This Master thesis discusses the possibility of covering electricity consumption in January 2017. The silver line of the thesis is particularly electricity, derived from renewable energy sources. The purpose is therefore to check whether the electricity systems hold data on a large share of electricity generated from renewable energy sources. In the case of January 2017, the purpose is also to show that in the drought months, when water is lacking for hydroelectric power plants, in periods when the wind blows less and in winter, when sun shines less, we can not count on renewable energy sources in any way, as shown in the energy forecasts.
The beginning of the thesis describes diagrams of electricity consumption and production and their general characteristics. The possibilities of covering the daily consumption diagram, which are mostly based on conditions, applying in the Slovenian electricity network, are presented. This is followed by a presentation of theoretical backgrounds of the electricity network stability with a description of three main types: the rotor angle, frequency and voltage stability.
Later on, the analysis within the thesis presents the state of energetics in this years’ first calendar month. For two countries, Slovenia and Germany, it presents the data about rates, contributed by individual production sources to the total energy production and the consumption coverage in January 2017. The discussed month was marked by weather conditions, since the temperature in most of Europe was lower than average, and in addition, there was very little precipitation in January. This was reflected in lower production of renewable energy sources, which consequently means, that the hole in production needed to be covered with conventional sources. To illustrate, how low or high the production of electricity by individual power plants was, the data for January 2017 were compared with the data of January 2016. As part of the analysis of Germany, the problem of inconsistent power of wind and solar plants, which endanger the stability of their own network as well as the networks of neighboring countries, is also presented.
In continuation, the analysis of the model with the software MATPOWER is described. As a starting situation for simulations serves the IEEE New England 39-bus system. The model is further modified, so that we can also include renewable sources, but the total consumption and production in the system change in accordance with the selected daily consumption diagram. We thus simulate different states in the system, which follow the course of the daily consumption diagram, while we also change the power of the included renewable energy sources.
This is followed by the presentation results of the executed simulations, where we observed, how renewable sources affect the changes is the power flow, losses and voltage in individual parts of the network. The starting state with conventional sources is compared to states, when the different power of wind plants is included.
The conclusion provides a commentary and explanation of the obtained results, which proved my previous expectations. So, in January this year, renewable energy sources did not contribute much to covering the consumption of electricity. In cases of Slovenia and Germany, lower production of hydroelectric power plants and wind farms is evident, as a result of poor hydrological conditions and minor overtaking in the current month. In both cases, above-average production was recorded by conventional sources, in particular thermal power plants, which had to cover the resulting hole in the production due to renewable energy sources. The presented results of the simulations also anticipate that the stochastic production of renewable energy sources, consequently causes major changes in power flows and losses on the lines. At the same time, there are also higher voltage fluctuations in individual parts of the system. These are all the changes that the system has to pass or adapt to, and negatively affect to the operation and stability of the entire power system.
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