Load Shedding and Smart-Direct Load Control Using Internet of Things in Smart Grid Demand Response Management

This paper proposes the use of a novel algorithm for smart-direct load control (S-DLC) and load shedding to minimize power outages in sudden grid load changes and reduce the peak-to-average ratio. The algorithm utilizes forecasting, shedding, and S-DLC. It also uses the Internet of Things and stream analytics to provide real-time load control, and generates a daily schedule for customers' equipped with intelligent electronic devices based on their demands, thermal comfort, and the forecasted load model. The demand response techniques are utilized for real-time load control and optimization. To test the algorithm, a simulation system was developed, which takes into account 100 customers owning randomly selected appliances. The results indicated that load shedding using autoregressive integrated moving average time-series prediction model, and applying S-DLC and Internet of Things can significantly reduce customers' power outage.