OPTICAL BASED EMISSION MONITORING SYSTEMS FOR COMBUSTION TURBINE SCR PROCESS CONTROL AND CEM APPLICATIONS

被引:0
|
作者
Himes, Richard [1 ]
机构
[1] EPRI, Palo Alto, CA 94304 USA
关键词
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In parallel with the trend of increasing gas generation, regulatory scrutiny of utility gas turbine emissions is projected to increase as utilities operate their gas turbine fleets dynamically in response to the variability of wind and solar generation resources. While SCR systems have historically provided significant incremental NOx control capability beyond dry low NOx combustor emission levels, associated ammonia injection process control systems are still reliant on extractive based sampling approaches, with up to several minute response time delays. These response time delays in ammonia injection control can lead to time periods of over, or under injection of SCR ammonia during load cycling. In-situ, optical based monitoring systems have the potential to improve SCR process control time response, while also reducing lifecycle operating and maintenance costs associated with NOx/diluent monitoring systems used for SCR process control. The current paper assesses the accuracy associated with several in-situ optical monitors applied on the stack of a gas turbine combined cycle unit. Moreover, the demonstration explores novel optical monitor configurations for multi-specie measurements that could ultimately reduce the number of measurement paths required for typical continuous emission monitoring (CEM) purposes (e.g., NO, NO2, CO, NH3, CO2, O-2 and H2O). In regard to potential CEM applications, the current paper also examines in-situ optical monitor calibration approaches required under the current CEM regulatory framework, associated issues and measurement configurations that could potentially comply with current CEM quality assurance requirements.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Optical characterization of concentrated dispersions:: applications to laboratory analyses and on-line process monitoring and control
    Buron, H
    Mengual, O
    Meunier, G
    Cayré, I
    Snabre, P
    POLYMER INTERNATIONAL, 2004, 53 (09) : 1205 - 1209
  • [32] Wind Turbine Monitoring and Control Systems Using Internet of Things
    Kalyanraj, D.
    Prakash, S. Lenin
    Sabareswar, S.
    2016 INTERNATIONAL CONFERENCE ON 21ST CENTURY ENERGY NEEDS - MATERIALS, SYSTEMS AND APPLICATIONS (ICTFCEN), 2016,
  • [33] Fuzzy linguistic control systems for process control applications
    Singh, YP
    Ahmad, N
    JOURNAL OF THE INSTITUTION OF ELECTRONICS AND TELECOMMUNICATION ENGINEERS, 1996, 42 (06): : 363 - 376
  • [34] Automatic Database Monitoring for Process Control Systems
    Kaneko, Hiromasa
    Funatsu, Kimito
    MODERN ADVANCES IN APPLIED INTELLIGENCE, IEA/AIE 2014, PT I, 2014, 8481 : 410 - 419
  • [35] Diagnostics and Condition Monitoring of Process Control Systems
    Lotz, Peter
    ATP EDITION, 2009, (04): : 30 - 35
  • [36] Adaptive systems for machining process monitoring and control
    DErrico, GE
    JOURNAL OF MATERIALS PROCESSING TECHNOLOGY, 1997, 64 (1-3) : 75 - 84
  • [37] CIPS-based alcohol production process monitoring and optimal control systems
    Qiang, S
    Zhang, T
    Gao, XZ
    Zhuang, XY
    CCA 2003: PROCEEDINGS OF 2003 IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1 AND 2, 2003, : 861 - 864
  • [38] NDT Based Process Monitoring and Control
    Wolter, Bernd
    Dobmann, Gerd
    Boller, Christian
    STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 2011, 57 (03): : 218 - 226
  • [39] APPLICATIONS OF MASS SPECTROMETERS TO PLASMA PROCESS MONITORING AND CONTROL
    BROWN, HL
    BUNYARD, GB
    LIN, KC
    SOLID STATE TECHNOLOGY, 1978, 21 (07) : 35 - 38
  • [40] Multivariable control and advanced monitoring: Applications to hydrocracking process
    Saudi Aramco's Riyadh Refinery, Saudi Arabia
    Saudi Aramco J. Technol., 2006, SUMMER (33-37):