Optimal energy modeling and planning in the power system via a hybrid firefly and cuckoo algorithm in the presence of renewable energy sources and electric vehicles

The integration of distributed generation resources, including electric vehicles (EVs), has become increasingly important in supplying grid loads. EVs have the potential to act as a distributed generation source and help reduce the electrical company's expenses. However, their extensive use in distribution networks may cause some difficulties for the electricity grids, such as economic and scientific functioning problems and the potential for other applications. In this study, we propose a model to control coordinated and uncoordinated charging systems of grid-connected electric cars using two wind turbines and one solar power plant as distributed generation sources. The model divides EVs into four classes based on their grid shares and the number of accidental vehicles per class, utilizing the normal distribution function. The suggested model is solved using a hybrid firefly and cuckoo method. The goal function of the model is a combination of yearly energy loss cost and the operational cost of distributed generating units. The simulation, conducted on a 33-bus IEEE grid, demonstrates that the proposed model is highly effective and efficient. The results indicate that random EV charging leads to significantly higher expenses compared to the coordinated charging approach. Additionally, the peak demand reduces when EV charging is coordinated.& COPY; 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).