Sensorless frequencyconverter-based. for LCC efficient pump and fan systems

Transcription

1 Sensorless frequencyconverter-based methods for LCC efficient pump and fan systems Tero Ahonen Lappeenranta University of Technology Finland

2 Outline of the presentation I. Role of a frequency converter in pump and fan systems II. Sensorless estimation of the system operational state III. Identification of system characteristics IV. Energy efficient system control with variable-speed usage V. Identification of operational states that reduce the system lifetime or cause an immediate failure

3 Part I: Role of a frequency converter in pump and fan systems

4 Frequency converter allows variablespeed system operation 35 High pump efficiency & poor system efficiency % 44% 60% 71% 73% Head (m) Flow rate (l/s) Poor pump efficiency & high system efficiency 870 rpm 1160 rpm 68% 58% 1450 rpm E s (Wh/m 3 )

5 Frequency converter as a sensorless measurement unit Converters with internal current and voltage measurements can provide estimates for Rotational speed, shaft torque and power Motor current and temperature System energy consumption System run-time These can be used to determine System operational state (flow rate, head, efficiency) System energy efficiency E s (kwh/m 3 ) Distribution of flow rate, E s etc.

6 Estimation accuracy of a DTC frequency converter 37 kw, 1480 rpm induction motor Torque estimation errors within 4.9 Nm (2.1 %) Speed estimation errors within 3.1 rpm (0.2 %) Power estimation errors within 0.77 kw (2.1 %) Ref.: T. Ahonen et al., Accuracy study of frequency converter estimates used in the sensorless diagnostics of induction-motor-driven systems, in Proc. EPE 2011 Conf., pp

7 Life-cycle costs in pump and fan systems dominated by energy, bounded by design Production losses 14 % Maintenance 4 % Investment 7 % Production losses 31 % Investment 5 % Energy 75 % Maintenance 6 % Energy 58 %

8 Role of a frequency converter in LCC efficient pump and fan systems IV. V.. III. II.

9 Part II: Sensorless estimation of the system operational state

10 Sensorless system state estimation by a frequency converter A parameter-adjustable pump or fan model can be implemented into the converter control scheme. n est P est QP-curve-based pump model QP and QH curves at n nom Q est H est E s,est The model provides estimates for the system operational state and energy efficiency that can be further used for process identification and energy efficiency optimization.

11 QP-curve-based pump model n est P est QP-curve-based pump model QP and QH curves at n nom Q est H est E s,est 8 QP curve 30 QH curve Power (kw) P est n nom Head (m) H est Q est Flow rate (l/s) n est Q est Flow rate (l/s) Ref.: T. Ahonen et al., Estimation of pump operational state with model-based methods, Energy Conversion and Management, vol. 51, no. 6, pp , June 2010.

12 Operation of a QP-curve-based pump model n est P est Affinity transform (1) for the shaft power estimate P est,n Flow rate interpolation from the QP curve Q est,n Head interpolation from the QH curve Q est,n H est,n (1): P (2): Q (3): H (4): E est,n est,n est,n s,est n n n n nom est n n Pest Q nom nom est est est 3 Q 2 P est est H est P est Q est Affinity transform (2) for the flow rate estimate Q est Estimation (4) of specific energy consumption Affinity transform (3) for the head estimate E s,est H est

13 Estimation accuracy of the QP-curvebased pump model 50% flow rate 100% flow rate 140% flow rate Q/Q < 8% Q/Q < 6% Q/Q < 20% at 1320/1560 rpm

14 Pilot test results for an industrial pulp pump system Sulzer ARP centrifugal pump Typical pump eff. 76%, max. eff. 85% Typical pump power cons. 240 kw 9% efficiency improvement equals 25kW lower power consumption Time (%) Relative flow rate (%)

15 Part III: Identification of system characteristics

16 Surrounding system characteristics Pump/fan operating point lies in the intersection of the device and surrounding process characteristic curves H H st k Q 2 Head (m) kq 2 5 H st Q, H n nom n est H process Flow rate (l/s) E s P tot Q s,min g dt H Minimum level of energy usage: E g H p st Ref.: T. Ahonen et al., Generic unit process functions set for pumping systems, in Proc. EEMODS 2011 Conf.

17 State estimation with the process-curvebased pump model n est Process-curve-based pump model Q est P est QH curve at n nom, H st and k H est Head (m) kq 2 5 H est H st Q est n nom n est H process Flow rate (l/s) Ref.: T. Ahonen et al., Estimation of pump operational state with model-based methods, Energy Conversion and Management, vol. 51, no. 6, pp , June 2010.

18 Identification of the surrounding system H st and k can be determined with applicable QP curve model estimates (Q est, H est ) using the LMS method QP estimates Est. system curve Head (m) Find best-fit values for H st and k with these estimates S H m i 1 process ( H est, i H st H st k k Q 2 Q 2 est, i ) Flow rate (l/s) Ref.: T. Ahonen et al., Frequency-converter-based hybrid estimation method for the centrifugal pump operational state, IEEE Trans. Ind. Electron., vol. 59, no. 12, pp , December 2012.

19 Combined (hybrid) usage of the pump models Process-curve-based model is used when operating on the flat part of the QP curve Process curve model is used QP curve model is used Process curve model is used

20 Head (m) Estimation accuracy of the processcurve-based pump model Process curve parameters were determined with 11 QP curve model estimates at rpm 35 % 65 % 70 % 68 % 60 % rpm 2 Meas. 1 5 QP est. 0 H 600 rpm process Flow rate (l/s) Rotational speed (rpm) Flow rate estimation error (l/s) QP curve estimation Process curve est.

21 Part IV: Energy efficient system control with variable-speed usage

22 How to achieve the minimum energy consumption? Specific energy consumption (Wh/m 3 ) m 1. Drive the system as energy efficiently as possible 2. Minimize the hydraulic losses (H st, k) 3. Use high efficiency components in the system 6.5 m 8 m X: 815 Y: H st =5-10 m, k= m X: 1155 Y: Rotational speed (rpm) System E s (Wh/m 3 ) overall eff Head (m) Ref.: T. Ahonen et al., Generic unit process functions set for pumping systems, in Proc. EEMODS 2011 Conf.

23 Energy efficient filling of a reservoir with a variable-speed pumping system Variable-speed operation allows energy efficient filling of a reservoir, but at which rotational speeds? H st,1 k H k LH H st,2 k H st,2 H st,1 LL Q

24 System identification and determination of an optimum rotational speed profile H H st,2 H st,1 Q Surrounding system and the pumping task are identified during the first run T est n est E s charts (curves) are determined for H st,1 and H st,2 cases Rotational speed profile is formed with the E s chart information k k Specific energy consumption (Wh/m 3 ) Optimum rotational speed (rpm) m 6.5 m 8 m X: 815 Y: H st =5-10 m, k= m X: 1155 Y: Rotational speed (rpm) st System static head (m)

25 Simulation results for a reservoir filling application System: H st =5-10 m, k=0.0149, 3.75 m 3 per reservoir filling Pump: Sulzer APP22-80, 1450 rpm Minimum energy consumption is achieved with the linear speed profile

26 Compensation of an oversized pump with variable-speed usage Pump: Sulzer APP22-80 with a larger impeller resulting in a 5-10 % higher output than needed Difference in E s is at smallest around 1050 rpm

27 Part V: Identification of operational states that reduce the system lifetime or cause an immediate failure

28 Pump cavitation and fluid recirculation, fan stalling n (rpm) ,0 1,0 2,0 3,0 4,0 5,0 Time (s) Scaled T (% of T nom ) 2,0 1,0 0,0-1,0-2,0 0,0 1,0 2,0 3,0 4,0 5,0 Time (s) No cavitation (BEP) Cavitation (max. flow)

29 Frequency-converter-based, sensorless detection of cavitation or stalling Determine n RMS,N and T RMS,N when the pump operates near the BEP Calculate the present n RMS and T RMS Cavitation (max. flow) Average speed at max. flow Is n RMS /n RMS,N over the threshold value? Yes No Cavitation may occur in the pump Is T RMS /T RMS,N over the threshold value? Yes No Pump is operating normally x x x DC AC RMS ( n) ( n) ( n) 1 M M 1 k 0 x( n) x 1 M M 1 k0 x( n k) DC x ( n) 2 AC ( n k) Ref.: T. Ahonen et al., Novel method for detecting cavitation in centrifugal pump with frequency converter, Insight, vol. 53, no. 8, August 2011.

30 TRMS/TRMS,N nrms/n RMS,N TRMS/TRMS,N nrms/nrms,n Test results Serlachius 1500 rpm Flow rate (l/s) Flow rate (l/s) Sulzer 1450 rpm Flow rate (l/s) Flow rate (l/s)

31 Detection of contamination in a fan impeller Impeller contamination is a root cause for several imbalance- and vibration-related faults in fans Torque (%) Rotational speed (%) Torque Clean impeller Contaminated impeller Time (s) Ref.: J. Tamminen et al., Detection of Mass Increase in a Fan Impeller with a Frequency Converter, IEEE Trans. on Ind. Electron., Digital Object Identifier: /TIE , 2012.

32 Operation of the fan impeller contamination detection algorithm Baseline measurement Starting the fan with constant torque ref. n est,1 Filtering and processing of estimates n 1 Calculation of the fan acceleration with (1) T ref,1 (1): est (2): J (3): m Fan est n limit,upper T ref,n est,n 2 J r 2 1 Fan 2 r2 n t T ref,1 est,1 limit,lower est,1 Calculation of mass increase with (2) and (3) est,n m est Starting the fan with constant torque ref. n est,n Filtering and processing of estimates n n Calculation of the fan acceleration with (1) n th detection measurement T ref,n

33 Test results Method has been successfully verified by laboratory measurements Mass (g) Actual mass Est. mass T ref =30% Measurement set Ref.: J. Tamminen et al., Detection of mass increase in a fan impeller with a frequency converter, IEEE Trans. on Ind. Electron., Digital Object Identifier: /TIE , 2012.

34 Summary

35 Role of the frequency converter in LCC optimization of pump and fan systems Detection of operational states degrading system lifetime: cavitation, stalling, recirculation, dryrunning, contamination build-up, etc. Production losses 14 % Maintenance 4 % Investment 7 % System performance monitoring: On-line specific energy consumption estimation, wear and air filter contamination detection, etc. Energy efficiency optimization: parallel pumping, compensation of oversizing, optimal speed profiles, etc. Energy 75 %

36 Main points I. Frequency converter is a versatile tool with monitoring and diagnostic abilities II. Sensorless pump and fan system operation estimation is possible with dedicated models III. Frequency converter by itself does not realize energy efficient system operation IV. Identification of adverse operational states can effectively decrease the risk of system faults