# Using generalized advanced data validation and reconciliation in steam power unit energy balancing

### Abstract

There are advantages to be gained by using a generalized method of data validation and reconciliation in energy conversion processes in terms of decreasing the uncertainty of measurements data. This method was used to complete the validation model of the process (conditional equations of optimization task) including substance and energy conservation principles with additional equations describing energy conversion processes. The methodology developed was used for example for calculations of data reconciliation in the selected steam power unit. The equations of steam flow capacity, adiabatic internal efficiency and equations resulting from the form of an isobaric line on the h-s diagram for a group of turbine stages were applied. Also applied as additional equations in the validation model were: Darcy’s equation of steam pressure drop in the pipeline into heat exchangers and Peclet’s equations of heat transfer and equations of over-cooling of condensate in regenerative heat exchangers. The criterion of an assessment of the decrease of measurements uncertainty in the form of global decrease of measurements variance after measurement data reconciliation is proposed. Derivation of the analyzed coefficient was based on the characteristic property of the measurements variance, coming from the variance-covariance matrix of measurements before and after data reconciliation. The criterion for selection of the mathematical form of additional equations in the validation model in reconciliation calculation was formulated. Professor Jan Szargut introduced and developed the advanced data validation and reconciliation method in Poland for thermodynamic analysis of energy conversion processes. The author of this paper engaged in further research on the development and application of this method in thermodynamic analyses.### References

1.Szargut J, K.Z. (1968) Theory of coordination of

material and energy balances in metallurgical pro-

cesses. Archives of Metallurgy, 123(2): 153.

2.Szargut J, R.E. (1952) Reconciliation of mass bal-

ances.. Works of the Institute of Metallurgy, 5(4).

3.Szargut J, K.Z. (1967) Reconciling of mass and en-

ergy balances in chemical processes.. Measurements,

Automation, Control, 2(13).

4.Kolenda, Z., Szmyd, J., Slupek, S., and Baez, L.M.

(1983) Numerical modelling of heat transfer processes

with supplementary data. The Canadian Journal of

Chemical Engineering, 61 (5), 627{634.

5.Kolenda Z, A.J.S. (1974) Coordination of Energy

Balances in Heat Transfer.. Bull. Polish Academy of

Science, 6(22).

6.T, S. (1991) The multistage and Multigroup Adjust-

ment of the Measurement Results,. Cracow University

of Technology, Monograph.

7.JT., S. (1984) Reconciliation Calculus in Thermal

Engineering.. Polish Academy of Sciences.

8. (1998) Numerical and experimental mathematical

modelling of heat and mass transfer processes using

unied least squares method.. Energy Conversion and

Management, 39.

9.Rusinowski, H., Szega, M., Szlek, A., and Wilk,

R. (2002) Methods of choosing the optimal param-

eters for solid fuel combustion in stoker-red boil-

ers. Energy Conversion and Management, 43 (9-12),

1363{1375.

10.Rusinowski, H., and Szega, M. (2001) The in

u-

ence of the operational parameters of chamber fur-

naces on the consumption of the chemical energy of

fuels. Energy, 26 (12), 1121{1133.

11.Rusinowski H., S.M., Ziebik A. (1997) Thermal In-

vestigations of Open-Flame Fired Furnaces in Copper

Metallurgy with the Application of the Least Squares

Adjustment Method.. Archives of Metallurgy and Ma-

terials, 42(4).

12.Almasy GA, S.T. (1975) Checking and Correc-

tion of Measurements on the Basis of Linear System

Model.. Problems of Control and Information Theory,

4(1).

13.W., H. (1980) Error theory and advanced data val-

idation calculation.. De Gruyter Lehrbuch.

14.Mikhail E, A.F. (1976) Observations and least

squares,. IEP-A, Dun Donnelly Publisher, New York.

15.Narasimhan S, J.C. (2000) Data Reconciliation

and Gross Error Detection. An Intelligent Use of Pro-

cess Data.. Houston, Texas: Gulf Publishing Com-

pany;.

16.S., S. (1975) Application of the data validation cal-

culation for thermal engineering experiments.. Vienna

University of Technology, Dissertation.

17.AG., S. (1964) Adjustment of measurement results

in the chemical industry.. Acta IMEKO 10-NL-145.

18.Veverka V, M.F. (1997) Material and Energy Bal-

ancing in the Process Industries. From Microscopic

Balances to Large Plants.. Computer-Aided Chemical

Engineering 7. Elsevier Science B.V.

19.Bagajewicz MJ, T.D.N., Chmielewski DJ (2010)

Smart Process Plants: Software and Hardware Solu-

tions for Accurate Data and Protable Operations..

New York: McGraw-Hill Company Inc.

20.MJ., B. (2001) Process Plant Instrumentation:

Design and Upgrade.. Technomic Publishing Com-

pany, Inc. Lancaster, Pennsylvania, USA;.

21.Tamhane AC, M.R.S.H. (1985) Data Reconcilia-

tion and Gross Error Detection in Chemical Process

Networks.. Technometrics, 27(4).

22.1, B.V.G.H.2000 P. VDI-Guidelines 2048. Uncer-

tainties of Measurement During Acceptance Tests on

Energy Conversion and Power Plants. Fundamentals.

23. VDI- Guidelines 2048. Uncertainties of Measure-

ment During Acceptance Tests on Energy Conversion

and Power Plants. Examples. Duesseldorf: Beuth

Verlag GmbH; 2001 Part 2..

24.M., S. (2016) Advanced Data Validation and Rec-

onciliation in Thermal Processes. Polish Academy of

Sciences { Branch in Katowice. Commission of Power

Engineering. Skalmierski Publishing House.

25.Szargut J, S.J. (1991) In

uence of the Preliminary

Estimation of Unknown on the Results of Coordina-

tion of Material and Energy Balances.. Bull. Pol.

Acad. Sci., Techn. Series, 39(2).

26.M., S. (2009) Advantages of an Application of

the Generalized Method of Data Reconciliation in

Thermal Technology.. Archives of Thermodynamics,

4(30).

27.M., S. (2015) Using data reconciliation to improve

the reliability of the energy evaluation of a gas-and-

steam CHP unit.. Journal of Power Technologies

(Polish Energy Mix 2014), 5(95).

28.M., S. (2009) Application of Data Reconciliation

Method for Increase of Measurements Reliability in

the Power Unit System of a Steam Power Plant..

Monograph No. 193. Silesian University of Tech-

nology Publisher, Gliwice.

29.M., S. (2008) Problems of estimating the enthalpy

value of the exhaust steam from a condensing turbine

in a generalized method of reconciliation of energy

balances in a steam power plant.. Archives of Ener-

getics, 1(38).

30.M., S. (2007) Problems of gross errors detection

in data reconciliation using principal component anal-

ysis.. Proc. of the 8-th Int. Carpathian Control Con-

ference ICCC'2007. The Slovak Republic.

31.M., S. (2006) Detection of Gross Measurement Er-

rors Using Constraints Test in Data Reconciliation Al-

gorithm and Interval Methods.. Proc. of the 7-th Int.

Carpathian Control Conference ICCC'2006. Ostrava,

Czech Republic.

32.S., P. (1992) Steam and Gas Turbines.. Polish

Academy of Science, Ossolineum Publishing House,

Wroc law{Warszawa{Krakow,.

33.M., S. (2018) Extended applications of the ad-

vanced data validation and reconciliation method in

studies of energy conversion processes.. Energy, 161.

material and energy balances in metallurgical pro-

cesses. Archives of Metallurgy, 123(2): 153.

2.Szargut J, R.E. (1952) Reconciliation of mass bal-

ances.. Works of the Institute of Metallurgy, 5(4).

3.Szargut J, K.Z. (1967) Reconciling of mass and en-

ergy balances in chemical processes.. Measurements,

Automation, Control, 2(13).

4.Kolenda, Z., Szmyd, J., Slupek, S., and Baez, L.M.

(1983) Numerical modelling of heat transfer processes

with supplementary data. The Canadian Journal of

Chemical Engineering, 61 (5), 627{634.

5.Kolenda Z, A.J.S. (1974) Coordination of Energy

Balances in Heat Transfer.. Bull. Polish Academy of

Science, 6(22).

6.T, S. (1991) The multistage and Multigroup Adjust-

ment of the Measurement Results,. Cracow University

of Technology, Monograph.

7.JT., S. (1984) Reconciliation Calculus in Thermal

Engineering.. Polish Academy of Sciences.

8. (1998) Numerical and experimental mathematical

modelling of heat and mass transfer processes using

unied least squares method.. Energy Conversion and

Management, 39.

9.Rusinowski, H., Szega, M., Szlek, A., and Wilk,

R. (2002) Methods of choosing the optimal param-

eters for solid fuel combustion in stoker-red boil-

ers. Energy Conversion and Management, 43 (9-12),

1363{1375.

10.Rusinowski, H., and Szega, M. (2001) The in

u-

ence of the operational parameters of chamber fur-

naces on the consumption of the chemical energy of

fuels. Energy, 26 (12), 1121{1133.

11.Rusinowski H., S.M., Ziebik A. (1997) Thermal In-

vestigations of Open-Flame Fired Furnaces in Copper

Metallurgy with the Application of the Least Squares

Adjustment Method.. Archives of Metallurgy and Ma-

terials, 42(4).

12.Almasy GA, S.T. (1975) Checking and Correc-

tion of Measurements on the Basis of Linear System

Model.. Problems of Control and Information Theory,

4(1).

13.W., H. (1980) Error theory and advanced data val-

idation calculation.. De Gruyter Lehrbuch.

14.Mikhail E, A.F. (1976) Observations and least

squares,. IEP-A, Dun Donnelly Publisher, New York.

15.Narasimhan S, J.C. (2000) Data Reconciliation

and Gross Error Detection. An Intelligent Use of Pro-

cess Data.. Houston, Texas: Gulf Publishing Com-

pany;.

16.S., S. (1975) Application of the data validation cal-

culation for thermal engineering experiments.. Vienna

University of Technology, Dissertation.

17.AG., S. (1964) Adjustment of measurement results

in the chemical industry.. Acta IMEKO 10-NL-145.

18.Veverka V, M.F. (1997) Material and Energy Bal-

ancing in the Process Industries. From Microscopic

Balances to Large Plants.. Computer-Aided Chemical

Engineering 7. Elsevier Science B.V.

19.Bagajewicz MJ, T.D.N., Chmielewski DJ (2010)

Smart Process Plants: Software and Hardware Solu-

tions for Accurate Data and Protable Operations..

New York: McGraw-Hill Company Inc.

20.MJ., B. (2001) Process Plant Instrumentation:

Design and Upgrade.. Technomic Publishing Com-

pany, Inc. Lancaster, Pennsylvania, USA;.

21.Tamhane AC, M.R.S.H. (1985) Data Reconcilia-

tion and Gross Error Detection in Chemical Process

Networks.. Technometrics, 27(4).

22.1, B.V.G.H.2000 P. VDI-Guidelines 2048. Uncer-

tainties of Measurement During Acceptance Tests on

Energy Conversion and Power Plants. Fundamentals.

23. VDI- Guidelines 2048. Uncertainties of Measure-

ment During Acceptance Tests on Energy Conversion

and Power Plants. Examples. Duesseldorf: Beuth

Verlag GmbH; 2001 Part 2..

24.M., S. (2016) Advanced Data Validation and Rec-

onciliation in Thermal Processes. Polish Academy of

Sciences { Branch in Katowice. Commission of Power

Engineering. Skalmierski Publishing House.

25.Szargut J, S.J. (1991) In

uence of the Preliminary

Estimation of Unknown on the Results of Coordina-

tion of Material and Energy Balances.. Bull. Pol.

Acad. Sci., Techn. Series, 39(2).

26.M., S. (2009) Advantages of an Application of

the Generalized Method of Data Reconciliation in

Thermal Technology.. Archives of Thermodynamics,

4(30).

27.M., S. (2015) Using data reconciliation to improve

the reliability of the energy evaluation of a gas-and-

steam CHP unit.. Journal of Power Technologies

(Polish Energy Mix 2014), 5(95).

28.M., S. (2009) Application of Data Reconciliation

Method for Increase of Measurements Reliability in

the Power Unit System of a Steam Power Plant..

Monograph No. 193. Silesian University of Tech-

nology Publisher, Gliwice.

29.M., S. (2008) Problems of estimating the enthalpy

value of the exhaust steam from a condensing turbine

in a generalized method of reconciliation of energy

balances in a steam power plant.. Archives of Ener-

getics, 1(38).

30.M., S. (2007) Problems of gross errors detection

in data reconciliation using principal component anal-

ysis.. Proc. of the 8-th Int. Carpathian Control Con-

ference ICCC'2007. The Slovak Republic.

31.M., S. (2006) Detection of Gross Measurement Er-

rors Using Constraints Test in Data Reconciliation Al-

gorithm and Interval Methods.. Proc. of the 7-th Int.

Carpathian Control Conference ICCC'2006. Ostrava,

Czech Republic.

32.S., P. (1992) Steam and Gas Turbines.. Polish

Academy of Science, Ossolineum Publishing House,

Wroc law{Warszawa{Krakow,.

33.M., S. (2018) Extended applications of the ad-

vanced data validation and reconciliation method in

studies of energy conversion processes.. Energy, 161.

Published

2020-04-14

How to Cite

SZEGA, Marcin.
Using generalized advanced data validation and reconciliation in steam power unit energy balancing.

**Journal of Power Technologies**, [S.l.], v. 100, n. 1, p. 68-84, apr. 2020. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/1525>. Date accessed: 05 nov. 2024.
Issue

Section

Contemporary Problems of Thermal Engineering 2018 Gliwice

Authors who publish with this journal agree to the following terms:

- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).