Building operation optimization is the main battlefield for energy saving and emission reduction in aiming to attain the dual carbon target. The optimization of building operations for energy efficiency should prioritize the issue of local photovoltaic consumption. Local consumption of PV can reduce the backward transfer of energy from the building to the grid, improve the stability of grid operation, and also reduce the unnecessary waste of PV resources. The local consumption of building PV usually relies on the assistance of ESSs (energy storage systems).However, the high construction and maintenance costs of ESS add to the cost burden of building operations. Virtual energy storage technology is a good method of optimizing the management of flexible loads, which can increase the local consumption capacity of buildings through the regulation inertia of flexible loads. Therefore, this paper proposes a virtual energy storage (VES) operation optimization strategy for distributed PV local consumption of flexible loads in public buildings, models for dynamic regulation of air-conditioning (AC) loads considering temperature variations and electric vehicle loads considering charging and discharging uncertainties were established, and unifies the dynamic VES indexes for air conditioning and electric vehicles, which significantly reduces the decision-making variables of the joint optimization process, and realizes overall Scheduling. The experimental results show that the PV consumption rate of the optimized building can reach 93% on average, which verifies that the public building’s own energy storage characteristics have a great potential for application in PV consumption.