The virtual power plant (VPP) integrates electric vehicle (EV) parking lots as both flexible consumers and prosumer, leveraging their bidirectional charging capabilities to improve grid stability and profitability. This paper defines a novel method to the improve economic aspect of distributed energy resources (DERs) in a distribution network through a VPP framework, actively contributing in day-ahead and regulation reserve markets. One of the main novelties of this study is using a forecasted price-based unit commitment approach for VPPs in microgrids with the aim of determining an optimal pricing strategy though addressing real-world operational complexities. Also, this study integrates a dual-role EV parking lots, acting both as a consumer and electricity provider, and explores its potential to minimize costs while optimizing charging and discharging agendas. The proposed optimization model tries to obtain maximum VPP profits in day-ahead and reserve markets by controlling the complexities of distributed thermal and electrical production, energy storage limits, and power balance restraints. By implementing an efficient model based on the a mixed-integer linear programming (MILP), a higher solution speeds, global optimality, and scalability for larger problems overcoming traditional limitations such as local optima and infeasibility in large-scale scenarios is achieved. By considering the uncertainties of solar and wind sources, a spinning reservation technique is used to increase microgrid stability. This study also examines how demand response programs help gas stations operate better and facilitate effective energy transfers between VPPs and the upstream network. As a major step toward increasing microgrid profitability and operational efficiency, the results demonstrate the superiority of establishing a strategic pathway for VPPs to optimize energy transactions, set competitive reserve market pricing, and handle market uncertainties.