基于实时电价的家庭能量管理系统设计与实现

发布时间：2017-12-31 01:41

本文关键词：基于实时电价的家庭能量管理系统设计与实现　出处：《南京理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：智能电网实现了信息的双向交互,用户在接收到电力市场信息之后,改变自身的电力消费行为的过程被称为需求响应。未来,越来越多的家庭用户将拥有自己的发电和储能设备。这类用户在进行需求响应时,需要综合考虑自身的产能,通过合理规划电器的用电时段,制定储能的充放电策略,实现自身能量体系的经济稳定运行。本文设计的能量管理系统结合日前实时电价和分布式发电出力预测,为负荷和储能制定日前规划,通过家庭局域网(HAN)向节点下发系统调度策略。主要工作包括:(1)针对HAN在本系统实现过程中的关键作用,选取ZigBee技术搭建这一无线传感网,针对拓扑结构、通信协议以及节点程序进行设计。(2)建立由所有可平移负荷工作时段规划组成的向量模型,以最小用电支出和最高分布式发电(DG)利用率为双重目标,使用离散二进制粒子群算法(Binary PSO)在可行域搜索最优解,完成可平移负荷的工作时段规划。(3)将蓄电池各时段末的荷电状态作为解向量,针对其工作特性约束,使用带动态罚函数的粒子群算法求解全天的最优充放电规划,规划利用蓄电池的充放电动作动态转移DG的出力,进一步减小供需差异和购电支出。(4)在搭建家庭混合供电系统模型的基础上,进行案例设计和算法实现。经过一系列对比试验,证明所设计的算法在提高供需匹配度和降低用户电费支出方面的有效性。(5)通过对系统通信机制的测试,完善系统软件及数据库的设计,使之成为一个具有交互性和实用性的家庭能量管理系统。
[Abstract]:Smart grid to achieve a two-way interactive information, after the user to power market information in the receiving process, change the power consumption behavior itself is called demand response. In the future, more and more home users will have their own power and energy storage equipment. This kind of user needs in response, need to consider their own production capacity, through reasonable planning appliances electricity charge and discharge time, making storage strategy, realize the stable operation of the economy itself energy system. The energy management system designed in this paper based on the real-time price and distributed generation output forecasting, load and storage before the date of making plan, through the home area network (HAN) scheduling system the strategy to the node. The main work includes: (1) for HAN in the system to achieve the key role in the process of choosing ZigBee technology to build a wireless sensor network, the topology structure, communication protocol And the node program design. (2) established by all vector model composed of translational work time planning, with minimal power expenditure and the highest utilization rate of distributed generation (DG) for the dual purpose of using discrete binary particle swarm optimization algorithm (Binary PSO) to search the optimal solution in the feasible region, complete the translation work planning time. (3) the battery state of charge at the end of each period as the solution vector, according to the working characteristics of constraints, optimal discharge planning using particle swarm algorithm for solving all day long with dynamic penalty function, output planning using dynamic battery charging and discharging action transfer DG, further reduce the differences in supply and demand and purchase expenditure. (4) to build a family based on hybrid power system model, case design and Realization of the algorithm. Through a series of comparative experiments, proved that the designed algorithm can improve the matching of supply and demand and reduce user The effectiveness of electricity expenditure. (5) by testing the communication mechanism of the system, we improve the design of system software and database, making it an interactive and practical family energy management system.

【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM73;TP311.52

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