Investigation on Demand Side Management Techniques in the Smart Grid using Game Theory and ICT Concepts

TL;DR

This paper explores how game theory and ICT can address demand side management challenges in smart grids by modeling, solving, and analyzing algorithms for energy load optimization among multiple users.

Contribution

It introduces a mathematical framework for demand side management using game theory and evaluates distributed ICT algorithms for scalable solutions.

Findings

Distributed algorithms can effectively solve demand management problems.

Convergence issues of algorithms pose challenges for optimal solutions.

Complexity increases with the number of energy users.

Abstract

This paper investigates how concepts from game theory and ICT can contribute to solve challenges in demand side management, an important concept in the upcoming smart grid. Demand side management is about modifying the energy load distribution on the demand side, for example in order to reduce peaks in energy usage. This can be done by shifting energy demands where possible. We start with describing a number of smart grid concepts and assumptions (smart meters, pricing, appliance scheduling) and explain the advantages demand side management has. After the introduction of game theoretic concepts, it becomes possible to mathematically describe the demand side management problem. Next step is to solve the mathematical formulation, and show how complex demand side management becomes if the number of energy users increases. By means of distributed ICT algorithms however, it is possible to still find a solution. Based on existing literature, different algorithms are studied. Though results in literature looked promising, several conclusions on convergence of the algorithm in general, and convergence towards the most optimal results in particular are challenged.