Electricity bill forecasting application by home energy monitoring system

Abstract

Home energy monitoring system has importance rule in home energy management. Many reports show that it has effectiveness for reducing energy consumption in home. But in medium term and long term of using home energy monitoring system there are some report show the rapidly dismiss of energy saving effective because of user do not pay attention anymore. For improve the traditional home energy monitoring system there are three concepts should be applied to the systems, 1) the system must be a learning tool not just a monitoring tool, 2) the system should be tailored made for individual users and 3) users should use less effort to dealing with the system. This article applied these concepts to home energy monitoring system and create an application to forecasting the user's electricity bill. The system has applications programming interface (API) that allow users to create applications upon their requirements. From API we have create an application to forecasting the user's electricity bill that report to user via email daily, user have less effort to receive and translate the information. And from that daily report user can learn of how their behaviors or their measures effect the electricity cost. The accuracy of electricity bill forecasting application was tested by comparing the forecast cost and actual cost and found 96% of accuracy, the result is highly acceptable.