Scheduling Smart Loads in Modern Buildings based on Metaheuristic Optimization

Abstract

Load scheduling is one of the most promising trends in smart grids. It enables renewable energy to be efficiently utilized and accommodated in the smart buildings. In this work, we propose a comprehensive scheduling approach of a group of non-preemptive loads in a ‘greedy’ manner in order to reduce the deficit between the aggregate scheduled load and the available low-cost generation and therefore, the levelized cost of energy (LCoE) can be minimized. In order to reduce the massive searching space and attain a good schedule within a reasonable time, an efficient metaheuristic optimization framework is proposed and implemented based on genetic algorithms. An illustrative example is used to carry out this work using artificially created loads representing different facilities inside a building complex.