Objective To address the challenges of strong uncertainties on both the supply and demand sides, as well as the difficulty in "electricity-carbon-green certificate" multi-objective coordination, faced by virtual power plants (VPP) during the green and low-carbon transition of new-type power systems, this paper constructs a VPP collaborative scheduling model integrating carbon trading and green certificate trading mechanisms.

Method First, targeting the randomness of wind and solar output on the supply side and the dynamics of load demand on the demand side, scenario-based stochastic optimization and scenario reduction clustering methods were adopted respectively to establish their uncertainty characterization models. Furthermore, carbon trading and green certificate trading costs were integrated into the scheduling model, with flexible resources such as energy storage and pumped storage taken into account, forming an "electricity-carbon-green certificate" collaborative optimization framework aimed at minimizing the total operating cost. To efficiently solve this complex model, a holistic swarm optimization (HSO) algorithm based on the metaphor-free optimization concept was proposed, which effectively enhanced the robustness and efficiency of the solution.

Result The study finds that: compared with existing similar uncertainty processing methods, the proposed supply-demand uncertainty modeling method proves more valuable for reference through verification on multiple datasets; the revenue is increased by 51.2% and 37.8% respectively compared with the scenarios of participating only in the electricity-green certificate market and the electricity-carbon market, verifying the effectiveness of the multi-market collaborative scheduling model in revenue enhancement. Participating in the electricity market, carbon market, and green certificate trading market can realize the superposition of multiple revenue sources.

Conclusion Case study analysis shows that, compared with traditional methods, the proposed model and algorithm can significantly improve carbon emission reduction benefits and green certificate revenue while ensuring economic efficiency, achieving multi-objective collaborative optimization.