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Finite Control Set Model Predictive Control for Complex Energy System with Large-Scale Wind Power
- Source :
- Shen, Y W, Yuan, J R, Shen, F F, Xu, J Z, Li, C K & Wang, D 2019, ' Finite Control Set Model Predictive Control for Complex Energy System with Large-Scale Wind Power ', Complexity, vol. 2019, 4358958 . https://doi.org/10.1155/2019/4358958, Complexity, Vol 2019 (2019)
- Publication Year :
- 2019
- Publisher :
- Hindawi, 2019.
-
Abstract
- Complex energy systems can effectively integrate renewable energy sources such as wind and solar power into the information network and coordinate the operation of renewable energy sources to ensure its reliability. In the voltage source converter-based high voltage direct current system, the traditional vector control strategy faces some challenges, such as difficulty in PI parameters tuning and multiobjective optimizations. To overcome these issues, a finite control set model predictive control-based advanced control strategy is proposed. Based on the discrete mathematical model of the grid-side voltage source converter, the proposed strategy optimizes a value function with errors of current magnitudes to predict switching status of the grid-side converter. Moreover, the abilities of the system in resisting disturbances and fault recovery are enhanced by compensating delay and introducing weight coefficients. The complex energy system in which the wind power is delivered by the voltage source converter-based high voltage direct current system is modeled by Simulink and simulation results show that the proposed strategy is superior to the tradition PI control strategy under various situations, such as wind power fluctuation and fault occurrences.
- Subjects :
- Multidisciplinary
Wind power
General Computer Science
Scale (ratio)
Article Subject
business.industry
Complex energy
020209 energy
020208 electrical & electronic engineering
Finite control set
02 engineering and technology
lcsh:QA75.5-76.95
Renewable energy
Model predictive control
0202 electrical engineering, electronic engineering, information engineering
Environmental science
lcsh:Electronic computers. Computer science
SDG 7 - Affordable and Clean Energy
Aerospace engineering
business
Solar power
Subjects
Details
- Language :
- English
- ISSN :
- 10762787
- Database :
- OpenAIRE
- Journal :
- Complexity
- Accession number :
- edsair.doi.dedup.....efdac9cf02cd399b8961d7d041ea1e09
- Full Text :
- https://doi.org/10.1155/2019/4358958