wind farm, including to what extent can its power outputs be maximized or made smooth. Furthermore, the project has produced a number of engineering models that facilitate contemporary and future research on wind energy control. These methods and models, in turn, provide potentially valuable scientific information for power and utility companies in their planning and operation of wind generation, and regional and national policy-makers in their promotion of alternative and renewable energy.
