交直流混合微电网的能量管理

发布时间：2018-03-24 19:14

本文选题：交直流混合微电网　切入点：可再生能源预测　出处：《山东大学》2017年硕士论文

【摘要】：微电网在提高能源利用效率,以及电力系统的可靠性、灵活机动性与环保性等方面具有极大的发展潜力,是电力系统的研究热门。其中,交直流混合微电网有效地将交流微电网与直流微电网各自的优点结合了起来,是微电网未来发展的必然趋势。但现有对微电网能量管理的研究主要针对交流微电网,且优化管理目标多为运行成本最小化、污染排放最小化等,没有考虑微电网中变换器在变流过程中所产生的成本及损耗对结果产生的影响,而对于交直流混合微电网,变换器的成本及损耗将直接影响其交流区与直流区之间的能量流动。因此,为了使交直流混合微电网运行节能降损,更经济高效,对其中流动的能量进行优化管理是至关重要的。本文分别从信息输入侧、电源侧以及需求侧对交直流混合微电网的能量管理做了系统的研究,主要工作如下:首先介绍了课题的背景意义,对微电网及微电网能量管理的相关研究现状进行了总结。在结合微电网发展特点的前提下,对交直流混合微电网的结构特征做了必要介绍,并对其中各个单元进行了特性介绍与数学建模。其次对交直流混合微电网能量管理信息输入层中的可再生能源的输出功率进行了基于改进粒子群优化BP神经网络方法的预测。文中针对BP神经网络收敛慢,以及粒子群优化算法易陷入局部极值无法跳出的问题提出了可根据适应度变化情况而自适应调节权重的改进粒子群算法以优化BP神经网络,并以某电厂的可再生能源发电功率数据为例进行仿真验证。结果证明,相比于基本算法,本文所提的改进算法收敛速度更快,在利用本文算法对可再生能源发电功率进行预测时,预测精度也高于传统算法。再次对交直流混合微电网中的电源侧进行了优化调度,以所建立的交直流混合微电网模型为优化对象,建立了多目标优化模型,探究了是否考虑变换器变流成本以及其损耗对优化调度结果的影响。仿真结果证明了所提策略不但能减小系统中变换器的损耗,还提高了整体的经济性能,更具有实际意义。最后对交直流混合微电网能量管理中的需求侧进行了优化调度,首先阐述了需求侧参与优化的重要意义,其次对负荷进行了分类并对可平移负荷建模分析,最后通过仿真结果证明了可控负荷参与优化调度后不但大幅度提高了微电网运行的经济性,更能确保微电网运行的安全与可靠。
[Abstract]:Microgrid has great potential in improving energy efficiency, reliability, flexibility and environmental protection of power system. Ac / DC hybrid microgrid combines the advantages of AC microgrid and DC microgrid effectively, which is the inevitable trend of the future development of microgrid, but the current research on energy management of microgrid is mainly focused on AC microgrid. The optimal management objectives are mostly operating cost minimization, pollution emission minimization, etc., without considering the effect of converter cost and loss on the results, but for AC / DC hybrid microgrid. The cost and loss of the converter will directly affect the energy flow between the AC and DC areas. Therefore, in order to make the AC / DC hybrid microgrid run energy saving and loss reduction, it is more economical and efficient. It is very important to optimize the flow energy management. In this paper, the energy management of AC / DC hybrid microgrid is studied from the information input side, the power side and the demand side, respectively. The main work is as follows: firstly, the background significance of the project is introduced, and the research status of microgrid and microgrid energy management is summarized. The structural characteristics of AC / DC hybrid microgrid are introduced. Then the output power of renewable energy in the energy management information input layer of AC / DC hybrid microgrid is studied based on improved particle swarm optimization BP neural network. In this paper, the convergence of BP neural network is slow, The particle swarm optimization (PSO) algorithm is easy to fall into the local extremum and cannot jump out. An improved PSO algorithm, which can adaptively adjust the weight according to the fitness change, is proposed to optimize the BP neural network. The simulation results show that the proposed algorithm converges faster than the basic algorithm. The prediction accuracy of the proposed algorithm is also higher than that of the traditional algorithm. Thirdly, the power side of AC / DC hybrid microgrid is optimized. Taking the AC / DC hybrid microgrid model as the optimization object, a multi-objective optimization model is established. The effect of converter converter cost and its loss on the optimal scheduling results is discussed. The simulation results show that the proposed strategy can not only reduce the converter loss, but also improve the overall economic performance. Finally, the demand side of AC / DC hybrid micro-grid energy management is optimized. Firstly, the importance of demand-side participating in optimization is expounded, and then the load is classified and the translatable load modeling is analyzed. Finally, the simulation results show that the operation of microgrid not only greatly improves the economy of microgrid operation, but also ensures the safety and reliability of microgrid operation.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM727

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