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在水电气气候联系的视角下,一种新的资源管理方法
Cigdem Coskun Dilcan1, Merih Aydinalp Koksal2
1Hacettepe University, Department of Environmental Engineering, Beytepe, 06800 Ankara, Turkiye; Present address: Ankara University, Water Management Institute, 06135 Ankara, Turkiye.
The Science of the total environment
|June 20, 2025
概括
本研究使用适应性神经模糊推理系统 (ANFIS) 模型预测化石燃料发电厂的用水量. 该ANFIS模型准确地预测了水消耗,这对于气候变化下的可持续水能管理至关重要.
科学领域:
- 环境科学 环境科学
- 能源系统 能源系统
- 适应气候变化 适应气候变化
背景情况:
- 有效地管理水和能源资源对于可持续性至关重要.
- 水能联系,特别是发电中的水消耗,面临着气候变化带来的挑战.
- 需要在发电厂使用水的预测工具.
研究的目的:
- 评估适应性神经模糊推理系统 (ANFIS) 模型,用于预测化石燃料发电厂的水消耗.
- 分析气候变化情景对未来发电用水需求的影响.
- 为水和能源资源管理提供决策工具.
主要方法:
- 应用了ANFIS模型,使用70个化石燃料工厂的运营数据和气象参数.
- 利用85%的培训和15%的测试数据分割进行模型优化.
- 使用平均绝对百分比误差 (MAPE) 和确定系数 (R2) 验证模型性能.
主要成果:
- 该ANFIS模型表现出强大的预测性能,其MAPE为4.62%和R2为0.9984.
- 预计到2053年,化石燃料发电厂的用水量将在2.13至2.46亿立方米之间.
- 根据各种气候情景,预计水的强度在993至1146 m3/GWh之间.
结论:
- 安菲斯模型是预测发电用水量的可靠工具.
- 气候变化对能源部门的水消耗有重大影响.
- 这些发现支持节水和有效的技术开发,以实现可持续的资源管理.
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