Research Article
Transmission Congestion Management in Deregulated Electricity Market using Multi-Objective Grasshopper Optimization Algorithm
@ARTICLE{10.4108/eai.27-11-2020.167288, author={Benjamin Chatuanramtharnghaka and Subhasish Deb}, title={Transmission Congestion Management in Deregulated Electricity Market using Multi-Objective Grasshopper Optimization Algorithm}, journal={EAI Endorsed Transactions on Energy Web}, volume={8}, number={33}, publisher={EAI}, journal_a={EW}, year={2020}, month={11}, keywords={Congestion management, generator rescheduling, optimization, multi-objective grasshopper optimization algorithm (MOGOA)}, doi={10.4108/eai.27-11-2020.167288} }- Benjamin Chatuanramtharnghaka
Subhasish Deb
Year: 2020
Transmission Congestion Management in Deregulated Electricity Market using Multi-Objective Grasshopper Optimization Algorithm
EW
EAI
DOI: 10.4108/eai.27-11-2020.167288
Abstract
In this paper, a study of multi-objective based congestion management is carried out by generator rescheduling with considering generator fuels cost. Due to the rapid growth of electrical load, the pressure in the transmission sector increases to provide transmission of power in a safe manner. But owing to the load growth, the transmission line power flow reaches beyond thermal limit which results in transmission congestion. The congestion management in the present work has been done in a multi-objective framework considering generator rescheduling method as one of the objectives. A Multi-objective Grasshopper Optimization Algorithm (MOGOA) is implemented to perform the optimization for elimination of congested line and minimizing the operational cost of the system. The efficacy of the proposed method has been compared and analyzed with different multi-objective algorithms in IEEE 30 bus test system.
Copyright © 2020 Benjamin Chatuanramtharnghaka et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.