Improved energy services provision through the intelligent control of distributed energy resources

Abstract

There is a need to improve the delivery of energy services, and utilizing distributed energy resources offers significant potential. We propose an energy service modeling technique that would capture temporal variations of its demand and value, and differentiate it from the electric energy consumed by the end-use equipment. We then use this technique with a novel energy service simulation platform that aims to maximize the net benefit derived from energy services. The simulation platform creates a strategy for how available distributed resources should be operated in order to provide the desired energy services while minimizing the cost of consumption. The corresponding optimization problem is solved using particle swarm optimization. The simulation platform proved capable of creating an operation schedule that maximizes net benefit under a range of challenging conditions.