基于智能用电系统的家庭用电策略研究

发布时间：2019-06-05 14:52

【摘要】：近年来，关于高级量测体系智能用电技术的研究大都集中在系统的终端设备、通信技术及其基本功能方面，对基本功能数据应用的研究相对较少。因此如何使用户根据电网公司的价格信息及自身能源结构，更加经济合理的用电已成为智能用电技术发展的趋势。本文目的是研究设计一种基于智能用电系统的家庭用电策略，通过该策略能够合理的调整家庭用电设备工况，，使用户达到用电质量最高、节省电费开支的目标。文章首先根据目前高级量测体系研究情况设计了家庭智能用电系统架构，并分别介绍系统的主站、户内网络、本地信息管理终端以及相应的通信技术。然后从家庭用电规划和家庭能量管理两部分开展家庭用电策略的研究，家庭用电规划为家庭能量管理提供参与规划的用电设备电能消耗数据。家庭用电规划的研究是结合用户的用电习惯与电网公司分时电价信息，以用电设备的启动时间为决策变量，以家庭的电费支出最少为规划为目标，建立家庭用电规划模型。家庭能量管理模型的建立是针对采用市电电网与光伏并网发电联合供电的新型家庭，把家庭的能耗节点分成调节室内温度能耗、热水加热能耗、蓄电池储能以及其他用电设备能耗，以室内温度调节功率、热水系统的加热开关、蓄电池充放电功率为控制量，跟踪室内温度与热水温度需求，以室温、热水服务质量最高和节省电费支出为目标。文章对家庭用电规划模型和家庭能量管理模型分别设计基于遗传算法的优化方法，并分析了求解家庭能量管理模型控制变量的约束条件，给出了相应的调整方法。为了验证遗传算法在求解家庭用电模型的有效性，对算法进行了仿真实验，经仿真得到该方法能够有效的节省用户的电费支出。
[Abstract]:In recent years, most of the research on intelligent power consumption technology of advanced measurement system has focused on the terminal equipment of the system, communication technology and its basic functions, but the research on the application of basic functional data is relatively small. Therefore, how to make users use electricity more economically and reasonably according to the price information of power grid companies and their own energy structure has become the development trend of intelligent power technology. The purpose of this paper is to study and design a household power consumption strategy based on intelligent power consumption system. Through this strategy, the working conditions of household electrical equipment can be reasonably adjusted, so that users can achieve the goal of the highest quality of electricity consumption and saving electricity expenditure. Firstly, according to the research situation of advanced measurement system, the architecture of home intelligent power consumption system is designed, and the main station, indoor network, local information management terminal and corresponding communication technology of the system are introduced respectively. Then the household power consumption strategy is studied from the two parts of household power planning and family energy management. Household power planning provides household energy management with the data of power consumption of electrical equipment involved in the planning. The research of household electricity planning is to establish a household electricity planning model based on the user's electricity habit and the time-sharing electricity price information of the power grid company, taking the start-up time of the electrical equipment as the decision variable and the minimum household electricity expenditure as the goal. The establishment of household energy management model is aimed at a new type of household which adopts the combined power supply of municipal power grid and photovoltaic grid-connected power generation. The household energy consumption nodes are divided into indoor temperature energy consumption and hot water heating energy consumption. Battery energy storage and other electrical equipment energy consumption, indoor temperature regulation power, hot water system heating switch, battery charge and discharge power as the control, tracking indoor temperature and hot water temperature requirements, at room temperature, Hot water service quality is the highest and electricity expenditure is saved as the goal. In this paper, the optimization methods based on genetic algorithm are designed for household power planning model and family energy management model, and the constraint conditions for solving the control variables of family energy management model are analyzed, and the corresponding adjustment methods are given. In order to verify the effectiveness of genetic algorithm in solving household power consumption model, the simulation experiments are carried out, and the simulation results show that this method can effectively save the electricity cost of users.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM76

【共引文献】