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基于用户分类的综合能源系统低碳运行策略

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综合能源系统(IES)是实现"双碳"目标的重要手段,然而系统内部不同类型用户用能行为各异,使得IES协调优化与低碳运行难度增加。为了充分发挥用户的主观能动性,基于用户行为分析对IES的用户行为进行建模,并通过卷积神经网络将用户分为激进型和保守型。构建IES运营商决策模型,确定电热能源的供应方式,针对不用类型用户设计相应的能源套餐。基于实际数据分析上述模型和方法的有效性,验证了用户分类在IES低碳运行中的价值。
Low-Carbon Operation Strategy of Integrated Energy System Based on User Classification
Integrated energy system(IES)is an important means to achieve the goal of"carbon peaking and carbon neutrality".However,different types of users in the system have different energy consumption behaviors,which makes the coordinated optimization and low-carbon operation of the integrated energy system more difficult.In order to give full play to the subjective initiative of users,the user behavior of the integrated energy system is modelled based on user behavior analysis,and users are classified into aggressive and conservative types by convolutional neural network(CNN).Then,the decision model of integrated energy system operator is constructed to determine the supply mode of electric heating energy,and the corresponding energy package is designed for different types of users.Finally,the effectiveness of the above models and methods is analyzed based on actual data,and the value of user classification in low-carbon operation of integrated energy systems is verified.

user classificationuser behaviorintegrated energy system(IES)low-carbon operation

张春雁、窦真兰、白冰青、王玲玲、蒋传文、熊展

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国网上海综合能源服务有限公司,上海 200023

上海交通大学电力传输与功率变换控制教育部重点实验室,上海 200240

用户分类 用户行为 综合能源系统 低碳运行

上海市科技计划资助项目

21DZ1208400

2024

上海交通大学学报
上海交通大学

上海交通大学学报

CSTPCD北大核心
影响因子:0.555
ISSN:1008-7095
年,卷(期):2024.58(1)
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