Power management in a microgrid using Teaching Learning Based Optimization Algorithm

As renewable sources are being added to the grid to meet the electricity demand of users everywhere, there is an optimization problem floating in the mix that, without being attended to, could waste not only power, but money as well. This problem, typically involving systems with two or more renewable energy installations, is known as power management and pertains to the appropriate time for power outputs of specified renewable sources. To maximize a power systems efficiency, it is necessary to monitor and regulate the output of each renewable source based off of the demand, and if a surplus occurs, then the power management is based of which renewable is most cost efficient to use first, second, etc. In this paper the problem of power management will be introduced with 6 separate types of energy sources, each with their own set of costs and constraints. The problem will then be analyzed and solved using a new, yet reliable algorithm.