摘要
电力需求管理机制可通过动态定价策略减少各建筑用电高峰时期的用电量。为使此类管理机制更具有可用性与扩展性,本文提出一种方法来预测家用设备的使用以自动获得电力管理机制的输入参数。文中通过无线功率计传感器网络(Wireless Power meter Sensor Network,WPSN)监控家用设备用电消耗,依据人们使用设备的习惯呈现周期性的特点,每24小时处理一次传感器提供的数据来预测次日哪种设备将会使用以及开始使用的时间。仿真与实验验证了预测设备使用的有效性,预测信息为负载需求管理系统自动输入参数,避免了用户复杂的手动设置。
Electricity demand management mechanisms can reduce buildings power demand at peak hours, by means of dynamic pricing strategies. In order to make these kinds of mechanisms more usable, this paper proposed a method for predicting the usage of household appliances to automatically provide inputs to electricity management mechanism. In our architecture we use a wireless power meter sensor network （WPSN） to monitor home appliances consumption. Based on the characteristics of people habits in using a device being nearly periodic, data provided by sensors are then processed every 24 hours to forecast which device will be used on the next day, at what time and for how long. The simulation and experimental test validate the effectiveness in predicting devices usage, and this information provides the input parameters required by load demand management systems ,hence avoiding complex manual setting by the user
出处
《系统仿真技术》
2016年第4期297-301,306,共6页
System Simulation Technology
基金
宿州学院2015年大学生创新创业计划项目(201510379083)
