Management of public water supply to reduce power cost and improve wind power uptake

Ronan Kernan; Xueqin Amy Liu; Sean McLoone; Brendan Fox

doi:10.1109/EEEIC.2016.7555810

Management of public water supply to reduce power cost and improve wind power uptake

Ronan Kernan, Xueqin Amy Liu, Sean McLoone, Brendan Fox

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

424 Downloads (Pure)

Abstract

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Original language	English
Title of host publication	2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	978-1-5090-2320-2
DOIs	https://doi.org/10.1109/EEEIC.2016.7555810
Publication status	Published - 01 Sept 2016
Event	16th International Conference on Environment and Electrical Engineering, EEEIC 2016 - Florence, Italy Duration: 07 Jun 2016 → 10 Jun 2016

Conference

Conference	16th International Conference on Environment and Electrical Engineering, EEEIC 2016
Country/Territory	Italy
City	Florence
Period	07/06/2016 → 10/06/2016

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Management of public water supply to reduce power cost and improve wind power uptake
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Cite this

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title = "Management of public water supply to reduce power cost and improve wind power uptake",

abstract = "This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.",

author = "Ronan Kernan and Liu, {Xueqin Amy} and Sean McLoone and Brendan Fox",

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note = "16th International Conference on Environment and Electrical Engineering, EEEIC 2016 ; Conference date: 07-06-2016 Through 10-06-2016",

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Kernan, R, Liu, XA , McLoone, S & Fox, B 2016, Management of public water supply to reduce power cost and improve wind power uptake. in 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)., 7555810, Institute of Electrical and Electronics Engineers Inc., 16th International Conference on Environment and Electrical Engineering, EEEIC 2016, Florence, Italy, 07/06/2016. https://doi.org/10.1109/EEEIC.2016.7555810

Management of public water supply to reduce power cost and improve wind power uptake. / Kernan, Ronan; Liu, Xueqin Amy ; McLoone, Sean et al.
2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC). Institute of Electrical and Electronics Engineers Inc., 2016. 7555810.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Management of public water supply to reduce power cost and improve wind power uptake

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