This study develops an optimization-based planning model for the deployment of renewable energy resources to meet electrified space heating and cooling demands. The model integrates building heat transfer characteristics, renewable energy potentials, and electricity transmission network constraints. Its objective is to minimize total investment and operational costs of generation, storage, and transmission, while capturing seasonal variability in supply and demand. The framework also evaluates the effects of finer temporal resolution and multiple operational periods through scenario-based simulations. Heating and cooling demands are estimated using degree-day metrics combined with building thermal transfer equations, assuming full electrification by renewable sources. Two strategies for heating electrification are investigated: assigning a predetermined share to each province, and optimizing the spatial distribution of electrification across provinces to meet overall targets. The model is applied to real-world data from Iran, which features diverse climates and substantial solar and wind potential. Results suggest widespread deployment of solar PV across most provinces, while wind development is concentrated in eastern regions such as Khorasan. Sensitivity analysis on storage system costs shows a balanced solar-wind combination when the storage prices is in the range $100-150/kWh. For the prices below or above this range respectively the solar or wind power plants dominate the generation mix. Transmission network expansion is most beneficial in provinces that serve as renewable hubs or major demand centers, though local supply is generally prioritized. Overall, findings indicate that the priority of heating electrification projects varies significantly among provinces, highlighting the importance of spatially differentiated planning strategies.