Autonomous demand-side optimization with load uncertainty

Abstract

Demand-side management (DSM) will play an important role in balancing the energy distribution and demand in future smart grids. Indeed DSM is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and help the energy providers reduce the peak load demand and reshape the load profile [1]-[4]. Achieving effective DSM is crucial to the success of the smart grid. The success of DSM programs mainly depends on how big a portion of the total energy load is controllable. Efficient DSM, promote immediate change of consumption by shifting or reducing load through incentives or pricing mechanisms [3]. In this article, we consider load control in a multiple residence setup, where energy consumption scheduler (ECS) devices in smart meters are employed for DSM. Several residential endusers share the same energy source and each residential user has non-adjustable loads, adjustable loads and a storage device. Residential users utilize ECS deployed inside their smart meters for the adjustable loads as well as charging and discharging of their storage devices. The smart meters with ECS functions interact automatically by running a centralized algorithm to find the optimal energy consumption schedule for each user in order to reduce the total energy cost as well as the peak-to-average-ratio (PAR) in load demands. The objective is to minimize the energy cost in the system as well as PAR. Simulation results demonstrate that our proposed scheme significantly reduces the PAR and the total cost of electricity.