A review on state of art development of model predictive control for renewable energy applicationsW. Razia Sultana, Sarat Kumar Sahoo, Sukruedee Sukchai, S. Yamuna and D. Venkatesh Renewable and Sustainable Energy Reviews, 2017, vol. 76, issue C, 391-406 Abstract: Renewable energy sector is undergoing rapid expansion as the global focus is shifting towards cleaner, reliable and sustainable resources. As the new installation of these resources are well underway, there is tremendous potential for exploring these to more advanced control algorithms. Model predictive control is gaining immense popularity because of its flexible controllability, its ability to be used in any of application irrespective of its field as well as the availability of fast processors. This paper presents a systematic review on Photo-voltaic (PV) and wind energy systems controlled by Model predictive control approach. The work presented here will help the researchers to further explore the flexibility of this controller for design, analysis and implementation in renewable energy systems. Keywords: Model predictive control; Photovoltaic systems; Wind energy systems; Grid connected systems; Stand-alone applications (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:rensus:v:76:y:2017:i:c:p:391-406 Ordering information: This journal article can be ordered from DOI: 10.1016/j.rser.2017.03.058 Access Statistics for this article Renewable and Sustainable Energy Reviews is currently edited by L. Kazmerski More articles in Renewable and Sustainable Energy Reviews from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.