Development of deterministic-stochastic model to integrate variable renewable energy-driven electricity and large-scale utility networks: Towards decarbonization petrochemical industry

Soonho Hwangbo, Sung Ku Heo, Chang Kyoo Yoo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

This paper aims to develop the mathematical model of electricity based on renewable energy and large-scale utility (eRELU) networks to achieve a low-carbon economy. Huge petrochemical industries allocated in South Korea are considered to evaluate the proposed model by techno-economic and environmental assessment subject to Korean renewable energy policy. The suggested mathematical model consists of two parts: the deterministic model to optimize industrial-scale utility networks and the stochastic model to construct clean electricity networks using variable renewable energy coupled with energy storage systems to provide feasible quantities of renewable electricity required from the optimized utility network. The resulting model is complemented by carbon capture and storage (CCS) systems in doing so the inevitable amount of greenhouse gases from boilers in utility networks can be significantly captured. Diverse scenarios under the uncertain parameters such as facility investment/operating costs and capacity factors of renewable energy are applied to the developed model, and the results show that the best scenario-based eRELU-CCS network reduces 16% of the total costs and capture/mitigate 114 tCO2/d comparing to the base case. It is expected that the proposed model will play an essential role in advancing the country's energy transition.

Original languageEnglish
Article number122006
JournalEnergy
Volume238
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • Climate change
  • Large-scale utility network
  • Mathematical programming
  • Petrochemical industry
  • Renewable energy policy
  • Variable renewable electricity

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