Unit commitment is one of the key enablers for achieving secure and economic operation in power systems. However

with the increasing integration of renewable energy at high penetration levels and growing complexity in grid infrastructures

conventional methods struggle to meet the grids demands for rapidity and precision. To address this challenge

the paper first analyzes the mathematical characteristics of the AC power flow constrained unit commitment model. Given the non-convex and nonlinear properties of the proposed model that introduce additional difficulties

this paper proposes a binary neighborhood dynamic extension method

which combines neighborhood dynamic analysis to offset the limitations of classical binary expansion theory and integrates quadratic convex relaxation techniques. Based on this approach

an efficient solution model for AC power flow constrained unit commitment model is developed

addressing the limitations of convex relaxation accuracy and the slow solving speed of binary expansion theory

and essentially eliminates non-convex nonlinearities and product terms between 0-1 integer variables and continuous variables in AC power flow and unit commitment models. The proposed approach can be directly solved using commercial solvers without requiring multiple iterations

which offers strong generality and scalability

making it applicable to various scenarios of power system optimization. Simulation results based on the IEEE39 system demonstrate that the method ensures efficient solutions to the unit commitment problem

with average power flow deviations of only 0.02%

unit output deviations below 0.1%

and approximately 60% improvement in solving efficiency.