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Predictive Control of Power Electronics Converters in Renewable Energy Systems

doi: 10.3390/en10040515
handle: 10397/68340
Predictive control has attracted much attention and has been widely used in power electronics and electric drives. However, further developments for applications in the field of renewable energy systems are still under investigation. In this paper, the principles of predictive control are studied with a focus on model predictive control (MPC) and vector-sequence-based predictive control (VPC). Based on these techniques, two control strategies for flexible power supply are developed. They are implemented in the most promising renewable energy systems, namely solar photovoltaic (PV) systems and wind generators, respectively. The experimental results based on a laboratory prototype show that the active and reactive powers supplied by the PV and wind generator can be controlled flexibly with excellent steady-state and transient performance. As the penetration level of the renewable energy sources in electricity network continues to rise, predictive control tends to be an attractive and powerful technique for power electronics converters in renewable energy systems.
- Hong Kong Polytechnic University China (People's Republic of)
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
- Hong Kong Polytechnic University (香港理工大學) Hong Kong
- Hong Kong Polytechnic University (香港理工大學) China (People's Republic of)
- Hong Kong Polytechnic University (香港理工大學) Hong Kong
Renewable energy, Power converters, predictive control; power converters; renewable energy; distributed generation, Predictive control, Distributed generation
Renewable energy, Power converters, predictive control; power converters; renewable energy; distributed generation, Predictive control, Distributed generation
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).23 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
