家庭智能用电优化策略及管理系统研究

发布时间：2018-11-01 10:48

【摘要】：智能用电是智能电网的重要环节之一,对解决环境污染、资源紧缺等问题有着重要作用。家庭智能用电管理系统是智能用电在居民用户侧的延伸,本文研究智能用电环境下的家庭用电管理系统,通过优化控制策略合理调整家庭用电设备的使用,从而达到节约能源、减少用户电费支出、削减和转移负荷的目的。由于目前绝大多数居民用户均采用分时电价的计费方式,因而本文首先基于分时电价提出了家庭用电设备优化策略,以在满足用户舒适度的同时减少用电费用为目标,并利用人工蜂群遗传算法对优化模型进行了求解,仿真结果验证了该优化策略的有效性。由于分时电价的计费方式存在一定的缺陷,可能会造成峰谷倒置的现象。而能够反映供需变化的实时电价是未来电网的发展趋势,因而本文又基于实时电价提出了家庭智能用电的通用优化策略,在达到用户满意度要求前提下,实现减少用电费用的目标,该优化策略避免了在最低的价格区间内形成新的用电高峰。通过对单一用户和多用户的算例仿真验证了该优化策略的有效性。最后,为了实现本文提出的家庭智能用电优化策略,本文基于高级量测体系和需求响应理论对家庭智能用电管理系统的总体架构、功能架构以及网络架构进行了方案设计,包括系统的用电终端硬件架构设计,系统的软件架构设计以及用电监控终端的人机交互界面设计,实现了电价查询、用电查询、参数设置、远程遥控、用电策略管理、安全设置等功能。
[Abstract]:Intelligent power consumption is one of the important links of smart grid, which plays an important role in solving environmental pollution and resource shortage. The household intelligent power consumption management system is the extension of intelligent power consumption on the user side of the residents. This paper studies the household electricity management system under the intelligent power environment, and adjusts the use of the household electric equipment reasonably through the optimization control strategy, so as to save energy. The purpose of reducing user electricity bills, reducing and shifting loads. At present, most of the residents use the time-sharing pricing method, so this paper firstly puts forward the optimization strategy of household power equipment based on the time-sharing price, which aims at reducing the cost of electricity consumption while satisfying the comfort of the users. The optimization model is solved by artificial bee colony genetic algorithm, and the simulation results verify the effectiveness of the optimization strategy. Due to some defects in the charging method of time-sharing electricity price, it may cause the phenomenon of peak-valley inversion. And the real-time electricity price which can reflect the change of supply and demand is the development trend of the future power grid. Therefore, based on the real-time electricity price, this paper proposes a general optimization strategy of household intelligent electricity consumption, which can meet the requirements of customer satisfaction. To achieve the goal of reducing the cost of electricity, the optimization strategy avoids the formation of new peaks in the lowest price range. The effectiveness of the optimization strategy is verified by the simulation of single user and multi-user. Finally, in order to realize the household intelligent power consumption optimization strategy proposed in this paper, based on the advanced measurement system and demand response theory, the overall structure, functional framework and network architecture of the household intelligent power consumption management system are designed. It includes the hardware architecture design of the power terminal, the software architecture design of the system and the man-machine interface design of the power monitoring terminal. It realizes the electricity price inquiry, the electricity inquiry, the parameter setting, the remote control, the power use strategy management. Safety settings and other functions.
【学位授予单位】：南京师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM76

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