Scinovex
articleTop 1% cited

Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid

IEEE Transactions on Smart Grid · 2010 · Vol. 1(3) · pp. 320–331
Amir-Hamed Mohsenian-RadVincent W. S. WongJuri JatskevichRobert SchoberAlberto Leon‐Garcia

Abstract

Most of the existing demand-side management programs focus primarily on the interactions between a utility company and its customers/users. In this paper, we present an autonomous and distributed demand-side energy management system among users that takes advantage of a two-way digital communication infrastructure which is envisioned in the future smart grid. We use game theory and formulate an energy consumption scheduling game, where the players are the users and their strategies are the daily schedules of their household appliances and loads. It is assumed that the utility company can adopt adequate pricing tariffs that differentiate the energy usage in time and level. We show that for a common scenario, with a single utility company serving multiple customers, the global optimal performance in terms of minimizing the energy costs is achieved at the Nash equilibrium of the formulated energy consumption scheduling game. The proposed distributed demand-side energy management strategy requires each user to simply apply its best response strategy to the current total load and tariffs in the power distribution system. The users can maintain privacy and do not need to reveal the details on their energy consumption schedules to other users. We also show that users will have the incentives to participate in the energy consumption scheduling game and subscribing to such services. Simulation results confirm that the proposed approach can reduce the peak-to-average ratio of the total energy demand, the total energy costs, as well as each user's individual daily electricity charges.

Smart Grid Energy ManagementGreen IT and SustainabilityMicrogrid Control and OptimizationSmart gridDemand responseEnergy consumptionComputer scienceEnergy managementNash equilibriumGame theoryScheduling (production processes)Load managementGrid

Funding

  • Canada Research Chairs
  • Natural Sciences and Engineering Research Council of Canada
Citations
2,731
FWCI
94.82
field-weighted impact
References
29
Percentile
100%
vs. same field & year
Citations per year
Cited by
Optimal Operation of Residential Energy Hubs in Smart Grids
IEEE Transactions on Smart Grid · 2012 · 494 citations
Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design
IEEE Transactions on Smart Grid · 2012 · 810 citations
Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach
IEEE Transactions on Smart Grid · 2013 · 778 citations
Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing
IEEE Transactions on Smart Grid · 2012 · 522 citations
Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads
IEEE Transactions on Industrial Informatics · 2011 · 2,824 citations
Demand-Side Management via Distributed Energy Generation and Storage Optimization
IEEE Transactions on Smart Grid · 2012 · 514 citations
Citation Network

How this paper connects to the literature. Drag to explore, click any node to open that paper.