小波分析在电力系统短期负荷预测中的应用研究
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摘要
电力负荷预测是电力系统运行与控制的基础,也是电力市场运作的基础,在电力市场的条件下对负荷预测提出了准确性、实时性、可靠性、智能性的要求。本文主要研究如何利用小波分析法建立具有更高精度和计算速度的短时负荷预测模型。论文深入的探讨了负荷特性,明确了负荷是具有规律性的;通过对小波分析理论和算法的理解,确定了用小波分析进行负荷预测的可行性。
本文是在实现了用灰色模型进行1小时短期负荷预测的软件开发后,为了探讨小波分析法在负荷预测中的应用而进行的。
论文基于李普希兹指数和小波模极大值之间的关系,对小波函数的选取做了探讨。
论文基于小波分析与局部奇异性理论,通过对模极大值调整,达到检测并消除不良数据的目的,从而为负荷预测提供能反应其变化规律的真实历史数据。
通过小波分解将负荷分为低频负荷和高频负荷,不同频带反映了负荷的不同周期性。运用利用周期性预测的PAR模型对中、低频分量做预测,对于高频波动则运用可以实现历史数据更新的指数平滑技术预测。最后重构得到负荷预测值。从而达到预测精度和建模效率的统一。通过仿真计算验证了模型的可行性。
The load forecasting is always an important base for the operation and scheduling of power system, as well as for the well-running of power market. With the power market open, a precise, intelligent, reliable and real-time load forecasting is in need.In this paper, the writer tried to show a detailed process of using wavelet analysis to forecast short-term power load by building the relatively simple and fast mathematic modes. By analyzing the load character, the writer showed the periodicity of load time series; by analyzing the theory and arithmetic of wavelet analysis, the writer showed the feasibility of load forecasting by wavelet analysis.This paper was a further study on one-hour short-term load forecasting after the writer developing a load forecasting software package by grey mode in order to find out the advantage of wavelet analysis in load forecasting.On the basic theory of the relationship between Lipchiestz exponent and maximum module, the paper showed the way to choose a suitable wavelet function before analyzing the curve.On the basic theory of wavelet and part irregularity, the writer checked out the irregular signals and adjusted them to a more smooth level so that the regularity of signal could be obvious.By deposing the signal into convergence of low frequencies and high frequencies, which reflect the periodicity of series, the writer used PAR mode to deal with the mid and low frequency time series while dealing with high frequency series by exponential smoothing method. The reconstruction process allows the last forecasting result.The simulating result proved the feasibility and advantage of this method.
本文是在实现了用灰色模型进行1小时短期负荷预测的软件开发后,为了探讨小波分析法在负荷预测中的应用而进行的。
论文基于李普希兹指数和小波模极大值之间的关系,对小波函数的选取做了探讨。
论文基于小波分析与局部奇异性理论,通过对模极大值调整,达到检测并消除不良数据的目的,从而为负荷预测提供能反应其变化规律的真实历史数据。
通过小波分解将负荷分为低频负荷和高频负荷,不同频带反映了负荷的不同周期性。运用利用周期性预测的PAR模型对中、低频分量做预测,对于高频波动则运用可以实现历史数据更新的指数平滑技术预测。最后重构得到负荷预测值。从而达到预测精度和建模效率的统一。通过仿真计算验证了模型的可行性。
The load forecasting is always an important base for the operation and scheduling of power system, as well as for the well-running of power market. With the power market open, a precise, intelligent, reliable and real-time load forecasting is in need.In this paper, the writer tried to show a detailed process of using wavelet analysis to forecast short-term power load by building the relatively simple and fast mathematic modes. By analyzing the load character, the writer showed the periodicity of load time series; by analyzing the theory and arithmetic of wavelet analysis, the writer showed the feasibility of load forecasting by wavelet analysis.This paper was a further study on one-hour short-term load forecasting after the writer developing a load forecasting software package by grey mode in order to find out the advantage of wavelet analysis in load forecasting.On the basic theory of the relationship between Lipchiestz exponent and maximum module, the paper showed the way to choose a suitable wavelet function before analyzing the curve.On the basic theory of wavelet and part irregularity, the writer checked out the irregular signals and adjusted them to a more smooth level so that the regularity of signal could be obvious.By deposing the signal into convergence of low frequencies and high frequencies, which reflect the periodicity of series, the writer used PAR mode to deal with the mid and low frequency time series while dealing with high frequency series by exponential smoothing method. The reconstruction process allows the last forecasting result.The simulating result proved the feasibility and advantage of this method.
引文
[1] Nima Amjady, Short-term hourly load forecasting using time-series modeling with peak load estimation capability. IEEE Trans. On power systems V61.16,No.3 Aug. 2001
[2] Juberias, et al. New arima model for hourly load forecasting. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,1999,1:314-319
[3] ZhengTongxin, et al. Hybrid wavelet-Kalman filter method for load forecasting.Electric Power Systems Research, 2000, 54(1): 11-17.
[4] l.Daubechies, Ten Lectures on Wavelet,Capital City Press, (1992).
[5] C. K. Chui, An introduction to Wavelet, Academic Press, (1992).
[6] L. R. Rabiner, B. Gold:Theory And Application Of Digital Signal Processing,Prentice-Hall, Inc.(1975)
[7] Luan. L. and Xie. Z. (1995)The wavelets detection for the jump points of signals with additive stationary noises. Tech. Rept. No. 29 of Inst. of Math. Statist. Peking University.
[8]Grossmann A. Wavelet transform and edge detection. Stochastics processes in physics and engineering. HazeainMeds. Dodrecht, Reidel, 1986.
[9] Mallat S, Zero-crossings of a wavelet transform[J].IEEE Trans, on Information Theory, 1991, 37 (4).
[10]Mallat S,Zhang S. Characterization of signals from multiscale edges [J].IEEE Trans on Pattern Analysis and Machine Intelligence, 1992,14(7):710-732.
[11] Park DC et al. Electric Load Forecasting Using an Artificial Network Network IEEE Transactions on MRS 1991, 6 (2)
[12]Angeline P J,et al .An evolutionary algorithm that constructs recurrent Neural networks, IEEE Trans on Neural Networks[J],1994.5(l ),55~65.
[13 Niu Dongxiao e t a 1, Adjustment grey model for load forecasting of power systems the Journal of Grey System, 1994,6(2).
[14] Cao L,Hong Yet al, Predicting chaotic time series with wavelet network, Physica D,1995.
[15]M.T.Hagan and S.M Behr, The Time Series Approach to short Term Load Forecasting ,IEEE Transaction on power Systems, Vol. 5,No.4,Nov 1990,pp.1535-1544.
[16]B.R. Szkuta ,L.A. Sanabria, T.S. Dillon. Electric price short-term forecasting
using artificial neural networks[J], IEEE Trans on PWS, 1999, 14(3), 851-857.
[17] Ziad Alaywan, Jack Allen. California electric restrueturing: a broad description of the development of the California ISO[J].IEEE Trans on PWS, 1998, 13(4): 14451452.
[18] Agnaldo J. Rocha Reis, Member, IEEE, and Alexandre P. Alves da Silva, Senior member Feature Extraction via Multiresolution Analysis for Short-Term Load forecasting, IEEE Trans on PWS, 2005, 1～10
[19] Taylor, J. W.; Buizza, R.; Neural network load forecasting with weather ensemble predictions, Power Systems, IEEE Transactions on, Volume: 17, Issue: 3, Aug. 2002
[20] Ling, S. H.; Leung, F.H.F.; Lam, H.K.; Tam, P.K.S.; Short-term electric load forecasting based on a neural fuzzy network, Industrial Electronics, IEEE Transactions on, Volume 50, Issue: 6, Dec. 2003 Pages: 1305- 1316
[21] Gwo-Ching Liao; Ta-Peng Tsao; Integrating evolving fuzzy neural networks and tabu search for short term load forecasting, Transmission and Distribution Conference and Exposition, 2003 IEEE PES, Volume: 2, 7-12 Sept. 2003 Pages:755- 762 vol.2
[22] Zhou Ren-jun; Duan Xian-zhong; Optimal combined load forecast based on the improved analytic hierarchy process, Power System Technology, 2002. Proceedings. Power Con. 2002. International Conference, Volume 2, 13-17 Oct. 2002 Pages: 1096- 1100 vol.2
[23] 杜怀松,电力系统负荷预测技术,华东电力[J]2000.9,50-52.
[24] 张健,曹志东,负荷预测在电力市场中的作用,山东电力技术 2000(2)
[25] 胡昌华,李国华,刘涛,周志杰:基于MATLAB的系统分析与设计一小波分析,西安电子科技大学出版社,(2004).
[26] 牛东晓,曹树华,赵磊,张文文.电力负荷预测技术及其应用 北京:中国电力出版社,1998
[27] 程正兴:小波分析算法与应用,西安交通大学出版社(2001)。
[28] 刘忠贵,邸双亮:小波分析及其应用,西安电子科技大学出版社(1997)。
[29] 候志检,吴际舜,张绮雨。电力系统短期负荷预报的几种改进手段,电力系统及其自动化,Vol.20,No.7.1996。
[30] 鞠平.姜巍等.%点短期负荷预测方法及其应用。电力系统及其自动化。Vol.25 No.22 Nov.25.2001。
[31] 牛东晓.陈志业邢棉等.具有二重趋势性季节型电力负荷预测组合优化灰色神经网络模型.中国电机工程学报.Vo.22 No.Ⅰ Jan 2002。
[32] 张国江,邱家驹,李继红,基于模糊推理系统的多因素电力负荷预测,电力系统自动化,Vol.26,No.5,March 2002。
[33] 软计算方法和数据挖掘理论在电力系统负荷预测中的应用。电力系统及其自动化学报,Vol.15,No.1,Feb.2003。
[34] 崔锦泰,小波分析导论,西安交通大学出版社(1995)。
[35] 任震,小波分析及其在电力系统中的应用,中国电力出版社(2003)。
[36] 邓聚龙,灰色预测与理论,武汉,华中哩工大学出版社(1996)。
[37] 赵宏伟,任震,黄雯莹,基于周期自回归模型的短期负荷预测,中国电机工程学报,Vol.17 No.5 Sep.1997。
[38] 顾洁,应用小波分析进行短期负荷预测,电力系统及其自动化学报,Vol.15 No.2 Apr.2003。
[39] 邰能灵,侯志俭,李涛,蒋传文,宋炯,基于小波分析的电力系统短期负荷预测方法,中国电机工程学报,Vol.23 No.1 Jan.2003。
[40] 谢宏,陈志业,牛东晓,短期电力负荷预测的数据主成份分析,电网技术,Vol.24 No.1 Jan.2000。
[41] 陈志业,牛东晓,电网短期电力负荷预测系统的研究,中国电机工程学报,Vol.15 No.1 Jan.1995。
[42] 牛东晓,陈志业,邢棉,谢宏,具有二重趋势性的季节型电力负荷预测组合优化灰色神经网络模型,中国电机工程学报,Vol.22No.1 Jan 2002。
[43] 莫维仁,张伯明,孙宏斌,扩展短期负荷预测方法的应用,电网技术,Vol.27 No.5,May.2003。
[44] 高山,单渊达,小波奇异性检测在负荷数据纠错和平滑处理中的应用,中国电机工程学报,Vol.21 No.11 Nov.2001。
[45] 胡长流,基于多阈值处理的信号多尺度估计算法,西南交通大学学报,vol.36 No.1 Feb.2001。
[46] 任震,黄群古,黄雯莹,张勇军,4种新的小波变换及其在发电机故障信号分析中的应用,电力系统自动化,vol.25 No.1 Jan.10 2001。
[47] 魏伟,负荷预测的新进展,华北电力大学学报[[J],2002.1。
[48] 周佃民,赖菲,电力系统负荷预测与电价预测,继电器[J],2001.10.
[49] 唐忠,基于小波门限包的负荷预测方法的研究,电力系统自动化学报[J],2001.8.
[50] 刘秀玉,刘娇,电力短期负荷预测模型与软件开发,微机算计信息[[J],2001.3.
[51] 汪峰,周京阳,能量管理系统第4讲,电力系统自动化[J],1997,21(4):66.
[52] 藤菲,王宁,电力负荷预测技术,黑龙江电力[[J],2002.10.
[53] 谢宏,陈志业,基于小波分解与气象因素影响的电力系统日负荷预测模型研 究,中国电机工程学报[J]2001.5
[54] 黄民翔,小波分析方法在电力系统短期负荷预测中的应用,电力系统及其自动化学报[J]2002.6 8-12.
[55] 蒋正威,自然分形在负荷预测中的应用,电网技术,Vol.28 No.24 Dec.2004。
[56] 赵宏伟,任震,黄雯莹,考虑周周期性的短期负荷预测,中国电机工程学报,Vol.17 No.3 May.1997。
[2] Juberias, et al. New arima model for hourly load forecasting. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,1999,1:314-319
[3] ZhengTongxin, et al. Hybrid wavelet-Kalman filter method for load forecasting.Electric Power Systems Research, 2000, 54(1): 11-17.
[4] l.Daubechies, Ten Lectures on Wavelet,Capital City Press, (1992).
[5] C. K. Chui, An introduction to Wavelet, Academic Press, (1992).
[6] L. R. Rabiner, B. Gold:Theory And Application Of Digital Signal Processing,Prentice-Hall, Inc.(1975)
[7] Luan. L. and Xie. Z. (1995)The wavelets detection for the jump points of signals with additive stationary noises. Tech. Rept. No. 29 of Inst. of Math. Statist. Peking University.
[8]Grossmann A. Wavelet transform and edge detection. Stochastics processes in physics and engineering. HazeainMeds. Dodrecht, Reidel, 1986.
[9] Mallat S, Zero-crossings of a wavelet transform[J].IEEE Trans, on Information Theory, 1991, 37 (4).
[10]Mallat S,Zhang S. Characterization of signals from multiscale edges [J].IEEE Trans on Pattern Analysis and Machine Intelligence, 1992,14(7):710-732.
[11] Park DC et al. Electric Load Forecasting Using an Artificial Network Network IEEE Transactions on MRS 1991, 6 (2)
[12]Angeline P J,et al .An evolutionary algorithm that constructs recurrent Neural networks, IEEE Trans on Neural Networks[J],1994.5(l ),55~65.
[13 Niu Dongxiao e t a 1, Adjustment grey model for load forecasting of power systems the Journal of Grey System, 1994,6(2).
[14] Cao L,Hong Yet al, Predicting chaotic time series with wavelet network, Physica D,1995.
[15]M.T.Hagan and S.M Behr, The Time Series Approach to short Term Load Forecasting ,IEEE Transaction on power Systems, Vol. 5,No.4,Nov 1990,pp.1535-1544.
[16]B.R. Szkuta ,L.A. Sanabria, T.S. Dillon. Electric price short-term forecasting
using artificial neural networks[J], IEEE Trans on PWS, 1999, 14(3), 851-857.
[17] Ziad Alaywan, Jack Allen. California electric restrueturing: a broad description of the development of the California ISO[J].IEEE Trans on PWS, 1998, 13(4): 14451452.
[18] Agnaldo J. Rocha Reis, Member, IEEE, and Alexandre P. Alves da Silva, Senior member Feature Extraction via Multiresolution Analysis for Short-Term Load forecasting, IEEE Trans on PWS, 2005, 1～10
[19] Taylor, J. W.; Buizza, R.; Neural network load forecasting with weather ensemble predictions, Power Systems, IEEE Transactions on, Volume: 17, Issue: 3, Aug. 2002
[20] Ling, S. H.; Leung, F.H.F.; Lam, H.K.; Tam, P.K.S.; Short-term electric load forecasting based on a neural fuzzy network, Industrial Electronics, IEEE Transactions on, Volume 50, Issue: 6, Dec. 2003 Pages: 1305- 1316
[21] Gwo-Ching Liao; Ta-Peng Tsao; Integrating evolving fuzzy neural networks and tabu search for short term load forecasting, Transmission and Distribution Conference and Exposition, 2003 IEEE PES, Volume: 2, 7-12 Sept. 2003 Pages:755- 762 vol.2
[22] Zhou Ren-jun; Duan Xian-zhong; Optimal combined load forecast based on the improved analytic hierarchy process, Power System Technology, 2002. Proceedings. Power Con. 2002. International Conference, Volume 2, 13-17 Oct. 2002 Pages: 1096- 1100 vol.2
[23] 杜怀松,电力系统负荷预测技术,华东电力[J]2000.9,50-52.
[24] 张健,曹志东,负荷预测在电力市场中的作用,山东电力技术 2000(2)
[25] 胡昌华,李国华,刘涛,周志杰:基于MATLAB的系统分析与设计一小波分析,西安电子科技大学出版社,(2004).
[26] 牛东晓,曹树华,赵磊,张文文.电力负荷预测技术及其应用 北京:中国电力出版社,1998
[27] 程正兴:小波分析算法与应用,西安交通大学出版社(2001)。
[28] 刘忠贵,邸双亮:小波分析及其应用,西安电子科技大学出版社(1997)。
[29] 候志检,吴际舜,张绮雨。电力系统短期负荷预报的几种改进手段,电力系统及其自动化,Vol.20,No.7.1996。
[30] 鞠平.姜巍等.%点短期负荷预测方法及其应用。电力系统及其自动化。Vol.25 No.22 Nov.25.2001。
[31] 牛东晓.陈志业邢棉等.具有二重趋势性季节型电力负荷预测组合优化灰色神经网络模型.中国电机工程学报.Vo.22 No.Ⅰ Jan 2002。
[32] 张国江,邱家驹,李继红,基于模糊推理系统的多因素电力负荷预测,电力系统自动化,Vol.26,No.5,March 2002。
[33] 软计算方法和数据挖掘理论在电力系统负荷预测中的应用。电力系统及其自动化学报,Vol.15,No.1,Feb.2003。
[34] 崔锦泰,小波分析导论,西安交通大学出版社(1995)。
[35] 任震,小波分析及其在电力系统中的应用,中国电力出版社(2003)。
[36] 邓聚龙,灰色预测与理论,武汉,华中哩工大学出版社(1996)。
[37] 赵宏伟,任震,黄雯莹,基于周期自回归模型的短期负荷预测,中国电机工程学报,Vol.17 No.5 Sep.1997。
[38] 顾洁,应用小波分析进行短期负荷预测,电力系统及其自动化学报,Vol.15 No.2 Apr.2003。
[39] 邰能灵,侯志俭,李涛,蒋传文,宋炯,基于小波分析的电力系统短期负荷预测方法,中国电机工程学报,Vol.23 No.1 Jan.2003。
[40] 谢宏,陈志业,牛东晓,短期电力负荷预测的数据主成份分析,电网技术,Vol.24 No.1 Jan.2000。
[41] 陈志业,牛东晓,电网短期电力负荷预测系统的研究,中国电机工程学报,Vol.15 No.1 Jan.1995。
[42] 牛东晓,陈志业,邢棉,谢宏,具有二重趋势性的季节型电力负荷预测组合优化灰色神经网络模型,中国电机工程学报,Vol.22No.1 Jan 2002。
[43] 莫维仁,张伯明,孙宏斌,扩展短期负荷预测方法的应用,电网技术,Vol.27 No.5,May.2003。
[44] 高山,单渊达,小波奇异性检测在负荷数据纠错和平滑处理中的应用,中国电机工程学报,Vol.21 No.11 Nov.2001。
[45] 胡长流,基于多阈值处理的信号多尺度估计算法,西南交通大学学报,vol.36 No.1 Feb.2001。
[46] 任震,黄群古,黄雯莹,张勇军,4种新的小波变换及其在发电机故障信号分析中的应用,电力系统自动化,vol.25 No.1 Jan.10 2001。
[47] 魏伟,负荷预测的新进展,华北电力大学学报[[J],2002.1。
[48] 周佃民,赖菲,电力系统负荷预测与电价预测,继电器[J],2001.10.
[49] 唐忠,基于小波门限包的负荷预测方法的研究,电力系统自动化学报[J],2001.8.
[50] 刘秀玉,刘娇,电力短期负荷预测模型与软件开发,微机算计信息[[J],2001.3.
[51] 汪峰,周京阳,能量管理系统第4讲,电力系统自动化[J],1997,21(4):66.
[52] 藤菲,王宁,电力负荷预测技术,黑龙江电力[[J],2002.10.
[53] 谢宏,陈志业,基于小波分解与气象因素影响的电力系统日负荷预测模型研 究,中国电机工程学报[J]2001.5
[54] 黄民翔,小波分析方法在电力系统短期负荷预测中的应用,电力系统及其自动化学报[J]2002.6 8-12.
[55] 蒋正威,自然分形在负荷预测中的应用,电网技术,Vol.28 No.24 Dec.2004。
[56] 赵宏伟,任震,黄雯莹,考虑周周期性的短期负荷预测,中国电机工程学报,Vol.17 No.3 May.1997。
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