Optimal energy control of a grid-connected solar-wind-based electric power plant applying the time of use tariff

dc.contributor.authorPHIRI, SIBONGILE FLORINA
dc.date.accessioned2018-06-13T08:43:12Z
dc.date.available2018-06-13T08:43:12Z
dc.date.issued2016
dc.descriptionPublished Thesisen_US
dc.description.abstractFurther combination of renewable sources is needed for improving grid economical management. Therefore, a good energy management of the hybrid renewable plant is more important to make the system more economically feasible. This study will promote to an optimal operational efficiency of a hybrid renewable energy plant. The initial objective will be minimizing the system operation and maintenance costs. Secondly maximizing the sales of energy to the grid based on the time-of-use tariffs scheme. Both wind and solar have tremendous potential for fulfilling the world’s energy needs. Renewable generation, especially from wind and solar concepts are critical technologies needed to address global warming and related issues. Solar and wind power plants exhibit changing dynamics, nonlinearities, and uncertainties challenges that require advanced control strategies to solve effectively. The use of more efficient control strategies would not only increase the performance of these systems, but would also increase the number of operational hours of solar and wind plants and therefore reduce the cost per kilowatt-hour (KWh) produced. The key challenge is to reduce the cost of renewable energies to reasonably priced levels. Control and related technologies will be necessary for solving these complex problems.en_US
dc.format.extent2 218 446 bytes, 1 file
dc.format.mimetypeApplication/PDF
dc.identifier.urihttp://hdl.handle.net/11462/1372
dc.language.isoen_USen_US
dc.publisherBloemfontein: Central University of Technology, Free Stateen_US
dc.rights.holderCentral University of Technology, Free State
dc.titleOptimal energy control of a grid-connected solar-wind-based electric power plant applying the time of use tariff
dc.typeThesisen_US

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