Demand-Side Management in Power Grids: An Ant Colony Optimization Approach

As more and more fossil fuels are burned in order to keep up with the overgrowing demand for energy it is becoming increasingly necessary to look for alternative energy sources. Reducing peak-time energy demand is important to make the best use of renewable energies. In this paper we present an Ant Colony Optimization (ACO) based approach for the problem of scheduling tasks so as to minimize peak-times and cost. This approach is compared with an existing Genetic Algorithm (GA) based approach. ACO managed to obtain very similar results compared with GA, with the cost of the schedules being sometimes slightly better than the Genetic Algorithm approach, especially for shorter execution times. The ACO approach also proved to be more consistent in its results than the GA approach.