AUTHOR=Hmingthanmawia David , Deb Subhasish , Datta Subir , Singh Ksh. Robert , Cali Umit , Ustun Taha Selim 

TITLE=Multi-objective-based economic dispatch and loss reduction in the presence of electric vehicles considering different optimization techniques

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1389822

DOI=10.3389/fenrg.2024.1389822

ISSN=2296-598X

ABSTRACT=In this paper, a multiobjective based economic dispatch management including EVs is employed to minimize the generator cost and active power loss. The entire system is retained for keeping in mind the economic operation of the whole system. Then, EVs are introduced to the system, taking into account vehicle requirements and load demands and considering EV constraints. The target of the proposed work is to demonstrate how effectively large scale EVs can participate in valley filling and peak load shaving along with multi-objective based cost and loss reduction. The proposed optimization problem is employed in an IEEE 30 bus system. The Multi-objective Grasshopper Optimization Algorithm is compared with Ant-Lion optimization to observe the minimum cost and total loss of the system. The results show that the total generation cost and power loss of the system decreases due to V2G mode of operation. Also, EVs provide an alternative method for dealing with peak load, while filling the off-peak hours effectively. The total generation cost and power loss for 24 hours using MOGOA without implementation of EVs are 8757.128 $/hr and 65.28509 MW. And with EVs, the total generation cost and power loss for 24 hours are 8617.077 $/hr and 55.65349 MW. Thus, with the implementation of EVs, the total generation cost reduced by 1.59 % and the total power loss reduced by 14.75 %. And with MOALO, the total generation cost and power loss for 24 hours without EVs are 8977.077 $/hr and 44.20877 MW. And with EVs, the total generation cost and power loss for 24 hours are 8923.529 $/hr and 41.69524 MW. Thus, with the implementation of EVs, the total generation cost reduced by 0.59 % and the total power loss reduced by 5.68%. The analysis of the results demonstrates how effectively EVs in V2G mode can reduce the dependency over the grid power during the time of peak load demand.