Deep Learning based optimal power flow with renewable integration

Abstract

There has been an escalation in the load demand and in order to meet these demands, the systems have to be more reliable. Distributed Generators help in improving the reliability of the systems by reducing power losses, increasing efficiency, lower fuel, and maintenance costs. The placement of DG in the most optimal position provides added advantage in achieving the above benefits. We have analyzed the IEEE 26-bus system to determine the optimal position of DG and measured the system's total power loss. Genetic Algorithm(GA) is used to identify the optimal location and size for the DG. The impact of DG is studied by comparing the losses, voltages before and after placement of DG. The obtained results indicate that the optimal sizing and placement of DG leads to a notable reduction in power loss and enhanced voltage profile. We have used MATLAB software for analysis. After analysis, installing DG at the optimal location resulted in a 1054.16 $/hour reduction in the cost of power generation.