Peak load optimization through 2-dimensional packing and multi-processor real-time scheduling

The use of real-time scheduling methods to coordinate a set of power loads is being explored in the field of Cyber-Physical Energy Systems, with the goal of optimizing the aggregated peak load of power used by many electric loads. Real-time scheduling has attractive features in this domain. Thanks to its inherent resource optimization, which limits the number of concurrent tasks that are running at the same time, real-time scheduling provides direct benefits to peak load optimization. This paper shows the combined use of a two-dimensional bin-packing method and an optimal multi-processor real-time scheduling algorithm to coordinate the activation of electric loads. The result is an effective global scheduling approach where the activation of loads is organized into a pattern that takes into account the timing constraints of the loads and the actual combination of active loads. The validation is done by scheduling a set of thermal loads (heaters) in a building, with accurately modeled temperature dynamics. The proposed method is shown to achieve a significant peak load reduction, up to around 70%, w.r.t. the traditional thermostat controller.