基于权责匹配的分布式发电就近交易动态过网费两阶段测算方法
1.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;
2.上海交通大学 国家电投智慧能源创新学院,上海200240;
3.上海非碳基能源转换与利用研究院,上海200240;
4.郑州大学 电气与信息工程学院,郑州 450001网络出版日期: 2025-04-28
基金资助
国家自然科学基金项目(52107115)
A Two-Stage Calculation of Dynamic Network Usage Charge for Distributed Energy Nearby Trading Based on Right-and-Responsibility-Matching Principle
1. Key Laboratory of Control of Power Transmission and Conversion of the Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China;
2. College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China;
3. Shanghai Non-carbon Energy Conversion and Utilization Institute, Shanghai 200240, China;
4. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
Online published: 2025-04-28
严毅1, 平健2, 3, 严正1, 贾乾罡4 . 基于权责匹配的分布式发电就近交易动态过网费两阶段测算方法[J]. 上海交通大学学报, 0 : 1 . DOI: 10.16183/j.cnki.jsjtu.2024.462
Reasonable calculation of network usage charge is an important prerequisite for promoting the development of distributed energy nearby trading. The existing methods for calculating network usage charge are challenging to balance the needs of grid companies to recover transmission and distribution asset investment and the operational needs to guide distributed energy nearby trading in smoothing the net load curve. The paper proposes a two-stage dynamic network usage charge measurement method based on right-and-responsibility-matching principle: first, a right-and-responsibility-matching static network usage charge measurement method is proposed to ensure the fair and reasonable recovery of network construction costs; then, a time-sharing dynamic adjustment method for network usage charge is proposed to motivate the users of distributed energy nearby trading to smooth the net load curve peak-to-valley difference through price signals. On this basis, a bilevel optimization model is established, with a dynamic adjustment model of network usage charge in the upper level and a distributed energy nearby trading model in the lower level, and the value of the dynamic network usage charge is measured by solving the model. Finally, simulation results show that the proposed method for calculating dynamic network usage charge can effectively ensure the reasonable recovery of transmission and distribution asset investments for grid companies while significantly reducing the peak-to-valley difference rate of the net load curve.
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