电力系统及其自动化学报2011，Vol.23Issue(3)：69-73,5.
短期负荷预测中对输入-输出关联度的改进
Improvement of Input-Output Correlations of Short-time Power Load Forecasting
袁斌 1方芩璐 2罗滇生 1王娟3
作者信息
- 1. 湖南大学电气与信息工程学院,长沙410082
- 2. 四川省成都电业局,成都610016
- 3. 63663部队技术部,乌鲁木齐841700
- 折叠
摘要
Abstract
In order to forecast the short—term power load more accurate, the meteorological factors in various regions across the province should be fully made use. Take Hunan Province as an example, the weight ratios of temperatures of the 14 regions of Hunan Province is got by using the Particle Swarm Optimization, which gives us a good weighted average global temperature. The optimized temperature is related to the power load of Hunan Province more closely. Take the optimized temperature as the input of the load forecast system, which can improve the precision of load forecasting. Examples show the effectiveness of the method.关键词
短期负荷预测/动态气温/关联度/粒子群Key words
short-time load forecasting/ dynamic temperature / correlations/ particle swarm分类
信息技术与安全科学引用本文复制引用
袁斌,方芩璐,罗滇生,王娟..短期负荷预测中对输入-输出关联度的改进[J].电力系统及其自动化学报,2011,23(3):69-73,5.
