Developing multi agent control methods for improved operational conditions in smart distribution networks

Demand for electricity is steadily increasing due to both population growth and economic growth in the world. Today, most of the energy demand is met by the use energy sources based on fossil fuels. However, due to decreasing reserves of fossil fuels and the consumption of these fuels caused global warming and damage to ecology, countries are in search of alternative ways. For this reason, some solutions such as using electric vehicles instead of conventional vehicles, making existing electrical power systems more efficient and increasing the use of renewable energy sources (RESs) have been proposed. The current electric power systems that have been in operation for 130 years can not meet today's needs. For example, peak demand in electrical power systems has increased in recent years due to population growth, use of inefficient electrical devices, user preferences and unnecessary energy wastage. Moreover, the increasing number of RESs included in the system cause some planning difficulties in the supply side. In addition, the electricity generated in the conventional electrical power system can not be stored and it is necessary to deliver electricity to the end users immediately. Therefore, the balance between supply and demand should be provided any moment. The amount of generation and consumption of electric energy varies greatly by the seasons, the regions and the specific time of the day. It is clear that consumption and generation fluctuations would occur in this case. Also, increased electrical energy demands cause an unbalanced loading, a low load factor and increasing losses in the electrical power system. In addition, losses occur as a result of inefficient use of electric energy in the generation, transmission, distribution. A new electrical power system approach is needed in the current situation. For this reason, research and development activities are being carried out all over the world on the new electrical power system structure called "smart grid". In this regard, many developed and developing countries have begun to create incentive programs at significant levels for different areas of the smart grid. Considering all of these aspects, it is important to carry out a thesis on the smart grids that have just begun to be searched in our country. This PhD thesis proposes power management laws that use smart grid infrastructure and provide the proper operation of distributed energy systems, which are mainly composed of RESs. While the mentioned power management laws are set, the control method called multi-agent systems in artificial intelligence studies is utilized. With the proposed laws, it is aimed to operate the electric power system with maximum efficiency and to be ensured the balance between supply and demand continuously. In this way, because it is effectively benefited from RESs, it is foreseen the reduction in power system losses, relief in loading of transformers and lines, and thus to reduction in carbon emissions. With smart grid technology, in addition to increasing in energy efficiency, energy quality will be positively affected. In order to implement these power management laws effectively, an exemplary power system model with smart grid features has been established. As an electrical power system model, although IEEE's 13 node test feeder has been preferred, it has been used with various modifications on the model. In the next stage, detailed simulation models of all the units including the renewable energy-based distributed generation resources are created in the simulation environment and by integrating them into the electrical power system a micro grid structure is created. The effects of laws developed on the system, especially on energy losses and voltage profiles, are tested in different case studies and then the results are evaluated.