Abstract
Consumptions through the factory have been computed in Chap. 5. By Table 5.32, they can be derived the most representative of them in which actuate by taking corrective measures in order to reduce single consumptions. This table provides as well the location where the most consumptions are concentrated. Hence, by means of the enumerated actions defined within Chap. 6, they can be computed generic electrical savings, which are described in the following sections.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
van Vugt M, Moye A, Sivakumar S (2019) Computational modelling approaches to meditation research: why should we care? Curr Opin Psychol 28:49–53. https://doi.org/10.1016/j.copsyc.2018.10.011
Brailsford SC, Eldabi T, Kunc M, Mustafee N, Osorio AF (2019) Hybrid simulation modelling in operational research: a state-of-the-art review. Eur J Oper Res 278(3):721–737. https://doi.org/10.1016/j.ejor.2018.10.025
Lamine CM, Said Z (2014) Energy analysis of single effect absorption chiller (LiBr/H2O) in an Industrial manufacturing of detergent. Energy Proc 50:105–112. https://doi.org/10.1016/j.egypro.2014.06.013
Various (2014) Guide to meteorological instruments and methods of observation, 8th edn. World Meteorological Organization
Nannarone A, Toro C, Sciubba E (2018) Multi-effect distillation desalination process: modeling and simulation. In: Presented at the 30th international conference on efficiency, cost, optimization, simulation and environmental impact of energy systems, San Diego, USA, July 2017. https://www.researchgate.net/publication/318207357_Multi-Effect_Distillation_Desalination_Process_Modeling_and_Simulation. Accessed 05 Nov 2018
Frantz C, Seifert B (2015) Thermal analysis of a multi effect distillation plant powered by a solar tower plant - ScienceDirect 69:1928–1937. https://doi.org/10.1016/j.egypro.2015.03.190
Ophir A, Gendel A (1994) Adaptation of the multi-effect distillation (MED) process to yield high purity distillate for utilities, refineries and chemical industry. Desalination 98(1):383–390. https://doi.org/10.1016/0011-9164(94)00164-2
El Ebaidi SK (2013) Water chemical analysis for different stages in Tobruk desalination plant. In: Presented at the the 13th international conference on materials science and its applications in oil and gas industries, Benghazi, August 2013
Chernozubov VB, Zaostrovsky FP, Shatsillo VG, Golub SI, Novilov EP, Tkach VI (1966) Prevention of scale formation in distillation desalination plants by means of seeding. Desalination 1(1):50–60. https://doi.org/10.1016/S0011-9164(00)84007-2
Cuviella-Suárez C, Colmenar-Santos A, Borge-Diez D, López-Rey Á (2018) Management tool to optimize energy and water consumption in the sanitary-ware industry. J Clean Prod 197, Part 1:280–296. https://doi.org/10.1016/j.jclepro.2018.06.195
Ammar Y, Li H, Walsh C, Thornley P, Sharifi V, Roskilly AP (2013) Reprint of ‘Desalination using low grade heat in the process industry: challenges and perspectives’. Appl Therm Eng 53(2):234–245. https://doi.org/10.1016/j.applthermaleng.2012.11.010
Dastgerdi HR, Whittaker PB, Chua HT (2016) New MED based desalination process for low grade waste heat. Desalination 395:57–71. https://doi.org/10.1016/j.desal.2016.05.022
Hatzikioseyian A, Kousi P (2003) Modelling and thermodynamic analysis of a Multi-effect Distillation (MED) plant for seawater desalination. ResearchGate, January 2003. https://www.researchgate.net/publication/242541781_MODELLING_AND_THERMODYNAMIC_ANALYSIS_OF_A_MULTI_EFFECT_DISTILLATION_MED_PLANT_FOR_SEAWATER_DESALINATION. Accessed 24 Jan 2017
Chen Q, Ja MK, Li Y, Chua KJ (2018) Experimental and mathematical study of the spray flash evaporation phenomena. Appl Therm Eng 130:598–610. https://doi.org/10.1016/j.applthermaleng.2017.11.018
Dubreuil A, Assoumou E, Bouckaert S, Selosse S, Maı¨zi N (2013) Water modeling in an energy optimization framework – the water-scarce middle east context. Appl Energy 101:268–279. https://doi.org/10.1016/j.apenergy.2012.06.032
Fritzmann C, Löwenberg J, Wintgens T, Melin T (2007) State-of-the-art of reverse osmosis desalination. Desalination 216(1):1–76. https://doi.org/10.1016/j.desal.2006.12.009
Cuviella-Suárez C, Colmenar-Santos A, Castro-Gil M (2012) Tri-generation system to couple production to demand in a combined cycle. Energy 40(1):271–290. https://doi.org/10.1016/j.energy.2012.01.073
Cuviella-Suárez C, Colmenar-Santos A, Borge-Diez D, Rosales-Asensio E (2019) Sanitary-ware factories: heat recovery strategies to optimize energy and water consumption. Energy Proc. 157:719–736. https://doi.org/10.1016/j.egypro.2018.11.238
Lazzaretto A, Andrea T (2001) Analytical and neural network models for gas turbine design and off-design simulation. Int J Thermodyn 4:173–182. https://doi.org/10.5541/ijot.78
Lecomte T (2010) Best Available Techniques (BAT) Reference Document for Large Combustion Plants - Industrial Emissions Directive 2010/75/EU (Integrated Pollution Prevention and Control), p 986
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Cuviella-Suárez, C., Borge-Diez, D., Colmenar-Santos, A. (2021). Proposals Calculation. In: Water and Energy Use in Sanitary-ware Manufacturing. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-030-72491-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-72491-7_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-72490-0
Online ISBN: 978-3-030-72491-7
eBook Packages: EnergyEnergy (R0)