Mitigating Power Losses in Distribution Systems: Integrating EV Charging Stations and Renewable Energy Sources

The growing unpredictability of electrical loads poses significant challenges to power distribution systems, leading to disparities between power generation and demand. This imbalance can result in adverse consequences, such as voltage instability and increased power losses within the system. This research paper addresses these issues by proposing a solution that integrates a tap-changing transformer with an adaptive Teaching-Learning-Based Optimization (TLBO) algorithm featuring linear regression. The primary objective is to regulate the transformer's tap settings dynamically, optimizing power distribution and mitigating losses caused by uncertain load conditions. To validate the approach, this paper implement the proposed model using the IEEE 15-Bus system within the MATLAB environment. Furthermore, to simulate real-world conditions and assess the system's response, an electric vehicle (EV) charging station is introduced into the distribution system. This addition introduces an element of uncertainty in the load profile. Various levels of EV penetration are considered to comprehensively evaluate the effectiveness of the proposed algorithm in minimizing power losses.