Page Title: The Institute of Environmental Analytics

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Page Description: We apply advanced data science techniques and software engineering to develop the tools, insight and advice to help you better understand the risks and opportunities

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Page Text: Project Story Reducing energy costs in cement manufacture This project was undertaken for Hanson UK to examine the potential for dynamic load shifting in order to minimise electricity costs and/or CO2 emissions. The overall objective was to identify when energy-intensive processes (such as cement milling) could be shifted to off-peak times in order to reduce energy costs via leveraging the availability of cheaper off-peak electricity as well as potentially increasing the use of renewable energy sources. Process Through initial workshops and user needs analysis with management and production staff, we developed an operational model to simulate the cement production process. This was brought together with energy consumption data to provide a proof-of-concept software tool to allow cement operators and plant management the ability to model the impact of load shifting on energy consumption and production output. A key aspect in the early stages of the project was confirmation of the objectives and measures of success (considering cost reduction, optimising CO2 emissions and key operational usability requirements) for the client. Solution Following an iterative development cycle and on-going presentations to Hanson staff, the IEA team developed a proof-of-concept software tool which let operators and management (i) explore scenarios to optimise cement production given operational targets, practical constraints (e.g. planned plant downtime) and trade-offs between objectives (e.g. cost versus CO2 emission saving) and (ii) run simulations against historic price data to compare actual with optimal schedules and quantify potential cost savings and benefits over weekly or monthly schedule optimisation. Impact The proof-of-concept software tool was used to explore a typical year using historic data on cement mill operations in 2018. Overall the likely cost saving between ‘business as usual’ and an optimised schedule was estimated to be a six figure £ sum in comparison to the actual costs incurred for that year, thereby justifying future work to explore how to operationalise load shifting technology. Testimonial The IEA team worked in a collaborative way to develop a model that optimised power costs and hence reduced Scope 2 CO2 emissions. The analysis IEA provided on historic data helped to identify power cost savings through changes to operations over a weekly production planning period and changes to within day operations by utilising existing equipment differently to the normal accepted practice. Iain Walpole, Hanson UK Tell us about your data challenge Get in touch The University of Reading's Data Protection policy . The icons in How we do it are from Icons8 .

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