Aiming at the problem of multi-energy collaborative optimization under the power internet of things, an optimization model of collaborative trading of wind and solar storage was established. The excellent regulation performance of pumped storage power (PSP) plant is used to bundle it with wind power plant and photovoltaic power plant in proportion to maximize the absorption of new energy; The other part participates in the main side market regulation to achieve collaborative optimization. Through the construction of landscape storage alliance, it aims to eliminate the deviation of landscape new energy output, so as to solve the security problem of information exchange in the internet of things. In addition, the Shapley value method is used to allocate the surplus value. In this process, considering the carbon emission requirements, the carbon reduction efficiency of electric vehicles(EV) is introduced on the load side, and it is constrained by the output of thermal power. At the same time, the electric energy storage regulation is added to the grid side to ensure the safe operation of the system in the power internet of things environment. This study adopts the volume quotation method on the subject side, so that all the new energy forecasts are cleared, while the load side is cleared following the market price fluctuations. Further considering the fluctuation deviation, the output of the multi-energy subject is optimized. Simulation results under different scenarios verify the feasibility and adaptability of the proposed optimization model.