Recent Advances in Local Energy Trading in the Smart Grid Based on Game--Theoretic Approaches

TL;DR

This paper reviews recent game-theoretic methods applied to local energy trading in smart grids, highlighting frameworks, taxonomies, and future research directions for renewable energy integration.

Contribution

It provides a comprehensive taxonomy and detailed framework of game-theoretic approaches for local energy trading in smart grids, including architecture and future challenges.

Findings

Game-theoretic methods effectively model energy trading scenarios.

Framework integrates renewable energy and storage considerations.

Identifies gaps and future research areas in smart grid energy trading.

Abstract

The global move towards efficient energy consumption and production has led to remarkable advancements in the design of the smart grid infrastructure. Local energy trading is one way forward. It typically refers to the transfer of energy from an entity of the smart grid surplus energy to one with a deficit. In this paper, we present a detailed review of the recent advances in the application of game--theoretic methods to local energy trading scenarios. An extensive description of a complete game theory-based energy trading framework is presented. It includes a taxonomy of the methods and an introduction to the smart grid architecture with a focus on renewable energy generation and energy storage. Finally, we present a critical evaluation of the current shortcomings and identify areas for future research.