Conference proceeding
Optimization of power and its variability with an artificial immune network algorithm
2011 IEEE/PES Power Systems Conference and Exposition, pp.1-8
03/2011
DOI: 10.1109/PSCE.2011.5772600
Abstract
A bi-objective optimization model of power and power changes generated by a wind turbine is discussed in this paper. The model involves two objectives, power maximization and power ramp rate (PRR) minimization. A new constraint for power maximization based on physics and process control theory is introduced. Data-mining algorithms were used to identify the model of power generation from the industrial data collected at a wind farm. The models and constraints derived from the data were integrated to optimize the power itself and the power variability, expressed as the power ramp rate. Due to the nonlinearity and complexity of the optimization model, an artificial immune network algorithm was used to solve it. The optimization results, such as computed operation strategies and the corresponding outputs, are demonstrated and discussed.
Details
- Title: Subtitle
- Optimization of power and its variability with an artificial immune network algorithm
- Creators
- Andrew Kusiak - University of IowaZijun Zhang - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- 2011 IEEE/PES Power Systems Conference and Exposition, pp.1-8
- DOI
- 10.1109/PSCE.2011.5772600
- Publisher
- IEEE
- Language
- English
- Date published
- 03/2011
- Academic Unit
- Industrial and Systems Engineering; Nursing
- Record Identifier
- 9984187073002771
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