Abstract: In the context of “carbon emission peaks and carbon neutrality, ” electric heating has become the mainstream heating method. Electric heating loads typically increase the operating pressure of the distribution network; therefore, it is necessary to expand the distribution network. Traditional planning methods have difficulty in solving the problem of flexible distribution network planning with a large number of electric heating-electric heat storage devices. Therefore, a low-carbon expansion planning method for a distribution network considering access to electric heating-electric heat storage devices is proposed. First, based on the optimal room temperature for heating buildings, wind speed and other factors were comprehensively considered to derive a temperature time-varying equation and solve it to obtain the heat load demand. Next, the output characteristics of the heat load demand, wind power, and photovoltaic power were used during the planning process to optimize the operation mode of the thermal storage electric boiler to achieve the lowest carbon emissions. Finally, the range and variance of the load rate was used as the uniformity index of the distribution network, and the multiobjective expansion plan for the distribution network was carried out to achieve comprehensive cost and line load rate uniformity. A case study was solved using a nested hybrid particle swarm optimization algorithm, which introduces a dynamic inertia weight to enhance the optimization ability of particle swarm optimization. Actual data from a specific area in Northeast China were used in the case studies to verify the feasibility of the proposed method.