考虑负荷时序特性的居民柔性资源低碳协同方法

在全球气候问题日益严峻的背景下，推动低碳发展具有重要意义，为实现居民侧用电低碳行为精准优化，提出一种考虑负荷时序特性的居民柔性资源低碳协同方法；文章分析了居民柔性资源的需求响应特性，对各类常见居民柔性资源进行分类；并综合考虑居民负荷的时间特性以及与外界环境因素的相关性，基于贝叶斯网络构造居民柔性资源用能概率模型，进一步分析了居民用电行为的时序特征，实现考虑时序特征的居民家电负荷舒适度建模；同时引入实时碳排放因子，考虑用户舒适度等约束，提出了考虑负荷时序特性的居民柔性资源低碳协同优化模型；仿真结果表明：所提优化模型能在提高用户用电经济性的同时，有效降低用户侧的碳排放量，实现经济性、低碳性多目标趋优。

Low Carbon Collaborative Method of Residential Flexible Resources Considering Load Timing Characteristics

In the context of increasingly severe global climate problems, it is of great significance to promote low-carbon development. In order to further optimize the low-carbon behavior of residential side electricity consumption, a low-carbon collaborative method of residential flexible resources was proposed considering the characteristics of load timing. This paper analyzes the demand response characteristics of resident flexible resources and classifies various common resident flexible resources. In addition, considering the time characteristics of residential load and its correlation with external environmental factors, the probability model of residential flexible resource energy use was constructed based on Bayesian network, and the time sequence characteristics of residential electricity consumption behavior were further analyzed, so as to realize the comfort modeling of household appliances load considering the time sequence characteristics. At the same time, the real-time carbon emission factor was introduced, and the constraints such as user comfort were taken into account. A low-carbon collaborative optimization model of residential flexible resources was proposed considering load timing characteristics. The simulation results show that the proposed optimization model can not only improve the electricity economy of the user, but also effectively reduce the carbon emission of the user side, so as to realize the multi-objective optimization of economy and low carbon.