A decomposition and coordination-based method for chiller plant optimization

2015 ◽  
Author(s):  
Danxu Zhang ◽  
Peter B. Luh ◽  
James Fan ◽  
Shalabh Gupta
Keyword(s):  
Decomposition And Coordination ◽  
Plant Optimization

Large Scale Plant Optimization Problems

1988 ◽  
Author(s):  
Paul Cronin ◽  
Harry Woerde ◽  
Rob Vasbinder
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Plant Optimization

Non-invasive temperature measurement of turbulent flows of aqueous solutions and gases in pipes

2020 ◽  
Vol 87 (9) ◽  
pp. 553-563
Author(s):  
Jörg Gebhardt ◽  
Guruprasad Sosale ◽  
Subhashish Dasgupta
Keyword(s):  
Surface Temperature ◽  
Temperature Measurement ◽  
Turbulent Flows ◽  
Fluid Dynamic ◽  
Industrial Applications ◽  
Static Case ◽  
Pipe Surface ◽  
Non Invasive ◽  
Step Model ◽  
Plant Optimization

AbstractAccurate and responsive non-invasive temperature measurements are enablers for process monitoring and plant optimization use cases in the context of Industry 4.0. If their performance is proven for large classes of applications, such measurement principles can replace traditional invasive measurements. In this paper we describe a two-step model to estimate the process temperature from a pipe surface temperature measurement. This static case model is compared to and enhanced by computational fluid dynamic (CFD) calculations to predict transient situations. The predictions of the approach are validated by means of controlled experiments in a laboratory environment. The experimental results demonstrate the efficacy of the model, the responsiveness of the pipe surface temperature, and that state of the art industrial non-invasive sensors can achieve the performance of invasive thermowells. The non-invasive sensors are then used to demonstrate the performance of the model in industrial applications for cooling fluids and steam.

Repowering and Retrofitting

2002 ◽  
Author(s):  
Andreas Pickard
Keyword(s):  
Steam Turbine ◽  
Power Plants ◽  
Free Market ◽  
Leading Edge ◽  
Project Planning ◽  
Combined Cycle ◽  
Steam Turbines ◽  
Planning Stage ◽  
Reheat Steam ◽  
Plant Optimization

At the start of this new century, environmental regulations and free-market economics are becoming the key drivers for the electricity generating industry. Advances in Gas Turbine (GT) technology, allied with integration and refinement of Heat Recovery Steam Generators (HRSG) and Steam Turbine (ST) plant, have made Combined Cycle installations the most efficient of the new power station types. This potential can also be realized, to equal effect, by adding GT’s and HRSG’s to existing conventional steam power plants in a so-called ‘repowering’ process. This paper presents the economical and environmental considerations of retrofitting the steam turbine within repowering schemes. Changing the thermal cycle parameters of the plant, for example by deletion of the feed heating steambleeds or by modified live and reheat steam conditions to suit the combined cycle process, can result in off-design operation of the existing steam turbine. Retrofitting the steam turbine to match the combined cycle unit can significantly increase the overall cycle efficiency compared to repowering without the ST upgrade. The paper illustrates that repowering, including ST retrofitting, when considered as a whole at the project planning stage, has the potential for greater gain by allowing proper plant optimization. Much of the repowering in the past has been carried out without due regard to the benefits of re-matching the steam turbine. Retrospective ST upgrade of such cases can still give benefit to the plant owner, especially when it is realized that most repowering to date has retained an unmodified steam turbine (that first went into operation some decades before). The old equipment will have suffered deterioration due to aging and the steam path will be to an archaic design of poor efficiency. Retrofitting older generation plant with modern leading-edge steam-path technology has the potential for realizing those substantial advances made over the last 20 to 30 years. Some examples, given in the paper, of successfully retrofitted steam turbines applied in repowered plants will show, by specific solution, the optimization of the economics and benefit to the environment of the converted plant as a whole.

Blending supplies for plant optimization

1998 ◽  
Vol 90 (8) ◽  
pp. 40-49 ◽  
Author(s):  
Susan K. Booth ◽  
C.B. Hagar ◽  
Eduardo Garaña ◽  
Herbert R. Hall
Keyword(s):  
Plant Optimization

scholarly journals Plant and Controller Optimization for Power and Energy Systems With Model Predictive Control

2021 ◽  
Vol 143 (8) ◽  
Author(s):  
Donald J. Docimo ◽  
Ziliang Kang ◽  
Kai A. James ◽  
Andrew G. Alleyne
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hybrid Electric Vehicle ◽  
Performance Metrics ◽  
Control Strategies ◽  
Transportation Systems ◽  
Thermal Dynamics ◽  
Plant Optimization ◽  
Power And Energy Systems ◽  
And Control

Abstract This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal dynamics within new components creates integration challenges, increasing component degradation, and reducing performance. Diminishing these issues requires novel plant designs and control strategies. The electrified mobility literature provides prior studies on plant and controller optimization, known as control co-design (CCD). A void within these studies is the lack of model predictive control (MPC), recognized to manage multi-domain dynamics for electrified systems, within CCD frameworks. This article addresses this through three contributions. First, a thermo-electromechanical hybrid electric vehicle (HEV) powertrain model is developed that is suitable for both plant optimization and MPC. Second, simultaneous plant and controller optimization is performed for this multi-domain system. Third, MPC is integrated within a CCD framework using the candidate HEV powertrain model. Results indicate that optimizing both the plant and MPC parameters simultaneously can reduce physical component sizes by over 60% and key performance metric errors by over 50%.

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