ew 17(13): e3

Research Article

A Real-Time monthly DR Price system for the Smart Energy Grid

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  • @ARTICLE{10.4108/eai.3-8-2017.152981,
        author={ASM Ashraf Mahmud and Paul Sant and Faisal Tariq and David Jazani},
        title={A Real-Time monthly DR Price system for the Smart Energy Grid},
        journal={EAI Endorsed Transactions on Energy Web},
        volume={4},
        number={13},
        publisher={EAI},
        journal_a={EW},
        year={2017},
        month={8},
        keywords={smart grid, real-time, price, demand response, stochastic process, user preference, peak to average ratio, price suggestion unit},
        doi={10.4108/eai.3-8-2017.152981}
    }
    
  • ASM Ashraf Mahmud
    Paul Sant
    Faisal Tariq
    David Jazani
    Year: 2017
    A Real-Time monthly DR Price system for the Smart Energy Grid
    EW
    EAI
    DOI: 10.4108/eai.3-8-2017.152981
ASM Ashraf Mahmud1,*, Paul Sant1, Faisal Tariq2, David Jazani3
  • 1: The University of Bedfordshire,
  • 2: Queen Mary University of London
  • 3: The University of Bedfordshire
*Contact email: asm.mahmud@beds.ac.uk

Abstract

The smart grid is the next generation bidirectional modern grid. Energy users’ are keen on reducing their bill and energy suppliers are also keen on reducing their industrial cost. Our demand response model would benefit them both. We have tested our model with the UK based traditional price value using a real-time basis. Energy users significantly reduced their bill and energy suppliers reduced their industrial cost due to load shifting. The Price Control Unit (PCU) and Price Suggestions Unit (PSU) utilise and embedded algorithms to vary price based upon demand. Our model makes suggestions based on energy threshold and makes use of stochastic approximation methods to produce prices. Our results shows that bill and peak load reductions benefit both the energy provider and users. This model also addresses users’ preferences, if users are non-responsive, they can still reduce their bills.