基于非机理性建模的电力现货市场异常电价预警方法

宋吉峰; 郑文彬; 陈明媛; 祁乐; 邹其

doi:10.19725/j.cnki.1007-2322.2024.0194

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基于非机理性建模的电力现货市场异常电价预警方法

电力市场 | 更新时间：2026-10-19

- 基于非机理性建模的电力现货市场异常电价预警方法
- Abnormal Electricity Price Warning Method for Electricity Spot Markets Based on Non-mechanistic Modeling
- 现代电力 2026年43卷第5期页码：952-960
- 作者机构：
  
  广西电网电力调度控制中心, 广西壮族自治区,南宁市,530000
- 作者简介：
  
  宋吉峰(1988)男，硕士研究生，工程师，研究方向为电力市场设计与运营，E-mail：songjifeng_1988@126.com
  郑文彬(1979)，男，硕士研究生，高级工程师，研究方向为电力市场设计与运营，E-mail：zhengwb.dd@gx.csg.cn
  陈明媛(1983)，女，博士研究生，高级工程师，研究方向为电力市场设计与运营，E-mail：MingyuanChen_gxu@163.com
  祁乐(1987)，男，硕士研究生，高级工程师，研究方向为电力市场设计与运营，E-mail：zouqi681209@163.com
  邹其(1993)，男，硕士研究生，工程师，研究方向为电力市场设计与运营，E-mail：806721400@qq.com
- 基金信息：
  
  广西电网公司科技项目(046000KK52222029)。
- DOI：10.19725/j.cnki.1007-2322.2024.0194
  中图分类号： 5
- 纸质出版：2026
- 稿件说明：
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宋吉峰, 郑文彬, 陈明媛, 等. 基于非机理性建模的电力现货市场异常电价预警方法[J]. 现代电力, 2026,43(5):952-960.

SONG Jifeng, ZHENG Wenbin, CHEN Mingyuan, et al. Abnormal Electricity Price Warning Method for Electricity Spot Markets Based on Non-mechanistic Modeling[J]. 2026, 43(5): 952-960.
宋吉峰, 郑文彬, 陈明媛, 等. 基于非机理性建模的电力现货市场异常电价预警方法[J]. 现代电力, 2026,43(5):952-960. DOI： 10.19725/j.cnki.1007-2322.2024.0194.

SONG Jifeng, ZHENG Wenbin, CHEN Mingyuan, et al. Abnormal Electricity Price Warning Method for Electricity Spot Markets Based on Non-mechanistic Modeling[J]. 2026, 43(5): 952-960. DOI： 10.19725/j.cnki.1007-2322.2024.0194.

摘要

大量新型市场主体在电力现货市场中兴起并享有一定的报价权，大幅增加了出清电价的灵活性、波动性、复杂性，提高了出现异常电价的风险。为保障电力现货市场安全稳定运营，有必要提出异常电价预警方法，提前防范和降低异常电价风险。首先，分析出清电价的异常表现与异常来源，从价格水平、价格波动、市场结构、成员行为、网络运行、系统管理、外部因素等7个方面构建出清电价状态预评估指标体系。其次，基于出清价格状态预评估指标体系，提出线性判别分析法(linear discriminant analysis

LDA)降维的BP神经网络预警方法和局部切空间排列法(local tangent space alignment

LTSA)降维的BP神经网络预警方法等两种不同的预警方法，在数据降维的基础上应用BP神经网络判断后续电价异常的可能性。最后，将所提出的异常电价预警方法应用于某地区电力现货市场的实际运营，结果显示，两种预警方法在异常电价预警中均有效，降维方法在给定的精度损失下能显著提高计算效率。

Abstract

A large number of new market participants have emerged in the electricity spot market and have been granted certain pricing rights. This development significantly improves the flexibility

volatility

and complexity of the clearing price

thereby elevating the risk of abnormal prices. To ensure the safe and stable operation of the electricity spot market

it is necessary to develop an abnormal price warning method to mitigate potential abnormal price risks in advance. Firstly

the abnormal performance and sources of the clearing price are analyzed. A pre-assessment indicator system for the state of the clearing price evaluation is constructed from seven aspects: price level

price volatility

market structure

participant behavior

network operation

system management

and external factors. Secondly

based on the pre-assessment indicator system

two different warning methods are proposed: a BP neural network warning method with dimensionality reduction using the linear discriminant analysis method and a BP neural network warning method with dimensionality reduction using the local tangent space alignment method. These methods apply BP neural networks to assess the possibility of subsequent price abnormalities after dimensionality reduction of the data. Finally

the proposed abnormal price warning methods are applied to the actual operational data of an electricity spot market in a certain region. The results indicate that both warning methods are effective for abnormal price warnings

and the dimensionality reduction methods significantly improve computational efficiency within a given accuracy loss.

关键词

Keywords

references

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