配电变压器选址优化模型研究及系统开发
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摘要
配电网络作为电力系统到达用户的最后一环,在整个电网损耗中,配电网络的损耗占有相当大的比例,合理的配电网络直接关系到电力部门的经济效益、用户的用电安全。因此,研究配电变压器选址优化模型、开发相应的软件系统具有重要的理论和现实意义。本文的工作主要包括以下几点：
(1)进行了电力负荷预测研究。电力负荷预测是配电变压器选址优化的基础工作,通过分析比较各预测算法,建立了基于灰色系统理论的电力负荷预测模型,利用该模型对规划区未来用电量进行了预测分析。
(2)建立了配电变压器经济个数、经济容量及经济供电半径计算模型。规划区的负荷量、负荷量密度、电压等级等因数均影响到配电变压器的经济个数,根据相关参数建立计算模型,对规划区的变压器经济个数、经济容量及经济供电半径进行了计算。
(3)提出了一种配电变压器选址优化改进模型(M-TLOM)。山地、丘陵等地区,负荷点的海拔高度对变压器选址结果有着重要的影响,同时由于在布线过程中弧垂的存在,输电线长度实际不是直线距离。因此对配电变压器选址优化传统模型进行了改进,引进由于弧垂存在的线路修正系数a,并引进海拔高度对距离计算公式进行了修正,提出了一种配电变压器选址优化改进模型(M-TLOM)。
(4)开发了一套配电变压器选址优化软件系统。选择Visual Basic平台开发了一套配电变压器选址优化软件系统(DTLOS1.0),该系统具有电力负荷预测、变压器经济个数计算及配电变压器地理位置计算等三大主要功能。
(5)工程实例分析。为了验证改进模型的效果及系统的功能,根据某区域负荷点的分布情况,分别选用配电变压器选址优化传统模型、改进模型对实例进行了变压器的选址优化,结果表明,配电变压器选址优化改进模型可以达到降低配网损耗的目的。
As the last link to the user, distribution network's power loss occupies a large proportion in the whole power network loss. A proper distribution network is directly related to the economic benefit of power sector, electricity safety of the users. Therefore, studying on the location model of distribution transformer and development of the corresponding software has an important theory and practical significance. Main work in the paper is as following:
(1) Research on the power load forecasting. Power load forecasting is the basis of distribution transformer location optimization, through comparative and analysis of the prediction algorithm, building the power load forecasting model based on grey system theory, then using the model forecast and analysis the future electricity of planning area.
(2) Build the calculation model of distribution transformer economic number、economic capacity and economic power supply radius. The factors of power load、power load density、voltage rating and etc of the planning area are all influence to distribution transformer economic number、 economic capacity and economic power supply radius, in this paper, building the calculation model according the relevant parameter and calculating the transformer economic number、economic capacity and economic power supply radius of the planning area.
(3)Put forward a kind of Modified-distribution transformer location optimization model (M-TLOM). In mountain、hilly areas, altitude of the load points has an important impact to transformer location results, at the same time, because of the existence of the sag in cabling process, the transmission line length is not straight line distance actually. For the reasons above, the paper modified the traditional distribution transformer location optimization model, introducing the line correction coefficient (a) because of the existence of the sag, and modified the line distance computational formula according introduce the altitude of the load points, to put forward the modified-distribution transformer location optimization model (M-TLOM).
(4) Develop the software system of distribution transformer location optimization. In the paper, development a software system of distribution transformer location optimization (DTLOS1.0) based on Visual Basic6.0. This system includes three functions of power loud forecasting、transformer economic number calculating and transformer geographical position calculating.
(5) Engineering example analysis. In order to verify the effect of modified model and the function of the system, according to the loud points'distribution of a regional, two results of the distribution transformer location optimization obtained by using the traditional and modified model respectively, from the results, we can found that the modified model can reduce the loss of distribution network.
(1)进行了电力负荷预测研究。电力负荷预测是配电变压器选址优化的基础工作,通过分析比较各预测算法,建立了基于灰色系统理论的电力负荷预测模型,利用该模型对规划区未来用电量进行了预测分析。
(2)建立了配电变压器经济个数、经济容量及经济供电半径计算模型。规划区的负荷量、负荷量密度、电压等级等因数均影响到配电变压器的经济个数,根据相关参数建立计算模型,对规划区的变压器经济个数、经济容量及经济供电半径进行了计算。
(3)提出了一种配电变压器选址优化改进模型(M-TLOM)。山地、丘陵等地区,负荷点的海拔高度对变压器选址结果有着重要的影响,同时由于在布线过程中弧垂的存在,输电线长度实际不是直线距离。因此对配电变压器选址优化传统模型进行了改进,引进由于弧垂存在的线路修正系数a,并引进海拔高度对距离计算公式进行了修正,提出了一种配电变压器选址优化改进模型(M-TLOM)。
(4)开发了一套配电变压器选址优化软件系统。选择Visual Basic平台开发了一套配电变压器选址优化软件系统(DTLOS1.0),该系统具有电力负荷预测、变压器经济个数计算及配电变压器地理位置计算等三大主要功能。
(5)工程实例分析。为了验证改进模型的效果及系统的功能,根据某区域负荷点的分布情况,分别选用配电变压器选址优化传统模型、改进模型对实例进行了变压器的选址优化,结果表明,配电变压器选址优化改进模型可以达到降低配网损耗的目的。
As the last link to the user, distribution network's power loss occupies a large proportion in the whole power network loss. A proper distribution network is directly related to the economic benefit of power sector, electricity safety of the users. Therefore, studying on the location model of distribution transformer and development of the corresponding software has an important theory and practical significance. Main work in the paper is as following:
(1) Research on the power load forecasting. Power load forecasting is the basis of distribution transformer location optimization, through comparative and analysis of the prediction algorithm, building the power load forecasting model based on grey system theory, then using the model forecast and analysis the future electricity of planning area.
(2) Build the calculation model of distribution transformer economic number、economic capacity and economic power supply radius. The factors of power load、power load density、voltage rating and etc of the planning area are all influence to distribution transformer economic number、 economic capacity and economic power supply radius, in this paper, building the calculation model according the relevant parameter and calculating the transformer economic number、economic capacity and economic power supply radius of the planning area.
(3)Put forward a kind of Modified-distribution transformer location optimization model (M-TLOM). In mountain、hilly areas, altitude of the load points has an important impact to transformer location results, at the same time, because of the existence of the sag in cabling process, the transmission line length is not straight line distance actually. For the reasons above, the paper modified the traditional distribution transformer location optimization model, introducing the line correction coefficient (a) because of the existence of the sag, and modified the line distance computational formula according introduce the altitude of the load points, to put forward the modified-distribution transformer location optimization model (M-TLOM).
(4) Develop the software system of distribution transformer location optimization. In the paper, development a software system of distribution transformer location optimization (DTLOS1.0) based on Visual Basic6.0. This system includes three functions of power loud forecasting、transformer economic number calculating and transformer geographical position calculating.
(5) Engineering example analysis. In order to verify the effect of modified model and the function of the system, according to the loud points'distribution of a regional, two results of the distribution transformer location optimization obtained by using the traditional and modified model respectively, from the results, we can found that the modified model can reduce the loss of distribution network.
引文
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[16]Hong WC.Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm[J]. Energy,2011,36(9):5568-5578
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[24]许童羽,孙艳辉.基于GIS和改进微分进化算法的农网变电站选址定容[J].电力系统保护与控制,2009,37(22)：34～39
[25]杨丽徙,王金凤,段嘉平.变电站定位及供电区域划分的计算几何方法[J].郑州大学学报,2003,24(4)：16～18,45
[26]杨丽徙,朱向前,陈根永,等.基于Voronoi图的变电站优化规划方法[J].电力系统及其自动化学报,2006,18(5)：10～13,20
[27]王成山,刘涛,谢莹华.基于混合遗传算法的变电站选址定容[J].电力系统自动化,2006,30(6)：30～34,47
[28]陈章潮,顾洁,孙纯军.改进的混合模拟退火-遗传算法应用于电网规划[J].电力系统自动化,1999,23(10)：28～31,40
[29]赵云飞,陈金富.层次分析法及其在电力系统中的应用[J].电力自动化设备,2004,24(9)：85～87,95
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[32]曾涛.基于粒子群文化算法的变电站规划研究[D].天津：天津大学,2008
[33]徐珍霞,顾洁.离散粒子群优化算法在变电站选址中的应用[J].电气应用,2006,25(4)：35～38,115
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[2]康重庆,夏清,张伯明.电力系统负荷预测研究综述与发展方向的探讨[J].电力系统自动化,2004,28(17)：1-11
[3]廉巍巍.电力系统中长期负荷预测模型的研究[D].山西：太原理工大学,2007
[4]赵渊,张夏菲,谢开贵.非参数自回归方法在短期电力负荷预测中的应用[J].高电压技术,2011,37(2)：429～435
[5]James W Taylor. Short-Term Load Forecasting With Exponentially Weighted Methods [J]. IEEE Transactions On Power Systems,2012,27(1):458-464
[6]顾洁.电力系统中长期负荷预测理论与方法研究[D].上海：上海交通大学,2004
[7]Peng T.M, Hubele N.F, Karady G.G. Advancement in the Application of Neural Network for Short-term Forecasting. IEEE Trans on Power Systems [J].1992,7(l):250-257
[8]赵菁,许克明.神经网络和模糊理论在短期负荷预测中的应用[J].电力系统及其自动化学报,2010,22(3)：129～133
[9]陈霞.灰色预测模型及其在电力负荷预测中的应用研究[D].江西：南昌大学,2007
[10]黄昕颖.高阶灰色预测模型在短期电力负荷预测中的应用研究[J].机电信息,2011,(18)：26～27
[11]江朋,童述林,万志宏.组合预测模型在电力系统负荷预测中的应用研究[J].自动化与信息工程,2011,(1)：46～48
[12]殷子皓.电力负荷预测方法浅谈[J].贵州电力技术,2010,(9)：77～80
[13]鲍正江,胡海兵.一种基于神经网络的电力负荷预测方法[J].浙江电力,2004,(4)：10～13
[14]M Ghiassi, David K Zimbra, H Saidane. Medium term system load forecasting with a dynamic artificial neural network model[J]. Electric Power Systems Research,2006,76(5):302-316
[15]Wang Liying, Liu Zheng. RVM with wavelet kernel combined with PSO for short-term load forecasting in electric power systems [J]. Przeglad Elektrotechniczny,2012,88(1B):146-149
[16]Hong WC.Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm[J]. Energy,2011,36(9):5568-5578
[17]Dai Hongwei,Yu Yixin, Huang Chunhua, et al. Optimal Planning of Distribution Substation Location and Size-Model and Algorithm[J]. International Journal of Electrical Power and Energy System,1996,18(6):353-357
[18]张达,袁东宁.城市中压配电变压器的优化规划模型和算法[J].天津电力技术,2002,(4)：5-9
[19]周敏,程浩忠,周中明.优化理论在城市配电网变电站选址中的应用[J].供用电,2003, 20(2)：7-10
[20]牛卫平,刘自发,张建华,等.基于GIS和微分进化算法的变电站选址及定容[J].电力系统自动化,2007,31(18)：82～86
[21]刘文霞.城市配网规划的优化算法、评价体系与智能技术的研究[D].河北：华北电力大学,2009
[22]刘自发,张建华.基于改进多组织粒子群体优化算法的配电网络变电站选址定容[J].中国电机工程学报,2007,27(1)：105～111
[23]董永峰,杨彦卿,宋洁,等.基于改进粒子群算法的变电站选址规划[J].继电器,2008,36(5)：32～35
[24]许童羽,孙艳辉.基于GIS和改进微分进化算法的农网变电站选址定容[J].电力系统保护与控制,2009,37(22)：34～39
[25]杨丽徙,王金凤,段嘉平.变电站定位及供电区域划分的计算几何方法[J].郑州大学学报,2003,24(4)：16～18,45
[26]杨丽徙,朱向前,陈根永,等.基于Voronoi图的变电站优化规划方法[J].电力系统及其自动化学报,2006,18(5)：10～13,20
[27]王成山,刘涛,谢莹华.基于混合遗传算法的变电站选址定容[J].电力系统自动化,2006,30(6)：30～34,47
[28]陈章潮,顾洁,孙纯军.改进的混合模拟退火-遗传算法应用于电网规划[J].电力系统自动化,1999,23(10)：28～31,40
[29]赵云飞,陈金富.层次分析法及其在电力系统中的应用[J].电力自动化设备,2004,24(9)：85～87,95
[30]Hsu YY, Chen J.L. Distribution Planning Using Knowledge-Based Expert System[J]. IEEE Trans on Power Systems,1990,5(3):1514-1519
[31]陈根军,唐国庆.基于禁忌搜索与蚁群最优结合算法的配电网规划[J].电网技术,2005,29(2)：23～27
[32]曾涛.基于粒子群文化算法的变电站规划研究[D].天津：天津大学,2008
[33]徐珍霞,顾洁.离散粒子群优化算法在变电站选址中的应用[J].电气应用,2006,25(4)：35～38,115
[34]陈媛莉.变电站规划模型改进研究[J].广东电力,2010,23(8)：10-13
[35]于佳,朴在林,孙荣国,等.GIS和粒子群算法在农村变电站选址规划中的应用[J].农业工程学报,2009,25(5)：146～149
[36]杨丽徙,陈庆文,王玲.基于最小覆盖圆的配电网变电站选址优化[J].电力系统及其自动化学报,2008,20(2)：73～77
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