An Adaptive Cognition System for Smart Grids With Context Awareness and Fault Tolerance

In recent years, smart grids have been a common interest for many consumers, because of their comfort, safety, robustness, and economic characteristics. This paper presents the development of a computational tool, as an adaptive cognition system for smart grids, having smart homes as their composing nodes. Such a tool has been named Smart Home Energy Aware-Preserver (SHEAP). SHEAP incorporates evolutionary computation algorithms, and communication protocols, to provide users with context awareness and fault tolerance. Moreover, SHEAP considers a smart home powered by solar and wind energy, as a small version of the smart grid. SHEAP demonstrates the benefits of having a smart home that can control the amount of power needed, according to the context of usage. Furthermore, SHEAP includes fault tolerant mechanisms to monitor and react on fault occurrences. Simulation shows that with a smart control of the load, the requirements for a green energy system are reduced. An economic analysis of the approach demonstrates the viability of the project reducing the usage of grid energy by utilizing green energy.