Multi-area economic/emission dispatch considering the impact of the renewable energy resources and electric vehicles

Abdollahzadeh Sangrodi, Rouhollah; Samiei-Moghaddam, Mahmoud; Hajizadeh, Amin

doi:10.22075/ijnaa.2022.6721

Multi-area economic/emission dispatch considering the impact of the renewable energy resources and electric vehicles

Document Type : Research Paper

Authors

Rouhollah Abdollahzadeh Sangrodi ¹

Mahmoud Samiei-Moghaddam ¹

Amin Hajizadeh ²

¹ Department of Electrical Engineering, Damghan Branch, Islamic Azad University, Damghan, Iran

² AAU ENERGY, Aalborg University, Esbjerg, Denmark

10.22075/ijnaa.2022.6721

Abstract

This paper proposed a model and method for multi-area economic/emission dispatch in the presence of renewable energy sources (RESs) and electric vehicles (EVs). The economic/Emission load dispatch model includes uncertain modeling of wind and solar renewable energy sources along with an uncertain model of electric vehicles and network demand with the objective of reducing economic and pollution costs of generation units. In this paper, the day-ahead electricity market is modeled on a 24-hour time period. Since it will be very difficult to solve the problem by increasing the time period and the number of generation units as well as considering the uncertainty, a meta-heuristic algorithm with the ability to solve large-scale problems and Investigate the concept of affordability based on the application of a thorough researched fast convergence has been presented. A modified particle swarm optimization (MPSO) algorithm has been proposed to solve the proposed problem due to the rapid convergence of hard optimization problems and achieve the optimal global result. A case study with four areas has been considered for the analysis of the proposed model and method, and two different approaches have been presented to illustrate the multi-area economic/emission dispatch and the results indicated the efficiency of the proposed model and method.

Keywords

Multi-Area economic dispatch

renewable energy

emission

uncertainty

electric vehicles

optimization

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