基于加权Voronoi图的变电站优化规划
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摘要
随着我国城市电网建设改造的快速发展,科学合理的城市电网规划已经成为一项非常重要的任务。在城网规划中,将进行负荷及负荷分布预测、变电站选址与定容、配电网规划和无功优化等各项工作,其中在负荷分布预测基础上进行的变电站位置和容量的确定工作是必要的环节。其结果直接影响未来电力系统的线路走径、网络结构、电网投资、运行经济性及供电可靠性等。
变电站优化规划中,新建变电站的数量、地理位置、容量及供电范围都是未知的,并且各个变量之间相互影响,相互制约。针对变电站优化规划这一城市电网规划工作中的重要环节,本文提出了一种基于加权Voronoi图的变电站优化规划方法,可以最终完成对变电站数量、容量、站址及供电范围的优化。该方法首先给出一种确定新建站容量组合的数学模型,并采用整数规划的优化技术同时得到其最优解和几组次优解。进而,根据是否含有已有站,分别给出利用常规Voronoi图法及综合考虑规划区域地形特点、区域面积和负荷分布情况的坐标几何方法产生初始站址。在此基础上,通过对Voronoi图进行加权来考虑负荷分布不均匀、各站额定容量和负载率不同对变电站供电范围的影响,进行变电站供电范围的整体优化,并确定新建站站址。
详细的算例和结果分析表明,与传统的基于坐标几何的变电站优化规划方法比较,本文提出的基于加权Voronoi图的变电站优化规划方法能够在保证计算速度的前提下,得到更好的规划方案,进而节省了变电站建设和运行费用及线路和网损费用,大大提高了变电站优化规划工作的科学性和实用性,结果能够较好地满足规划工作的要求。
With the rapid development of expansion and reform for urban power systems in China, urban power system planning has become an urgent work. Urban distribution network planning includes several steps such as Load Forecasting, Substation Locating and Sizing, Distribution Network Planning and Reactive Sources Optimal Planning. Among these steps, Substation Locating and Sizing based on Load Forecasting is a complex but important step, because its result will affect many aspects directly such as power line routing, network structure, power network investment, operation economy level and power supply reliability.
In substation optimal planning, the number, site, capacity and service region of the new substation are to be caculated, and the relationship of these factors is very complex. Substation optimization planning plays an important role in urban network planning. This paper presents a novel method for substation planning based on weighted Voronoi diagram, which can optimize the quantities, locations, sizes and power supply areas of substation. Firstly, a mathematic model is proposed to get the capacity combinations of new substations, in which the optimum solution and suboptimum solutions can also be obtained simultaneously by integer programming. Then, according to the existence of substations, two methods are adopted to get the initial locations. One is ordinary Voronoi diagram method and the other is geometrical method which can consider local topographic characteristics, area of planning district and load distribution. The uneven load distribution, the different rated capacity and the load rates of each substation can affect the power supply areas seriously. To take account of the affections, a substation optimization method based on weighted Voronoi diagram is proposed to automatically decide the power supply areas of each substation and optimize the locations of new substations.
Real examples show that with the similar computing speed, the proposed method has a better substation optimization planning result than traditional substation optimization planning method based on geormetry coordinate, improves the scientificalness and adaptability of substation optimization planning result and can meet the practical planning requirements all the better.
变电站优化规划中,新建变电站的数量、地理位置、容量及供电范围都是未知的,并且各个变量之间相互影响,相互制约。针对变电站优化规划这一城市电网规划工作中的重要环节,本文提出了一种基于加权Voronoi图的变电站优化规划方法,可以最终完成对变电站数量、容量、站址及供电范围的优化。该方法首先给出一种确定新建站容量组合的数学模型,并采用整数规划的优化技术同时得到其最优解和几组次优解。进而,根据是否含有已有站,分别给出利用常规Voronoi图法及综合考虑规划区域地形特点、区域面积和负荷分布情况的坐标几何方法产生初始站址。在此基础上,通过对Voronoi图进行加权来考虑负荷分布不均匀、各站额定容量和负载率不同对变电站供电范围的影响,进行变电站供电范围的整体优化,并确定新建站站址。
详细的算例和结果分析表明,与传统的基于坐标几何的变电站优化规划方法比较,本文提出的基于加权Voronoi图的变电站优化规划方法能够在保证计算速度的前提下,得到更好的规划方案,进而节省了变电站建设和运行费用及线路和网损费用,大大提高了变电站优化规划工作的科学性和实用性,结果能够较好地满足规划工作的要求。
With the rapid development of expansion and reform for urban power systems in China, urban power system planning has become an urgent work. Urban distribution network planning includes several steps such as Load Forecasting, Substation Locating and Sizing, Distribution Network Planning and Reactive Sources Optimal Planning. Among these steps, Substation Locating and Sizing based on Load Forecasting is a complex but important step, because its result will affect many aspects directly such as power line routing, network structure, power network investment, operation economy level and power supply reliability.
In substation optimal planning, the number, site, capacity and service region of the new substation are to be caculated, and the relationship of these factors is very complex. Substation optimization planning plays an important role in urban network planning. This paper presents a novel method for substation planning based on weighted Voronoi diagram, which can optimize the quantities, locations, sizes and power supply areas of substation. Firstly, a mathematic model is proposed to get the capacity combinations of new substations, in which the optimum solution and suboptimum solutions can also be obtained simultaneously by integer programming. Then, according to the existence of substations, two methods are adopted to get the initial locations. One is ordinary Voronoi diagram method and the other is geometrical method which can consider local topographic characteristics, area of planning district and load distribution. The uneven load distribution, the different rated capacity and the load rates of each substation can affect the power supply areas seriously. To take account of the affections, a substation optimization method based on weighted Voronoi diagram is proposed to automatically decide the power supply areas of each substation and optimize the locations of new substations.
Real examples show that with the similar computing speed, the proposed method has a better substation optimization planning result than traditional substation optimization planning method based on geormetry coordinate, improves the scientificalness and adaptability of substation optimization planning result and can meet the practical planning requirements all the better.
引文
[1] 陈章潮,唐德光,城市电网规划与改造,北京:中国电力出版社,1998
[2] 全国电力系统城市供电专业工作网,城网动态,1998,3
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[22] M.R.Haghifam,M.Shahabi,Optimal Location and Sizing of HV/MV Substations in Uncertainty Load Environment Using Genetic Algorithm,Electric Power Systems Research,2002,63(1):37~50
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[29] 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,郑州大学学报(工学版),2003,24(4):16~18
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[31] 闫卫阳,郭庆胜,李圣权,基于加权 Voronoi 图的城市经济区划分方法探讨,华中师范大学学报(自然科学版),2003,37(4):567~571
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[37] Gahegan M,Lee I,Data Structures and Algorithms to Support Interactive Spatial Analysis Using Dynamic Voronoi Diagrams,Computer, Environment and Urban Systems,2000,24(5):509~537
[38] Aurenhammer F,Edelsbrunner H,An Optimal Algorithm for Constructing The Weighed Voronoi Diagram in The Plane,Pattern Recognition,1984,17(2): 251~257
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[2] 全国电力系统城市供电专业工作网,城网动态,1998,3
[3] 天津大学电力与能量系统研究所,城市电网规划计算机辅助决策系统,天津:天津大学,1995,3
[4] E.Lakervi,M.Nurmi,Present Status in Applying Mathematical Plannning Methods in AM/FM/GIS system,In:Proceedings of International Conference on Electricity Distribution-CIRED,Birtningham (UK),1997:2~5
[5] E.Lakervi,E.J.Holmes 著,范明天,张祖平,岳宗斌译,配电网络规划与设计,中国电力出版社,1999
[6] G.L.Thompson,D.L.Wall,A Branch and Bound Model for Choosing Optimal Substation Locating ,IEEE Trans. on Power Apparatus &System,1981 PAS-100(5):2683~2688
[7] M.A. El-Kady,Computer-aided Planning of Distribution Substation and Primary Feeder,IEEE Transaction on PAS-1036,1984:1183~1189
[8] E.Masud,An Interactive Procedure for Sizing and Timing Distribution Substation Using Optimization Techniques,IEEE Trans,PAS 93,1974:1281~1286
[9] T.Gonen , I.L.Ramirez-Rosado , Optimal Multi-stage Planning of Power Distribution System,IEEE Transaction on Power Delivery 2(2),1987:512~519
[10] D.M.Crawford,S.B.Holt,A Mathematical Optimization Technique for Locating and Sizing Distribution Substation and Deriving Their Optimal Service Areas,IEEE Trans. on Power Apparatus & System,1975,PAS-94(2):230~235
[11] D.I.Sun,D.R.Farris,P.J.Cote,et al,Optimal Distribution Substation and Primary Feeder Planning via the Fixed Charge Network Formulation,IEEE Trans. on Power Apparatus & Systems,1982,PAS-101(3):602~609
[12] D.L.Wall , J.E.D.Northcate-Green , Optimization Methods Applied to Distribution Planning,In:Proceedings of the American Power Conference,1978(40):1263~1271
[13] K.Aoki,K.Nara.T.Sutoh,et al,New Approximate Optimization Method for Distribution System Planning,IEEE Trans. on Power Systems,1990,5(1):126~132
[14] H.L.Wills,J.V.Aunstoos,Some Unique Signal Processing Application in Power System Planning,IEEE Trans. on ASSP,1979,27(6):685~697
[15] H.K.Temraz,M.M.A.Salama,A Planning Model for Siting, Sizing and Timing of Distribution Substation and Defining the Associated Service Area,Elsevier Power System Research,62,(2002),145~152,24,January,2002
[16] 刘巍,章健,变电站站址优化方法的研究,郑州轻工业学院学报(自然科学版),2003,18(1):31~34
[17] 赵军,石永海,专家系统在变电站选址中的应用,华北电力学院学报,1992(1):24~31
[18] 杨丽徙,王家耀,贾德峰,等,GIS 与模糊模式识别理论在变电站选址中的应用,电力系统自动化,2003,27(18):87~89
[19] J.Hyun-Soo,Dong-Joon,K.Jin-O,Neural-Tabu Algorithm in Optimal Routing of Distribution Network Considering Reliability Indices,Power Engineering Society Winter Meeting,2000,IEEE 4,2000:2340~2344
[20] 陈根军,李继洸，基于 Tabu 搜索的配电网络规划,电力系统自动化,2001,25(7):40~44
[21] 王成山,刘涛,谢莹华,基于混合遗传算法的变电站选址定容,电力系统自动化,2006,30(6):30~34
[22] M.R.Haghifam,M.Shahabi,Optimal Location and Sizing of HV/MV Substations in Uncertainty Load Environment Using Genetic Algorithm,Electric Power Systems Research,2002,63(1):37~50
[23] E.Miguez,E.Diaz-Dorado,Cidras.J,An Application of an Evolution Strategy in Power Distribution System Planning , In: Evolutionary Computation Proceedings,IEEE World Congress on Computational Intelligence,1998,241~246
[24] D.E.Bouchard,M.M.A.Salama,A.Y.Chikhani,Optimal Feeder Routing and Optimal Substation Sizing and Placement Using Guided Evolutionary Simulated Annealing,Proceeding 1995 Canadian Conference on Electrical and Computer Engineering,Montreal,Canada,Sep 1995,Vol.2,5-8Page(s):688~691
[25] 高炜欣,罗先觉,基于 Hopfield 神经网络的多阶段配电变电站的规划优化,电工技术学报,2005,20(5):58~64
[26] 高炜欣,罗先觉,朱颖,贪心算法结合 Hopfield 神经网络优化配电变电站规划,电网技术,2004,28(7):73~76
[27] DAI Hong-wei,YU Yi-xin,HUANG Chun-hua et al,Optimal Planning of Distribution Substation Location and Size-model and Algorithm. Electrical Power and Energy Systems,1996,18(6):353~327
[28] 张崇见,余贻鑫,严雪飞,中压配电变压器优化规划,电力系统自动化,1999,23(1):27~30
[29] 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,郑州大学学报(工学版),2003,24(4):16~18
[30] 杨丽徙,王金凤,王家耀,基于 Voronoi 图的配电变压器定位和供电区域划分,测绘通报,2004,5:33~35
[31] 闫卫阳,郭庆胜,李圣权,基于加权 Voronoi 图的城市经济区划分方法探讨,华中师范大学学报(自然科学版),2003,37(4):567~571
[32] Okabe A,Boots B,Sugihara K,et al,Spatial Tessellations:Concepts and Applications of Voronoi Diagrams (Second Edition),New York: John Wiley and Sons,2000
[33] 王新生,郭庆胜,姜友华,一种用于界定经济客体空间影响范围的方法—Voronoi 图,地理研究,2000,19(3):311~315
[34] Okabe A,Boots B,Sugihara K,Nearest Neighborhood Operations with Generalized Voronoi Diagram , International Journal of Geographical Information Systems,1994,8 (1):43~71
[35] 普雷帕拉塔 FP,沙莫斯 M.I.,计算几何,庄心谷译,北京:科学出版社,1992
[36] Held M. VRONI,An Engineering Approach to The Reliable and Efficient Computation of Voronoi Diagram of Point and Line Segments,Computational Geometry,2001,18 (1):95~123
[37] Gahegan M,Lee I,Data Structures and Algorithms to Support Interactive Spatial Analysis Using Dynamic Voronoi Diagrams,Computer, Environment and Urban Systems,2000,24(5):509~537
[38] Aurenhammer F,Edelsbrunner H,An Optimal Algorithm for Constructing The Weighed Voronoi Diagram in The Plane,Pattern Recognition,1984,17(2): 251~257
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