Financial Benefits of Process Data Reconciliation in Power Generating Plants

2006 ◽  
Author(s):  
Andy Jansky
Keyword(s):  
Peak Load ◽  
Data Reconciliation ◽  
Process Data ◽  
Process Measurement ◽  
Financial Benefits ◽  
Entire Plant ◽  
Output Time ◽  
Main Factors ◽  
Measurement Uncertainties ◽  
Plant Process

Process Data Reconciliation (PDR) is a certified method that calculates the most likely values considering process measurement uncertainties and closing all energy- and material balances where all interdependencies within the entire plant process are fulfilled in a covariance matrix. There are three main factors that generate the financial benefits for the user of reconciled data, depending on the type of plant and base/peak load behaviour: • Increased efficiency / maximized output; • Time advantage in retrieving “lost” megawatts; • Reduction of maintenance costs.

Global Balance of Plant in NPPs Using Process Data Reconciliation According to VDI 2048

2014 ◽  
Author(s):  
Magnus Langenstein ◽  
Bernd Laipple
Keyword(s):  
Monitoring System ◽  
Mass Flow ◽  
Online Monitoring ◽  
Water Mass ◽  
Data Reconciliation ◽  
Measurement Information ◽  
Feed Water ◽  
Process Data ◽  
Operation Conditions ◽  
Plant Process

The large quantities of measurement information gathered throughout a plant process make the closing of the mass and energy balance nearly impossible without the help of additional tools. For this reason, a variety of plant monitoring tools for closing plant balances was developed. A major problem with the current tools lies in the non-consideration of redundant measurements which are available throughout the entire plant process. The online monitoring reconciliation system is based on the process data reconciliation according to VDI 2048 standard and is using all redundant measurements within the process to close mass and energy balances. As a result, the most realistic process with the lowest uncertainty can be monitored. This system is installed in more than 35 NPPs worldwide and is used ○ as a basis for correction of feed water mass flow and feed water temperature measurements (recover of lost Megawatts). ○ as a basis for correction of Taverage (Tav) (recover of steam generator outlet pressure in PWRs). ○ for maintaining the thermal core power and the feed water mass flow under continuous operation conditions. ○ for automatic detection of erroneous measurements and measurement drift. ○ for detection of inner leakages, non-condensable gases and system losses. ○ for calculating non measured values (e.g. heat transfer coefficients, ΔT, preheater loads,…). ○ as a monitoring system for the main thermodynamic process. ○ for verifying warranty tests more accurate. ○ as a application of condition-based maintenance and component monitoring. ○ for What-if scenarios (simulation, not PDR) This paper describes the methodology according to VDI 2048 (use of Gaussian correction principle and quality criterias). The benefits gained from the use of the online monitoring system are demonstrated.

Global Balance of Plant Using Process Data Reconciliation According to VDI2048

2009 ◽  
Author(s):  
Magnus Langenstein ◽  
Bernd Laipple
Keyword(s):  
Quality Control ◽  
Monitoring System ◽  
Data Reconciliation ◽  
Measurement Information ◽  
Process Data ◽  
Balance Of Plant ◽  
Monitoring Tools ◽  
Plant Monitoring ◽  
Day To Day Operations ◽  
Plant Process

The large quantities of measurement information gathered throughout a plant process make the closing of the plant balance nearly impossible without the help of additional tools. For this reason, a variety of plant monitoring tools for closing plant balances have been developed. A major problem with the current tools lies in the non-consideration of redundant process information which is available throughout the plant. The monitoring system ProcessPlus™ is based on the process data reconciliation program VALI 4, which is certified according to the VDI 2048 standard and is using all redundant pieces of information within the process. Plausibility checks and structured quality control serve as the foundation for the system. Among other components, a procedural process image, significant diagnosis and monitoring tools have been developed and now offer a fast and economically ideal support for process optimization. This paper describes the methodology according to VDI 2048 and the benefits gained from the use of an online plant monitoring system by means of examples from day-to-day operations.

Intelligence Selection System for Honing Parameter Based on Genetics and Artificial Neural Networks

2010 ◽  
Vol 102-104 ◽  
pp. 846-850
Author(s):  
Wen Yu Pu ◽  
Yan Nian Rui ◽  
Lian Sheng Zhao ◽  
Chun Yan Zhang
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Selection System ◽  
Process Data ◽  
Replacement Strategy ◽  
Machining Quality ◽  
Main Factors ◽  
Artificial Neural ◽  
Neural Networks Optimization ◽  
The Relationship

Appropriate selecting of process parameters influences the machining quality greatly. For honing, the main factors are product precision, material components and productivity. In view of this situation, a intelligence selection model for honing parameter based on genetics and artificial neural networks was built by using excellent robustness, fault-tolerance of artificial neural networks optimization process and excellent self-optimum of genetic algorithm. It can simulate the decision making progress of experienced operators, abstract the relationship from process data and machining incidence, realize the purpose of intelligence selection honing parameter through copying, exchanging, aberrance, replacement strategy and neural networks training. Besides, experiment was performed and the results helped optimize the theories model. Both the theory and experiment show the updated level and feasibility of this system.

Effect of redundancy on estimation accuracy in process data reconciliation

1987 ◽  
Vol 42 (9) ◽  
pp. 2115-2121 ◽  
Author(s):  
Alexandros Kretsovalis ◽  
Richard S.H. Mah
Keyword(s):  
Data Reconciliation ◽  
Estimation Accuracy ◽  
Process Data

Industrial AFB-Fired Gas Turbine Systems With Topping Combustors

1980 ◽  
Author(s):  
C. L. Marksberry ◽  
B. C. Lindahl
Keyword(s):  
Gas Turbine ◽  
Heat Exchangers ◽  
Gas Turbines ◽  
State Of The Art ◽  
Industrial Plant ◽  
Process Data ◽  
Low Emission ◽  
Anthracite Culm ◽  
Near Term ◽  
Plant Process

An Atmospheric Fluidized Bed (AFB) combustor providing thermal input to gas turbines is a promising near-term means of decreasing national premium fuel consumption, in an AFB many solid fuels, including marginal fuels such as anthracite culm, bituminous gob, high sulfur coals, lignite, and petroleum coke, can be used effectively providing both very low emission levels and acceptable return-on-investment. This paper discusses the state of AFB/gas turbine cogeneration technology with reference to typical industrial plant applications. Design considerations and design limits for both the AFB heat exchangers and the topping combustor are discussed and compared. An example based on plant process data and commercially available components is also presented. Both the heat exchangers and the combustors are viewed with reference to state-of-the-art technology.

Analysis on Negative Peak Regulation Ability of Regional Power Grid and Constrained Receivability of Wind Power Capacity

2014 ◽  
Vol 953-954 ◽  
pp. 486-492
Author(s):  
Jie Ren ◽  
De Zhi Chen ◽  
Feng Gao ◽  
He Nan Wang ◽  
Jian She Tian ◽  
...  
Keyword(s):  
Wind Power ◽  
Power Grid ◽  
Peak Load ◽  
Analytical Prediction ◽  
Regional Power ◽  
Power Capacity ◽  
Negative Peak ◽  
Great Pressure ◽  
Load Regulation ◽  
Main Factors

As wind power in China is developing more and more rapidly, the characteristics of wind power output such as randomness and volatility have brought great pressure to the system peak load regulation. On the basis of defining negative peak regulation ability, this paper gives out the calculation formula of negative peak regulation ability including wind power and the main factors of influencing the negative peak regulation ability are calculated. Aimed at the regional power grid in the target year 2014, this paper makes some analytical prediction on such main factors and calculates the negative peak regulation ability, and the amount of the acceptance of wind power bound by it, and makes some sensitivity analysis of the negative peak regulation ability and the amount of the acceptance of wind power.

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