Existing guidance method of demand-side participating in flexible interaction do not fully consider the influence of social infor?mation such as preferential information on load

resulting in a large deviation between the actual role of the guiding cues and the expectedresults. In view of such situation

the Attention-LSTM model is used to forecast the load adjustment under the effect of social information

such as guiding cues. Coupon guidance method could be determined with this model. Take time of use tariff and coupon as an example

coupon guidance method considering the influence of preferential information is proposed

to guide consumers to change their electricityconsumption behaviors for less cost of purchasing electricity. And on this basis

a decision-making model of purchase-sale strategy consid?ering the influence of preferential information in multi-level electricity market is established

to maximize the revenue of electricity retail?ers and verify the feasibility and effectiveness of the proposed guidance method

which is solved by particle swarm optimization algorithmand CPLEX

to obtain the optimal guidance strategy and purchase strategy of electricity retailers. An example based on Australian datashows that the electricity purchasing and selling optimization model of electricity ratailers base on coupons guiding can effectively guidecustomers to actively participate in the interaction.