For smart building with photovoltaic installations, most of the time it is in the situation of unbalanced supply and demand, and there is the problem of large dependence on the power grid, such as“surplus power on the Grid, lack of power to buy”. In order to enhance the rate of local consumption of new energy and reduce the cost of power consumption for users. A power sharing scheduling strategy based on the optimal aggregation mode of building users is proposed, taking into account the complementary behavior of different users. First, An aggregation model based on the landscape theory energy function driven by an non- equilibrium cobweb pricing model is established to seek the aggregation combination with the best effect of power sharing among users, and the package price of power sharing within the combination is set by the matching degree of supply and demand. Then taking into account the uncertainty of generators‘output and users’behavior, the light robust optimization theory is used to solve the scheduling strategy of power sharing within the resulting aggregation portfolio, and the effectiveness of the proposed model is verified through example simulations.