In the context of the deep peak regulation auxiliary service market, the costs of unit peak regulation and auxiliary service fees have a significant impact on power generation companies. To address this issue, this paper proposes an optimization model for annual generation plan that takes into account deep peak regulation auxiliary services and multiple typical days. To achieve effective scene acquisition, a typical scene clustering method with considering the coupling of load and wind power is proposed, thereby effectively solving the simulation problem of multiple typical daily scenes in a month. By considering the deep peak regulation cost, auxiliary services compensation, benefit from electricity sales and carbon trading cost, the model established the income constraints of generation companies participating in the auxiliary service market to ensure profitability for market entities. As the model is a nonlinear mixed integer programming problem, this paper uses linearization strategy and CPLEX solver to achieve an efficient solution. Finally, simulation analysis is conducted using a modified example system, verifying the effectiveness of the proposed model.