计及源荷低碳性与CCGP的两阶段优化调度

TWO-STAGE OPTIMAL SCHEDULING CONSIDERING CCGP AND LOW-CARBON NATURE OF SOURCE SIDE AND LOAD SIDE

在低碳经济背景下解决火电机组碳排放高和源荷预测误差导致的全局信息不匹配问题,提出计及源荷低碳性与机会约束目标规划(CCGP)的两阶段调度模型。首先,规划阶段兼顾源荷低碳经济性与安全性,建立需求响应后计及碳交易和源荷不确定的调度模型。其次,调整阶段计及预测信息不匹配影响和激励型负荷,以出力调整偏差最小优化实时出力。最后,通过确定性等价理论对模型转化,在改进IEEE 30节点系统中验证模型。结果表明:所提模型有效降低了系统碳排放量与运行成本,提高了风电消纳能力及评估备用容量缺额需求。

In the context of low-carbon economy,a two-stage scheduling model considering low-carbon nature of source side and load side and chance constrained goal programming(CCGP)is proposed to solve the global information mismatch problem caused by high carbon emission and source-load prediction error.Firstly,in the planning stage,considering the low-carbon economy and security of source-load,a scheduling model considering carbon trading and source-load uncertainty after demand response is established.Then,the adjustment stage takes into account the prediction information mismatch and incentive load,and optimizes the real-time output with the minimum output adjustment deviation.Finally,the model is transformed by deterministic equivalence theory and verified in the improved IEEE 30-bus system.The results show that the proposed model effectively reduces the system’s carbon emissions and operating costs,improves the wind power accommodation capacity and evaluates the demand for reserve capacity shortage.