Day-ahead demand side management using symbiotic organisms search algorithm

According to the present scenario, as demand for electricity has increased both in terms of base load energy and peak availability, it is vital to emphasise on the concept of demand side management (DSM). DSM assures efficient utilisation of facilities by managing the energy resources of the customers and optimally modifying their energy demand profiles. It is extremely useful for the power industry to integrate the smart grids with a DSM framework for achieving a sustainable energy goal. This study focuses on modelling of DSM using a day-ahead load shifting approach as a minimisation problem. For optimisation purpose, symbiotic organisms search (SOS) algorithm has been used. A platform independent of the control parameter is unique and exhibits paramount features of this algorithm. The formulated work has been tested on different areas of smart grid applications viz. residential, commercial and industrial types of customers. A comparison of outcomes, obtained from several algorithms with the proposed SOS algorithm, has been carried out on the basis of peak load reduction leading to lessening of a utility bill. Finally, it is proven that demand management, while using the SOS approach, exhibits better accuracy than the other algorithms compared in the present framework.