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The optimal behavior of renewable energy resources and government's energy consumption subsidy design from the perspective of green technology implementation

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  • Lee, Chien-Chiang
  • Hussain, Jafar
  • Chen, Yongxiu

Abstract

Carbon emissions are a major problem in the industrial sector due to energy consumption. As a solution, this research first investigates the impact of energy consumption and shortfall on green technology implementation from 1000 textile firms in Punjab, Pakistan and for energy shortfall incorporates subsidy variables to make green technology implementation possible via a binary logistic regression model. Second, we develop a simulation-based optimization model to measure the optimal behavior of energy consumption parameters to clean the environment under green technology implementation. The results depict that renewable energy resources (coal, corn cobs, and wood) positively affect green technology implementation. Interestingly, energy shortfall (electricity and gas) is also impacted positively due to the move of industries towards renewable resources during this shortage period. We find a higher quantity of wood in optimal behavior analysis instead of coal and cobs due to its ease of availability. An optimal subsidy on electricity shortfall is found to be greater than the natural gas shortfall subsidy due to its higher shortfall. This study helps the government to decide the optimal energy shortfall for saving energy usage and to manage the optimal level of subsidies in order to overcome energy usage problems. It also benefits the textile industry in deciding over the optimal energy consumption level to make the environment clean in terms of green technology implementation.

Suggested Citation

  • Lee, Chien-Chiang & Hussain, Jafar & Chen, Yongxiu, 2022. "The optimal behavior of renewable energy resources and government's energy consumption subsidy design from the perspective of green technology implementation," Renewable Energy, Elsevier, vol. 195(C), pages 670-680.
    • Handle: RePEc:eee:renene:v:195:y:2022:i:c:p:670-680
    DOI: 10.1016/j.renene.2022.06.070
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