基于结构方程的电力市场效率优化路径方法

LIU Dunnan

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基于结构方程的电力市场效率优化路径方法

更新时间：2025-08-13

- 基于结构方程的电力市场效率优化路径方法
- Automation of Electric Power Systems Vol. 40, Issue 7, Pages: 36-41(2016)
- 作者机构：
  
  新能源电力系统国家重点实验室(华北电力大学),北京市,102206
- 作者简介：
- 基金信息：
- DOI：
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- Published：2016
- 稿件说明：
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LIU Dunnan. [J]. Automation of electric power systems, 2016, 40(7): 36-41.
DOI：

LIU Dunnan. [J]. Automation of electric power systems, 2016, 40(7): 36-41. DOI：

摘要

电力市场的交易既要遵从电力系统的物理规律，也要遵从市场的经济学规律，同时还受到市场参与者主观意愿等潜在的、非物理因素的影响。因此，电力市场的数学建模需要有效地发掘和描述这些影响电力系统运行的潜在变量及其相互作用关系。然而这些影响因素之间的关系错综复杂，难以定量计量，而结构方程模型的潜在变量分析方法，将因子分析与路径分析相结合，非常适合于电力市场的复杂影响因素建模，并且可以有效地量化影响电力市场效率的因素，建立电力市场实践过程中的“输出量”与“输入量”之间的定量关系模型，实现进一步的“反馈控制”，为未来的电力市场设计提供参考，为电力市场的进一步发展提供借鉴。因此，研究基于结构方程模型的电力市场效率的建模方法，为电力市场定量分析提供一种有效的数学工具。最后，结合中国2004至2005年东北区域电力市场的实际竞价数据进行实证建模验证了模型的有效性。

Abstract

Transactions in the electricity market have to comply not only with the physical laws in the power system

but also with the economic laws. At the same time

they are affected by a series of potential and non-physical factors

such as market participants' subjective intentions. Therefore

it is imperative to find a scientific mathematical modeling method to effectively explore and describe the impact of those potential variables as well as their interrelation. However

the relationship between these factors is complicated and difficult to measure quantitatively. An analysis of latent variables in structural equation modeling will be well suited for the electricity market by combining the methods of factor analysis and path analysis. And it can effectively quantify the factors that affect the efficiency

establish a quantitative relationship model in the process of electricity market practice between the “output” and “input”

realize further “feedback control” and provide a reference for electricity market design and development. Efficiency modeling based on structural equation modeling is proposed to provide an effective mathematical tool for the quantitative analysis in electricity market. Finally

the validity of this model is verified by the empirical analysis of a pilot electricity market in the northeast of China from 2004 to 2005. This work is supported by National Natural Science Foundation of China (No. 71401055).

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