一项基于多个线性回归模型的多能互补电力系统碳排放预测研究
Jiangbo Sha1, Wenni Kang1, Rui Ma1
1State Grid Ningxia Electric Power Co., Ltd. Technical Research Institute, Yinchuan, 750002, Ningxia, China.
Carbon balance and management
|February 8, 2026
概括
本研究引入了多重线性回归模型,用于准确预测多能电力系统中的碳排放. 该模型有效处理大型数据集,识别准确排放预测的关键因素.
科学领域:
- 能源系统工程 能源系统工程
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 多种能源的互补电力系统产生了大量的操作数据,这给准确的碳排放预测带来了挑战.
- 现有的方法很难有效地处理大规模的分布式数据以进行可靠的预测.
研究的目的:
- 为多能源互补电力系统开发高精度碳排放预测方法.
- 确定这些系统中影响碳排放的关键因素.
- 为了提高计算可扩展性和预测效率.
主要方法:
- 分析多能源互补电力系统结构和碳排放强度.
- 选择初步影响碳排放的因素.
- 使用显著性测试构建和优化多重线性回归模型.
- 该模型与MapReduce平行框架的集成.
主要成果:
- 优化的多重线性回归模型表现出高度的适合性.
- 预测错误是最小的,范围从0.00516%到0.00818%,表明高准确度.
- 该模型成功地有效处理了大规模的分布式数据.
结论:
- 开发的方法准确地预测了多能源互补电力系统中的碳排放.
- 该模型的发现为有效的碳减排政策提供了基础.
- 预计每年的碳排放量将增加到2031年,然后下降到2034年.
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