上海交通大学学报

上海交通大学学报

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基于动态碳熵的主动配电网低碳能量管理策略（网络首发）

  

  1. 1.太原理工大学电气与动力工程学院；2.太原理工大学煤电清洁智能控制教育部重点实验室；3.清华大学电机系
  • 基金资助:
    山西省基础研究计划资助项目(202303021212059)； 国家自然科学基金资助项目（52407133）；

Low-carbon Energy Management in Active Distribution Networks Based on Dynamic Carbon Entropy

  1. （1. College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030002, China；2. Key Laboratory of Clean Intelligent Control of Coal Electricity of the Ministry of Education, Taiyuan University of Technology, Taiyuan 030002, China；3. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China）

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摘要： 在推进能源转型和双碳目标的背景下，新型电力系统中的主动配电网通过提高新能源渗透率和发挥需求侧管理作用可以实现规模化节能减排。为此提出一种基于动态碳熵的主动配电网两阶段低碳能量管理策略，以碳价为价格信号，引导柔性负荷参与低碳需求响应。首先，对碳熵模型进行分析，建立考虑储能的碳熵模型，细化需求侧碳排放特征。在此基础上，提出节点碳势评估指标，评估系统碳排放的清洁程度。随后，构建基于动态碳熵的主动配电网两阶段低碳优化调度模型，同时利用分时电价以及节点碳价的引导作用，促进新能源消纳，降低系统碳排放的同时有一定的削峰填谷作用。最后，在IEEE33节点系统设置多个场景来验证所提低碳能量管理模型的有效性和优越性，算例结果表明可以实现主动配电网低碳能量管理。

关键词: 主动配电网, 动态碳熵, 需求响应, 低碳能量管理

Abstract: In the context of energy transition and "dual carbon" goal, active distribution networks in the new power system can achieve scalable energy conservation and emissions reduction by increasing the penetration of renewable energy and leveraging demand-side management. To this end, a two-stage low-carbon energy management strategy based on dynamic carbon entropy theory is proposed. Carbon pricing serves as the price signal to encourage flexible loads to participate in low-carbon demand response. Firstly, the carbon entropy model is analyzed and an carbon entropy model considering energy storage is proposed, refining the carbon emission characteristics of the demand side. Building on this foundation, the evaluation index of node carbon potential is put forward to evaluate the cleanliness of carbon emission of the system. Secondly, a two-stage low-carbon optimization scheduling model is developed for active distribution networks based on the dynamic carbon entropy. The proposed model utilizes the guidance of time-of-use electricity prices and node carbon prices to promote the integration of new energy sources, reduce system carbon emissions, and play a role in peak shaving and valley filling. Finally, the proposed model's effectiveness is validated using an IEEE 33-node system, demonstrating the feasibility and advantages of the proposed low-carbon energy management method through case studies in active distribution networks.

Key words: active distribution network, dynamic carbon entropy, demand response, low-carbon energy management

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