Sayyad Nojavan

A single plug-in electric vehicle (PEV) cannot participate in reserve and day-ahead markets as they cannot meet the energy requirements of independent system operators (ISO). However, they can be gathered by a PEV aggregator and play a role in so called markets. On the other hand the PEV aggregators are to deal with the uncertainties that go along with these markets and can highly affect their profit. In order to cover these uncertainties scenario-based stochastic approach can be taken into to account to optimally schedule the PEV aggregators so that the maximum profit is obtained. The main contribution of this paper is to involve risk related uncertainties through the downside risk constraints (DRC) which results in risk-constrained stochastic optimization model. The main advantage of this method is that it can provide the owner of PEV aggregator with decisions that are made by considering various quantities for risk. CPLEX solver of GAMS software is employed to solve the problem which is formulated as mixed-integer linear programming (MILP) model. To investigate the accomplishment of DRC, risk-averse state of model is compared to risk-neutral which in former one the profit is reduced meanwhile that risk-in-profit (RIP) is declined.