4.6 Article

Energy audit and management of environmental GHG emissions based on multi-objective genetic algorithm and data envelopment analysis: An agriculture case

Journal

ENERGY REPORTS
Volume 10, Issue -, Pages 1507-1520

Publisher

ELSEVIER
DOI: 10.1016/j.egyr.2023.08.020

Keywords

Energy audit; Environmental sustainability; Optimization; Multi-objective genetic algorithm

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This study aimed to address the challenges of energy consumption and environmental emissions in the mushroom production sector through energy audit analysis and life cycle assessment. Results showed significant energy imbalance and inefficiency in mushroom production, with electrical energy consumption being the largest contributor. The study also identified opportunities for energy savings, particularly in compost, through the use of optimization techniques.
This study aimed to address the challenges of energy consumption and environmental emissions in the mushroom production sector through an energy audit analysis and life cycle assessment approach. The main objective of the study was to estimate energy and environmental indicators, optimize their outputs using multi-objective genetic algorithm and data envelopment analysis methods, and identify opportunities for energy savings in the mushroom production process. The energy flow analysis revealed that the total input energy for mushroom production was 1022537.82 MJ/m2, while the total output energy was only 11125.94 MJ/m2, resulting in an energy use efficiency rate of 0.01, indicating significant energy imbalance and inefficiency. Electrical energy consumption had the largest share of total consumed energy, approximately 80.6%. The life cycle assessment results showed that the mushroom production chain emits about 8.50 x 10+3 kg of CO2 GHG. The results of energy optimization demonstrate that between 6.5% and 25% reductions in energy utilization can be achieved during mushroom production. Among the input energies, compost had the largest quota in energy savings of almost 7% and 26% by data envelopment analysis and multi-objective genetic algorithm techniques, respectively. Thus, it is recommended to implement the multi-objective genetic algorithm technique to identify opportunities for energy savings and reduce environmental emissions in the mushroom production sector, which can lead to significant energy savings and contribute to environmental sustainability while reducing operating costs.& COPY; 2023 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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