A distribution network planning method based on the integration of operation and planning and coordinated with the transmission network

With the increasing integration of renewable energy into power grid, traditional roles transmission and distribution networks have become less distinct at operational level. The between network planning (DNP) operation is crucial to ensure grid stability. Existing research has primarily focused on collaborative control networks, leaving a gap in integrated DNP, since few works can handle integer variables. This study proposes method based coordinated with network. It aims minimize investment costs while considering local generation units, distributed renewables, constraints. Using heterogeneous decomposition algorithm (HGD), optimization model alternates two assisted by injected parameters for global optimality. A convolutional neural (CNN) surrogate then used rapidly optimize precise plans that coordinate Experimental results IEEE 30 69 cases demonstrate proposed approach offers valuable engineering benefits, reducing iteration counts up 20% improving accuracy compared other algorithms.