PDF Publication Title:
Text from PDF Page: 026
Mathematics 2022, 10, 3167 26 of 27 3. Jain, N.; Alleyne, A.G. Exergy-based optimal control of a vapor compression system. Energy Convers. Manag. 2015, 92, 353–365. https://doi.org/10.1016/j.enconman.2014.12.014. 4. Espejel-Blanco, D.F.; Hoyo-Montaño, J.A.; Arau, J.; Valencia-Palomo, G.; García-Barrientos, A.; Hernández-De-León, H.R.; Camas-Anzueto, J.L. HVAC Control System Using Predicted Mean Vote Index for Energy Savings in Buildings. Buildings 2022, 12, 38. https://doi.org/10.3390/buildings12010038. 5. Kou, X.; Du, Y.; Li, F.; Pulgar-Painemal, H.; Zandi, H.; Dong, J.; Olama, M.M. Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response. IEEE Open Access J. Power Energy 2021, 8, 186–197. https://doi.org/10.1109/OAJPE.2021.3075426. 6. Macieira, P.; Gomes, L.; Vale, Z. Energy Management Model for HVAC Control Supported by Reinforcement Learning. Energies 2021, 14, 8210. https://doi.org/10.3390/en14248210. 7. Navas, S.J.; Rubio, F.R.; Ollero, P.; Lemos, J.M. Optimal control applied to distributed solar collector fields with partial radiation. Sol. Energy 2018, 159, 811–819. https://doi.org/10.1016/j.solener.2017.11.052. 8. MacCracken, M.M. Thermal energy storage myths. Energy Eng. 2004, 101, 69–80. https://doi.org/10.1080/01998590409509274. 9. Rismanchi, B.; Saidur, R.; BoroumandJazi, G.; Ahmed, S. Energy, exergy and environmental analysis of cold thermal energy storage (CTES) systems. Renew. Sustain. Energy Rev. 2012, 16, 5741–5746. https://doi.org/10.1016/j.rser.2012.06.002. 10. Oró, E.; De Gracia, A.; Castell, A.; Farid, M.; Cabeza, L. Review on phase change materials (PCMs) for cold thermal energy storage applications. Appl. Energy 2012, 99, 513–533. https://doi.org/10.1016/j.apenergy.2012.03.058. 11. Mehling, H.; Cabeza, L.F. Heat and Cold Storage with PCM; Springer: Berlin/Heidelberg, Germany, 2008. 12. Bista, S.; Hosseini, S.E.; Owens, E.; Phillips, G. Performance improvement and energy consumption reduction in refrigeration systems using phase change material (PCM). Appl. Therm. Eng. 2018, 142, 723–735. https://doi.org/10.1016/j.applthermaleng.2018.07.068. 13. Dutil, Y.; Rousse, D.R.; Salah, N.B.; Lassue, S.; Zalewski, L. A review on phase-change materials: Mathematical modeling and simulations. Renew. Sustain. Energy Rev. 2011, 15, 112–130. https://doi.org/10.1016/j.rser.2010.06.011. 14. Berdja, M.; Hamid, A.; M’ahmed, C.; Sari, O. Novel approach to optimize the dimensions of phase change material thermal storage heat exchanger in refrigeration systems. Int. J. Energy Res. 2019, 43, 231–242. https://doi.org/10.1002/er.4254. 15. Wang, F.; Maidment, G.; Missenden, J.; Tozer, R. The novel use of phase change materials in refrigeration plant. Part 1: Experimental investigation. Appl. Therm. Eng. 2007, 27, 2893–2901. https://doi.org/10.1016/j.applthermaleng.2005.06.011. 16. Wang, F.; Maidment, G.; Missenden, J.; Tozer, R. The novel use of phase change materials in refrigeration plant. Part 2: Dynamic simu- lation model for the combined system. Appl. Therm. Eng. 2007, 27, 2902–2910. https://doi.org/10.1016/j.applthermaleng.2005.06.009. 17. Wang, F.; Maidment, G.; Missenden, J.; Tozer, R. The novel use of phase change materials in refrigeration plant. Part 3: PCM for control and energy savings. Appl. Therm. Eng. 2007, 27, 2911–2918. https://doi.org/10.1016/j.applthermaleng.2005.06.010. 18. Mosaffa, A.; Farshi, L.G.; Ferreira, C.I.; Rosen, M. Advanced exergy analysis of an air conditioning system incorporating thermal energy storage. Energy 2014, 77, 945–952. https://doi.org/10.1016/j.energy.2014.10.006. 19. Bejarano, G.; Ortega, M.G.; Normey-Rico, J.E.; Rubio, F.R. Optimal control analysis and Practical NMPC applied to refrigeration systems. ISA Trans. 2020, 107, 90–106. https://doi.org/10.1016/j.isatra.2020.07.041. 20. Yao, Y.; Shekhar, D.K. State of the art review on model predictive control (MPC) in Heating Ventilation and Air-conditioning (HVAC) field. Build. Environ. 2021, 200, 107952. https://doi.org/10.1016/j.buildenv.2021.107952. 21. Shafiei, S.E.; Stoustrup, J.; Rasmussen, H. Model predictive control for flexible power consumption of large-scale refrigera- tion systems. In Proceedings of the American Control Conference (ACC), Portland, OR, USA, 4–6 June 2014; pp. 412–417. https://doi.org/10.1109/ACC.2014.6858921. 22. Shafiei, S.E.; Alleyne, A. Model predictive control of hybrid thermal energy systems in transport refrigeration. Appl. Therm. Eng. 2015, 82, 264–280. https://doi.org/10.1016/j.applthermaleng.2015.02.053. 23. Schalbart, P.; Leducq, D.; Alvarez, G. Ice-cream storage energy efficiency with model predictive control of a refrigeration system coupled to a PCM tank. Int. J. Refrig. 2015, 52, 140–150. https://doi.org/10.1016/j.ijrefrig.2014.08.001. 24. Bejarano, G.; Suffo, J.J.; Vargas, M.; Ortega, M.G. Novel scheme for a PCM-based cold energy storage system. Design, modelling and simulation. Appl. Therm. Eng. 2018, 132, 256–274. https://doi.org/10.1016/j.applthermaleng.2017.12.088. 25. Rodríguez, D.; Bejarano, G.; Vargas, M.; Lemos, J.M.; Ortega, M.G. Modelling and cooling power control of a TES-backed-up vapour- compression refrigeration system. Appl. Therm. Eng. 2020, 164, 114415. https://doi.org/10.1016/j.applthermaleng.2019.114415. 26. Bell, I.H.; Wronski, J.; Quoilin, S.; Lemort, V. Pure and Pseudo-pure Fluid Thermophysical Property Evaluation and the Open- Source Thermophysical Property Library CoolProp. Ind. Eng. Chem. Res. 2014, 53, 2498–2508. https://doi.org/10.1021/ie4033999. 27. Alfaya, J.A.; Bejarano, G.; Ortega, M.G.; Rubio, F.R. Controllability analysis and robust control of a one-stage refrigeration system. Eur. J. Control 2015, 26, 53–62. https://doi.org/10.1016/j.ejcon.2015.08.001. 28. Bejarano, G.; Rodríguez, D.; Alfaya, J.A.; Ortega, M.G.; Castaño, F. On identifying steady-state parameters of an experimental mechanical- compression refrigeration plant. Appl. Therm. Eng. 2016, 109, 318–333. https://doi.org/10.1016/j.applthermaleng.2016.08.021. 29. Bejarano, G.; Vargas, M.; Ortega, M.G.; Castaño, F.; Normey-Rico, J.E. Efficient simulation strategy for PCM-based cold-energy storage systems. Appl. Therm. Eng. 2018, 139, 419–431. https://doi.org/10.1016/j.applthermaleng.2018.05.008. 30. Bejarano, G.; Rodríguez, D.; Alfaya, J.A.; Gil, J.D.; Ortega, M.G. Optimization and Cascade Robust Temperature Control of a Refrigerated Chamber. In Proceedings of the 9th IFAC Symposium on Robust Control Design, Florianopolis, Brazil, 3–5 September 2018; pp. 110–115. https://doi.org/10.1016/j.ifacol.2018.11.090. 31. REN—Redes Energéticas Nacionais, Lisbon (Portugal). Sistemas de Informação de Mercados de Energia. Available online: http://www.mercado.ren.pt/PT/Electr/ (accessed on 6 August 2020).PDF Image | Refrigeration Systems with Thermal Energy Storage
PDF Search Title:
Refrigeration Systems with Thermal Energy StorageOriginal File Name Searched:
mathematics-10-03167.pdfDIY PDF Search: Google It | Yahoo | Bing
Turbine and System Plans CAD CAM: Special for this month, any plans are $10,000 for complete Cad/Cam blueprints. License is for one build. Try before you buy a production license. More Info
Waste Heat Power Technology: Organic Rankine Cycle uses waste heat to make electricity, shaft horsepower and cooling. More Info
All Turbine and System Products: Infinity Turbine ORD systems, turbine generator sets, build plans and more to use your waste heat from 30C to 100C. More Info
CO2 Phase Change Demonstrator: CO2 goes supercritical at 30 C. This is a experimental platform which you can use to demonstrate phase change with low heat. Includes integration area for small CO2 turbine, static generator, and more. This can also be used for a GTL Gas to Liquids experimental platform. More Info
Introducing the Infinity Turbine Products Infinity Turbine develops and builds systems for making power from waste heat. It also is working on innovative strategies for storing, making, and deploying energy. More Info
Need Strategy? Use our Consulting and analyst services Infinity Turbine LLC is pleased to announce its consulting and analyst services. We have worked in the renewable energy industry as a researcher, developing sales and markets, along with may inventions and innovations. More Info
Made in USA with Global Energy Millennial Web Engine These pages were made with the Global Energy Web PDF Engine using Filemaker (Claris) software.
Sand Battery Sand and Paraffin for TES Thermo Energy Storage More Info
CONTACT TEL: 608-238-6001 Email: greg@infinityturbine.com (Standard Web Page)