TY - JOUR
T1 - Hierarchical control for collaborative electric vehicle charging to alleviate network congestion and enhance EV hosting in constrained distribution networks
AU - González-Garrido, Amaia
AU - González-Pérez, Mikel
AU - Asensio, Francisco Javier
AU - Cortes-Borray, Andrés Felipe
AU - Santos-Mugica, Maider
AU - Vicente-Figueirido, Ibon
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2024/9
Y1 - 2024/9
N2 - This paper introduces a novel hierarchical architecture aimed at enhancing coordination between distribution system operators and electric vehicle aggregators in order to minimize Electric Vehicle (EV) charging costs for users while optimizing EV hosting capacity to alleviate network congestion. Real-world distribution networks are employed to evaluate EV charging strategies and their impact on medium and low-voltage networks. Two distinct EV charging optimization strategies are proposed to ensure fair power allocation among EV Aggregators (EVAs), alleviating congestion while managing EV charging power efficiently. Results demonstrate that the proposed collaborative EV charging effectively flattens the load curve, reducing peak power and avoiding grid congestion. The main findings underscore the importance of incentivizing EV flexibility to support Distribution System Operator (DSO) objectives beyond static tariffs. Furthermore, a battery degradation model is introduced into the optimization problem, reducing high currents and capacity decay. Despite capturing a higher mean electricity price, the total cost of EV charging is reduced.
AB - This paper introduces a novel hierarchical architecture aimed at enhancing coordination between distribution system operators and electric vehicle aggregators in order to minimize Electric Vehicle (EV) charging costs for users while optimizing EV hosting capacity to alleviate network congestion. Real-world distribution networks are employed to evaluate EV charging strategies and their impact on medium and low-voltage networks. Two distinct EV charging optimization strategies are proposed to ensure fair power allocation among EV Aggregators (EVAs), alleviating congestion while managing EV charging power efficiently. Results demonstrate that the proposed collaborative EV charging effectively flattens the load curve, reducing peak power and avoiding grid congestion. The main findings underscore the importance of incentivizing EV flexibility to support Distribution System Operator (DSO) objectives beyond static tariffs. Furthermore, a battery degradation model is introduced into the optimization problem, reducing high currents and capacity decay. Despite capturing a higher mean electricity price, the total cost of EV charging is reduced.
KW - Battery degradation model
KW - Charging optimization
KW - Distribution networks
KW - Hierarchical control
KW - Network congestion
UR - http://www.scopus.com/inward/record.url?scp=85196523425&partnerID=8YFLogxK
U2 - 10.1016/j.renene.2024.120823
DO - 10.1016/j.renene.2024.120823
M3 - Article
AN - SCOPUS:85196523425
SN - 0960-1481
VL - 230
JO - Renewable Energy
JF - Renewable Energy
M1 - 120823
ER -