An advanced energy management of microgrid system based on genetic algorithm

Abstract : Immense growth has happened in the field of microgrid (MG) and the energy management system (EMS) methods in the past decade. It is estimated that there is still a huge potential of growth remaining in the field of EMS in the coming years. The main role of EMS is to autonomously determine hour-by-hour the optimum dispatch of MG and main grid energy to satisfy load demand needs. This paper is focused on developing an advanced EMS model able to determine the optimal operating strategies regarding to energy costs minimization, pollutant emissions reduction, MG system constraints and better utilization of renewable resources of energy such as wind and photovoltaic through daily load demand. The proposed optimization model of EMS is formulated and solved based on genetic algorithm (GA). The efficient performance of the algorithm and its behavior is illustrated and analyzed in detail considering winter load demand profile.
Liste complète des métadonnées

https://hal-normandie-univ.archives-ouvertes.fr/hal-02156594
Contributeur : Christine Rouil <>
Soumis le : vendredi 14 juin 2019 - 14:54:20
Dernière modification le : samedi 15 juin 2019 - 01:35:24

Identifiants

  • HAL Id : hal-02156594, version 1

Collections

Citation

Moataz Elsied, Amrane Oukaour, Hamid Gualous, Radwan Hassan, Amr Amin. An advanced energy management of microgrid system based on genetic algorithm. 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), Jun 2014, Istanbul, Turkey. pp.2541-2547. ⟨hal-02156594⟩

Partager

Métriques

Consultations de la notice

21