A probabilistic demand side management approach by consumption admission control

TL;DR

This paper proposes a probabilistic demand management method for smart grids that uses statistical demand characterization to control appliance operation, ensuring supply-demand balance without hard limits.

Contribution

It introduces a novel demand control approach based on tail probability estimation and statistical resource management principles for smart grid applications.

Findings

Effective demand balancing through probabilistic control.

Reduced reliance on hard demand limits.

Improved efficiency in demand response management.

Abstract

New generation electricity network called Smart Grid is a recently conceived vision for a cleaner, more efficient and cheaper electricity system. One of the major challenges of electricity network is that generation and consumption should be balanced at every moment. This paper introduces a new concept for controlling the demand side by the means of automatically enabling/disabling electric appliances to make sure that the demand is in match with the available supplies, based on the statistical characterization of the need. In our new approach instead of using hard limits we estimate the tail probability of the demand distribution and control system by using the principles and the results of statistical resource management.