Turning Dynamic Sensor Measurements From Gas Turbines Into Insights: A Big Data Approach

2019 ◽  
Author(s):  
Roman Karlstetter ◽  
Robert Widhopf-Fenk ◽  
Jakob Hermann ◽  
Driek Rouwenhorst ◽  
Amir Raoofy ◽  
...  
Keyword(s):  
Gas Turbines ◽  
Power Plants ◽  
Large Scale ◽  
Time Windows ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Combustion Dynamics ◽  
Measurement Analysis ◽  
Data Pipeline ◽  
Sensor Measurement

Abstract Gas turbine power plants generate an ever growing amount of high frequency dynamic sensor data. One of the applications of this data is the protection against problems induced by combustion dynamics, as, e.g., with the ArgusOMDS system developed by IfTA. In the light of digitalization, this data has the potential to also be used in other areas and ultimately transform maintenance, repair and overhaul approaches. However, current solutions are not designed to cope with the large time windows needed for a general analysis and this can hinder development of advanced machine analysis algorithms. In this work, we present an end-to-end approach for large scale sensor measurement analysis, employing data mining techniques and enabling machine learning algorithms. Our approach covers the complete data pipeline from sensor measurement acquisition to analysis and visualization. We demonstrate the feasibility of our approach by presenting several case studies that prove the benefits over existing solutions.

Enhanced Fuel Flexibility and Emissions Compliance for Gas Turbines Through Model Based Controls Technology

2013 ◽  
Author(s):  
Ranjith Malapaty ◽  
Suresh M. V. J. J.
Keyword(s):  
Power Generation ◽  
Natural Gas ◽  
Gas Turbines ◽  
Power Plants ◽  
Power Demand ◽  
Combustion Dynamics ◽  
Fuel Flexibility ◽  
Plant Operations ◽  
Lng Fuel ◽  
Alternate Fuels

The world is facing complex and mounting environmental challenges. Increased fuel costs and increased market capacity in power generation markets is driving a transformation in power plant operations. Power plants are seeking ways to maximize revenue potential during peak conditions and minimize operational costs during off-peak conditions. Although proven natural gas reserves have increased globally by nearly 50% over the last 20 years, much of this growth has been focused in select regions and countries. In parallel to the discovery of new reserves is the increase in power demand across the globe. However, there are many regions of the globe in which power demand is not being matched by increased local supplies of natural gas, or in infrastructure required to supply natural gas to power generation assets. Given these drivers, there is growing global interest in LNG & alternate fuels. This phenomenon is driving a trend to explore the potential of using LNG fuels which can be easily transported across the globe as an alternative for power generation. In a carbon-constrained environment, the technology trend is for combustion systems capable of burning LNG fuel in combination with delivering the required operability. This paper will focus on developments in GE’s heavy duty gas turbines that enable operation on fuels with varying properties, providing fuel flexibility for sustainable power generation and better emissions compliance. GE’s turbine control system employs physics-based models of gas turbine operability boundaries (e.g., emissions, combustion dynamics, etc.), to continuously estimate current boundary levels and make adjustments as required.

scholarly journals Experimental Flame Front Characterisation in a Lean Premix Burner Operating with Syngas Simplified Model Fuel

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2377
Author(s):  
Edward Canepa ◽  
Alessandro Nilberto
Keyword(s):  
Flame Front ◽  
Gas Turbines ◽  
Power Plants ◽  
Large Scale ◽  
Combined Cycle ◽  
Turbulent Flames ◽  
Operating Conditions ◽  
Simplified Model ◽  
Fuel Ratio ◽  
Fluorescence Measurements

The recent growing attention to energy saving and environmental protection issues has brought attention to the possibility of exploiting syngas from gasification of biomass and coal for the firing of industrial plants included in the, so called, Integrated Gasification Combined Cycle power plants. In order to improve knowledge on the employ of syngas in lean premixed turbulent flames, a large scale swirl stabilized gas-turbine burner has been operated with a simplified model of H2 enriched syngas from coal gasification. The experimental campaign has been performed at atmospheric pressure, with operating conditions derived from scaling the real gas turbines. The results are reported here and consist of OH-PLIF (OH Planar Laser Induced Fluorescence) measurements, carried out at decreasing equivalence of air/fuel ratio conditions and analysed together with the mean aerodynamic characterisation of the burner flow field in isothermal conditions obtained through LDV (Laser Doppler Velocimetry) and PIV (Particle Image Velocimetry) measurements. The OH concentration distributions have been analysed statistically in order to obtain information about the location of the most reactive zones, and an algorithm has been applied to the data in order to identify the flame fronts. In addition, the flame front locations have been successively interpreted statistically to obtain information about their main features and their dependence on the air to fuel ratio behaviour.

scholarly journals Analysis of the behaviour of biofuel-fired gas turbine power plants

2012 ◽  
Vol 16 (3) ◽  
pp. 849-864 ◽  
Author(s):  
Marcos Escudero ◽  
Ángel Jiménez ◽  
Celina González ◽  
Rafael Nieto ◽  
Ignacio López
Keyword(s):  
Power Generation ◽  
Co2 Emissions ◽  
Gas Turbines ◽  
Power Plants ◽  
Large Scale ◽  
Fossil Fuels ◽  
Technological Development ◽  
Combined Cycle ◽  
Promising Alternative ◽  
Reduction Of Co2

The utilisation of biofuels in gas turbines is a promising alternative to fossil fuels for power generation. It would lead to a significant reduction of CO2 emissions using an existing combustion technology, although considerable changes appear to be required and further technological development is necessary. The goal of this work is to conduct energy and exergy analyses of the behaviour of gas turbines fired with biogas, ethanol and synthesis gas (bio-syngas), compared with natural gas. The global energy transformation process (i.e., from biomass to electricity) also has been studied. Furthermore, the potential reduction of CO2 emissions attained by the use of biofuels has been determined, after considering the restrictions regarding biomass availability. Two different simulation tools have been used to accomplish this work. The results suggest a high interest in, and the technical viability of, the use of Biomass Integrated Gasification Combined Cycle (BioIGCC) systems for large scale power generation.

scholarly journals Decentralized and Collaborative Scheduling Approach for Active Distribution Network with Multiple Virtual Power Plants

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3208 ◽  
Author(s):  
Xiangyu Li ◽  
Dongmei Zhao ◽  
Baicang Guo
Keyword(s):  
Distribution System ◽  
Gas Turbines ◽  
Power Plants ◽  
Large Scale ◽  
Distribution Network ◽  
Virtual Power ◽  
Distributed Energy ◽  
Active Distribution Network ◽  
Active Distribution System ◽  
Virtual Power Plants

In order to build an active distribution system with multi virtual power plants (VPP), a decentralized two-stage stochastic dispatching model based on synchronous alternating direction multiplier method (SADMM) was proposed in this paper. Through the integration of distributed energy and large-scale electric vehicles (EV) in the distribution network by VPP group, coordinative complementarity, and global optimization were realized. On the premise of energy autonomy management of active distribution network (AND) and VPP, after ensuring the privacy of stakeholders, the power of tie-line was taken as decoupling variable based on SADMM. Furthermore, without the participation of central coordinators, the optimization models of VPPs and distribution networks were decoupled to achieve fully decentralized optimization. Aiming at minimizing their own operating costs, the VPPs aggregate distributed energy and large-scale EVs within their jurisdiction to interact with the upper distribution network. On the premise of keeping operation safe, the upper distribution network formulated the energy interaction plan with each VPP, and then, the global energy optimization management of the entire distribution system and the decentralized autonomy of each VPP were achieved. In order to improve the stochastic uncertainty of distributed renewable energy output, a two-stage stochastic optimization method including pre-scheduling stage and rescheduling stage was adopted. The pre-scheduling stage was used to arrange charging and discharging plans of EV agents and output plans of micro gas turbines. The rescheduling stage was used to adjust the spare resources of micro gas turbines to deal with the uncertainty of distributed wind and light. An example of active distribution system with multi-VPPs was constructed by using the improved IEEE 33-bus system, then the validity of the model was verified.

Gas Turbine Machinery Diagnostics: A Brief Review and a Sample Application

2017 ◽  
Author(s):  
Cody W. Allen ◽  
Chad M. Holcomb ◽  
Mauricio de Oliveira
Keyword(s):  
Machine Learning ◽  
Gas Turbine ◽  
Gas Turbines ◽  
Health Management ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Sensor Data ◽  
Industry Standard ◽  
Industrial Gas Turbines ◽  
Sample Application

The intersection of machine learning methods and gas turbine sensor data has expanded rapidly in the last decade to include numerous applications of regression, clustering, and even neural network algorithms. Learning algorithms have pushed traditional engine health management into the realm of prognostic health management. This paper starts with a review of several common computational methods used to monitor the condition of gas turbines currently employed by both industry and academia. Sources of application of machine learning algorithms from outside the gas turbine industry are also brought in. Focus is generally placed on industrial gas turbines with an industry standard monitoring system. The authors explore beyond gas path analysis with a novel use of machine learning algorithms to engine component classification. The paper concludes with a case study of applying learning algorithms to machine data to identify different fuel valves.

Alternative Fuel Considerations for Gas Turbine Combustion

2007 ◽  
Author(s):  
Peter J. Stuttaford
Keyword(s):  
Natural Gas ◽  
Gas Turbine ◽  
Carbon Dioxide Emissions ◽  
Gas Turbines ◽  
Power Plants ◽  
Practical Implementation ◽  
Combustion Dynamics ◽  
Gaseous Fuels ◽  
Wide Range ◽  
Critical Combustion

Gas turbines have the advantage of being able to operate on a wide range of fuels. Given the escalating cost of conventional fuel sources such as natural gas, there is increasing interest in, and implementation of, systems burning lower cost fuel gases. There are significant combustor performance effects when utilizing different fuels. Flame stability, emissions, durability, and combustion dynamics are critical combustion parameters which must be controlled when varying fuel constituents. Significant emphasis continues to be placed on the use of liquefied natural gas (LNG) as well as syngas derived from coal and petroleum coke. The elimination of carbon from gaseous coal based fuels also offers the possibility of burning hydrogen to reduce or eliminate carbon dioxide emissions. Existing stringent emissions permits must be met by power plants utilizing these different fuels. There is also a requirement for the flexible use of these fuels allowing power plants to switch real time between fuel sources using the same combustion hardware, without affecting commercial generating schedules. This highlights the requirement for fuel preparation and control skids, as well as robust combustion systems, for reliable plant operations. The objective of this work is to review fuel properties which affect combustion and consider the methods and tools used to characterize the subsequent combustion characteristics. The work focuses on gaseous fuel premixed combustion. A full scale high pressure combustion test stand was used to evaluate the effects of various gaseous fuels on given gas turbine combustor configurations. Data collected through the testing of natural gas containing heavy hydrocarbons, as might be expected from liquefied LNG or refinery offgas, and hydrogen based syngas fuel blends with natural gas to simulate various coal gas blends, is presented with conclusions drawn based upon the critical combustion parameters mentioned above. A methodology for fuel characterization and combustor qualification for the acceptable operation of gas turbine combustors on various gaseous fuels is discussed. The practical implementation of multi-fuel systems on commercially operating engines is also discussed, with emphasis on diluent free premixed systems.

Waste minimization program in Shuaiba Industrial Area

1999 ◽  
Vol 39 (10-11) ◽  
pp. 289-295
Author(s):  
Saleh Al-Muzaini
Keyword(s):  
Solid Waste ◽  
Power Plants ◽  
Large Scale ◽  
Industrial Area ◽  
Waste Minimization ◽  
Regulatory Body ◽  
Eastern Sector ◽  
Western Sector ◽  
Petroleum Companies ◽  
The Cost

The Shuaiba Industrial Area (SIA) is located about 50 km south of Kuwait City. It accommodates most of the large-scale industries in Kuwait. The total area of the SIA (both eastern and western sectors) is about 22.98 million m2. Fifteen plants are located in the eastern sector and 23 in the western sector, including two petrochemical companies, three refineries, two power plants, a melamine company, an industrial gas corporation, a paper products company and, two steam electricity generating stations, in addition to several other industries. Therefore, only 30 percent of the land in the SIA's eastern sector and 70 percent of land in the SIA's western sector is available for future expansion. Presently, industries in the SIA generate approximately 204,000 t of solid waste. With future development in the industries in the SIA, the estimated quantities will reach 240,000 t. The Shuaiba Area Authority (SAA), a governmental regulatory body responsible for planning and development in the SIA, has recognized the problem of solid waste and has developed an industrial waste minimization program. This program would help to reduce the quantity of waste generated within the SIA and thereby reduce the cost of waste management. This paper presents a description of the waste minimization program and how it is to be implemented by major petroleum companies. The protocols employed in the waste minimization program are detailed.

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

scholarly journals On the Root Causes of the Fukushima Daiichi Disaster from the Perspective of High Complexity and Tight Coupling in Large-Scale Systems

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 414
Author(s):  
Atsuo Murata ◽  
Waldemar Karwowski
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Large Scale ◽  
High Complexity ◽  
Tight Coupling ◽  
Large Scale Systems ◽  
Safety Issues ◽  
Loss Of Coolant ◽  
Station Blackout ◽  
Fukushima Daiichi

This study explores the root causes of the Fukushima Daiichi disaster and discusses how the complexity and tight coupling in large-scale systems should be reduced under emergencies such as station blackout (SBO) to prevent future disasters. First, on the basis of a summary of the published literature on the Fukushima Daiichi disaster, we found that the direct causes (i.e., malfunctions and problems) included overlooking the loss of coolant and the nuclear reactor’s failure to cool down. Second, we verified that two characteristics proposed in “normal accident” theory—high complexity and tight coupling—underlay each of the direct causes. These two characteristics were found to have made emergency management more challenging. We discuss how such disasters in large-scale systems with high complexity and tight coupling could be prevented through an organizational and managerial approach that can remove asymmetry of authority and information and foster a climate of openly discussing critical safety issues in nuclear power plants.

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