考虑多重周期性的短期电价预测

ZHANG Xian; WANG Jianxue; WANG Xifan; WANG Xiuli

您当前的位置：

首页 >

文章列表页 >

考虑多重周期性的短期电价预测

更新时间：2025-08-13

- 考虑多重周期性的短期电价预测
- Automation of Electric Power Systems Vol. 31, Issue 3, Pages: 4-8(2007)
- 作者机构：
  
  1. 国家电网公司电力交易中心,北京市,100031
  2. 西安交通大学电气工程学院,陕西省,西安市,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2007
- 稿件说明：
移动端阅览
ZHANG Xian, WANG Jianxue, WANG Xifan, et al. [J]. Automation of electric power systems, 2007, 31(3): 4-8.
DOI：

ZHANG Xian, WANG Jianxue, WANG Xifan, et al. [J]. Automation of electric power systems, 2007, 31(3): 4-8. DOI：

摘要

考虑到电价各时段变化以及周末与工作日变化的差异，提出了区分周末的分时段短期电价预测模型。该模型首先将各日中同一时段的电价形成该时段的电价序列，再将各时段电价序列分为工作日电价序列和周末电价序列。这样形成了多个消除了日周期性和星期周期性的子电价序列，分别对各子电价序列进行预测以得到预测日电价。采用基于小波分析的广义回归神经网络对这些子电价序列分别进行提前一天的预测，各子电价序列的预测电价就形成了下一天的预测电价。采用该方法对西班牙电力市场电价进行了长时间的连续预测，并与已有的预测方法进行了详细的比较分析，研究表明该方法能够提供更准确的预测电价。

Abstract

The features of electricity prices in one period are different from that in another period. Furthermore， the price of weekday is generally higher than that of weekend. A period-decoupled short-term electricity price forecasting method based on separating weekend is presented. The prices of the same time period in each day form the period-decoupled price sequence， then each period-decoupled price sequence is separated into one weekday price sequence and one weekend price sequence. Thus some electricity price subsequences are obtained. The generalized regression neural network（GRNN） based on wavelet analysis is applied to forecast the day-ahead price for each electricity price subsequence respectively， and the hourly price of the forecasted day is obtained by seriating the forecasted prices of each subsequence. The proposed method is applied to forecast electricity price for Spanish electricity market in numerical examples， and it is compared with four existing methods. The comparisons of forecasting results indicate that the proposed method can provide more accurate predictions.

关键词

Keywords

references

Views

1670

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Double-branch Day-ahead Electricity Price Forecasting Based on Inception and Attention Mechanism

Data-driven Research on Electricity Markets: Challenges and Prospects

Hybrid Model-driven and Data-driven Approach to Price Forecasting in Bilateral Contract Electricity Markets

Related Author

BI Guihong

KONG Fanwen

HUANG Ze

CHEN Dongjing

LUO Zhao

YANG Yi

GUO Hongye

ZHENG Kedi

Related Institution

School of Electric Power Engineering, Kunming University of Science and Technology

Power China Guiyang Engineering Corporation Limited

State Key Laboratory of Control and Simulation of Power System and Generation Equipments, Tsinghua University

Department of Electrical Engineering, Tsinghua University

Faculty of Electronic Information & Electrical Engineering, Dalian University of Technology

⁰