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- W2305295088 abstract "Introduction Supply-demand balancing act in electricity grids is a very demanding task. It requires constant monitoring of the network and very fast response to system changes. Poor regulation might lead to brownouts or even blackouts of the whole country. At the same time, increasing number of renewables add another layer of complexity due to their inherent variability in power output. Luckily, recent advancement in communication and sensing technologies enable the advancement of Smart Grid. It will supply utilities and grid managers with additional set of tools for maintaining system balance and stability. A novel method is being developed at Lancaster University, which focuses on Demand Side Management (DSM) technique using real-time pricing (RPT). It proposes to use state of the art machine learning techniques Artificial Neural Networks (ANN) to control the total consumption using pricing signal, which is sent to residential Energy Management Units (EMU). It is expected that increased number of smart appliances and intelligent Heating Ventilation and Air Conditioning (HVAC) system will contribute in reacting to the state of electricity network. The main research challenge in this novel technique is to be able to shed the load without creating even bigger peaks of energy consumption at other times." @default.
- W2305295088 created "2016-06-24" @default.
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- W2305295088 date "2013-11-08" @default.
- W2305295088 modified "2023-09-27" @default.
- W2305295088 title "Energy management methods in scalable smart grid" @default.
- W2305295088 hasPublicationYear "2013" @default.
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