考虑碳交易量自适应决策的输电网两阶段鲁棒规划

Two-Stage Robust Planning for Transmission Network Considering Adaptive Decision of Carbon Trading Volume

低碳化是新型电力系统未来发展趋势,在规划层面模拟水平年碳交易量对实现未来电网低碳经济运行具有重要作用.基于此,提出考虑碳交易量自适应决策的输电网鲁棒规划方法.首先,构建基于基准线法的碳配额交易成本计量方法,并考虑碳交易量约束,建立考虑风电和负荷不确定性的两阶段鲁棒规划模型.其次,利用松-紧解耦法将子问题按时间解耦为安全可行性检测子问题和低碳可行性检测子问题,并采用列和约束生成算法求解两阶段鲁棒规划模型,根据安全约束与碳配额交易量约束在各不确定场景下反馈的割信息,分析模型可行解空间与碳配额交易量阈值参数设置的映射关系,自适应决策碳交易量上下限.最后,以改进的IEEE-RTS 24节点系统进行算例仿真,分析低碳规划模型、碳配额交易量、碳价对规划结果的影响.结果表明所提模型实现了规划方案在经济性和低碳性方面的协同优化.

Low carbon is the future development trend of new power system,and the simulation of horizontal annual carbon trading volume at the planning level plays an important role in realizing the low-carbon economic operation of future power grid.Based on this understanding,a robust planning method for transmission network considering adaptive decision-making of carbon trading volume is proposed.First,a measurement method of carbon quota trading cost based on the baseline method is constructed,and a two-stage robust programming model considering the uncertainty of wind power and load is established considering the constraint of carbon trading volume.Then,the relax-and-enforce decoupling method is used to decouple the sub-problem into security feasibility detection sub-problem and low carbon feasibility detection sub-problem according to time,and the two-stage robust programming model is solved by using the column and constraint generation algorithm.Based on the cut information feedback from the security constraint and the carbon quota trading volume constraint in each uncertain scenario,the mapping relationship between the feasible solution space of the model and the setting of the threshold parameter of carbon quota trading volume is analyzed,and the upper and lower limits of carbon trading volume are adaptively decided.Finally,the improved IEEE-RTS 24-node system is simulated to analyze the impacts of the low-carbon planning model,carbon quota trading volume,and carbon price on the planning results.The results show that the proposed model realizes the coordinated optimization of the planning scheme in terms of economy and low carbon.