This paper introduces a consensus-based generalized multi-population aggregative game coordination approach with application to electric vehicles charging under transmission line constraints. The algorithm enables agents to seek an equilibrium solution while considering the limited infrastructure capacities that impose coupling constraints among the users. The Nash-seeking algorithm consists of two interrelated iterations. In the upper layer, population coordinators collaborate for a distributed estimation of the coupling aggregate term in the agents’ cost function and the associated Lagrange multiplier of the coupling constraint, transmitting the latest updated values to their population’s agents. In the lower layer, each agent updates its best response based on the most recent information received and communicates it back to its population coordinator. For the case when the agents’ best response mappings are non-expansive, we prove the algorithm’s convergence to the generalized Nash equilibrium point of the game. Simulation results demonstrate the algorithm’s effectiveness in achieving equilibrium in the presence of a coupling constraint.

A Consensus-Based Generalized Multi-Population Aggregative Game with Application to Charging Coordination of Electric Vehicles / Ghavami, Mahsa; Ghaffarzadeh Bakhshayesh, Babak; Haeri, Mohammad; Como, Giacomo; Kebriaei, Hamed. - In: IEEE CONTROL SYSTEMS LETTERS. - ISSN 2475-1456. - 7:(2023), pp. 3435-3440. [10.1109/LCSYS.2023.3326993]

A Consensus-Based Generalized Multi-Population Aggregative Game with Application to Charging Coordination of Electric Vehicles

Giacomo Como;
2023

Abstract

This paper introduces a consensus-based generalized multi-population aggregative game coordination approach with application to electric vehicles charging under transmission line constraints. The algorithm enables agents to seek an equilibrium solution while considering the limited infrastructure capacities that impose coupling constraints among the users. The Nash-seeking algorithm consists of two interrelated iterations. In the upper layer, population coordinators collaborate for a distributed estimation of the coupling aggregate term in the agents’ cost function and the associated Lagrange multiplier of the coupling constraint, transmitting the latest updated values to their population’s agents. In the lower layer, each agent updates its best response based on the most recent information received and communicates it back to its population coordinator. For the case when the agents’ best response mappings are non-expansive, we prove the algorithm’s convergence to the generalized Nash equilibrium point of the game. Simulation results demonstrate the algorithm’s effectiveness in achieving equilibrium in the presence of a coupling constraint.
File in questo prodotto:
File Dimensione Formato  
A Consensus-Based Generalized Multi-Population Aggregative Game with Application to Charging Coordination of Electric Vehicles.pdf

accesso aperto

Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 341.71 kB
Formato Adobe PDF
341.71 kB Adobe PDF Visualizza/Apri
getPDF.jsp.pdf

non disponibili

Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 666.37 kB
Formato Adobe PDF
666.37 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2983681