Management of public water supply to reduce energy cost and improve wind power uptake
Data(s) |
29/08/2016
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Resumo |
<p>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.</p> |
Identificador |
http://dx.doi.org/10.1109/EEEIC.2016.7555810 http://www.scopus.com/inward/record.url?scp=84988369885&partnerID=8YFLogxK |
Idioma(s) |
eng |
Publicador |
Institute of Electrical and Electronics Engineers Inc. |
Direitos |
info:eu-repo/semantics/restrictedAccess |
Fonte |
Kernan , R , Liu , X A , McLoone , S & Fox , B 2016 , Management of public water supply to reduce energy cost and improve wind power uptake . in EEEIC 2016 - International Conference on Environment and Electrical Engineering . , 7555810 , Institute of Electrical and Electronics Engineers Inc. , 16th International Conference on Environment and Electrical Engineering, EEEIC 2016 , Florence , Italy , 7-10 June . DOI: 10.1109/EEEIC.2016.7555810 |
Palavras-Chave | #Demand Side Management #Genetic Algorithms #optimisation #Real Time Pricing #water pumping #Wind Power #/dk/atira/pure/subjectarea/asjc/2100/2102 #Energy Engineering and Power Technology #/dk/atira/pure/subjectarea/asjc/2100/2105 #Renewable Energy, Sustainability and the Environment #/dk/atira/pure/subjectarea/asjc/2200/2208 #Electrical and Electronic Engineering |
Tipo |
contributionToPeriodical |