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Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry

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  • Heo, SungKu
  • Byun, Jaewon
  • Ifaei, Pouya
  • Ko, Jaerak
  • Ha, Byeongmin
  • Hwangbo, Soonho
  • Yoo, ChangKyoo

Abstract

In alignment with climate change mitigation plans, renewable and sustainable energy integration into the industrial sector should be investigated for decarbonization purposes by 2050. This study aims to examine the feasibility of decarbonization of mega-scale industrial parks with two emerging technologies; first, an integrated energy system involving an air separation unit (ASU) and a liquid air energy storage (LAES)-based power generation system (ALPG) with the assistance of a large-scale liquified natural gas (LNG) plant and second, the green electricity predicted by various renewable energy (VRE) scenarios using an AI-driven generative model concerning techno-economic and environmental analyses. Firstly, the electricity demand of mega-scale petrochemical industrial complexes was allocated, and remote sensing data of VRE (wind and solar) were collected in South Korea. Then, the ALPG was modeled to consider the actual operation of an LNG plant near target complexes. Subsequently, the CC-informed VRE scenario generation model (CC-VRES) based on an adversarial autoencoder (AAE) algorithm was developed to generate VRE scenarios considering the CC effects. Finally, techno-economic and environmental assessments were conducted to target the mega-DIP by 2050. The results showed that the levelized cost of electricity of the proposed ALPG was 150 $/MWh, which is enough to supply the required sustainable electricity, considering the Korean energy plan and CC effects in the CC-VRES model. Therefore, the excess VRE can be used to decarbonize the target industrial parks; it is anticipated that 26,084 GW h/yr of renewable and sustainable electricity will be generated and cover the total electricity demand of Yeosu and Ulsan target complexes while reducing 13,943-kilo t CO2 eq./yr through 2050.

Suggested Citation

  • Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    • Handle: RePEc:eee:rensus:v:189:y:2024:i:pa:s1364032123007918
    DOI: 10.1016/j.rser.2023.113933
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    1. Mayer, Martin János & Biró, Bence & Szücs, Botond & Aszódi, Attila, 2023. "Probabilistic modeling of future electricity systems with high renewable energy penetration using machine learning," Applied Energy, Elsevier, vol. 336(C).
    2. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    3. Antonelli, Marco & Barsali, Stefano & Desideri, Umberto & Giglioli, Romano & Paganucci, Fabrizio & Pasini, Gianluca, 2017. "Liquid air energy storage: Potential and challenges of hybrid power plants," Applied Energy, Elsevier, vol. 194(C), pages 522-529.
    4. He, Tianbiao & Chong, Zheng Rong & Zheng, Junjie & Ju, Yonglin & Linga, Praveen, 2019. "LNG cold energy utilization: Prospects and challenges," Energy, Elsevier, vol. 170(C), pages 557-568.
    5. Dong, Lei & Wang, Lijie & Khahro, Shahnawaz Farhan & Gao, Shuang & Liao, Xiaozhong, 2016. "Wind power day-ahead prediction with cluster analysis of NWP," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1206-1212.
    6. Poncela, Marta & Poncela, Pilar & Perán, José Ramón, 2013. "Automatic tuning of Kalman filters by maximum likelihood methods for wind energy forecasting," Applied Energy, Elsevier, vol. 108(C), pages 349-362.
    7. Rodrigues, E.M.G. & Godina, R. & Santos, S.F. & Bizuayehu, A.W. & Contreras, J. & Catalão, J.P.S., 2014. "Energy storage systems supporting increased penetration of renewables in islanded systems," Energy, Elsevier, vol. 75(C), pages 265-280.
    8. Lin, Boqiang & Wu, Wei & Bai, Mengqi & Xie, Chunping & Radcliffe, Jonathan, 2019. "Liquid air energy storage: Price arbitrage operations and sizing optimization in the GB real-time electricity market," Energy Economics, Elsevier, vol. 78(C), pages 647-655.
    9. Chengqing, Yu & Guangxi, Yan & Chengming, Yu & Yu, Zhang & Xiwei, Mi, 2023. "A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks," Energy, Elsevier, vol. 263(PE).
    10. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    11. Ebrahimi, Armin & Meratizaman, Mousa & Akbarpour Reyhani, Hamed & Pourali, Omid & Amidpour, Majid, 2015. "Energetic, exergetic and economic assessment of oxygen production from two columns cryogenic air separation unit," Energy, Elsevier, vol. 90(P2), pages 1298-1316.
    12. Sun, Mucun & Feng, Cong & Zhang, Jie, 2020. "Probabilistic solar power forecasting based on weather scenario generation," Applied Energy, Elsevier, vol. 266(C).
    13. Hwangbo, Soonho & Heo, SungKu & Yoo, ChangKyoo, 2022. "Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry," Energy, Elsevier, vol. 238(PC).
    14. Sciacovelli, A. & Vecchi, A. & Ding, Y., 2017. "Liquid air energy storage (LAES) with packed bed cold thermal storage – From component to system level performance through dynamic modelling," Applied Energy, Elsevier, vol. 190(C), pages 84-98.
    15. Cassola, Federico & Burlando, Massimiliano, 2012. "Wind speed and wind energy forecast through Kalman filtering of Numerical Weather Prediction model output," Applied Energy, Elsevier, vol. 99(C), pages 154-166.
    16. Xie, Chunping & Hong, Yan & Ding, Yulong & Li, Yongliang & Radcliffe, Jonathan, 2018. "An economic feasibility assessment of decoupled energy storage in the UK: With liquid air energy storage as a case study," Applied Energy, Elsevier, vol. 225(C), pages 244-257.
    17. Kim, SangYoun & Heo, SungKu & Nam, KiJeon & Woo, TaeYong & Yoo, ChangKyoo, 2023. "Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach," Energy, Elsevier, vol. 282(C).
    18. Lazić, Lazar & Pejanović, Goran & Živković, Momčilo, 2010. "Wind forecasts for wind power generation using the Eta model," Renewable Energy, Elsevier, vol. 35(6), pages 1236-1243.
    19. Kim, Juwon & Noh, Yeelyong & Chang, Daejun, 2018. "Storage system for distributed-energy generation using liquid air combined with liquefied natural gas," Applied Energy, Elsevier, vol. 212(C), pages 1417-1432.
    20. Li, Jinghua & Zhou, Jiasheng & Chen, Bo, 2020. "Review of wind power scenario generation methods for optimal operation of renewable energy systems," Applied Energy, Elsevier, vol. 280(C).
    21. She, Xiaohui & Zhang, Tongtong & Cong, Lin & Peng, Xiaodong & Li, Chuan & Luo, Yimo & Ding, Yulong, 2019. "Flexible integration of liquid air energy storage with liquefied natural gas regasification for power generation enhancement," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    22. Østergaard, Poul Alberg & Jantzen, Jan & Marczinkowski, Hannah Mareike & Kristensen, Michael, 2019. "Business and socioeconomic assessment of introducing heat pumps with heat storage in small-scale district heating systems," Renewable Energy, Elsevier, vol. 139(C), pages 904-914.
    23. Ma, Tao & Østergaard, Poul Alberg & Lund, Henrik & Yang, Hongxing & Lu, Lin, 2014. "An energy system model for Hong Kong in 2020," Energy, Elsevier, vol. 68(C), pages 301-310.
    24. Madlener, Reinhard & Kowalski, Katharina & Stagl, Sigrid, 2007. "New ways for the integrated appraisal of national energy scenarios: The case of renewable energy use in Austria," Energy Policy, Elsevier, vol. 35(12), pages 6060-6074, December.
    25. Vehvilainen, Iivo & Pyykkonen, Tuomas, 2005. "Stochastic factor model for electricity spot price--the case of the Nordic market," Energy Economics, Elsevier, vol. 27(2), pages 351-367, March.
    26. Kam, Olle Michel & Noël, Stéphane & Ramenah, Harry & Kasser, Pierre & Tanougast, Camel, 2021. "Comparative Weibull distribution methods for reliable global solar irradiance assessment in France areas," Renewable Energy, Elsevier, vol. 165(P1), pages 194-210.
    27. Evans, Annette & Strezov, Vladimir & Evans, Tim J., 2012. "Assessment of utility energy storage options for increased renewable energy penetration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4141-4147.
    28. Tawn, R. & Browell, J., 2022. "A review of very short-term wind and solar power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    29. Yang Guo & Jinping Tian & Lyujun Chen, 2020. "Managing energy infrastructure to decarbonize industrial parks in China," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    30. She, Xiaohui & Peng, Xiaodong & Nie, Binjian & Leng, Guanghui & Zhang, Xiaosong & Weng, Likui & Tong, Lige & Zheng, Lifang & Wang, Li & Ding, Yulong, 2017. "Enhancement of round trip efficiency of liquid air energy storage through effective utilization of heat of compression," Applied Energy, Elsevier, vol. 206(C), pages 1632-1642.
    31. Nie, S. & Huang, Charley Z. & Huang, G.H. & Li, Y.P. & Chen, J.P. & Fan, Y.R. & Cheng, G.H., 2016. "Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing," Applied Energy, Elsevier, vol. 162(C), pages 772-786.
    32. Thapar, Sapan & Sharma, Seema & Verma, Ashu, 2016. "Economic and environmental effectiveness of renewable energy policy instruments: Best practices from India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 487-498.
    33. Cheng, Yuanyuan & Yao, Xin, 2021. "Carbon intensity reduction assessment of renewable energy technology innovation in China: A panel data model with cross-section dependence and slope heterogeneity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    34. Wang, Chen & Akkurt, Nevzat & Zhang, Xiaosong & Luo, Yimo & She, Xiaohui, 2020. "Techno-economic analyses of multi-functional liquid air energy storage for power generation, oxygen production and heating," Applied Energy, Elsevier, vol. 275(C).
    35. Costoya, X. & deCastro, M. & Carvalho, D. & Arguilé-Pérez, B. & Gómez-Gesteira, M., 2022. "Combining offshore wind and solar photovoltaic energy to stabilize energy supply under climate change scenarios: A case study on the western Iberian Peninsula," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    36. Vidal-Amaro, Juan José & Østergaard, Poul Alberg & Sheinbaum-Pardo, Claudia, 2015. "Optimal energy mix for transitioning from fossil fuels to renewable energy sources – The case of the Mexican electricity system," Applied Energy, Elsevier, vol. 150(C), pages 80-96.
    37. Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    38. Ghritlahre, Harish Kumar & Prasad, Radha Krishna, 2018. "Application of ANN technique to predict the performance of solar collector systems - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 84(C), pages 75-88.
    39. Cao, J.C. & Cao, S.H., 2006. "Study of forecasting solar irradiance using neural networks with preprocessing sample data by wavelet analysis," Energy, Elsevier, vol. 31(15), pages 3435-3445.
    40. Carrillo, C. & Obando Montaño, A.F. & Cidrás, J. & Díaz-Dorado, E., 2013. "Review of power curve modelling for wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 572-581.
    41. He, Xiufen & Liu, Yunong & Rehman, Ali & Wang, Li, 2021. "A novel air separation unit with energy storage and generation and its energy efficiency and economy analysis," Applied Energy, Elsevier, vol. 281(C).
    42. Abdin, I.F. & Fang, Y.-P. & Zio, E., 2019. "A modeling and optimization framework for power systems design with operational flexibility and resilience against extreme heat waves and drought events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 706-719.
    43. Zuluaga, Carlos D. & Álvarez, Mauricio A. & Giraldo, Eduardo, 2015. "Short-term wind speed prediction based on robust Kalman filtering: An experimental comparison," Applied Energy, Elsevier, vol. 156(C), pages 321-330.
    44. Castorrini, Alessio & Gentile, Sabrina & Geraldi, Edoardo & Bonfiglioli, Aldo, 2023. "Investigations on offshore wind turbine inflow modelling using numerical weather prediction coupled with local-scale computational fluid dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    45. Corrêa da Silva, Rodrigo & de Marchi Neto, Ismael & Silva Seifert, Stephan, 2016. "Electricity supply security and the future role of renewable energy sources in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 328-341.
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