基于分布式发电和储能的家庭能量管理系统设计与优化调度算法研究

发布时间：2018-06-17 16:17

本文选题：家庭能量管理 + 高级测量体系　；参考：《浙江大学》2017年硕士论文

【摘要】：随着传统化石能源的短缺与环境保护需求的日益增长,近几年我国开始大力提倡分布式可再生能源的建设,出台了一系列相关的法律法规对制约分布式发电市场发展的诸多因素进行了政策调整。而随着分布式发电在普通家庭中的普及以及智能家居的快速发展,普通家庭的用电结构也迎来了变革的契机。当前的家庭用电缺少与大电网的信息交互和对家中用电设备的智能调度,导致用户对于家庭可再生能源利用效率低下,在用电高峰期却又不得不向大电网购电。这种不合理的用电结构不但使用户的用电费用增加,还让大电网在用电高峰期不堪重负,对大电网的稳定运行造成了威胁。为了指导用户更好的用电,基于分布式发电和储能的家庭能量管理系统应运而生。本文从框架设计和能量优化调度策略两个方面对家庭能量管理系统进行了研究。首先,提出了一个基于高级量测体系(AMI)的家庭能量管理系统框架。该框架采用本地信息管理终端作为家庭中数据存储和调度的核心,使用移动设备与用户进行交互。然后对家庭中的发电和用电设备分别进行了建模。提出了一种改进离散二进制粒子群算法(DBPSO)对家庭中的柔性负荷进行调度,并加入了基于实时电价(RTP)的储能调度策略进行优化。最后,设计了仿真对比案例,分析了算法的有效性和抗干扰性。
[Abstract]:With the shortage of traditional fossil energy and the increasing demand for environmental protection, in recent years, China began to vigorously promote the construction of distributed renewable energy. A series of related laws and regulations have been issued to adjust the policy of restricting the development of distributed power generation market. With the popularity of distributed power generation in ordinary homes and the rapid development of smart homes, the electricity structure of ordinary households has also ushered in the opportunity of change. At present, the lack of information interaction between household electricity and large power grid and intelligent dispatching of household power equipment lead to the low efficiency of household renewable energy utilization, but also have to purchase electricity from large power grid during the peak period of power consumption. This unreasonable structure not only increases the power consumption cost of the users, but also makes the large power grid unbearable during the peak period, which poses a threat to the stable operation of the large power grid. In order to guide users to use electricity better, the household energy management system based on distributed generation and energy storage came into being. In this paper, the family energy management system is studied from two aspects: frame design and energy optimal scheduling strategy. Firstly, a family energy management system framework based on Amis is proposed. The framework uses local information management terminal as the core of data storage and scheduling in the home, and uses mobile devices to interact with users. Then the electricity generation and electrical equipment in the home are modeled respectively. An improved discrete binary Particle Swarm Optimization (DBPSO) algorithm is proposed to schedule the flexible load in the home, and an energy storage scheduling strategy based on RTP is added to optimize the scheduling strategy. Finally, a simulation case is designed to analyze the effectiveness and anti-interference of the algorithm.
【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】：TM73;TP311.52

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