Real-Time Thermodynamic Performance Monitoring and Optimum Thermoeconomic Operation of Power Plants

2011 ◽  
Author(s):  
G. Hariharan ◽  
B. Kosanovic
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Real Time ◽  
Power Plants ◽  
Operating Conditions ◽  
Recursive Least Squares ◽  
Time Data ◽  
Real Time Data ◽  
One Step ◽  
Inputs And Outputs

The ability of modern power plant data acquisition systems to provide a continuous real-time data feed can be exploited to carry out interesting research studies. In the first part of this study, real-time data from a power plant is used to carry out a comprehensive heat balance calculation. The calculation involves application of the first law of thermodynamics to each powerhouse component. Stoichiometric combustion principles are applied to calculate emissions from fossil fuel consuming components. Exergy analysis is carried out for all components by the combined application of the first and second laws of thermodynamics. In the second part of this study, techniques from the field of System Identification and Linear Programming are brought together in finding thermoeconomically optimum plant operating conditions one step ahead in time. This is done by first using autoregressive models to make short-term predictions of plant inputs and outputs. Then, parameter estimation using recursive least squares is used to determine the relations between the predicted inputs and outputs. The estimated parameters are used in setting up a linear programming problem which is solved using the simplex method. The end result is knowledge of thermoeconomically optimum plant inputs and outputs one step ahead in time.

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

Test and Analysis of Exhaust Pollutants from Automobiles Based on GPS Technology

2010 ◽  
Vol 40-41 ◽  
pp. 675-681
Author(s):  
Ming Li Xian ◽  
Qing Huang Yong
Keyword(s):  
Real Time ◽  
Data Gathering ◽  
Operating Conditions ◽  
Vehicle Emission ◽  
Testing System ◽  
Time Data ◽  
Gps Technology ◽  
Urban Road ◽  
Real Time Data ◽  
Object Of Study

Taking the actual running vehicles on the urban roads of Ningpo City as the object of study, by using the brand-new on-vehicle automobile exhaust real-time testing system, and through actual testing by tracking the running vehicles and real-time data gathering, The paper analyzed urban road operating conditions, the vehicle emission situation on the actual roads, obtained the relations between the operating conditions, the speed and emissions and the law by which the automobile operating conditions affect the automobile exhausts.

Real-Time Data Communication Method for Smart Power Plants

2021 ◽  
Author(s):  
Xiaozhi Du ◽  
Wei Huang ◽  
Qiaohui Yang ◽  
Yurong Duan
Keyword(s):  
Real Time ◽  
Power Plants ◽  
Data Communication ◽  
Time Data ◽  
Smart Power ◽  
Communication Method ◽  
Real Time Data

Data-mining massive real-time data in a power plant: challenges, problems and solutions

2002 ◽  
Vol 3 (5) ◽  
pp. 538-542 ◽  
Author(s):  
Chen Jian-hong ◽  
Ren Hao-ren ◽  
Sheng De-ren ◽  
Li Wei
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Time Data ◽  
Real Time Data ◽  
Problems And Solutions

The Applications of Real-Time Data Mining Technology in Fault Prediction of Power Plant Generator

2015 ◽  
Vol 740 ◽  
pp. 351-354
Author(s):  
Feng Li ◽  
Hong Bin Wang ◽  
Dao Jun Deng ◽  
Yan Xia Zhang
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Fault Prediction ◽  
Time Data ◽  
Mining Technology ◽  
Online Security ◽  
Real Time Data

This paper mainly discusses the applications of real-time data mining technology in fault prediction of power plant generator. Massive real-time historical data of thermal power plant turbine generator equipment is stored to realize comprehensive quantitative assessment of thermal power plant turbine generator’s online security status and potential failure Early Warning. It is based on the Real-time data mining analysis and modeling techniques.

Fuzzy multi-objective decision making approach for nuclear power plant installation

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Energy Supply ◽  
Energy Demand ◽  
Nuclear Power ◽  
Power Plants ◽  
Total Duration ◽  
Objective Functions ◽  
Multi Objective

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.

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