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Optimal operation control of hybrid renewable energy systems

Thesis (D. Tech. (Electrical Engineering)) -- Central University of Technology, Free State, 2014 / For a sustainable and clean electricity production in isolated rural areas, renewable energies appear to be the most suitable and usable supply options. Apart from all being renewable and sustainable, each of the renewable energy sources has its specific characteristics and advantages that make it well suited for specific applications and locations.
Solar photovoltaic and wind turbines are well established and are currently the mostly used renewable energy sources for electricity generation in small-scale rural applications. However, for areas in which adequate water resources are available, micro-hydro is the best supply option compared to other renewable resources in terms of cost of energy produced.
Apart from being capital-cost-intensive, the other main disadvantages of the renewable energy technologies are their resource-dependent output powers and their strong reliance on weather and climatic conditions. Therefore, they cannot continuously match the fluctuating load energy requirements each and every time.
Standalone diesel generators, on the other hand, have low initial capital costs and can generate electricity on demand, but their operation and maintenance costs are very high, especially when they run at partial loads. In order for the renewable sources to respond reliably to the load energy requirements, they can be combined in a hybrid energy system with back-up diesel generator and energy storage systems. The most important feature of such a hybrid system is to generate energy at any time by optimally using all available energy sources. The fact that the renewable resources available at a given site are a function of the season of the year implies that the fraction of the energy provided to the load is not constant. This means that for hybrid systems comprising diesel generator, renewable sources and battery storage in their architecture, the renewable energy fraction and the energy storage capacity are projected to have a significant impact on the diesel generator fuel consumption, depending on the complex interaction between the daily variation of renewable resources and the non-linear load demand.
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This was the context on which this research was based, aiming to develop a tool to minimize the daily operation costs of standalone hybrid systems. However, the complexity of this problem is of an extremely high mathematical degree due to the non-linearity of the load demand as well as the non-linearity of the renewable resources profiles. Unlike the algorithms already developed, the objective was to develop a tool that could minimize the diesel generator control variables while maximizing the hydro, wind, solar and battery control variables resulting in saving fuel and operation costs.
An innovative and powerful optimization model was then developed capable of efficiently dealing with these types of problems.
The hybrid system optimal operation control model has been simulated using fmincon interior-point in MATLAB. Using realistic and actual data for several case studies, the developed model has been successfully used to analyse the complex interaction between the daily non-linear load, the non-linear renewable resources as well as the battery dynamic, and their impact on the hybrid system’s daily operation cost minimization.
The model developed, as well as the solver and algorithm used in this work, have low computational requirements for achieving results within a reasonable time, therefore this can be seen as a faster and more accurate optimization tool.

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:cut/oai:ir.cut.ac.za:11462/670
Date January 2014
CreatorsKusakana, Kanzumba
ContributorsH.J. Vermaak, Bloemfontein: Central University of Technology, Free State :Department of Electrical, Electronic and Computer Engineering
PublisherBloemfontein: Central University of Technology, Free State
Source SetsSouth African National ETD Portal
Languageen_US
Detected LanguageEnglish
TypeThesis
Format1 137 358 byte, 1 file, Application/PDF
RightsCentral University of Technology, Free State

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