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基于时间分解技术的中远期逐时负荷预测模型
引用本文:严通煜,杨迪珊,项康利,柯圣舟,林红阳.基于时间分解技术的中远期逐时负荷预测模型[J].电力系统保护与控制,2019,47(6):110-117.
作者姓名:严通煜  杨迪珊  项康利  柯圣舟  林红阳
作者单位:国网福建省电力有限公司经济技术研究院,福建福州,350012;国网福建省电力有限公司经济技术研究院,福建福州,350012;国网福建省电力有限公司经济技术研究院,福建福州,350012;国网福建省电力有限公司经济技术研究院,福建福州,350012;国网福建省电力有限公司经济技术研究院,福建福州,350012
基金项目:国网福建经研院研发咨询项目资助(SGFJJY00 GHJS1700062)“居民用电模型建立”;国家电网公司科技项目资助(XM2017020034670)“电能替代规划模型、政策模拟及应用研究”
摘    要:中远期电力负荷预测对于引导电网规划建设和提升电力系统资源优化配置具有重要意义。为解决当前中远期负荷预测时间尺度过大、预测精度有限的问题,利用时间分解技术,对电力负荷的长期趋势与短期特征分别进行建模分析,从而提出一种新型预测方法,将中远期负荷预测的时间尺度缩短至小时,实现中远期逐时负荷预测。算例分析表明,所建模型在中远期逐时负荷预测方面的性能优于现有的同类模型,具有较高的全局精度和稳定性。同时,能够有效呈现电力负荷的概率密度特征和极值特性,有望为中远期电力规划提供参考。

关 键 词:中远期负荷预测  逐时负荷  时间分解  多元线性回归
收稿时间:2018/4/4 0:00:00
修稿时间:2018/6/11 0:00:00

Mid-long term hourly load forecasting model based on time decomposition
YAN Tongyu,YANG Dishan,XIANG Kangli,KE Shengzhou and LIN Hongyang.Mid-long term hourly load forecasting model based on time decomposition[J].Power System Protection and Control,2019,47(6):110-117.
Authors:YAN Tongyu  YANG Dishan  XIANG Kangli  KE Shengzhou and LIN Hongyang
Affiliation:Economic and Technological Research Institute, State Grid Fujian Electric Power Company Limited, Fuzhou 350012, China,Economic and Technological Research Institute, State Grid Fujian Electric Power Company Limited, Fuzhou 350012, China,Economic and Technological Research Institute, State Grid Fujian Electric Power Company Limited, Fuzhou 350012, China,Economic and Technological Research Institute, State Grid Fujian Electric Power Company Limited, Fuzhou 350012, China and Economic and Technological Research Institute, State Grid Fujian Electric Power Company Limited, Fuzhou 350012, China
Abstract:Mid-long term load forecasting is of great significance for guiding the planning and construction of the power grid and improving the optimal allocation of power system resources. At present, the time scale of the medium and long term load forecasting is too large and the prediction precision is limited. To overcome this defect, this paper uses time decomposition technology to respectively analyze the long-term trend and short-term characteristics of power load, and then proposes a new prediction method, which will shorten the time scale of mid-long term load forecasting to hours and achieve mid-long term hourly load forecasting. The case study shows that the performance of the proposed model is better than the existing similar models. It has high global accuracy and stability. At the same time, it can effectively present the probability density characteristics and extreme value characteristics of power load. The proposed method is expected to provide reference for mid-long term planning of power grid. This work is supported byR & D Consulting Program of Economic and Technological Research Institute of State Grid Fujian Electric Power Company Limited:Establishment of Residential Electricity Model (No. SGFJJY00GHJS1700062) and Science and Technology Project of State Grid Corporation of China:Electric Energy Alternative Planning Model, Policy Simulation and Application Research (No. XM2017020034670).
Keywords:mid-long term load forecasting  hourly load  time decomposition  multiple linear regression
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