蒸汽数据1

蒸汽数据1 火力发电的基本原理是：燃料在燃烧时加热水生成蒸汽，蒸汽压力推动汽轮机旋转，然后汽轮机带动发电机旋转，产生电能。在这一系列的能量转化中，影响发电效率的核心是锅炉的燃烧效率，即燃料燃烧加热水产生高温高压蒸汽。锅炉的燃烧效率的影响因素很多，包括锅炉的可调参数，如燃烧给量，一二次风，引风，返料风，给水水量；以及锅炉的工况，比如锅炉床温、床压，炉膛温度、压力，过热器的温度等。

赛题描述

经脱敏后的锅炉传感器采集的数据（采集频率是分钟级别），根据锅炉的工况，预测产生的蒸汽量。

Steam Data 1
The basic principle of thermal power generation is as follows: When fuel undergoes combustion, it heats water to generate steam. The steam pressure drives the steam turbine to rotate, which in turn drives the generator to rotate and produce electric energy. In this series of energy conversion processes, the core factor affecting power generation efficiency is the combustion efficiency of the boiler, that is, the process of fuel combustion heating water to produce high-temperature and high-pressure steam.
There are many factors affecting the combustion efficiency of the boiler, including the boiler's adjustable parameters such as fuel feed rate, primary and secondary air, induced draft air, material return air and feedwater flow rate; as well as the boiler's operating conditions, such as bed temperature, bed pressure, furnace temperature, pressure and superheater temperature, etc.

Problem Description
The desensitized data collected by boiler sensors (with a minute-level sampling frequency) is used to predict the generated steam volume based on the operating conditions of the boiler.

搜集汇总

背景与挑战

背景概述

该数据集是一个用于预测火力发电蒸汽量的回归任务数据集，包含脱敏的锅炉传感器分钟级采集数据，涉及38个特征变量和1个目标变量。数据分为训练集和测试集，旨在通过锅炉工况参数（如温度、压力等）预测蒸汽产量，评估指标为均方误差（MSE），适用于能源效率优化和机器学习建模研究。