Multi-dimensional energy consumption scheduling for an event-based demand response.

Abstract

Demand Side Management plays an important role in the emerging smart grid by reducing peak load and adapting demand side resources to fluctuating generation. We here demonstrate an approach to optimally scheduling the energy consumption of individual dwellings so as to maximize individual net reward subject to utility-imposed constraints and user preference constraints. We categorize load resources in terms of their flexibility in energy consumption and operating time. Particle swarm optimization is used to solve the optimization problem. Optimization is performed for different types of dwellings and Load. With respect to the unscheduled peak, reductions range from about 1%, for maximum comfort, to about 24%, for minimum comfort. Under CPP DR requests, with respect to TOU pricing, there is effectively no change in the peak under the minimum comfort scenario. As comfort increases, the DR request is able to depress the peak by up to 10% under the maximum comfort scenario. Thus, even under the modest TOU pricing, it is comfort, not CPP, that constrains the DR response