Abstract: Offshore wind power will become an important technological option for China to achieve carbon emission peak and carbon neutrality due to its more utilization hours for electric power generation. However, with the continuous increase in the offshore wind power installed capacity, its intermittency and fluctuation will have a significant impact on the security and stability of power systems, as well as the economic operation of electricity markets. To characterize the correlation between wind speeds at different station sites, the vine copula theory is used for offshore wind power modeling and a joint distribution model is constructed for multiple wind farms by using the C-vine copula function. On this basis, a method is proposed for constructing the typical congestion scenarios in the electricity market based on the consensus clustering. Numerical simulation calculations are conducted with the simplified power grid architecture data of Guangdong province, China to empirically analyze the changes in key indicators such as generation structure of the power system, carbon emissions, and market electricity prices before and after the large-scale grid-integration of offshore wind power.