基于改进人工蜂群算法的输电网扩展规划研究

发布时间：2018-04-19 00:16

本文选题：输电网规划 + 人工蜂群算法　；参考：《广西大学》2014年硕士论文

【摘要】：随着输电网规模不断扩大,规划复杂性的增加,采用智能优化算法进行输电网规划是很有必要的。人工蜂群算法是一种新型的智能优化算法,因其具有计算速度快、参数少、鲁棒性好和易与其他算法结合等优点,近年来已经在许多领域得到了广泛的应用。本文对人工蜂群算法进行改进,并将其应用于输电网规划中,为输电网规划研究提供了一个全新的方向和路径。本文针对标准人工蜂群算法存在计算精度不高、容易过早陷入局部最优和迭代后期速度慢等缺点,对算法进行六点改进：(1)初始化阶段采用混沌初始化方法和反向学习策略生成初始蜜源位置；(2)引领蜂阶段引入变异算子和交叉算子来更新蜜源位置,并用退火选择策略接受新蜜源；(3)选择阶段采用锦标赛选择策略来计算每个蜜源被跟随蜂选择的概率；(4)跟随蜂阶段引入学习因子来更新蜜源位置,并用退火选择策略接受新蜜源；(5)为了提高当前最优蜜源的质量,对其进行动态的混沌局部搜索；(6)侦察蜂阶段对停滞进化的蜜源进行混沌搜索。通过对三个经典测试函数进行测试,结果表明,改进人工蜂群算法能有效加快收敛速度,提高搜索精度,其性能优于标准人工蜂群算法。建立以年新建费用与年网损费用之和最小的输电网单目标规划模型,并以Garver-6和Garver-18节点系统为例,验证改进人工蜂群算法应用于输电网规划中的有效性。最后建立以年新建费用最小、年网损费用最小、新建输电走廊费用最小和剩余输电容量费用最小为优化目标的输电网多目标规划模型,并用改进人工蜂群算法求解,通过算例验证本文提出的多目标规划模型的正确性和有效性。
[Abstract]:With the expansion of transmission network scale and the increase of planning complexity, it is necessary to adopt intelligent optimization algorithm for transmission network planning.Artificial bee colony algorithm is a new kind of intelligent optimization algorithm. It has been widely used in many fields in recent years because of its advantages of fast computing speed, less parameters, good robustness and easy to combine with other algorithms.In this paper, artificial bee colony algorithm is improved and applied to transmission network planning, which provides a new direction and path for transmission network planning research.In this paper, we aim at the shortcomings of standard artificial bee colony algorithm, such as low precision, easy to fall into local optimum prematurely and slow speed in late iteration, etc.In the initialization phase of the algorithm, chaotic initialization method and reverse learning strategy are used to generate the initial honey source position. The mutation operator and crossover operator are introduced to update the honey source position in the honeybee phase.Using the annealing selection strategy to accept the new honeycomb 3) the tournament selection strategy was used to calculate the selection probability of each honeybee. The learning factor was introduced in the following phase to update the honey source position.In order to improve the quality of the current optimal nectar source, a dynamic chaotic local search is carried out on the honeycomb to search the stagnant nectar source in the phase of reconnaissance bee.By testing three classical test functions, the results show that the improved artificial bee colony algorithm can effectively speed up the convergence speed and improve the search accuracy, and its performance is better than the standard artificial bee colony algorithm.A single objective programming model of transmission network is established based on the minimum sum of annual new cost and annual loss cost. Taking Garver-6 and Garver-18 node system as examples, the effectiveness of the improved artificial bee colony algorithm in transmission network planning is verified.Finally, a multi-objective programming model of transmission network with minimum annual new cost, minimum annual network loss cost, minimum cost of new transmission corridor and minimum cost of residual transmission capacity is established, and solved by improved artificial bee colony algorithm.An example is given to verify the correctness and validity of the proposed multiobjective programming model.
【学位授予单位】：广西大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM715

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