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 proceedingConference contribution

1 Citation (Scopus)
261 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 languageEnglish
Title of host publication2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)978-1-5090-2320-2
DOIs
Publication statusPublished - 01 Sep 2016
Event16th International Conference on Environment and Electrical Engineering, EEEIC 2016 - Florence, Italy
Duration: 07 Jun 201610 Jun 2016

Conference

Conference16th International Conference on Environment and Electrical Engineering, EEEIC 2016
CountryItaly
CityFlorence
Period07/06/201610/06/2016

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  • Cite this

    Kernan, R., Liu, X. A., 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.. https://doi.org/10.1109/EEEIC.2016.7555810