考虑预测误差不确定性的源-荷-广义储低碳经济动态优化调度  

Dynamic optimal scheduling of source-load-generalized storage low carbon economy considering prediction error uncertainty

作　　者：吴佩芝 徐天奇[1,2] 李琰 李晓兰[1] 崔琳 WU Peizhi;XU Tianqi;LI Yan;LI Xiaolan;CUI Lin(The Key Laboratory of Cyber-Physical Power System of Yunnan Colleges and Universities,School of Electrical and Information Engineering,Yunnan Minzu University,Kunming 650504,China;Yunnan Key Laboratory of Unmanned Autonomous System,Kunming 650504,China)

机构地区：[1]云南民族大学电气信息工程学院云南省高校电力信息物理融合系统重点实验室,昆明650504 [2]云南省无人自主系统重点实验室,昆明650504

出　　处：《重庆理工大学学报（自然科学）》2024年第5期276-285,共10页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(62062068)。

摘　　要：基于确定性模型的低碳经济调度方法无法准确描述不确定因素对电网碳排放的影响。据此,从系统层面考虑源-荷两侧不确定性,构建了一种低碳经济动态优化调度模型。采用混合高斯概率密度估计刻画风、光预测误差的不确定性,提出一种考虑净负荷预测误差的正负旋转备用容量概率约束方法;为减少系统的碳排放量,一从发电端考虑,引入碳交易机制,建立含有阶梯型碳交易成本的系统总运行成本最低的调度目标函数;二从用户层面考虑,将需求响应负荷同实际储能设备视为广义储能参与日前-日内滚动优化调度;在IEEE39节点系统进行不同场景分析,验证了所提的调度模型实现系统低碳、经济运行目标的有效性,也挖掘了需求响应负荷的减碳潜力。With the integration of a high proportion of new energy into the power grid,the current low-carbon economy scheduling method based on deterministic model is unable to accurately describe the impact of uncertainties on carbon emissions.With the consideration of the uncertainties on both sides of the source-load from the system level,a dynamic optimal scheduling model for low-carbon economy is built.First,the uncertainty of wind and light prediction errors is described by mixed Gaussian probability density estimation,and a probabilistic constraint method of positive and negative rotating reserve capacity considering net load forecasting errors is proposed.Second,to reduce the carbon emissions of the system:on the power generation side,the carbon trading mechanism is introduced to build the scheduling objective function with the lowest total operating cost of the system with stepped carbon transaction cost;on the users’side,the demand response load and the actual energy storage equipment are regarded as generalized energy storage to participate in the day-to-day rolling optimal dispatching.Finally,different scenarios are analyzed in the IEEE39 node system to verify the effectiveness of the proposed scheduling model to achieve low-carbon and efficient operation goals,tapping the carbon reduction potential of the demand response load.

关 键 词：碳交易机制 混合高斯 需求响应负荷 广义储能 净负荷预测误差 优化调度 

分 类 号：TM73[电气工程—电力系统及自动化]