吕梁市中长期负荷综合预测模型的研究
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摘要
负荷预测是电网规划的基础性工作,为电网规划提供了必不可少的基础数据,其精度的高低直接影响着整个规划工作的优劣。影响负荷预测的因素很多且具有不确定性,预测的方法和模型众多且各有优缺点及适用场合,预测的思路也千差万别,所以准确的负荷预测难度很大。
本文分析和探讨了电网规划中负荷预测涉及的各项内容,包括预测对象、预测内容、预测流程、预测思路、预测原理、预测的模型等,对电网规划中负荷预测进行了整体性的分析、研究,其中重点是预测模型的分析和研究。
对于预测模型,本文对适用于电网规划中长期负荷预测的各种单一模型进行了详细分析,说明了它们的优缺点和适用范围。对组合预测模型也进行了分析研究,对其中常用的方法和当前研究的热点课题进行了探讨,并创新地提出了一种基于灰色关联度进行最优组合的方法,能够有效的提高预测精度。
在提出预测模型和组合预测的基础上,对吕梁市负荷特性进行了分析,利用单一模型及组合模型进行了负荷预测和结果校验,通过计算选择适用于吕梁市负荷预测的模型。
Load forecasting is one of the basic works of power network planning. It provides necessary and basic data for power network planning, the precision of these data decides the quality of power network planning. Load forecasting has many uncertain influence factors, and each method or model for load forecasting has its own advantages, faults and application range, and the predicting idea varies greatly, so it is of great difficulty to forecast load accurately.
This paper analyzes and discusses every aspects of load forecasting involved in the power networks planning, which including object, content, and flow, method, principle and model of load forecasting etc. The load forecasting in power network planning is tudied synthetically, which emphasizes on the model of load forecasting.
As to the model, each single model suited to the load forecasting in power net work planning is analyzed in detail, which advantages, disadvantages and application range are summarized. On combined forecasting, the model is studied in this paper, the method in common use and hot topic in current study is discussed, then a new model based gray correlation to different weight to the best combination, which can improve the prediction accuracy.
Lastly, based on the proposed model and combined forecasting, on the analysis to the load characteristic of Lvliang, Load forecasting and result calibration of Lvliang based on single model and the combination model is given, selecting by calculating the load forecast for the model Lvliang City.
本文分析和探讨了电网规划中负荷预测涉及的各项内容,包括预测对象、预测内容、预测流程、预测思路、预测原理、预测的模型等,对电网规划中负荷预测进行了整体性的分析、研究,其中重点是预测模型的分析和研究。
对于预测模型,本文对适用于电网规划中长期负荷预测的各种单一模型进行了详细分析,说明了它们的优缺点和适用范围。对组合预测模型也进行了分析研究,对其中常用的方法和当前研究的热点课题进行了探讨,并创新地提出了一种基于灰色关联度进行最优组合的方法,能够有效的提高预测精度。
在提出预测模型和组合预测的基础上,对吕梁市负荷特性进行了分析,利用单一模型及组合模型进行了负荷预测和结果校验,通过计算选择适用于吕梁市负荷预测的模型。
Load forecasting is one of the basic works of power network planning. It provides necessary and basic data for power network planning, the precision of these data decides the quality of power network planning. Load forecasting has many uncertain influence factors, and each method or model for load forecasting has its own advantages, faults and application range, and the predicting idea varies greatly, so it is of great difficulty to forecast load accurately.
This paper analyzes and discusses every aspects of load forecasting involved in the power networks planning, which including object, content, and flow, method, principle and model of load forecasting etc. The load forecasting in power network planning is tudied synthetically, which emphasizes on the model of load forecasting.
As to the model, each single model suited to the load forecasting in power net work planning is analyzed in detail, which advantages, disadvantages and application range are summarized. On combined forecasting, the model is studied in this paper, the method in common use and hot topic in current study is discussed, then a new model based gray correlation to different weight to the best combination, which can improve the prediction accuracy.
Lastly, based on the proposed model and combined forecasting, on the analysis to the load characteristic of Lvliang, Load forecasting and result calibration of Lvliang based on single model and the combination model is given, selecting by calculating the load forecast for the model Lvliang City.
引文
[1]牛东晓,曹树华,赵磊等.电力负荷预测技术及其应用[M].北京：中国电力出版社,1998：10-15
[2]M.Daneshdoost,M.lotfalian,GBunlroonggit,etc. Neural Network with Fuzzy Set Based Classification for Short-Term Load forecasting[J]. USA IEEE Trans Power systems, 2003,13(4):1386-1391
[3]E.Doveh,P.Feigin,D.Greig,etc. Experience with FNN models for Medium Term Power Demand Predictions[J]. USA IEEE Trans. Power Delivery,2000,14(2):538-546
[4]Mohammed,D.Park,R.Mechant,etc. Practical Experiences with an Adaptive Neural Network short term Load Forecasting System[J].USA IEE Trans. Power Delivery,1999,10(1):254-265
[5]K.Padmakumari, K.P.Mohandas, S.Thiruvengadam. Long term distribution demand forecasting using neuron fuzzy computations[J]. UK Electrical Power and Energy System.1999,21(2):315-312
[6]Bartels.Robert, Fiebig.DenzilG Residential End Use Electricity Demand Results from a Designed Experiment[J]. USA Energy journal,2000,21(2):51-57
[7]Khotanzad, R.C.Hwang, A.Abaye,et al. An Adaptive Modular Artificial Neural Network Hourly Load Forecaster and its Implementation at Electric Utilities[J]. USA IEEE International Conference on NN, Conference Proceedings,2001:1032-1036
[8]A.G.Bakirtzis, J.B.Throcharis, S.J.Kiartzis,etc. Short Term Load Forecasting Using Fuzzy Nerual Networks[J]. USA IEEE Trans Energy Conversion,2002,10(3):1518-1824
[9]N.VaPnik.The nature of statistical learning theory[M]. Newyork: SPringer-Verlag,1995.
[10]伍力,吴捷.负荷中长期负荷预测中一种改进的模糊聚类算法[J].电网技术,2000,24(1)：36-38
[11]耿光飞,郭喜庆.模糊线性回归法在负荷预测中的应用[J].电网技术,2002,26(4)：19-21
[12]于九如,杨泽华.模糊线性回归及其应用实例[J].系统工程理论与实践,1995(4)：32-37
[13]黄伟,费维刚.模糊理论在中长期预测中的应用[J].电力系统及其自动化学报,1999,11(4)：25-29
[14]陈章潮,顾洁.改进的相似优先比模型在浦东新区电力负荷预测中的应用[J].上海交通大学学报,29(3)：16-19
[15]李儒,吴捷.改进的优化组合预测方法在城网负荷预测中的应用[J].汕头科技.2002(1)：38-40
[16]何仰赞,温增银.电力系统分析[M].武昌：华中科技大学出版社,2002：25-34
[17]方向晖等.中低压配电网规划与设计基础[M].北京：中国水利水电出版社,2004(4)：34-54
[18]葛少云,尹页秀等.开发小区配电网规划[J].中国电力,2003,36：12-16
[19]余贻鑫,张崇见,张弘鹏.空间电力负荷预测小区用地分析[J].电力系统自动化,2001,25(6)：23-26
[20]王天华,王平洋,袁钦成.空间负荷预测中不确定因素的处理方法[J].电网技术,2001,25(1)：22-25
[21]徐辉.电力系统负荷预测方法及特点[J].山东电力技术,2004(6)：75-77
[22]郭秀花.Excel 2003在市场营销中的应用[M].电子工业出版社,2005：236-266
[23]温丽华.灰色系统理论及其应用[D].哈尔滨工程大学,2003：30-46
[24]Deng JL.The law of grey cause and white effect in GM(1,1)[J]. Journal of Grey System,1993(3):224-226
[25]Deng JL.Grey modeling in less data[J].The Journal of Grey System,1993(3):222-224
[26]周宏,黄审,戴韧等.几种灰色模型用于电力消费中期预测研究[J].电网技术,2000,24(7)：35-43
[27]邓聚龙.灰理论基础[M].武汉：华中科技大学出版社,2002：34-41
[28]顾洁,申刚,徐光虎.改进的电力系统中长期负荷预测方法研究[J].电力自动化设备,2002,22(6)：1-4
[29]李林川,吕冬,武文杰.一种简化的电力系统负荷线性组合预测法[J].电网技术,2002,26(10)：10-13
[30]Blagajac S, Krajcar S, Skrlec D. Computational tool to support spatial electric load forecasting[C]. Electrotechnical Conference,2000,3:1116-1119
[31]Kab Ju Hwang,Gwang Won Kin.Spatial load forecasting model for electrical distribution planning[J].KORUS 2004 Proceedings the 8th Russian-Korean International Symposium,2004,1:237-241
[32]Wu H C,Lu C N. A Spatial Modeling Technique for Small Area Load Forecast[J].IEEE Power Engineering Society Summer Meeting,2001,2:1205-1210
[33]Brown, R E,Hanson, A P, Hagan, D L.Long Range Spatial Load Forecasting Using Non-Uniform Areas[C].IEEE Transmission and Distribution Conference,1999,1:369-373
[34]Chow,M.-Y,Tram, H.methodology of urban re-development consideration in spatial load forecasting[J].IEEE Transactions,1997,12(2):996-1001
[35]马晓东,庄敏辉等.空间负荷预测在苏州工业园区电网规划中的应用[J].江苏电机工程,2006,(5)：24-26
[36]杨占刚.中短期负荷预测系统设计与实现[D].天津大学,2006：12-33
[37]聂威.组合预测模型在中山电力中长期负荷预测系统中的应用[D].电子科技大学,2007：13-19
[38]罗治强,张焰等.中压配电网中长期负荷预测实践[J].电力自动化设备,2003,23(3)：27-29
[39]叶旭东.地区电网负荷预测与优化模式理论及应用研究[D].辽宁工程技术大学,2006：23-26
[2]M.Daneshdoost,M.lotfalian,GBunlroonggit,etc. Neural Network with Fuzzy Set Based Classification for Short-Term Load forecasting[J]. USA IEEE Trans Power systems, 2003,13(4):1386-1391
[3]E.Doveh,P.Feigin,D.Greig,etc. Experience with FNN models for Medium Term Power Demand Predictions[J]. USA IEEE Trans. Power Delivery,2000,14(2):538-546
[4]Mohammed,D.Park,R.Mechant,etc. Practical Experiences with an Adaptive Neural Network short term Load Forecasting System[J].USA IEE Trans. Power Delivery,1999,10(1):254-265
[5]K.Padmakumari, K.P.Mohandas, S.Thiruvengadam. Long term distribution demand forecasting using neuron fuzzy computations[J]. UK Electrical Power and Energy System.1999,21(2):315-312
[6]Bartels.Robert, Fiebig.DenzilG Residential End Use Electricity Demand Results from a Designed Experiment[J]. USA Energy journal,2000,21(2):51-57
[7]Khotanzad, R.C.Hwang, A.Abaye,et al. An Adaptive Modular Artificial Neural Network Hourly Load Forecaster and its Implementation at Electric Utilities[J]. USA IEEE International Conference on NN, Conference Proceedings,2001:1032-1036
[8]A.G.Bakirtzis, J.B.Throcharis, S.J.Kiartzis,etc. Short Term Load Forecasting Using Fuzzy Nerual Networks[J]. USA IEEE Trans Energy Conversion,2002,10(3):1518-1824
[9]N.VaPnik.The nature of statistical learning theory[M]. Newyork: SPringer-Verlag,1995.
[10]伍力,吴捷.负荷中长期负荷预测中一种改进的模糊聚类算法[J].电网技术,2000,24(1)：36-38
[11]耿光飞,郭喜庆.模糊线性回归法在负荷预测中的应用[J].电网技术,2002,26(4)：19-21
[12]于九如,杨泽华.模糊线性回归及其应用实例[J].系统工程理论与实践,1995(4)：32-37
[13]黄伟,费维刚.模糊理论在中长期预测中的应用[J].电力系统及其自动化学报,1999,11(4)：25-29
[14]陈章潮,顾洁.改进的相似优先比模型在浦东新区电力负荷预测中的应用[J].上海交通大学学报,29(3)：16-19
[15]李儒,吴捷.改进的优化组合预测方法在城网负荷预测中的应用[J].汕头科技.2002(1)：38-40
[16]何仰赞,温增银.电力系统分析[M].武昌：华中科技大学出版社,2002：25-34
[17]方向晖等.中低压配电网规划与设计基础[M].北京：中国水利水电出版社,2004(4)：34-54
[18]葛少云,尹页秀等.开发小区配电网规划[J].中国电力,2003,36：12-16
[19]余贻鑫,张崇见,张弘鹏.空间电力负荷预测小区用地分析[J].电力系统自动化,2001,25(6)：23-26
[20]王天华,王平洋,袁钦成.空间负荷预测中不确定因素的处理方法[J].电网技术,2001,25(1)：22-25
[21]徐辉.电力系统负荷预测方法及特点[J].山东电力技术,2004(6)：75-77
[22]郭秀花.Excel 2003在市场营销中的应用[M].电子工业出版社,2005：236-266
[23]温丽华.灰色系统理论及其应用[D].哈尔滨工程大学,2003：30-46
[24]Deng JL.The law of grey cause and white effect in GM(1,1)[J]. Journal of Grey System,1993(3):224-226
[25]Deng JL.Grey modeling in less data[J].The Journal of Grey System,1993(3):222-224
[26]周宏,黄审,戴韧等.几种灰色模型用于电力消费中期预测研究[J].电网技术,2000,24(7)：35-43
[27]邓聚龙.灰理论基础[M].武汉：华中科技大学出版社,2002：34-41
[28]顾洁,申刚,徐光虎.改进的电力系统中长期负荷预测方法研究[J].电力自动化设备,2002,22(6)：1-4
[29]李林川,吕冬,武文杰.一种简化的电力系统负荷线性组合预测法[J].电网技术,2002,26(10)：10-13
[30]Blagajac S, Krajcar S, Skrlec D. Computational tool to support spatial electric load forecasting[C]. Electrotechnical Conference,2000,3:1116-1119
[31]Kab Ju Hwang,Gwang Won Kin.Spatial load forecasting model for electrical distribution planning[J].KORUS 2004 Proceedings the 8th Russian-Korean International Symposium,2004,1:237-241
[32]Wu H C,Lu C N. A Spatial Modeling Technique for Small Area Load Forecast[J].IEEE Power Engineering Society Summer Meeting,2001,2:1205-1210
[33]Brown, R E,Hanson, A P, Hagan, D L.Long Range Spatial Load Forecasting Using Non-Uniform Areas[C].IEEE Transmission and Distribution Conference,1999,1:369-373
[34]Chow,M.-Y,Tram, H.methodology of urban re-development consideration in spatial load forecasting[J].IEEE Transactions,1997,12(2):996-1001
[35]马晓东,庄敏辉等.空间负荷预测在苏州工业园区电网规划中的应用[J].江苏电机工程,2006,(5)：24-26
[36]杨占刚.中短期负荷预测系统设计与实现[D].天津大学,2006：12-33
[37]聂威.组合预测模型在中山电力中长期负荷预测系统中的应用[D].电子科技大学,2007：13-19
[38]罗治强,张焰等.中压配电网中长期负荷预测实践[J].电力自动化设备,2003,23(3)：27-29
[39]叶旭东.地区电网负荷预测与优化模式理论及应用研究[D].辽宁工程技术大学,2006：23-26