A proactive active and reactive power collaborative optimization strategy considering low-carbon demand is proposed to address issues such as voltage exceeding limits caused by the high proportion of new energy connected to the distribution network. Firstly, in order to fully tap into the potential of carbon reduction in the system, a tiered carbon trading model is established to stimulate load side adjustment of electricity consumption behavior and achieve low-carbon response. Then, considering the operational requirements of the distribution network, a collaborative optimization model is constructed with the goal of minimizing network loss, voltage deviation, and comprehensive operating costs, and compensating equipment and flexible loads as decision variables. To overcome the drawbacks of slow convergence speed and susceptibility to local optima in the Pelican algorithm, an improved Pelican algorithm is proposed. In the early stage of the algorithm, Bernoulli chaotic mapping is used to initialize the population and sparrow vigilance mechanism and nonlinear inertia weights are introduced to balance and enhance the exploration and development capabilities of the algorithm. In the later stage of iteration, the Cauchy perturbation is used to enhance the algorithm′s ability to escape from local optima. Finally, the effectiveness of the proposed strategy and algorithm was verified through simulation of an improved IEEE33 node system.