Applications of Rough Set Theory in Demand Side Management of Electrical Power Industry: A Review

The global demand for electricity is at its peak right now due to exponential advancement of technology. While electricity demand around the world is increasing, the potential scarcity of fossil fuel is roadblocking the supply side to meet this increasing demand. The most feasible solution to this problem is demand response (DR) strategies in demand side management (DSM). A crucial issue towards demand response implementation is dealing with the heterogeneric and inconsistent characteristics of customer consumption patterns in power industry, less customer engagement to manage the demand side. This kind of data can be analyzed with more accuracy using rough set theory (RST). It is a powerful mathematical tool that has the strength to deal with vague, inconsistent, and incomplete data. When it comes to demand side management of electrical power industry, rough set theory has a potential to be implemented as a powerful and accurate tool for customer data analysis. This paper aims to project the currents trends of rough set theory application to implement demand response strategies in demand side management of electrical power industry by conducting a comprehensive review on the existing literature. Applications of rough set theory in terms of demand/price forecasting, fault detection, decision rule generation in electrical power industry are mapped out to provide a clear vision for the overall RST implementations and advantages. Recommendations and suggestions are provided for more appropriate and efficient future application and research.