Abstract: The uncertainties of wind and photovoltaic power generations has brought about new challenges for the equivalent inertia evaluation of power systems with high proportional renewable energy. Generally, the inertia evaluation methods under deterministic scenarios cannot effectively reflect the trend of time series changes of the power system inertia. In order to evaluate the uncertainty of the system inertia caused by the renewable energy fluctuation, this paper proposes a new method for equivalent inertia probability evaluation based on the Slice Sampling Markov Chain Monte Carlo (S-MCMC). Firstly, the inertia composition and characteristics of power systems with high proportional renewable energy are analyzed, and the effective mechanical inertia provided by the synchronous rotating equipment and the effective virtual inertia provided by the wind power and photovoltaic power are quantitatively calculated respectively. Secondly, the correlation model between the wind speed and light intensity is established based on the Copula function, and the probability evaluation of the system equivalent inertia is carried out through the S-MCMC, so as to obtain the time series variation interval of the system equivalent inertia. Finally, simulation analysis is conducted on the modified IEEE 39 bus system to verify the effectiveness of the proposed method and analysis results.