| 电力系统短期负荷预测模型设计 |
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| 引用本文： | 曾燕飞.电力系统短期负荷预测模型设计[J].广东电力,2011,24(4):49-53. |
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| 作者姓名： | 曾燕飞 |
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| 作者单位： | 广东技术师范学院自动化学院; |
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| 基金项目： | 广东技术师范学院科研项目(08kjy12) |
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| 摘 要： | 设计了一种基于反向传播(back propagation,BP)算法与模糊控制规则相结合的电力系统短期负荷综合预测模型,前者完成电力负荷中具有相对平稳的基本负荷分量,后者完成因天气变化、节假日等因素引起的随机负荷分量.由于模型引进了平滑系数、遗忘系数、不平均隶属函数等,提高了BP神经网络的学习速度,可充分反映负荷对温度...
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| 关 键 词： | 短期负荷 反向传播神经网络 Fuzzy规则 预测控制 |
Design of Short-term Load Forecasting Model in Power System |
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| ZENG Yan-fei.Design of Short-term Load Forecasting Model in Power System[J].Guangdong Electric Power,2011,24(4):49-53. |
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| Authors: | ZENG Yan-fei |
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| Affiliation: | ZENG Yan-fei(School of Automation,Guangdong Polytechnic Normal University,Guangzhou,Guangdong 510635,China) |
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| Abstract: | A short-term load forecasting model based on integration of back propagation(BP) algorithm with fuzzy rules is designed.The former fulfills base load components of relative stability in power load,and the latter fulfills random load components due to weather changes,holidays and so on.The introduction of smooth coefficient model,forgetting factor,unaverage subjection function improves learning speed of BP neural networks and fully reflects temperature sensitivity at load time. |
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| Keywords: | short-term load BP neural networks Fuzzy rules predictive control |
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