A Demand Side Management with Appliance Controllability Analysis in Smart Home

Abstract

As global energy consumption keeps increasing, the energy efficiency has become an important issue. Demand-side management (DSM) system is a technology that can be used to solve this issue. In many houses, there are some time periods in a day when inhabitants have high electricity demands, and these peaks will cause a burden on the smart grid. In order to solve energy efficiency problem, the demand-side management system can help users to postpone non-immediately needed demands to off-peak hour subject to the mechanism of real-time pricing policy. In addition, with the development of Internet of Things technology, the devices which have internet module can form a home area network, enabling DSM to monitor the entire state of the house and to control appliances. However, due to the uncertainty of user behavior, it is hard to find the good control policy for energy saving, considering that different users may have various habits and the appliance usage tends to be irregular. Therefore, the ability of DSM will be restricted in order to avoid disturbing the user comfort. In the proposed work, a smart home demand-side management system within home area network was implemented, including multiple agents with reinforcement learning for managing different appliances, energy storage system, and renewable energy. The proposed system also keeps the user's comfort based on the activity of user and controllability of appliances. As a result, the simulation studies show that the proposed DSM system can reduce 42.36% peak demand value and achieve 32.79% cost reduction. The cost reduction value can be further increased by 22.41% when the concept of energy self-awareness is combined into demand-side management system.