A cuckoo load scheduling optimization approach for smart energy management

Several load scheduling optimization models have been proposed for smart grid systems. Nevertheless, most of the existing models assume the presence of a pricing mechanism such as time of use (TOU) and consider single objective functions that are suitable for application under specific conditions. This paper proposes a generic load scheduling optimization model that can be employed under different operating conditions and can handle different scheduling criteria. In particular, the model considers TOU and allows the integration of distributed renewable energy systems (DRES). In addition, the load scheduling model is solved using the Cuckoo optimization algorithm. Performance of the Cuckoo algorithm is validated by formulating and solving an equivalent MILP model to the load scheduling problem. A set of experiments is designed to compare optimality and time performance of the Cuckoo and its equivalent MILP model. The Cuckoo results has also shown superior or at least comparable results to the published results in the literature. A case study has been performed using real data taken from an academic building in Egypt to demonstrate the model applicability under different conditions. The results show that the building under specific conditions can achieve energy cost savings that range from 57% to 80%. The results have also provided useful managerial implications.