Thesis
Wind energy systems and effects of large ramping events on regulation and operating reserves in the Washington grid
Washington State University
Master of Science (MS), Washington State University
2010
Handle:
https://hdl.handle.net/2376/100609
Abstract
In this thesis we present planning goals for backup generation capacities in Washington State to ensure renewable energy standards set forth in Initiative 937 (I-937) and regulation reserve, or load-following, requirements established by the North American Electric Reliability Corporation (NERC) can be accomplished. As wind energy in Washington has seen significant growth in recent years, it is considered to be the primary source for renewable generation to meet I-937. Thus, we begin with a discussion of wind energy systems and common controls. A simple mathematical model of a wind turbine is presented and simulated to illustrate their performance. This provides a foundation of how such systems operate and demonstrates why integration into the power system on a large scale can present challenges with meeting regulation and limits imposed on area control error (ACE). Next, we review the potential for wind generation development in Washington State and what has already been addressed in several integration studies performed by Bonneville Power Administration (BPA) and the Northwest Power and Conservation Council (NPCC). Finally, we use a simplified model of the Western Electric Coordination Council (WECC) Interconnection to simulate the performance of Automatic Generation Control (AGC) of the Washington Grid during large wind ramping events. From these simulations, we propose future backup capacity additions in the form of gas turbines to ensure NERC reliability standards and criteria are achieved.
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Details
- Title
- Wind energy systems and effects of large ramping events on regulation and operating reserves in the Washington grid
- Creators
- Timothy Daniel Scheffler
- Contributors
- Anjan Bose (Degree Supervisor)
- Awarding Institution
- Washington State University
- Academic Unit
- Electrical Engineering and Computer Science, School of
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University; [Pullman, Washington] :
- Identifiers
- 99900525033601842
- Language
- English
- Resource Type
- Thesis