In the smart grid, retail price determination by electricity retailer is necessary in the presence of hydrogen storage systems and plug-in electric vehicles under pool market price uncertainty. Therefore, in this paper, realtime pricing is proposed in comparison with time-of-use pricing and fixed pricing. Furthermore, an interval optimization approach is proposed for pool market price uncertainty modeling. In this approach, uncertaintybased profit function of retailer is reformulated as a deterministic bi-objective problem with average and deviation profits as the conflict objective functions which average profit should be maximized while deviation profit should be minimized. Furthermore, epsilon constraint method is used to solve the proposed bi-objective model in order to obtain Pareto solutions. Finally, fuzzy satisfying approach is used to select the trade-off solution from Pareto solutions. The obtained results show that average profit of retailer increases in the real-time pricing in comparison with time-of-use pricing and fixed pricing. Also, deviation profit of retailer decreases in the proposed interval optimization approach in comparison with deterministic approach. The proposed mixedinteger linear programming model is solved using CPLEX solver under GAMS optimization software. To validate the better performance of proposed model, three types of retail price determination under deterministic and interval optimization approaches are utilized and the results are compared with each other.
