由人工智能驱动的中国电力行业低碳绩效评估 - - 以上海电力有限公司为例
1Sichuan College of Architectural Technology, China.
Heliyon
|February 3, 2025
概括
中国的电力行业需要一个新的绩效评估系统,以实现低碳发展. 本研究使用人工智能驱动的DPSIR-TOPSIS模型来评估上海电力,为未来的低碳计划提供战略.
科学领域:
- 环境科学 环境科学
- 能源政策 能源政策
- 人工智能的人工智能
背景情况:
- 中国的工业转型强调低碳发展,特别是在能源领域.
- 电力企业需要为可持续实践量身定制的绩效评估系统.
- 人工智能 (AI) 的整合为低碳生产提供了新的机会.
研究的目的:
- 为中国的电力企业开发和应用一种新的绩效评估框架.
- 评估人工智能对能源行业低碳生产战略的影响.
- 为加强中国电力部门的低碳倡议提供可行的建议.
主要方法:
- 使用驱动-压力-状态-冲击-响应-技术,以类似于理想解决方案的顺序偏好 (DPSIR-TOPSIS) 模型.
- 将人工智能集成到DPSIR-TOPSIS分析中,以加强战略规划.
- 对上海电力有限公司进行了案例研究,以验证该框架.
主要成果:
- 由人工智能驱动的DPSIR-TOPSIS模型有效地简化了复杂的环境和性能因素.
- 该分析为上海电力公司提供了对未来低碳运营的更清晰的战略前景.
- 确定了改善企业低碳绩效的关键领域.
结论:
- 开发的框架提供了一个强大的方法来评估电力行业的低碳性能.
- 持续监测,鼓励研究和政策支持对于推进低碳努力至关重要.
- 人工智能集成对于优化可持续能源发展的战略规划和执行至关重要.
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