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文章摘要
市域范围内计及需求侧响应的电量和绿证分配的快速计算方案
Rapid calculation scheme for electricity quantity and green certificateallocation considering demand response within the municipal scope
Received:November 25, 2024  Revised:January 15, 2025
DOI:10.19753/j.issn1001-1390.2025.05.005
中文关键词: 需求侧响应  电量  绿证分配  Kriging元模型
英文关键词: demand response, electricity quantity, green certificate allocation, Kriging metamodel
基金项目:适应新型电力系统高比例新能源接入的电力中长期交易模式及关键技术研究
Author NameAffiliationE-mail
FAN Qiannan State Grid Tianjin Economic Research Institute qiannanfan@outlook.com 
WANG Zhongrong Tianjin Electricity Trading Center Co, Ltd cat_pipi@126.com 
YU Liya Tianjin Electricity Trading Center Co, Ltd 286209351@qq.com 
Liang Xiaohang Tsinghua University 1135469468@qq.com 
BAO Jie Tianjin Electricity Trading Center Co, Ltd baojiebj@163.com 
LIU Shuyong* State Grid Tianjin Economic Research Institute lsy78@126.com 
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中文摘要:
      目前,随着电力市场改革的进行,电力市场中电量和绿证分配方案是当下亟需解决的问题。针对市域范围内计及需求侧响应的电量和凭证的日前分配场景,构建了主从博弈模型,并通过Kriging模型代理优化的方式进行求解。同直接求解的方法相比,这种算法可以降低计算需求,提高计算速度,实现在若干区域中对应不同的绿证比例,实现电量和凭证在区域间的精准分配。通过所提到的模型计算,还能够对不同电量情况下的电力市场电量和绿证分配进行模拟,能够满足工程实际应用需求。
英文摘要:
      Currently, with the ongoing reform of the electricity market, the allocation schemes for electricity quantity and green certificates in the electricity market are urgent issues that need to be addressed. This paper focuses on the day-ahead allocation scenario of electricity quantity and certificates considering demand response within the municipal scope, constructs a leader-follower game model, and solves it through the Kriging model surrogate optimization method. Compared with direct solution methods, this algorithm can reduce computational requirements, improve calculation speed, and achieve precise allocation of electricity quantity and certificates among different regions with corresponding green certificate proportions. Through the calculation using the proposed model, it is also possible to simulate the allocation of electricity quantity and green certificates in the electricity market under different electricity quantity scenarios, which can be applied in practical engineering.
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