A Meta-heuristic Optimization based approach for Residential Demand-side Management

Immensely changing electrical load consumption patterns due to the advent of new electrical appliances have resulted in reliability issues in the operation of electrical utilities. These issues induce high stress upon the power generating utilities at peak load consumption hours. Frequent occurrence of such events reduces the system efficiency in supplying adequate power to the consumers. It also increases system maintenance as the power generating equipment continues to operate under such heavy stress. Demand-side management (DSM) techniques help the electrical utilities to reduce system stress by distributing the load demand over the entire period of operation. Numerous DSM techniques have been suggested so far to mitigate the difficulties faced by the power utilities. Still, a high segment of those is based upon the conventional optimization techniques such as particle swarm optimization, genetic algorithm etc. Presently, there exists a number of meta-heuristic optimization technique that performs more efficiently than those conventional techniques. In this paper, a DSM model based upon three meta-heuristic techniques has been suggested. Out of these three, the most efficient optimization technique-based DSM model is chosen by comparing their ability to reduce peak load. These DSM models have been designed using the MATLAB 2018a platform.