Özet:

As a result of the increasing trend from renewable energy sources to electricity production in recent years, distributed production plants, especially photovoltaic (PV)-based sources, have become quite widespread in the electricity distribution networks, and the share of these plants is increasing on a daily basis. The impact of this situation on the network has gained an increasing importance today. As a general blood, the concept of "production where consumption is" can help the network to work in better conditions, such as lower technical losses and ideal-approximate voltage profiles; the network can work in worse conditions, if it is not well planned, distributed production is done much below or much above the need of the network. In these cases, it increases the investment that the distribution system operators (DSO) need to make in order for the network to work in sustainable working conditions. Among these investments, the most practically applied are the replacement of current lines with high lines of power capacity, the addition of new lines/connections to the network and the reactive power combination through capacitors. Due to the nature of the designs of PV inverters, they can provide capacitive or industrial reactive power support within certain limits, and the use of these inverters as reactive power compensators can reduce the need for investment. In this study, a Python-based particle volume optimization (PSO) algorithm will be developed to calculate the optimal amount of reactive power support that needs to be taken to improve the voltage profile of the network, taking into account the reactive power limits of the PV power plants in the distribution network. For network modeling, analysis and simulation, the DIgSILENT PowerFactory network analysis program will be used and will be connected through Python to the network modeled with the developed optimization algorithm and the necessary analysis will be carried out and.

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