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Optimizing energy costs in a zinc and lead mine

Kinsella, Alan, Smeaton, Alan F. orcid logoORCID: 0000-0003-1028-8389, Hurley, Barry, O'Sullivan, Barry and Simonis, Helmut (2016) Optimizing energy costs in a zinc and lead mine. In: Innovative Applications Of Artificial Intelligence (IAAI 16), 12-17 Feb 2016, Phoenix AZ..

Abstract
Boliden Tara Mines Ltd. consumed 184.7 GWh of electricity in 2014, equating to over 1% of the national demand of Ireland or approximately 35,000 homes. Ireland's industrial electricity prices, at an average of 13 c/KWh in 2014, are amongst the most expensive in Europe. Cost effective electricity procurement is ever more pressing for businesses to remain competitive. In parallel, the proliferation of intelligent devices has led to the industrial Internet of Things paradigm becoming mainstream. As more and more devices become equipped with network connectivity, smart metering is fast becoming a means of giving energy users access to a rich array of consumption data. These modern sensor networks have facilitated the development of applications to process, analyse, and react to continuous data streams in real-time. Subsequently, future procurement and consumption decisions can be informed by a highly detailed evaluation of energy usage. With these considerations in mind, this paper uses variable energy prices from Ireland’s Single Electricity Market, along with smart meter sensor data, to simulate the scheduling of an industrial-sized underground pump station in Tara Mines. The objective is to reduce the overall energy costs whilst still functioning within the system's operational constraints. An evaluation using real-world electricity prices and detailed sensor data for 2014 demonstrates significant savings of up to 10.72% over the year compared to the existing control systems.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Optimisation
Subjects:Computer Science > Computer software
DCU Faculties and Centres:Research Institutes and Centres > INSIGHT Centre for Data Analytics
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of the Twenty-Eighth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-16). .
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland
ID Code:21211
Deposited On:06 May 2016 13:00 by Alan Smeaton . Last Modified 31 Oct 2018 11:33
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