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Research Papers

A Multivariable Newton-Based Extremum Seeking Control for Condenser Water Loop Optimization of Chilled-Water Plant

[+] Author and Article Information
Baojie Mu

Department of Electrical Engineering,
The University of Texas at Dallas,
Richardson, TX 75080
e-mail: baojie.mu@utdallas.edu

Yaoyu Li

Associate Professor
Mem. ASME
Department of Mechanical Engineering,
The University of Texas at Dallas,
Richardson, TX 75080
e-mail: yaoyu.li@utdallas.edu

John E. Seem

High Altitude Trading, Inc.,
Jackson, WY 83001
e-mail: john.seem@gmail.com

Bin Hu

Department of Compressor Engineering,
School of Energy and Power Engineering,
Xi'an Jiaotong University,
Xi'an, Shaanxi 710049, China
e-mail: hb1223@stu.xjtu.edu.cn

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 2, 2014; final manuscript received June 12, 2015; published online August 20, 2015. Assoc. Editor: Yang Shi.

J. Dyn. Sys., Meas., Control 137(11), 111011 (Aug 20, 2015) (10 pages) Paper No: DS-14-1449; doi: 10.1115/1.4031051 History: Received November 02, 2014

This paper presents a multivariable Newton-based extremum seeking control (ESC) scheme for efficient operation of a chilled-water plant. A modelica-based dynamic simulation model of the chilled-water plant consists of one screw chiller and one counter-flow cooling tower was adopted for evaluation of proposed two-input Newton-based ESC controller. The ESC controller takes the total power of the chiller compressor, the cooling-tower fan, and the condenser water (CW) pump as feedback signal and discovers the optimum outputs of cooling-tower fan speed and the condenser-loop water flow rate to maximize the power efficiency in real time with the cooling load being satisfied. Remarkable energy saving is observed for several testing conditions.

Copyright © 2015 by ASME
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References

Figures

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Fig. 1

Schematic of a typical chilled-water ventilation and air-conditioning system

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Fig. 2

Nearly convex power map in terms of tower fan air flow [5]

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Fig. 3

Nearly convex power map in terms of CW flow rate [27]

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Fig. 4

Block diagram of gradient based ESC

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Fig. 5

Newton-based ESC Proposed by Ghaffari et al. [29]

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Fig. 6

Revised schematic of Newton-based multivariable ESC

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Fig. 7

Schematic of two-input ESC strategy for chilled-water plant with variable tower fan and CW flow

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Fig. 8

Power map of chiller-tower system in terms of tower fan speed and CW flow rate

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Fig. 9

Tower fan channel: step tests and input dynamics estimate

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Fig. 10

Tower fan speed channel: selection of dither frequency, HP and LP filters

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Fig. 11

Condensing water flow channel: step tests and input dynamics estimate

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Fig. 12

CW flow channel: selection of dither frequency, HP and LP filters

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Fig. 13

Profiles of total power, fan speed, and CW flow

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Fig. 14

Profiles of evaporator superheat and chilled-water temperature control

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Fig. 15

Profiles of gradients for fan channel and CW channel

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Fig. 16

(a) Trajectory for the inverse of Hessian estimate and (b) angle trajectories of estimated eigenvectors and precalibrated vectors

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Fig. 17

Profiles of total power, fan speed, and CW flow

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Fig. 18

Profiles of evaporator superheat and chilled-water temperature control

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Fig. 19

DFW ambient condition from 1:00 am of July 11th to 12:00 pm of July 13th

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Fig. 20

Profiles of total power, fan speed, and CW flow

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Fig. 21

Total power comparison of ESC with fixed tower fan speed and CW flow operations

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Fig. 22

Profiles of total power, fan speed, and CW flow (δ=0.00005)

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Fig. 23

Profiles of Hessian inverse (δ=0.00005)

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Fig. 24

Profiles of eigenvalues of Hessian estimator for different δ

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Fig. 25

Comparison of inputs and output for the gradient and the Newton based ESC

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Fig. 26

Comparison of gradient profiles for the fan and CW channels between the gradient and the Newton based ESC

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