Sequential Combustion in Gas Turbines: The Key Technology for Burning High Hydrogen Contents With Low Emissions

燃烧 燃烧室 天然气 工艺工程 降额 核工程 环境科学 化学 废物管理 工程类 热力学 物理 功率(物理) 有机化学
作者
Mirko R. Bothien,Andrea Ciani,John Wood,Gerhard Fruechtel
标识
DOI:10.1115/gt2019-90798
摘要

Abstract Excess energy generation from renewables can be conveniently stored as hydrogen for later use as a gas turbine fuel. Also, the strategy to sequestrate CO2 from natural gas will require gas turbines to run with hydrogen-based fuels. In such scenarios, high temperature low emission combustion of hydrogen is a key requirement for the future gas turbine market. Ansaldo Energia’s gas turbines featuring sequential combustion have an intrinsic advantage when it comes to fuel flexibility and in particular hydrogen-based fuels. The sequential combustion system is composed of two complementary combustion stages in series: one premix stage followed by an auto-ignited second stage overcoming the limits of traditional premix combustion systems through a highly effective extra tuning parameter, i.e. the temperature between the first and the second stage. The standard Constant Pressure Sequential Combustion (CPSC) system as applied in the GT36 engine is tested, at high pressure, demonstrating that a modified operation concept allows stable combustion with no changes in combustor hardware for the whole range of natural gas and hydrogen blends. It is shown that in the range from 0% to 70% (vol.) hydrogen, stable combustion is achieved at full nominal exit temperature, i.e. without any derating and thus clearly outperforming other available conventional premixed combustors. Operation between 70% and 100% is possible as well and only requires a mild reduction of the combustor exit temperature. By proving the transferability of the single-can high pressure results to the engine, this paper demonstrates the practicality of operating the Ansaldo Energia GT36 H-Class gas turbine on fuels containing unprecedented concentrations of hydrogen while maintaining excellent performance and low emissions both in terms of NOx and CO2.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
无奈的苗条完成签到,获得积分10
刚刚
研友_VZG7GZ应助琛哥物理采纳,获得10
1秒前
每天100次发布了新的文献求助10
1秒前
1秒前
大个应助hp571采纳,获得10
1秒前
Twistzz完成签到,获得积分10
1秒前
2秒前
我是老大应助暖羊羊Y采纳,获得10
2秒前
why911完成签到,获得积分10
3秒前
climber发布了新的文献求助10
4秒前
4秒前
虚拟的乞完成签到,获得积分10
4秒前
molihuakai应助华夫饼采纳,获得10
4秒前
Lucky牛发布了新的文献求助10
4秒前
4秒前
5秒前
微笑给微笑的求助进行了留言
6秒前
Hello应助chengyou采纳,获得10
6秒前
loy发布了新的文献求助20
6秒前
窝瓜顶呱呱完成签到,获得积分10
6秒前
6秒前
soda完成签到,获得积分10
7秒前
无奈的苗条关注了科研通微信公众号
8秒前
踏实不斜发布了新的文献求助10
9秒前
欢呼的不尤完成签到,获得积分10
10秒前
大胆金针菇完成签到,获得积分10
10秒前
lyzzz发布了新的文献求助10
10秒前
sleepless完成签到,获得积分10
10秒前
10秒前
11秒前
11秒前
领导范儿应助平常心采纳,获得10
11秒前
12秒前
12秒前
MYY完成签到,获得积分10
13秒前
yiyi131发布了新的文献求助10
13秒前
Yrzyc应助天真的眼睛采纳,获得10
13秒前
共享精神应助迟迟采纳,获得10
13秒前
天天快乐应助yiyi采纳,获得10
14秒前
NexusExplorer应助Bo采纳,获得10
14秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Materials selection in mechanical design 500
Bounds for Statistical Estimation in Semiparametric Models 500
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6477542
求助须知:如何正确求助?哪些是违规求助? 8279378
关于积分的说明 17657260
捐赠科研通 5559693
什么是DOI,文献DOI怎么找? 2910880
邀请新用户注册赠送积分活动 1887826
关于科研通互助平台的介绍 1741360