Power Management through Aging-Based Task Scheduling Algorithms for Smart Grids

This paper presents new algorithms for keeping the supply and demand balanced. Here, a power management scheme is proposed which employs a static and dynamic task scheduling approach based on aging priority factor. To implement the proposed task scheduling algorithm, loads are categorized into uninterruptable and interruptible (or deferrable) loads and then an adaptive priority, based on an aging concept, is assigned to improve the effectiveness of peak shaving while considering the consumer's comfort (by responding to the loads in the desirable interval). The scheduler uses the proposed algorithm to choose between different loads with different priorities at each time slot and the priority will be updated for the next time interval. This paper also discusses a new strategy for taking the peak hours into consideration for adjusting priority factors and helping the power system to have an efficient load dispatch. This goal is achieved by using an artificial neural network to forecast the next day load profile and make the scheduler aware of the peak hours. The system is simulated using MATLAB software and the results show that the Peak to Average Ratio (PAR) is significantly improved by applying the proposed algorithm to real data.