A Game Theoretic Optimization Framework for Home Demand Management Incorporating Local Energy Resources

Abstract

Facilitated by advanced ICT infrastructure and optimization techniques, smart grid has the potential to bring significant benefits to the energy consumption management. This paper presents a game theoretic consumption scheduling framework based on the use of mixed integer programming to schedule consumption plan for residential consumers. In particular, the optimization framework incorporates integration of locally generated renewable energy in order to minimise dependency on conventional energy and the consumption cost. The game theoretic model is designed to coordinatively manage the scheduling of appliances of consumers. The Nash equilibrium of the game exists and the scheduling optimization converges to an equilibrium where all consumers can benefit from participating in. Simulation results are presented to demonstrate the proposed approach and the benefits of home demand management.

Recent advances of the signal processing techniques in future smart grids

“…In [37], image processing techniques are introduced for the safety of dams and smart grids. The cyber security issues of the bad data injection are discussed in [38], where the authors proposed the independent component analysis technique to handle Techniques Image Processing [57] Wavelet [32], [58] Gradient Based Techniques [63] ICA, PCA [66]- [68] Neural Networks [64] DFT [62] Autoregressive Moving Average [35] Likelihood Ratio [33] Mutual Information Ratio [30] Kalman Filter [39] Game Theory [49] Fig. 4 Applications of signal processing techniques in smart grids the situation.…”

“…A compression technique which is an essential part of all types of data storage and communications is developed for the smart grid waveforms [63]. Furthermore, game theory based approach is presented for home power demand management in [64]. In [65], a signal processing based energy management in coordinated multipoint system is proposed for the smart grids.…”

“…Fault Detection [33], [36], [37], [64] Noise recursive discrete Fourier transform (RDFT) algorithm is developed to estimate instantaneous frequencies in smart grids. In references [69,70], the authors presented the concept of a modern smart home and the inclusion of renewable energy with the smart grid scenario to reduce the electric bills accordingly.…”

An Incentivized Auction-Based Group-Selling Approach for Demand Response Management in V2G Systems

“…In [10], the DRM problem is addressed in a network of multiple utility companies and consumers using a Stackelberg game to maximize the revenue of each utility company and the payoff of each user. [11] presents a noncooperative game theoretic consumption scheduling framework based on mixed integer programming optimization technique to schedule the energy consumption at household level. In [12], the interaction between utility companies and residential users is modeled as a two-level game, where the competition among utility companies is a non-cooperative game and the interaction among residential users is an evolutionary game.…”

A Mean Field Game Theoretic Approach to Electric Vehicles Charging

“…Compared to a fully coordinated design where the optimal beamformers are jointly designed, the scheme provided benefits in terms of lower system complexity and overheads. Game theory is very suitable for analysing the interaction of consumers and utility operators in order to achieve efficient distributed demand management [22], [23]. More detailed discussions on demand management and game theory can be found in [24].…”