Optimization of Microgrid fed from Hybrid Energy Sources using the Swarm Intelligence

To combat the widening gap between demand and supply, it is crucial to include renewableenergy sources as a Distributed Generation newline (DG). Despite their usefulness in reducing the gap, REsources place a heavy pressure on generation scheduling, particularly wind power. Utilities are compelledto use wind curtailment due to fluctuations in wind energy output, which reduces the incentive to switch torenewable sources of power. Demand Side Management (DSM) is one approach to this problem, since itadjusts demand in real time to match generation while the grid is operating. Conventional DemandResponse (DR) systems were created to minimise consumption during peak hours by arranging userloads in exchange for incentives. The Smart Grid (SG) concept provides a high-tech means ofcommunication for keeping tabs on and managing the power grid. This motivated the creation of asophisticated DR technique known as Demand Dispatch (DD), in which consumption is timesynchronizedwith electricity production. In order to deal with the fluctuations in wind power production,this thesis proposes a DD method. The entities involved in DD and the way in which data is sharedbetween them are laid out in an operational framework. In order to find and evaluate all of the studiesthat have been published on a certain topic, researchers often undertake systematic literature reviews.