【作者】 陈新宇；

【导师】 李燕青；

【作者基本信息】 华北电力大学（河北） ， 电力系统及其自动化， 2009， 硕士

【摘要】 配电网网架优化是配电网络规划中的重点和难点工作,对其进行优化规划可大大提高整体配电网运行的可靠性、经济性和安全性。针对配电网网架优化问题,本文选用年综合费用最小的单阶段模型作为目标函数。在建立以上配电网网架优化模型的基础上,本文在原始粒子群优化算法(PSO)中设置动态最大限制速度基础上,提出一种速度自适应粒子群优化算法。经过神经网络的测试表明,该算法在收敛速度和精度上都优于原始算法,并且参数选取灵活,容易实现。将改进算法应用于配电网网架优化规划中,并利用盲信息模糊评价理论进行满意度评价,得出该算法在实际网架优化中的实用性和优越性。更多还原

【Abstract】 Distribution network structure optimization is the focus of distribution network planning and difficult work, to optimize the planning can greatly enhance the overall operation of distribution network reliability, economy and security.For the distribution network structure optimization problem, this choice of the smallest annual comprehensive cost of single-stage model as the objective function. In the establishment of the above optimization model for distribution network structure, based on the article in the original particle swarm optimization (PSO) is set dynamically based on the maximum speed limit, proposed a rate of Adaptive particle swarm optimization algorithm. Through the neural network tests show that the algorithm convergence speed and accuracy are better than the original algorithm, and parameter select flexible and easy to implement. Will improve the algorithm is applied to optimize the distribution network structure planning, and use the theory of fuzzy evaluation of blind information satisfaction evaluation, obtained the algorithm actual truss optimization practicality and superiority.更多还原