Ing. Jan Votava

The system presented in this study aims to manage and connect microgrid solar energy systems to the public grid and include them within the generation system in an effective and stable manner. This system can be applied to microgrids that are in operation or under study based on the Internet of Things, with the availability of different operating modes (DYN - DYN with load selection - ECO - ECO with load selection ) that are easy to navigate between according to the load required to be fed. The presented ECO mode is characterized by using weather-related conditions to improve financial savings by increasing the contribution to the peak load. The presented management system and its effectiveness were tested by a software code designed for this purpose using MATLAB, taking into account the extreme cases of weather fluctuations due to climate change by generating inputs based on data enrichment using artificial intelligence for one year (derived from the results of a 10-day simulation) that include constraints to generate these parameters and the relationship between these constraints. The management system decides the main source of electrical energy to supply loads, charge the battery, and sell or buy energy from the grid according to a set of criteria and according to the specified operating mode. The comparison results in ECO mode showed that the average percentage of battery participation in the maximum load was 14.5%, which increased to 31.8% when weather restrictions were added. The improved ECO mode also achieved an additional 17% saving compared to DYN mode. In addition to reducing the maximum load by increasing battery participation in this load, which contributes to the stability of the electrical network.

This work deals with the creation of a control model for a system with CHP units, heat pump and energy storage. By simulating such system, it can be designed and optimized for primary energy consumption and investment. The model also enables extrapolation of the monitored quantities from energy consumption over a known period of time.

This paper analyzes the accuracy of the calculation of the energy needed for the heating of residential buildings by heat pumps. The reference value is the consumption obtained from the actual time course of temperature and the heat loss calculated by solving the partial differential equations. This value is compared with the results obtained using average daily and monthly temperatures and using a static wall model without heat capacity. The calculations are performed for the Carnot heat pump and for the currently used WPL18 heat pump.

Further improvement of FACTS (Flexible Alternating Current Transmission System) control can help to increase the transient stability of a power system without adding extra grid inertia. Sophisticated optimization algorithms and modern Computer Algebra Systems provide new means of controller synthesis for power systems. The paper presents an approach of enhancement of transient stability using FACTS devices, particularly STATCOM (Static Synchronous Compensators), combined with optimization. Furthermore, chapter 3 describes different ways of defining the objective function. Different approaches are compared using the case study model that was implemented in MATLAB/Simulink.

This paper presents technical analysis of the usage of steam accumulator in the combined heat and power production and also in all general steam production. Created mathematical model is possible to use for evening on wanted slope of steam flow change.

This paper deals with the possibility of energy consumption measurement using numerical integration. In this paper is described method based on Simpson integration and its comparison with standard analytical method of evaluating of energy consumption. The result of this article is a comparison of the error of energy of the analytical and numerical methods, depending on the number of samples required.

This paper presents a mathematical model that is developed to economically optimize a small and a medium-sized local cogeneration system. This model was developed to find the economically optimal configuration of the cogeneration system with respect to state aid, which forms a significant part of the revenue for small and medium-sized systems. The model respects the production of heat, so it won't be exceeded the economically justifiable demand, which means that the same amount of heat will be produced as in the supply of heat through conventional sources, which is essential for obtaining the aid. Therefore, the model is suitable for use in the design of cogeneration systems with average seasonal heat demand up to 5 MW. These are typical hospitals, hotels, office buildings and small factories. The model can design an accumulation tanks and a bivalent heat source to cover the maximum and minimum peaks in heat requirements, it also respects the thermal losses of buildings and climatic data in the given location. It is also possible to design a system for the preparation of hot water during the summer months.