TY - JOUR
T1 - Optimal Decision Making Framework of an Electric Vehicle Aggregator in Future and Pool markets
AU - Rashidizadeh-Kermani, Homa
AU - Najafi, Hamid Reza
AU - Anvari-Moghaddam, Amjad
AU - Guerrero, Josep M.
PY - 2018
Y1 - 2018
N2 - Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain optimal decision making of an EV aggregator. To deal with mentioned uncertainties, the aggregator’s risk aversion is applied using conditional value at risk (CVaR) method in the proposed model. The proposed two-stage risk-constrained decision-making problem is applied to maximize EV aggregator’s expected profit in an uncertain environment. The aggregator can participate in the future and pool market to buy the required energy of EVs and offer optimal charge/discharge prices to the EV owners. In this model, in order to assess the effects of EVs owners’ reaction to the aggregator’s offered prices on the purchases from electricity markets, a sensitivity analysis over risk factor is performed. The numerical results demonstrate that with the application of the proposed model, the aggregator can supply EVs with lower purchases from markets.
AB - Electric vehicle (EV) aggregator, as an agent between the electricity market and EV owners, participates in the future and pool market to supply EVs’ requirement. Because of the uncertain nature of pool prices and EVs’ behaviour, this paper proposed a two-stage scenario-based model to obtain optimal decision making of an EV aggregator. To deal with mentioned uncertainties, the aggregator’s risk aversion is applied using conditional value at risk (CVaR) method in the proposed model. The proposed two-stage risk-constrained decision-making problem is applied to maximize EV aggregator’s expected profit in an uncertain environment. The aggregator can participate in the future and pool market to buy the required energy of EVs and offer optimal charge/discharge prices to the EV owners. In this model, in order to assess the effects of EVs owners’ reaction to the aggregator’s offered prices on the purchases from electricity markets, a sensitivity analysis over risk factor is performed. The numerical results demonstrate that with the application of the proposed model, the aggregator can supply EVs with lower purchases from markets.
KW - Aggregator
KW - Conditional Value at Risk (CVaR)
KW - Electric Vehicle
KW - future market
KW - Pool market
U2 - 10.22098/joape.2006.3608.1288
DO - 10.22098/joape.2006.3608.1288
M3 - Journal article
SN - 2322-4576
VL - 6
SP - 157
EP - 168
JO - Journal of Operation and Automation in Power Engineering
JF - Journal of Operation and Automation in Power Engineering
IS - 2
M1 - 2
ER -