Management and Control of Distributed Energy Generation Systems Via Artificial Intelligence Techniques

摘要

For the past twenty years, the world has been suffering from global warming and climate crisis. Although technology develops rapidly such as burning fossil fuels to generate energy, existing resources fade conversely as well as lots of greenhouse gases are released into the atmosphere. On the other hand, developing countries e.g., Turkey is among the countries largely dependent on energy imports. This dependency has increased interest in new and alternative energy sources. Thus, the concept of renewable energy sources (RESs) has gained quite good importance. As a result of that, the industry of RESs and its application areas have developed and received much attention over the last two decades. The development of renewable-based distributed generation (DG) systems such as solar, wind, and biomass, etc., has become more prevalent year by year. To enable more widescale exploitation of RESs in microgrids, DGs have gained prominence recently. Thereby, direct current (DC) microgrids including DGs are preferred in the field of renewable energy. Small scaled DC microgrids aim to provide smooth power flow from renewables to the load side instantaneously. Due to the intermittent nature of renewables which have variances of solar irradiance, temperature, and wind speed, etc., as a source, the problem of maximum power attaining arises. The solution to this problem aims to make optimal utilization and operation of distributed energy generation systems. To solve this problem, it is aimed to utilize distributed energy generation systems in an optimal way.In this thesis study, the design, modeling, implementation, and operation of a microgrid have been described, in which a standalone hybrid power system has been installed for an education and research laboratory. To satisfy defined load profiles and sustain the desired power level, the design, operation, and control of power converters are a remarkable part of performing microgrids as well. To ascend the resilience of DC microgrids, battery storage systems (BSSs) are also used as backup units for supplying uninterrupted power. The main task of BSSs is to compensate for the lack of power when the load is higher than supplied power or store the surplus of power in case that the load demand is less than the extracted power. In other words, by draining and storing the power, BSSs help to increase the flexibility of the system and keep the main DC bus voltage within acceptable bounds. For a robust DC microgrid structure, the presented control algorithm includes an energy management system (EMS) between renewables, batteries, and loads. The modeling of the general system has been developed in the MATLAB/Simulink environment. Additionally, case studies have been exemplified to further demonstrate the simulated system. Within this scope, certain load profiles not only have been fed but also power flow has been managed and analyzed to ensure effective and flexible operation with two different EMS cases. The real-time operation has been also provided to validate the system under various input and output conditions during a lab course.As mentioned, proper control of power electronics converters as the main carrier of the system is essential. Besides, the rise of DC microgrid applications challenges possible issues upon integrating the conventional grid.