The master thesis deals with the issue of optimizing electric energy consumption using a battery storage system at the end users. The thesis researches and presents in detail the battery storage system, which, as an active element for optimized electric energy consumption, operates in parallel with the electric power system and a renewable source of electric energy, in this case a solar power plant. A system like this enables optimized electric energy consumption and thus relieves the electric power system during the time when it is most loaded, while at the same time reducing operating costs. The goal is to acquire and accumulate the knowledge necessary for the development of such system from a technical point of view and to build a simulation model, with which it is possible to test, simulate and analyse the operation of such system or to serve as an aid in dimensioning of such system in reality.
In the first part of the thesis, we focus on the theoretical side of the system and an in-depth technical description of each key component that such systems contain. Various technologies that can be used in such systems are presented and it is elaborated which technologies are most suitable for the aforementioned issue. It gathers all the necessary theoretical knowledge that allows us to create a simulation model.
In the second part of the thesis, the simulation model which was developed in the Matlab programming environment with the Simulink simulation tool is described and presented in detail, using the knowledge gained from the theoretical part. The operation of each component in the simulation model is precisely elaborated and described.
In the last part of the thesis, there is a detailed analysis of the results that we obtained using the simulation model. The results contain an analysis of measurements in the warmest month of the year, when running costs of the building are the lowest and the presence of solar energy is the highest, and in the coldest month, when running costs are the highest and the presence of solar energy is the lowest.
We have come to certain conclusions that contribute to understanding the issues of developing such systems and the problems that may appear in their development. From the analysis of the results, we can conclude that the consumption from the grid decreases on average, especially during the time when consumption is the highest and the network is the most loaded. This can consequently reduce the predetermined connected power of consumers on the network, which allows the electric power system to be freed up for new consumers, without major investments in expanding the electric power system infrastructure. During the analysis, we also identified some suggestions for improvements, especially with the optimization of the entire system with the energy management system or EMS, which could further optimize energy consumption and thus the efficiency of the system with the help of larger amounts of data and more complex predictive models, machine learning and artificial intelligence. In addition, with appropriate sizing of the battery storage and solar power plant, we could further optimize the operation of the entire system and thus increase efficiency. Nevertheless, this work represents a good basis for understanding, developing and improving such systems, which represent added value in pursuing the goals of a sustainable energy future.
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