为有效减少虚拟电厂运行过程中碳排放并应对可再生能源波动性带来的调度挑战，该文提出一种基于阶梯碳交易机制的两阶段鲁棒优化模型，旨在实现低碳性、鲁棒性与经济性之间的多维度权衡。首先，构建集成电转气与碳捕集设备的虚拟电厂系统模型，通过解耦 CO2 捕集与处理过程，以增强模型对碳减排的灵活性与适应性。其次，利用可调不确定集合对新能源出力波动性建模，在最不利情境下，以最小化购能成本、碳成本及需求响应补偿成本为优化目标建立鲁棒优化框架，并结合 C&CG 算法进行求解，以确保系统在不确定性环境下的最优调度策略。最后，通过引入阶梯碳交易机制，对电力调度进行精细化约束，避免因过度保守导致的经济损失。算例结果表明，该模型在增强系统抗风险能力和减少经济损失的同时，通过阶梯碳交易机制有效避免调度过度保守，实现了低碳与经济性兼顾的运行目标。
Low-carbon Economic-robust Optimization Scheduling of Multi-energy Complementary Virtual Power Plants
To effectively reduce carbon emissions during virtual power plant operations and address the scheduling challenges posed by renewable energy volatility,this paper proposes a two-stage robust optimization model based on a tiered carbon trading mechanism,aiming to balance low carbon emissions,robustness,and economic efficiency.First,a virtual power plant system model integrating power-to-gas technology and carbon capture equipment is constructed,enhancing carbon reduction flexibility by decoupling CO2 capture and processing stages.Second,an adjustable uncertainty set models renewable energy volatility,enabling a robust optimization framework with objectives to minimize energy procurement,carbon,and demand response costs under worst-case scenarios.This framework is solved by using a column-and-constraint generation algorithm(C&CG)to ensure optimal scheduling under uncertainty.Finally,a tiered carbon trading mechanism refines power dispatch constraints to mitigate economic losses from overly conservative scheduling.Case studies demonstrate that this model enhances system resilience and reduces economic losses while achieving a balanced low-carbon,economically efficient operational objective through the tiered carbon trading mechanism.
combined heat and powercarbon capturepower-to-gastiered carbon tradinguncertaintytwo-stage robust optimization
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维普
