As the installed capacity of wind power continues to increase, the problem of curtailed wind power is becoming serious in China, especially in the northern region during the winter heating season. To solve the problem of wind-heat conflict during the heating period in the Three North area, an electric boiler with thermal storage (EBTS) is installed at the end of the grid where wind power is difficult to accommodate and using curtailed wind power to supply heat promotes local accommodation. In this paper, a multi-objective optimization model of wind power accommodation based on the wind power-EBTS system for heating is established. The goals of maximizing wind power accommodation, minimizing the number of times EBTS must be adjusted, and minimizing operating costs are presented, and a bi-level optimization scheme is designed. An improved multi-objective particle swarm optimization algorithm is used to solve these functions, and an optimal compromise solution from the generated Pareto solution set is filtered using the fuzzy membership method. Based on actual data from a demonstration project in China's Jilin Province, the simulation results verify that this method can effectively reduce operating costs and improve wind power accommodation.