An Optimal Hybrid Management of Electric Vehicle Fleet Charging and Load Scheduling in Active Electric Distribution System
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper introduces a novel scheduling framework designed to manage the charging of electric vehicles (EVs) in a way that considers its effects on the power grid. Leveraging the Alternating Direction Method of Multipliers (ADMM), the methodology offers a significant advantage by enabling decentralized sub-problems, allowing for efficient and rapid solutions. The methodology developed as an algorithmic framework incorporates various scheduling approaches for EV charging, including demand management techniques like valley filling and peak shaving, along with real-time pricing (RTP) considerations. These strategies aim to modify individual electricity consumption patterns to reduce peak demand, ultimately enhancing energy efficiency and ensuring the stability of the power system. The results of the study highlight the crucial role of distributed optimization in improving both demand management strategies and cost objectives. The results indicated that the proposed method shows significant improvement in overall energy efficiency when compared to the state-of-the-art centralized convex optimization framework. © 1972-2012 IEEE.
Açıklama
Anahtar Kelimeler
alternating direction method of multipliers (ADMM), demand side management, Electric vehicle integration, energy management system, load balancing, Convex optimization, Costs, Demand side management, Electric power distribution, Energy efficiency, Energy management, Energy management systems, Fleet operations, Interactive computer systems, Alternating direction method of multiplier, Alternating directions method of multipliers, Convex functions, Electric vehicle integrations, Load scheduling, Load-Balancing, Optimisations, Power systems stability, Real - Time system, Vehicle fleets, Real time systems
Kaynak
IEEE Transactions on Industry Applications
WoS Q Değeri
Scopus Q Değeri
Q1
Cilt
60
Sayı
4
