TY - JOUR
T1 - Multi-Objective Optimization of EV Charging and Discharging for Different Stakeholders
AU - Lu, Shaofeng
AU - Han, Bing
AU - Xue, Fei
AU - Jiang, Lin
AU - Qian, Kejun
N1 - Publisher Copyright:
© 2015 CSEE.
PY - 2023/11/1
Y1 - 2023/11/1
N2 - As a dynamic energy storage system, electric vehicles (EV) play important roles in future power grids. In this paper, a model for EV aggregator participation in the electricity market has been built with a focus on the feasibility issue of the model arising from economic interest inconsistencies between different stakeholders: EV owners and aggregator. In the model, the EV aggregator attends day-ahead energy and reserve markets for profit maximization by scheduling charging and discharging behaviors of EVs. This issue exists since different stakeholders have different interests which are not necessarily consistent, e.g. profit maximization leads to increasing EV owners' charging fee. To investigate the economic relationship between the two stakeholders, two multi-objective optimization methods (weighted sum and Ε-constraint methods) are proposed to take the aggregator profit and EV owners' charging fee into account in the model. A sensitivity analysis is applied to examine the aggregator profit under different price scenarios, which reveals the internal relationship between EV owners' charging fees and aggregator profit. The proposed EV charging and discharging strategy in this paper could be used to determine the settlement price between the aggregator and owners to ensure the feasibility of participation from both EV owners and stakeholders in electricity markets.
AB - As a dynamic energy storage system, electric vehicles (EV) play important roles in future power grids. In this paper, a model for EV aggregator participation in the electricity market has been built with a focus on the feasibility issue of the model arising from economic interest inconsistencies between different stakeholders: EV owners and aggregator. In the model, the EV aggregator attends day-ahead energy and reserve markets for profit maximization by scheduling charging and discharging behaviors of EVs. This issue exists since different stakeholders have different interests which are not necessarily consistent, e.g. profit maximization leads to increasing EV owners' charging fee. To investigate the economic relationship between the two stakeholders, two multi-objective optimization methods (weighted sum and Ε-constraint methods) are proposed to take the aggregator profit and EV owners' charging fee into account in the model. A sensitivity analysis is applied to examine the aggregator profit under different price scenarios, which reveals the internal relationship between EV owners' charging fees and aggregator profit. The proposed EV charging and discharging strategy in this paper could be used to determine the settlement price between the aggregator and owners to ensure the feasibility of participation from both EV owners and stakeholders in electricity markets.
KW - Aggregator
KW - EV
KW - EV owners
KW - economic inconsistency issue
KW - electricity market
KW - multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=85152625822&partnerID=8YFLogxK
U2 - 10.17775/CSEEJPES.2020.02300
DO - 10.17775/CSEEJPES.2020.02300
M3 - Article
AN - SCOPUS:85152625822
SN - 2096-0042
VL - 9
SP - 2301
EP - 2308
JO - CSEE Journal of Power and Energy Systems
JF - CSEE Journal of Power and Energy Systems
IS - 6
ER -