Optimum sitting and sizing of distributed solar energy generation systems for grid integration and clearance of possible problems

Keywords: Distributed generation, solar energy, renewable energy, distributed solar energy systems, optimization The present study is the first to present the solar energy potential of Türkiye and the change and development of distributed solar energy installed power within the frame of current laws and regulations. Considering the data present, DSEG SWOT analysis study of Türkiye and suggestions are presented in order to enable maximum benefit from solar energy. The primary aim of the present study is to enable DSEG connections to distribution systems with optimum values. In earlier studies DSEG systems are considered like stable active power source as pf =1 pu and relevant analyzes are optimum site and size based on this assumption. While conducting analyses of the present thesis study, power factor is considered as a third parameter for problem solving. The optimum values for the 2xN size placement problem primarily express the site to which the DSEG unit will be connected and the size of connection. The 3xN dimensional problem is the development of the 2xN placement problem and expresses the site, size and power factor. In the 3xN solutions, the power factor is considered for three different cases. In the first case, the power factor unit value is bPF=1 pu. In the second case, the power factor is a constant value sPF=0.85 pu, and in the third, the optimum value of the power factor is oPF. Optimization algorithms are used for the DSPG optimal allocation process, which is a problem of optimization. Particle swarm algorithm improved with contrast-based learning - OBPSO and hybrid PSOGSA algorithms are proposed to solve the problem of optimization. Planning will be insufficient in cases where the change in distribution system possible loads is not considered while integrating DSEG. To overcome this disadvantage, bus load variation sensitivity analysis has been proposed as a new method to analyze the changes that will occur in the network loads. bus sensitivity analysis (BSA) enables to determine the most sensitive bus and sensitivity levels to load changes that will occur in the system. With the information obtained for the analyzed system, the most suitable busses for DSEG integration can be easily obtained. Moreover, BSA is used as a new objective function for DSEG integration problems and as a new method to obtain optimum values for optimization algorithms. The studies conducted have revealed that adding power factor as a new parameter to the optimization problem provides more reduction in the active power loss compared to other power factor cases. Furthermore, the BSA method yielded better results if used as an objective function in case of system load increases. It has been concluded that OBPSO and PSOGSA algorithms are more efficient than the other algorithms compared in solving DSEG integration problem.