针对风电场最优环形集电线路方案搜索空间大、搜索时间长的问题,首次将频率图模型引入到集电线路规划问题中,提出基于频率图-蚁群算法的风电场环形集电线路优化方法。首先,根据风电机组的位置坐标计算出风电机组之间的距离矩阵;继而通过频率四边形,构建表示风电机组及其连接关系的频率图模型,将风电机组之间的距离矩阵转化为频率矩阵;在频率矩阵中,最优环形集电线路内机组连线的频率大于大部分其他机组连线的频率,根据该性质迭代删除大量不在最优环形集电线路方案中的机组连线,从而大幅缩小最优集电线路方案的搜索空间;利用蚁群算法,在缩小的搜索空间中搜索最优解,得到风电场最优或近优的环形集电线路方案。通过实例验证：应用删边方法,删除了约70%不在最优解中的机组连线,大大缩小了最优解的搜索空间,验证了频率图模型的优势。
Abstract
To tackle the issues of large search space and long computation time for searching the optimal circular collection line in wind farms, the optimization method is proposed based on the frequency graph-ant colony algorithm. Firstly, the distance matrix is constructed using according to the coordinates of wind turbines in a given wind farm. Secondly, the frequency graph model is computed with the frequency quadrilaterals, which illustrates the wind turbines and their connections. The distance matrix is converted into the frequency matrix. In the frequency matrix, the frequencies of the lines in the optimal solution are higher than those of most of the other lines between the wind turbines. Based on this property, a lot of the lines excluding from the optimal solution while between the wind turbines are eliminated. The search space of the optimal solution is significantly reduced. The ant colony algorithm is employed to detect the optimal solution within the reduced search space and the optimal or near-optimal solution is found. The experimental results illustrated that approximately 70% of lines that are not in the optimal solution are deleted. It greatly reduces the search space of the optimal solution and verifies the advantages of the frequency graph.
关键词
风电场 /
集电线路 /
路径规划 /
频率图 /
蚁群算法
Key words
wind farm /
electric lines /
path planning /
frequency graph /
ant colony algorithm
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参考文献
[1] 吴伊雯. 基于混合生态共生算法的海上风电场集电线路优化方法研究[D]. 北京: 华北电力大学, 2020.
WU Y W.Collection line optimization method for offshore wind farm based on hybrid symbiotic organism search algorithm[D]. Beijing: North China Electric Power University, 2020.
[2] 魏书荣, 樊潇, 黄苏融, 等. 海上风电场环形结构集电系统可用率等值计算方法[J]. 河海大学学报(自然科学版), 2016, 44(1): 89-94.
WEI S R, FAN X, HUANG S R, et al.Method for calculating equivalent availability of ring collector system for an offshore wind farm[J]. Journal of Hohai University (natural sciences), 2016, 44(1): 89-94.
[3] OUJANA S, AMODEO L, YALAOUI F, et al.Mixed-integer linear programming, constraint programming and a novel dedicated heuristic for production scheduling in a packaging plant[J]. Applied sciences, 2023, 13(10): 6003.
[4] 胡朝阳. 海上风电场布机及线缆优化设计[D]. 西安: 西安理工大学, 2023.
HU Z Y.Optimized design of offshore wind farm layout and cables[D]. Xi’an: Xi’an University of Technology, 2023.
[5] 李俊贤. 基于生成树算法的陆上风电场集电系统综合优化[D]. 成都: 电子科技大学, 2020.
LI J X.Comprehensive optimization of onshore wind farm collection system based on spanning tree algorithm[D]. Chengdu: University of Electronic Science and Technology of China, 2020.
[6] SLOWIK A, KWASNICKA H.Evolutionary algorithms and their applications to engineering problems[J]. Neural computing and applications, 2020, 32(16): 12363-12379.
[7] 谢七月, 刘广帅, 刘瑶, 等. 基于改进灰狼算法的定日镜场布局优化方法[J]. 太阳能学报, 2024, 45(11): 394-400.
XIE Q Y, LIU G S, LIU Y, et al.Improved grey wolf optimization algorithm for heliostats field layout[J]. Acta energiae solaris sinica, 2024, 45(11): 394-400.
[8] 龙嘉玲, 张存吉, 宁黎华, 等. 基于改进遗传算法的装配线平衡优化研究[J]. 机电工程技术, 2023, 52(8): 153-156, 225.
LONG J L, ZHANG C J, NING L H, et al.Research on assembly line balance optimization based on improved genetic algorithm[J]. Mechanical & electrical engineering technology, 2023, 52(8): 153-156, 225.
[9] 冀佳奇, 王永, 黎响. 基于布谷鸟算法的风电机组装配序列优化[J]. 太阳能学报, 2024, 45(4): 174-180.
JI J Q, WANG Y, LI X.Assembly sequence optimization for wind turbines based on cuckoo algorithm[J]. Acta energiae solaris sinica, 2024, 45(4): 174-180.
[10] HAN Z P, WANG Y, TIAN D.Ant colony optimization for assembly sequence planning based on parameters optimization[J]. Frontiers of mechanical engineering, 2021, 16(2): 393-409.
[11] 高博, 孙浩, 刘盛. 基于改进鲸鱼算法的太阳能热发电站镜场优化布置[J]. 太阳能学报, 2023, 44(10): 209-217.
GAO B, SUN H, LIU S.Heliostat field layout optimization of solar tower power station based on improved whale algorithm[J]. Acta energiae solaris sinica, 2023, 44(10): 209-217.
[12] WU Y, XIA T Q, WANG Y F, et al.A synchronization methodology for 3D offshore wind farm layout optimization with multi-type wind turbines and obstacle-avoiding cable network[J]. Renewable energy, 2022, 185: 302-320.
[13] DUAN S L, JIANG S L, DAI H, et al.The applications of hybrid approach combining exact method and evolutionary algorithm in combinatorial optimization[J]. Journal of computational design and engineering, 2023, 10(3): 934-946.
[14] WANG Y.An approximate method to compute a sparse graph for traveling salesman problem[J]. Expert systems with applications, 2015, 42(12): 5150-5162.
[15] DENG Q R, WANG Y, CHEN L P.A heuristic algorithm to compute a subgraph for TSP based on frequency quadrilaterals[J]. Journal of physics: conference series, 2021, 1995(1): 012041.
[16] WANG Y, REMMEL J.A binomial distribution model for the traveling Salesman Problem based on frequency quadrilaterals[J]. Journal of graph algorithms and applications, 2016, 20(2): 411-434.
[17] REINELT G.TSPLIB--a traveling salesman problem library [EB/OL]. http://comopt.ifi.uniheidelberg.de/software/TSPLIB95/, 1991.
[18] WANG Y, REMMEL J.A method to compute the sparse graphs for traveling salesman problem based on frequency quadrilaterals[C]//Lecture Notes in Computer Science, Kuwait City, Kumait, 2018, 10823:286-299.
[19] 张纪会, 徐心和. 一种新的进化算法: 蚁群算法[J]. 系统工程理论与实践, 1999, 19(3): 84-87.
ZHANG J H, XU X H.A new evolutionary algorithm-ant colony algorithm[J]. Systems engineering-theory & practice, 1999, 19(3): 84-87.
[20] GE D D, QI H F, Wang Z Z, et al.Cardinal optimizer (COPT) user guide[EB/OL]. https://guide.coap.online/copt/en-doc, 2023.
基金
国家重点研发计划“战略性科技创新合作”重点专项资助（2022YFE0207000）; 中央高校基本科研业务费项目（2024JC006）
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