A Dynamic Real-Time Optimization Algorithm for the Revenue Assessment of a Vehicle-To-Grid System in Presence of Wear Cost Model - COPERNIC Accéder directement au contenu
Communication Dans Un Congrès Année : 2022

A Dynamic Real-Time Optimization Algorithm for the Revenue Assessment of a Vehicle-To-Grid System in Presence of Wear Cost Model

Résumé

This paper presents a linear programming optimization algorithm with changeable weighting factors for reaching maximum revenue in the peak-value duration of the PV power and electricity price in a smart Vehicle-to-Grid (V2G) system. In order to render an accurate revenue assessment, the EV battery wear model is also taken into consideration through the parameters including the equivalent daily discount, estimated cycle life, the battery capital cost and battery salvation value. Moreover, a linear objective function is proposed by exerting the forecasted PV power profile to constitute the dynamic weighting factors for the EV battery power variables. The comparative simulation results in MATLAB/Simulink verify that the proposed dynamic optimization algorithm can reach its maximum revenue in three times i.e., the peak-value duration of the PV power, the peak-value duration of electricity price and the end of the simulation. In addition, the results affected by the EV battery wear model are presented.
Fichier principal
Vignette du fichier
389725 - Majid MEHRASA.pdf (888.76 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03663327 , version 1 (10-05-2022)

Identifiants

  • HAL Id : hal-03663327 , version 1

Citer

Majid Mehrasa, Khaled Hajar, Mehrdad Gholami, Khaled Hajar, Antoine Labonne, et al.. A Dynamic Real-Time Optimization Algorithm for the Revenue Assessment of a Vehicle-To-Grid System in Presence of Wear Cost Model. Electrimacs 2022 - 14th International Conference of TC-Electrimacs Committee, May 2022, Nancy, France. ⟨hal-03663327⟩
125 Consultations
84 Téléchargements

Partager

Gmail Facebook X LinkedIn More