Efficient power management based on adaptive whale optimization technique for residential load

The traditional energy market is being transformed with modern communication technology, with an interactive generation-load communication topology for energy management in a domestic utility connected over a micro smart grid (MSG). In the traditional energy market, the consumer's role is limited to power consumption. Modern microgrids allow the user to interact with the grid and have increased the energy efficiency of domestic utilities. It is very much necessary to study the role of distributed generation in demand-side management for a proper energy management system in MSG. This paper highlights the interactive areas for the user with the grid to minimize the losses and improve the grid efficiency, thereby minimizing the cost for the user. An agent-based system for the identification of priority and non-priority loads is discussed in this paper, along with an Adaptive Whale Optimization Algorithm (AWOA) for load switching based on priority. Simulation is conducted in MATLAB to validate the proposed technique. The effectiveness of the proposed framework is assessed by comparing it to the Whale optimization Algorithm (WOA) and cases without scheduling. By implementing AWOA, the following improvements were observed: the total electricity cost decreased by an average of 1.33% for 6 residential buildings. In the similar manner, the lad deviation of 1.36% is achieved by implementing AWOA compared to AWO Algorithm.