Optimal Strategy of Retail Companies in the Day-Ahead Markets in the Presence of Non-Dispatchable Renewable Sources and Electric Vehicle Aggregators

One of the most important issues in the electricity retail market is determining the optimal price of electricity by retailers to consumers, which, in addition to pinpointing the profit of retailers, also provides the general interests of customers. Electric vehicles and a hydrogen-based energy storage unit including a fuel cell unit can have a special capability in energy management. In this article, the problem of determining the selling price and managing the energy resources for a retail intermediary agent in the smart grid under the influence of the existing uncertainties is investigated. In this study, the impacts of the presence of several generation companies (GENCOs) in a wholesale pool market structure incorporating bilateral contracts are considered while the fossil-fuel-based small-scale distributed generation units, electric vehicles aggregators, renewable energy sources (PV and WT), and hydrogen-based storage systems are supposed to participate in the retail market level. Moreover, the uncertainty of pool market prices, load profile, the intensity of sunlight and temperature, and wind speed are modeled using the Monte Carlo method. The optimization problem aims to maximize the retailers' profitability and to determine the optimal strategy of retailers in different levels of electricity markets using the gorilla troop optimization method. The proposed model has been simulated for different pricing modes, including fixed pricing, time-based rate pricing, and real-time pricing, and the results have been evaluated.