چكيده به لاتين
Due to the progress made in the electricity industry and with the penetration of extensive energy sources, it has caused the creation of microgrids. Unlike the traditional electricity grid, microgrids create an active distribution network. Due to the increase in the use of extensive energy sources and the creation of flexibilities, therefore, it is necessary to examine the connection of microgrids in the distribution network. Therefore, connecting several microgrids and how they interact with the distribution network is very important. In this research, the energy management in the distribution network connected to several microgrids has been investigated in the conditions of creating flexibility of load response programs. In microgrids, various production sources such as wind and solar renewable energy sources, fuel cell, microturbine, diesel generator, energy storage and electric car parking are considered. Due to the presence of parameters with uncertainty, the random optimization method has been used to model the uncertainties. The considered parameters include the production of wind and solar renewable energy sources, load consumption and power exchange prices. In order to model the problem, firstly, the modeling of the equipment inside the microgrids is presented, and in the next stage, the modeling related to the use of load response programs is presented. Then, the aforementioned models have been integrated in the problem of energy management of the distribution network connected to several microgrids. Due to the existence of different production sources, the goal of the problem is not only to reduce costs, and in addition to reducing costs, reducing carbon pollution is also considered. The mentioned model has been implemented on the standard network of 69 buses, on which 8 microgrids are located in the end buses of the branches of this network. 4 study examples including modeling without considering load response programs and electric cars, considering only load response programs, considering only electric car parking and considering the simultaneous existence of load response programs and electric car parking. has been The results show the improvement of network conditions by applying flexible methods. Using load response programs reduces costs by 3.29% and using electric car parking also reduces costs by 0.83%, while simultaneously using both of the aforementioned methods reduces costs by 4.13%.
