基于多阶段双重博弈的多园区随机场景低碳分布式调度优化

Low-carbon Distributed Scheduling Optimization for Multi-park Stochastic Situations Based on a Multi-stage Dual Game

多园区综合能源系统在碳交易机制下存在多主体交互问题,保障信息隐私的基础上协调园区多场景下利益分配冲突,是实现综合能源系统低碳发展的关键。该文通过分析碳交易和绿证交易原理,构建运营商与多园区的绿证-碳排放联动双层交易框架。利用Stackelberg博弈理论建立中间运营商与多园区间领导跟随关系,制定上级购售电价引导园区制定机组出力计划。在此基础上,结合Nash博弈理论,实现多园区智能体间议价合作博弈,以保证多园区间收益与公平分配。随后,基于随机场景法与条件风险价值理论,提出一种多阶段双重博弈的多园区随机场景低碳分布式调度优化方法,并将改进交替方向乘子法与差分进化法相结合,解耦不同园区系统,实现分布式求解,保护各参与主体隐私同时提升收敛速度。最后,通过搭建多园区综合能源系统进行仿真,验证所提调度方法在新能源多场景下可优化园区利益矛盾,有效提升多园区整体效益,降低碳排放。

To achieve the integrated energy system's low-carbon development,it is essential to coordinate the conflict of interest distribution under various park scenarios on the basis of protecting information privacy.This paper analyzes the principles of carbon emission trading and green certificate trading to build a two-tier trading framework of green card-carbon emission linkage theory.With the aim of setting the electricity selling and purchasing price and directing the park in setting the unit production plan,the Stackelberg theory is employed to create a leader-follower relationship.For the purpose of realizing the bargaining and cooperative game among multi-parks and equitable distribution among multi-parks,the Nash theory is combined on this basis.Then,using the stochastic scenario method and conditional value at risk theory,a multi-stage dual game approach for multi-park stochastic scenario low-carbon distributed dispatch optimization is proposed.And the alternating direction multiplier method is combined with the differential evolution method to decouple various park systems and safeguard the privacy of each participant.Finally,the proposed scheduling method can improve the overall advantages of multi-park and lower carbon emissions while optimizing the competing interests of parks under new energy multi-scenarios through the case analysis.