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Energy-efficient smart grid communications

Energy-efficient smart grid communications

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Information and communication technologies (ICTs) are playing an important role in the modernization of the power grid. Communication networks for the smart grid should be energy-efficient (EE), so that these extra associated networks themselves will not significantly increase energy consumption of the total grid. More importantly, communication devices should not have to be recharged frequently and ideally would keep working even during extreme situations such as blackouts. A significant amount of research efforts have been put into reducing energy consumption of networks powered by the smart grid. However, the impact of green ICTs on the smart grid communications and applications remains to be explored. In this chapter, we surveyed EE smart grid communication networks, which are divided into three domains: smart grid home area networks (SG-HANs), smart grid neighborhood area networks (SG-NANs), and smart grid wide area networks (SG-WANs). To the best of our knowledge, this is the first survey of EE smart communications networks. Due to the importance of SG-NANs, this chapter focuses on SG-NANs, where data aggregation units (DAUs) communicate with home gateways (HGWs). Moreover, a multicell orthogonal frequency-division multiple access (OFDMA) cellular network is proposed for an SG-NAN. In order to improve energy-efficiency of the SG-NAN, a distributed resource allocation scheme is proposed, which also takes HGW fairness and priority into consideration. Average data rates are considered, since they are more appropriate from the HGWs' perspective. The EE resource allocation with fairness optimization problem is transformed from a fractional to equivalent subtractive form, which is subsequently modeled as a non-cooperative game. Interference pricing functions are used to drive the Nash equilibrium (NE) to Pareto optimal. An EE resource allocation iterative algorithm is designed for the resource allocation optimization problem. Simulation results show the effectiveness of the proposed scheme on energy-efficiency and HGW fairness.

Chapter Contents:

  • 15.1 Introduction
  • 15.2 Energy-efficient wireless smart grid communications
  • 15.3 System model
  • 15.4 Problem transformation
  • 15.5 Non-cooperative game formulation
  • 15.5.1 Utility function of each DAU in the multicell OFDMA cellular network
  • 15.5.2 Game formulation within each time slot
  • 15.6 Analysis of the proposed EE resource allocation game with fairness
  • 15.6.1 Subchannel assignment algorithm
  • 15.6.2 Non-cooperative EE power allocation game
  • 15.6.3 Properties of the interference pricing function factors
  • 15.6.4 Existence of the NE in the proposed game
  • 15.6.5 Proposed parallel iterative algorithm
  • 15.7 EE resource allocation iterative algorithm
  • 15.8 Simulation results and discussions
  • 15.9 Conclusions
  • Appendix
  • A. Proof of Theorem 15.1
  • B. Proof of Proposition 15.5
  • C. Proof of Proposition 15.3
  • Bibliography

Inspec keywords: smart power grids; home networks; energy conservation; game theory; power consumption; cellular radio; OFDM modulation; Pareto optimisation; resource allocation; frequency division multiple access; wide area networks

Other keywords: home gateways; SG-NAN; information and communication technology; Pareto optimal; fairness optimization problem; smart grid home area networks; smart grid neighborhood area networks; cellular network; Nash equilibrium; energy consumption; distributed resource allocation; SG-HAN; noncooperative game; smart grid wide area networks; green ICT; OFDMA; energy-efficient smart grid communications; interference pricing functions; SG-WAN; multicell orthogonal frequency division multiple access

Subjects: Modulation and coding methods; Energy conservation; Mobile radio systems; Game theory; Energy utilisation; Computer communications; Optimisation techniques; Game theory; Other computer networks; Power system management, operation and economics; Optimisation techniques; Multiple access communication; Probability theory, stochastic processes, and statistics

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