| 引用本文: | 王文婷,安爱民,保承家,等.基于改进代价敏感直推式支持向量机的发电企业
滥用市场力识别[J].电力系统保护与控制,2022,50(11):102-111. |
| WANG Wenting,AN Aimin,BAO Chengjia,et al.Identification of abuse of market power by power generation companies based on an improved cost-sensitive transductive support vector machine[J].Power System Protection and Control,2022,50(11):102-111 |
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| 摘要: |
| 随着现货市场的加速推进，准确地实时识别滥用市场力行为是电力市场违规行为管理的一项关键性任务。将改进的支持向量机与变分不等式求解算法结合，实现了在只有少量发电企业有标签数据情形下仍可以准确实时地识别发电企业滥用市场力行为。首先，结合电力市场实际情况，构造了滥用市场力识别指标体系，并基于电力市场高维数据的特点对数据进行降维。其次，针对发电企业有标签数据占总体数据小部分及数据不平衡的特点，提出了基于改进代价敏感直推式支持向量机的发电企业滥用市场力识别方法。然后，考虑到半监督算法求解时间较长，将求解问题转化为高效的变分不等式求解问题，并使用定制近邻法进行求解。最后，利用UCI数据集、电力市场仿真数据及实际电力市场数据进行试验。结果表明，该识别方法可以将滥用市场力的发电企业快速有效地识别出来。 |
| 关键词: 发电企业 市场力 直推式支持向量机 代价敏感 变分不等式 |
| DOI：DOI: 10.19783/j.cnki.pspc.211109 |
| 分类号: |
| 基金项目:国家电网有限公司科技项目资助(52094020001A) |
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| Identification of abuse of market power by power generation companies based on an improved cost-sensitive transductive support vector machine |
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WANG Wenting1, AN Aimin1, BAO Chengjia2, PING Chang2, CHENG Ziyun2
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(1. School of Electrical Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China;
2. State Grid Gansu Electric Power Company, Lanzhou 730050, China)
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| Abstract: |
| With the rapid advance of the spot market, it is critical to identify the abuse of market power accurately and in a timely fashion. This paper combines an improved support vector machine with a variational inequality solving algorithm to realize the accurate identification of the abuse of market power by power generation enterprises when only a few power generation enterprises have label data. First, based on the actual situation of the power market, it constructs an index system to identify the abuse of market power, and reduces the dimension of the high-dimensional data of the power market. Secondly, in view of the fact that the label data of power generation enterprises account for a small part of the total data and the data are unbalanced, a method to identify the abuse of market power of power generation enterprises based on the improved cost-sensitive transductive support vector machine is proposed. Considering the long solution time of the semi-supervised algorithm, the problem is transformed into an efficient solving problem of variational inequality, and a customized proximal point algorithm is used. Finally, UCI data set, power market simulation data and actual power market data are used to carry out experiments. The results show that this method can quickly and effectively identify power generation enterprises that abuse market power.
This work is supported by the Science and Technology Project of State Grid Corporation of China (No. 52094020001A). |
| Key words: power generation enterprises market power direct push support vector machine cost sensitive variational inequality |
