Using historical data processing method to optimize energy hub

Dongmin Yu; Francis Robinson; Wenhua Zha; Simon Le Blond

doi:10.1109/UPEC.2015.7339781

Using historical data processing method to optimize energy hub

Dongmin Yu, Francis Robinson, Wenhua Zha, Simon Le Blond

Department of Electronic & Electrical Engineering

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

2 Citations (SciVal)

Abstract

After the Energy Hub concept was proposed by Martin Geidl, it became a very popular topic for research into optimising the control and utilisation of energy resources. There are many widely-used methods to optimize Energy Hub operation; however many have limitations when the system is dynamic or the system behaviour is nonlinear. This paper provides a novel method to address those limitations. The method is based on an historical data processing technique to predict the Energy Hub load. By using this method, energy cost can be reduced by at least 12.3% per day.

Original language	English
Title of host publication	50th International Universities' Power Engineering Conference (UPEC), 2015
Publisher	IEEE
ISBN (Print)	9781467396820
DOIs	https://doi.org/10.1109/UPEC.2015.7339781
Publication status	Published - 1 Sept 2015
Event	50th International Universities Power Engineering Conference (UPEC2015) - UK, Stoke on Trent, UK United Kingdom Duration: 1 Sept 2015 → 4 Sept 2015

Conference

Conference	50th International Universities Power Engineering Conference (UPEC2015)
Country/Territory	UK United Kingdom
City	Stoke on Trent
Period	1/09/15 → 4/09/15

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10.1109/UPEC.2015.7339781

http://dx.doi.org/10.1109/UPEC.2015.7339781

Cite this

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title = "Using historical data processing method to optimize energy hub",

abstract = "After the Energy Hub concept was proposed by Martin Geidl, it became a very popular topic for research into optimising the control and utilisation of energy resources. There are many widely-used methods to optimize Energy Hub operation; however many have limitations when the system is dynamic or the system behaviour is nonlinear. This paper provides a novel method to address those limitations. The method is based on an historical data processing technique to predict the Energy Hub load. By using this method, energy cost can be reduced by at least 12.3% per day.",

author = "Dongmin Yu and Francis Robinson and Wenhua Zha and {Le Blond}, Simon",

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AU - Yu, Dongmin

AU - Robinson, Francis

AU - Zha, Wenhua

AU - Le Blond, Simon

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N2 - After the Energy Hub concept was proposed by Martin Geidl, it became a very popular topic for research into optimising the control and utilisation of energy resources. There are many widely-used methods to optimize Energy Hub operation; however many have limitations when the system is dynamic or the system behaviour is nonlinear. This paper provides a novel method to address those limitations. The method is based on an historical data processing technique to predict the Energy Hub load. By using this method, energy cost can be reduced by at least 12.3% per day.

AB - After the Energy Hub concept was proposed by Martin Geidl, it became a very popular topic for research into optimising the control and utilisation of energy resources. There are many widely-used methods to optimize Energy Hub operation; however many have limitations when the system is dynamic or the system behaviour is nonlinear. This paper provides a novel method to address those limitations. The method is based on an historical data processing technique to predict the Energy Hub load. By using this method, energy cost can be reduced by at least 12.3% per day.

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DO - 10.1109/UPEC.2015.7339781

M3 - Chapter in a published conference proceeding

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BT - 50th International Universities' Power Engineering Conference (UPEC), 2015

PB - IEEE

T2 - 50th International Universities Power Engineering Conference (UPEC2015)

Y2 - 1 September 2015 through 4 September 2015

ER -

Using historical data processing method to optimize energy hub

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