| نویسندگان | Mostafa Vahedipour-Dahraie |
| نشریه | Applied Sciences |
| شماره صفحات | 1-26 |
| شماره سریال | 7 |
| شماره مجلد | 10 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2017 |
| نوع نشریه | چاپی |
| کشور محل چاپ | سوئیس |
| نمایه نشریه | ISI،JCR،Scopus |
| کلید واژه ها | bi, level stochastic programming; balancing market; conditional value at risk (CVaR); day, ahead (DA) market; electric vehicle (EV) aggregator |
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چکیده مقاله
This paper proposes a stochastic bi-level decision-making model for an electric vehicle
(EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to
participate in day-ahead (DA) and balancing markets, and provides energy price offers to the EV
owners in order to maximize its expected profit. Moreover, from the EV owners’ viewpoint, energy
procurement cost of their EVs should be minimized in an uncertain environment. In this study, the
sources of uncertainty—including the EVs demand, DA and balancing prices and selling prices
offered by rival aggregators—are modeled via stochastic programming. Therefore, a two-level
problem is formulated here, in which the aggregator makes decisions in the upper level and the EV
clients purchase energy to charge their EVs in the lower level. Then the obtained nonlinear bi-level
framework is transformed into a single-level model using Karush–Kuhn–Tucker (KKT) optimality
conditions. Strong duality is also applied to the problem to linearize the bilinear products. To deal
with the unwilling effects of uncertain resources, a risk measurement is also applied in the
proposed formulation. The performance of the proposed framework is assessed in a realistic case
study and the results show that the proposed model would be effective for an EV aggregator
decision-making problem in a competitive environment.