含光伏出力的配电网动态重构与检修优化研究

发布时间：2018-12-08 20:11

【摘要】：随着全球环境污染和能源危机日益严峻,作为清洁可再生能源重要形式之一的光伏发电在电力系统中的渗透率越来越高。然而光伏发电受光照强度的影响,其输出功率具有不确定性,这对配电网的规划和运行带来了极大的影响。本文考虑到含光伏出力的配电网中越来越多的不确定因素,通过引入不确定性理论,研究含光伏出力的配电网相关问题,包括含光伏出力的配电网的动态重构及含光伏出力的配电网检修计划优化。首先,基于云量预报信息,考虑随机模糊因素对光伏出力的预测进行建模。考虑到光伏出力受光照强度的影响较大,而光照强度受云量的影响较大,因此采用云遮系数法来预测有云天气下的光照强度,考虑到云量预报的不确定性,引入不确定理论中的随机模糊理论对云量和云遮系数之间的不确定性进行分析建模,得到对应云量下的光照强度,进而利用HOMER中的光伏出力模型预测光伏发电系统的有功功率输出。其次,基于光伏出力预测模型,提出了一种含光伏出力的配电网动态重构优化方法。考虑光伏出力的变化情况,在一段时间内根据给定的开关动作次数的约束尽可能地减小系统的网络损耗,优化系统的网络运行结构。在IEEE-33节点配电系统上对提出的配电网动态重构方法进行了仿真实验,验证了所提方法的有效性和可行性。最后,基于不确定理论研究含光伏出力的配电网检修计划的优化。优化过程中考虑到配电网中存在的多种不确定因素,包括光伏出力的不确定性、负荷的波动性以及检修设备故障率的不确定性,建立了基于机会测度约束的检修计划优化模型,使检修成本和可靠性成本的悲观值最小化,兼顾考虑了经济性和可靠性,并采用两层混合优化算法对该模型进行求解。在IEEE-33节点配电系统上对提出的配电网检修计划优化方法进行了仿真实验,验证了所提方法的有效性和可行性。
[Abstract]:With the global environmental pollution and energy crisis becoming increasingly severe, photovoltaic power generation, as one of the important forms of clean and renewable energy, is becoming more and more permeable in the power system. However, photovoltaic power generation is affected by the intensity of light, and its output power is uncertain, which has a great impact on the planning and operation of distribution network. In this paper, considering the more and more uncertain factors in the distribution network with photovoltaic output, by introducing the uncertainty theory, the related problems of the distribution network with photovoltaic output are studied. It includes the dynamic reconfiguration of the distribution network with photovoltaic output and the optimization of the maintenance plan of the distribution network with the photovoltaic output. Firstly, based on cloud forecast information and considering random fuzzy factors, the prediction of photovoltaic force is modeled. Considering that the photovoltaic output is greatly affected by the light intensity and the light intensity is influenced by the amount of cloud, the cloud cover coefficient method is used to predict the light intensity in the cloud weather, and the uncertainty of the forecast of the cloud amount is taken into account. The stochastic fuzzy theory in uncertainty theory is introduced to analyze and model the uncertainty between cloud cover coefficient and cloud cover coefficient, and the illumination intensity under the corresponding cloud mass is obtained. Then the active power output of photovoltaic power generation system is predicted by using the photovoltaic output model in HOMER. Secondly, based on the photovoltaic force prediction model, a dynamic reconfiguration optimization method with photovoltaic output is proposed. Considering the variation of photovoltaic force, the network loss of the system is reduced as much as possible according to the constraints of the given switching times in a certain period of time, and the network operation structure of the system is optimized. Simulation experiments on the proposed dynamic reconfiguration method of distribution network on IEEE-33 node distribution system are carried out to verify the effectiveness and feasibility of the proposed method. Finally, based on uncertainty theory, the optimization of distribution network maintenance plan with photovoltaic output is studied. Considering many uncertain factors in distribution network, including the uncertainty of photovoltaic output, fluctuation of load and failure rate of overhauling equipment, a maintenance plan optimization model based on opportunity measure constraint is established. The pessimistic value of maintenance cost and reliability cost is minimized, the economy and reliability are considered, and the two-layer hybrid optimization algorithm is used to solve the model. A simulation experiment is carried out on the IEEE-33 node distribution system to verify the effectiveness and feasibility of the proposed method.
【学位授予单位】：浙江大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM711

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