考虑碳排放交易的日前调度双阶段鲁棒优化模型

Two-stage Robust Optimization Model of Day-ahead Scheduling Considering Carbon Emissions Trading

在应对风荷不确定因素影响的同时,如何在日前调度中实现电网的低碳经济运行,是当代电力系统面临的重要挑战。该文提出利用双阶段鲁棒优化模型应对风荷不确定因素,并利用碳交易机制平衡电网的经济性与环保性。同时为了响应政府的碳减排目标,提出碳配额交易量约束,并基于双阶段鲁棒优化模型对碳配额额度上下限进行求解。算法上,基于列和约束生成算法对模型进行求解,将主模型线性化为混合整数线性规划（mixedintegerlinear programming,MILP）模型,将子模型基于时间解耦后求解,提高计算效率。以IEEE118节点为算例并采用GAMS/CPLEX编程求解,分析低碳调度模型、碳配额交易量、碳交易价格以及不确定量对调度结果的影响,验证了提出模型的有效性。

ABSTRACT： How to achieve the low-carbon economic operation in day-ahead scheduling while coping with the influence of wind and load uncertainty is an important challenge for the modem power system, This paper proposed the two-stage robust optimization to cope with uncertainty, and balanced the economy and environmental protection of power grid with carbon emissions trading. Meanwhile, to response to the carbon emissions target of government, the constraint concerning carbon trading quota was involved in the model. And the upper and lower bound of quota were calculated based on two-stage robust optimization. In algorithm ways, the model was solved with a column-and- constraint generation method. The master problem was linearized to a mixed integer linear programming and the subproblem was time-decoupled to improve computational efficiency. Taking IEEE l 1 S-bus system for example and GAMS/CPLEX was utilized to solve proposed models. To verify the efficiency of proposed model, this paper further analyzed the impact on dispatch tragedy made by low-carbon dispatch model, carbon trading price, carbon trading quota and uncertainty.