At present

a high proportion of renewable energy is integrated into smart distribution networks. The power outputs of renewable energy

such as wind and photovoltaic energy

are featured by randomness and uncertainties. In addition

different types of loads have different demand response characteristics with significant uncertainty. These parameters pose great challenges to the safety and reliability of the smart distribution network in the planning stage. Therefore

a renewable energy seasonal correlation model is proposed to exploit the complementary seasonal characteristics between wind and photovoltaic power outputs

thereby reducing the uncertainty of renewable energy. Moreover

a sub-DR model considering the uncertainties of user willingness for different types of loads is modelled

and an industrial load demand response pricing mechanism considering the interaction between supply and demand is developed. Finally

a stochastic planning model

which incorporates system operation considerations

is established to achieve synergistic coordination among generation

load

and storage in the smart distribution network. The numerical examples show that the proposed method can effectively alleviate the randomness and uncertainties of renewable energy power output in the IEEE 33-bus system and IEEE 123-bus system and ensure the stable operation of the system.