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A real-time monthly DR price system for the smart energy grid

  • Queen Mary University of London

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
2 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)e3
JournalOzp -Institut fur Staats und Politikwissenschaft-
Volume4
Issue number13
DOIs
Publication statusPublished - 3 Aug 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Demand response
  • Peak to average ratio
  • Price
  • Price suggestion unit
  • Real-time
  • Smart grid
  • Stochastic process
  • User preference

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