Improved energy efficiency in paper making through reducing dryer steam consumption using advanced process control

Over the last two or three years, the increasing costs of energy and worsening market conditions have focussed even greater attention within paper mills than before, on considering ways to improve efficiency and reduce the energy used in paper making. Arising from a multivariable understanding of paper machine operation, Advanced Process Control (APC) technology enables paper machine behaviour to be controlled in a more coherent way, using all the variables available for control. Furthermore, with the machine under better regulation and with more variables used in control, there is the opportunity to optimise machine operation, usually providing very striking multi-objective performance improvement benefits of a number of kinds. Traditional three term control technology does not offer this capability. The paper presents results from several different paper machine projects we have undertaken around the world. These projects have been aimed at improving machine stability, optimising chemicals usage and reducing energy use. On a brown paperboard machine in Australasia, APC has reduced specific steam usage by 10%, averaged across the grades; the controller has also provided a significant capacity to increase production. On a North American newsprint machine, the APC system has reduced steam usage by more than 10%, and it provides better control of colour and much improved wet end stability. The paper also outlines early results from two other performance improvement projects, each incorporating a different approach to reducing the energy used in paper making. The first of these two projects is focussed on optimising sheet drainage, aiming to present the dryer with a sheet having higher solids content than before. The second project aims to reduce specific steam usage by optimising the operation of the dryer hood.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Improving turbomachinery design process management

It is widely acknowledged that a company's ability to aquire market share, and hence its profitability, is very closely linked to the speed with which it can produce a new design. Indeed, a study by the U.K. Department of Trade and Industry has shown that the critical factor which determines profitability is the timely delivery of the new product. Late entry to market or high production costs dramatically reduce profits whilst an overrun on development cost has little significant effect. This paper describes a method which aims to assist the designer in producing higher performance turbomachinery designs more quickly by accelerating the process by which they are produced. The adopted approach combines an enhanced version of the 'Signposting' design process management methodology with industry-standard analysis codes and Computational Fluid Dynamics (CFD). It has been specifically configured to enable process-wide iteration, near instantaneous generation of guidance data for the designer and fully automatic data handling. A successful laboratory experiment based on the design of a large High Pressure Steam Turbine is described and this leads on to current work which incorporates the extension of the proven concept to a full industrial application for the design of Aeroengine Compressors with Rolls-Royce plc.

High sensitive NO2 gas sensor with low power consumption using selectively grown ZnO nanorods.

The noble gas sensor using multiple ZnO nanorods was fabricated with CMOS compatible process and sol-gel growth method on selective area and gas response characteristics to NO2 gas of the sensor device were investigated. We confirmed the sensors had high sensitive response denoted by the sensitivity of several tens for NO2 gas sensing and also showed pretty low power consumption close to 20 mW even though the recovery of resistance come up to almost the initial value.

Optimisation of fuel usage and steam availability in the power and steam plant of a paper mill

This paper presents the results of a project aimed at minimising fuel usage while maximising steam availability in the power and steam plant of a large newsprint mill. The approach taken was to utilise the better regulation and plant wide optimisation capabilities of Advanced Process Control, especially Model Predictive Control (MPC) techniques. These have recently made their appearance in the pulp and paper industry but are better known in the oil and petrochemical industry where they have been used for nearly 30 years. The issue in the power and steam plant is to ensure that sufficient steam is available when the paper machines require it and yet not to have to waste too much steam when one or more of the machines suffers an outage. This is a problem for which MPC is well suited. It allows variables to be kept within declared constraint ranges, a feature which has been used, effectively, to increase the steam storage capacity of the existing plant. This has resulted in less steam being condensed when it is not required and in significant reductions in the need for supplementary firing. The incidence of steam being dump-condensed while also supplementary firing the Combined Heat & Power (CHP) plant has been reduced by 95% and the overall use of supplementary firing is less than 30% of what it was. In addition the plant runs more smoothly and requires less operator time. The yearly benefit provided by the control system is greater than £200,000, measured in terms of 2005 gas prices.

Zero carbon manufacturing facility - Towards integrating material, energy, and waste process flows

The increasing pressure on material availability, energy prices, as well as emerging environmental legislation is leading manufacturers to adopt solutions to reduce their material and energy consumption as well as their carbon footprint, thereby becoming more sustainable. Ultimately manufacturers could potentially become zero carbon by having zero net energy demand and zero waste across the supply chain. The literature on zero carbon manufacturing and the technologies that underpin it are growing, but there is little available on how a manufacturer undertakes the transition. Additionally, the work in this area is fragmented and clustered around technologies rather than around processes that link the technologies together. There is a need to better understand material, energy, and waste process flows in a manufacturing facility from a holistic viewpoint. With knowledge of the potential flows, design methodologies can be developed to enable zero carbon manufacturing facility creation. This paper explores the challenges faced when attempting to design a zero carbon manufacturing facility. A broad scope is adopted from legislation to technology and from low waste to consuming waste. A generic material, energy, and waste flow model is developed and presented to show the material, energy, and waste inputs and outputs for the manufacturing system and the supporting facility and, importantly, how they can potentially interact. Finally the application of the flow model in industrial applications is demonstrated to select appropriate technologies and configure them in an integrated way. © 2009 IMechE.

Building more sustainable solutions in production-consumption systems: the case of food for people with reduced access

In new product development, the ability to integrate different dimensions of sustainability at a value chain level is still a complex, problematic goal. As product-service approaches are increasingly enabling the introduction of more sustainable paths, this paper describes the authors' experience thus far when building insights into conditions for the implementation of integrated solutions in a process of co-development and testing in real life conditions, which are driven by a social need focusing on food for people with reduced access. Throughout this process, which brought together producers, consumers and other stakeholders to design and test industrialised, sustainable solutions, empirical evidence demonstrates feasibility and usefulness of the approach and insight into the conditions for implementing interactive, comprehensive multi-stakeholder processes in real life situations. In addition, results show that the delivery of innovative solutions enabled to offer social added value, economic profits and environmental improvements under specific experimental conditions. © 2006 Elsevier Ltd. All rights reserved.

Water droplet flow paths and droplet deposition in low pressure steam turbines

The complex three-dimensional two-phase flow in a low pressure steam turbine is investigated with comprehensive numerical flow simulations. In addition to the condensation process, which already takes place in the last stages of steam turbines, the numerical flow model is enhanced to consider the drag forces between the droplets and the vapour phase. The present paper shows the differences in the flow path of the phases and investigates the effect of an increasing droplet diameter. For the flow simulations a performance cluster is used because of the high effort for such multi-momentum two-phase flow calculations. In steam turbines the deposition of small water droplets on the stator blades or on parts of the casing is responsible for the formation of large coarse water droplets and these may cause additional dissipation as well as damage due to blade erosion. A method is presented that uses detailed CFD data to predict droplet deposition on turbine stator blades. This simulation method to detect regions of droplet deposition can help to improve the design of water removal devices. © Springer-Verlag Berlin Heidelberg 2013.

Unsteady numerical study of wet steam flow in a low pressure steam turbine

In steam power plants condensation already starts in the flow path of the low pressure part of the steam turbine, which leads to a complex three-dimensional two-phase flow. Wetness losses are caused due to thermodynamic and mechanical relaxation processes during condensation and droplet transport. The present investigation focuses on the unsteady effects due to rotor-stator interaction on the droplet formation process. Results of unsteady three dimensional flow simulations of a two-stage steam turbine are presented, whereby this is the first time that non-equilibrium condensation is considered in such simulations. The numerical approach is based on RANS equations, which are extended by a wet steam specific nucleation and droplet growth model. Despite the use of a high performance cluster the unsteady simulation has a considerably high simulation time of approximately 60 days by use of 48 CPUs. © Springer-Verlag Berlin Heidelberg 2012.

Modelling and validation of wet steam flow in a low pressure steam turbine

Results of numerical investigations of the wet steam flow in a three stage low pressure steam turbine test rig are presented. The test rig is a scale model of a modern steam turbine design and provides flow measurements over a range of operating conditions which are used for detailed comparisons with the numerical results. For the numerical analysis a modern CFD code with user defined models for specific wet steam modelling is used. The effect of different theoretical models for nucleation and droplet growth are examined. It is shown that heterogeneous condensation is highly dependent on steam quality and, in this model turbine with high quality steam, a homogeneous theory appears to be the best choice. The homogeneous theory gives good agreement between the test rig traverse measurements and the numerical results. The differences in the droplet size distribution of the three stage turbine are shown for different loads and modelling assumptions. The different droplet growth models can influence the droplet size by a factor of two. An estimate of the influence of unsteady effects is made by means of an unsteady two-dimensional simulation. The unsteady modelling leads to a shift of nucleation into the next blade row. For the investigated three stage turbine the influence due to wake chopping on the condensation process is weak but to confirm this conclusion further investigations are needed in complete three dimensions and on turbines with more stages. Copyright © 2011 by ASME.

Experimental study of the effects of temperature variation on droplet size and wetness fraction in a low-pressure model steam turbine

The three-stage low-pressure model steam turbine at the Institute of Thermal Turbomachinery and Machinery Laboratory (ITSM) was used to study the impact of three different steam inlet temperatures on the homogeneous condensation process and the resulting wetness topology. The droplet spectrum as well as the particle number concentration were measured in front of the last stage using an optical-pneumatic probe. At design load, condensation starts inside the stator of the second stage. A change in the steam inlet temperature is able to shift the location of condensation onset within the blade row up- or downstream and even into adjoining blade passages, which leads to significantly different local droplet sizes and wetness fractions due to different local expansion rates. The measured results are compared to steady three-dimensional computational fluid dynamics calculations. The predicted nucleation zones could be largely confirmed by the measurements. Although the trend of measured and calculated droplet size across the span is satisfactory, there are considerable differences between the measured and computed droplet spectrum and wetness fractions. © IMechE 2013 Reprints and permissions: sagepub.co.uk/ journalsPermissions.nav.