Industrial processes and the smart grid: overcoming the variability of renewables by using built-in process storage and intelligent control strategies

References

• Abdulwakil, Muhammad Mansur, Abdul Samad Abdul-Rahim, and Mohd Alsaleh. 2020. “Bioenergy Efficiency Change and Its Determinants in EU-28 Region: Evidence Using Least Square Dummy Variable Corrected Estimation.” Biomass and Bioenergy 137 (June), Elsevier Ltd. doi:10.1016/j.biombioe.2020.105569.
   Google Scholar
• Alizadeh, Reza, Peter D. Lund, and Leili Soltanisehat. 2020. “Outlook on Biofuels in Future Studies: A Systematic Literature Review.” Renewable and Sustainable Energy Reviews, doi:10.1016/j.rser.2020.110326.
   Web of Science ®Google Scholar
• Alsaleh, Mohd, and A. S. Abdul-Rahim. 2018. “Determinants of Cost Efficiency of Bioenergy Industry: Evidence from EU28 Countries.” Renewable Energy 127 (November): Elsevier Ltd: 746–762. doi:10.1016/j.renene.2018.04.085.
   Google Scholar
• Alsaleh, Mohd, A. S. Abdul-Rahim, and H. O. Mohd-Shahwahid. 2017. “Determinants of Technical Efficiency in the Bioenergy Industry in the EU28 Region.” Renewable and Sustainable Energy Reviews, doi:10.1016/j.rser.2017.04.049.
   Web of Science ®Google Scholar
• Billings, Blake W., and Kody M. Powell. 2022. “Grid-Responsive Smart Manufacturing: A Perspective for an Interconnected Energy Future in the Industrial Sector.” AIChE Journal 68 (12): John Wiley & Sons, Ltd: e17920. doi:10.1002/AIC.17920.
   Web of Science ®Google Scholar
• Billings, Blake W., Philip J. Smith, Sean T. Smith, and Kody M. Powell. 2022. “Industrial Battery Operation and Utilization in the Presence of Electrical Load Uncertainty Using Bayesian Decision Theory.” Journal of Energy Storage 53 (September), Elsevier Ltd. doi:10.1016/j.est.2022.105054.
   Google Scholar
• Bracale, Antonio, Pierluigi Caramia, Pasquale de Falco, and Tao Hong. 2020. “A Multivariate Approach to Probabilistic Industrial Load Forecasting.” Electric Power Systems Research 187 (October): Elsevier: 106430. doi:10.1016/j.epsr.2020.106430.
   Google Scholar
• Chen, Yunzhi, Blake Billings, Sammy Partridge, Brittany Pruneau, and Kody M. Powell. 2022. “Grid-Responsive Smart Manufacturing: Can the Manufacturing Sector Help Incorporate Renewables?” IFAC-PapersOnLine 55 (10): Elsevier: 637–642. doi:10.1016/J.IFACOL.2022.09.473.
   Google Scholar
• Chen, Yunzhi, Lizzie Pinegar, Jake Immonen, and Kody M. Powell. 2023. “Conversion of Food Waste to Renewable Energy: A Techno-Economic and Environmental Assessment.” Journal of Cleaner Production 385 (January), Elsevier Ltd. doi:10.1016/j.jclepro.2022.135741.
   Google Scholar
• Chong, Lee Wai, Yee Wan Wong, Rajprasad Kumar Rajkumar, Rajpartiban Kumar Rajkumar, and Dino Isa. 2016. “Hybrid Energy Storage Systems and Control Strategies for Stand-Alone Renewable Energy Power Systems.” Renewable and Sustainable Energy Reviews, doi:10.1016/j.rser.2016.07.059.
   Google Scholar
• Cole, Wesley, and A. Will Frazier. 2020. “Cost Projections for Utility-Scale Battery Storage.” https://www.nrel.gov/docs/fy20osti/75385.pdf.
   Google Scholar
• Gallo, A. B., J. R. Simões-Moreira, H. K. M. Costa, M. M. Santos, and E. Moutinho dos Santos. 2016. “Energy Storage in the Energy Transition Context: A Technology Review.” Renewable and Sustainable Energy Reviews, doi:10.1016/j.rser.2016.07.028.
   Web of Science ®Google Scholar
• Ho, An, Daniel Hill, John Hedengren, and Kody M. Powell. 2022. “A Nuclear-hydrogen Hybrid Energy System with Large-Scale Storage: A Study in Optimal Dispatch and Economic Performance in a Real-World Market.” Journal of Energy Storage 51 (July), Elsevier Ltd. doi:10.1016/j.est.2022.104510.
   Google Scholar
• Huang, Xuefei, Seung Ho Hong, Mengmeng Yu, Yuemin DIng, and Junhui Jiang. 2019. “Demand Response Management for Industrial Facilities: A Deep Reinforcement Learning Approach.” IEEE Access 7: Institute of Electrical and Electronics Engineers Inc.: 82194–82205. doi:10.1109/ACCESS.2019.2924030.
   Web of Science ®Google Scholar
• Kelley, Morgan T., Tam T. Do, and Michael Baldea. 2022. “Evaluating the Demand Response Potential of Ammonia Plants.” AIChE Journal 68 (3): John Wiley & Sons, Ltd: e17552. doi:10.1002/AIC.17552.
   Web of Science ®Google Scholar
• Machalek, Derek, and Kody Powell. 2019. “Automated Electrical Demand Peak Leveling in a Manufacturing Facility with Short Term Energy Storage for Smart Grid Participation.” Journal of Manufacturing Systems 52 (July): Elsevier: 100–109. doi:10.1016/j.jmsy.2019.06.001.
   Google Scholar
• Machalek, Derek, Aaron Young, Landen Blackburn, Pratt Rogers, and Kody M. Powell. 2020. “Mine Operations as a Smart Grid Resource: Leveraging Excess Process Storage Capacity to Better Enable Renewable Energy Sources.” Minerals Engineering 145 (January): Pergamon: 106103. doi:10.1016/j.mineng.2019.106103.
   Google Scholar
• Mishra, Shubhangi, Gaurav Saini, Saikat Saha, Anurag Chauhan, Anuj Kumar, and Santanu Maity. 2022. “A Survey on Multi-Criterion Decision Parameters, Integration Layout, Storage Technologies, Sizing Methodologies and Control Strategies for Integrated Renewable Energy System.” Sustainable Energy Technologies and Assessments 52 (August), Elsevier Ltd. doi:10.1016/j.seta.2022.102246.
   Google Scholar
• NREL. 2012. “Life Cycle Greenhouse Gas Emissions from Solar Photovoltaics.” Carbonigiovanni.It. https://www.nrel.gov/docs/fy13osti/56487.pdf.
   Google Scholar
• Olatomiwa, Lanre, Saad Mekhilef, M. S. Ismail, and M. Moghavvemi. 2016. “Energy Management Strategies in Hybrid Renewable Energy Systems: A Review.” Renewable and Sustainable Energy Reviews, doi:10.1016/j.rser.2016.05.040.
   Google Scholar
• Otashu, Joannah I., and Michael Baldea. 2019. “Demand Response-Oriented Dynamic Modeling and Operational Optimization of Membrane-Based Chlor-Alkali Plants.” Computers & Chemical Engineering 121 (February): Pergamon: 396–408. doi:10.1016/j.compchemeng.2018.08.030.
   Google Scholar
• Rapier, Robert. 2020. “Estimating the Carbon Footprint of Utility-Scale Battery Storage.” https://www.forbes.com/sites/rrapier/2020/02/16/estimating-the-carbon-footprint-of-utility-scale-battery-storage/?sh=6cec55767adb.
   Google Scholar
• Sulaima, Mohamad Fani, Siti Aishah Abu Hanipah, Nur Rafiqah Abdul Razif, Intan Azmira Wan Abdul Razak, Aida Fazliana Abdul Kadir, and Zul Hasrizal Bohari. 2020. “Industrial Energy Load Profile Forecasting Under Enhanced Time of Use Tariff (ETOU) Using Artificial Neural Network.” International Journal of Advanced Computer Science and Applications 11 (12): The Science and Information (SAI) Organization Limited: 204–209. doi:10.14569/IJACSA.2020.0111226.
   Web of Science ®Google Scholar
• Tsay, Calvin, Ankur Kumar, Jesus Flores-Cerrillo, and Michael Baldea. 2019. “Optimal Demand Response Scheduling of an Industrial Air Separation Unit Using Data-Driven Dynamic Models.” Computers & Chemical Engineering 126 (July): Pergamon: 22–34. doi:10.1016/j.compchemeng.2019.03.022.
   Google Scholar
• US EIA. 2022. “Monthly Energy Review.” https://www.eia.gov/totalenergy/data/monthly/pdf/mer.pdf.
   Google Scholar
• Wang, Shasha, Scott J. Mason, and Harsha Gangammanavar. 2020. “Stochastic Optimization for Flow-Shop Scheduling with on-Site Renewable Energy Generation Using a Case in the United States.” Computers & Industrial Engineering 149 (November): Pergamon: 106812. doi:10.1016/j.cie.2020.106812.
   Google Scholar