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Neural network based real-time pricing in demand side management for future smart grid

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date10/04/2015
Host publicationPower Electronics, Machines and Drives (PEMD 2014), 7th IET International Conference on
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)9781849198158
<mark>Original language</mark>English
EventThe 7th IET international conference on power electronics, machines and drives (PEMD 2014) - Manchester, United Kingdom
Duration: 8/04/201410/04/2014

Conference

ConferenceThe 7th IET international conference on power electronics, machines and drives (PEMD 2014)
Country/TerritoryUnited Kingdom
CityManchester
Period8/04/1410/04/14

Conference

ConferenceThe 7th IET international conference on power electronics, machines and drives (PEMD 2014)
Country/TerritoryUnited Kingdom
CityManchester
Period8/04/1410/04/14

Abstract

Electricity grid is currently being transformed into smart grid. Increased number of renewables require more and more ancillary services to backup intermittent power generation. A very important topic in tomorrow's electricity grid is demand side management. This tool should be used as an alternative for traditional backup power reserves. It requires a deep understanding on how consumption depends on dynamic pricing. This paper proposes a method for modelling the electricity demand response to a real-time pricing. A virtual smart house is modelled using Gridlab-D smart grid simulator. The HVAC system is setup to respond to real-time price sent by the utility. The paper is analysing the ability of neural network to predict the exact price, which is sent to the end user in order to maintain the supply balance in the system. It should also reduce the peaks in demand and increase system resilience.