Robust Worst-Case Analysis of Demand-Side Management in Smart Grids

TL;DR

This paper introduces a robust model for demand-side management in smart grids that accounts for demand uncertainty, ensuring cost reduction for users and reliable cost estimates for suppliers.

Contribution

It presents a new realistic model incorporating demand uncertainty, along with algorithms and analysis for its solution in smart grid management.

Findings

Effective reduction in users' energy costs in real-time markets

Provides reliable production cost estimates for energy suppliers

Demonstrates solution existence and convergence of algorithms

Abstract

Demand-side management presents significant benefits in reducing the energy load in smart grids by balancing consumption demands or including energy generation and/or storage devices in the user's side. These techniques coordinate the energy load so that users minimize their monetary expenditure. However, these methods require accurate predictions in the energy consumption profiles, which make them inflexible to real demand variations. In this paper we propose a realistic model that accounts for uncertainty in these variations and calculates a robust price for all users in the smart grid. We analyze the existence of solutions for this novel scenario, propose convergent distributed algorithms to find them, and perform simulations considering energy expenditure. We show that this model can effectively reduce the monetary expenses for all users in a real-time market, while at the same time it provides a reliable production cost estimate to the energy supplier.