Model for sustainable carbon emission reduction energy development and smart grid technology strategy
In the context of sustainable energy development to reduce carbon emissions, the application of new energy sources and smart grid technologies in power systems is becoming more widespread. However, current research results on power system technology strategies for carbon emission reduction are not s...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2024-11-01
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| Series: | AIMS Energy |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/energy.2024055 |
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| Summary: | In the context of sustainable energy development to reduce carbon emissions, the application of new energy sources and smart grid technologies in power systems is becoming more widespread. However, current research results on power system technology strategies for carbon emission reduction are not satisfactory. To address this problem, a model for optimal power system operation and scheduling based on the prediction error mechanism and synthetic fuel technology is proposed. The model used the carbon trading mechanism to further reduce carbon emissions and the carnivorous plant algorithm to optimize the scheduling strategy. The results indicate that the model demonstrates significant advantages in terms of carbon emission, total operating cost, prediction accuracy, and energy utilization efficiency, respectively, at 60.8 kg, 2517.5 yuan, 96.5%, and 90.2%, indicating that it utilizes energy more fully and helps to enhance the overall energy efficiency of the system. The calculation time of the optimized power system was only 12.5 s, the stability was as high as 98.7%, and the satisfaction rate was 95.6% in terms of user satisfaction. Compared to other contemporary designs, the proposed model can successfully reduce the system's carbon emissions while increasing energy efficiency. The model has positive implications for smart grid and sustainable development. |
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| ISSN: | 2333-8334 |