Modelling, validation, and control of an industrial fuel gas blending system

In industrial fuel gas preparation, there are several compositional properties that must be controlled within specified limits. This allows client plants to use the fuel gas mixture safely without having to adjust and control the composition themselves. The variables to be controlled are the Higher Heating Value (HHV), Wobbe Index (WI), Flame Speed Index (FSI), and Pressure (P). These variables are controlled by adjusting the volumetric flow rates of several inlet gas streams of which some are makeup streams (always available) and some are wild streams that vary in composition and availability (by-products of plants). The inlet streams need to be adjusted in the correct ratios to keep all the controlled variables (CVs) within limits while minimising the cost of the gas blend. Furthermore, the controller needs to compensate for fluctuations in inlet stream compositions and total fuel gas demand (the total discharge from the header). This dissertation describes the modelling and model validation of an industrial fuel gas header as well as a simulation study of three different Model Predictive Control (MPC) strategies for controlling the system while minimising the overall operating cost.Dissertation (MEng)--University of Pretoria, 2011.Electrical, Electronic and Computer Engineeringunrestricte

Economic hybrid non-linear model predictive control of a dual circuit induced draft cooling water system

Petrochemical plants require the addition and removal of energy to and from the process and the movement of material to, from, and within the process piping and vessels. These fundamental mass and energy transfer requirements are typically achieved through the use of process utilities, which include electricity, steam, fuel gas, cooling water and compressed air. Utilities are responsible for a significant portion of the operating cost of a plant. Therefore, reduction in the consumption of utilities is a common process optimisation area. The situation is different when it comes to the generation and transportation of these utilities, which are often overlooked with regard to optimisation. In this paper, the potential benefits of utility optimisation are illustrated with particular focus on the generation and transportation areas. The main objectives are reductions in electrical energy consumption and cost and are illustrated for a dual circuit cooling water system. This system is non-linear and also hybrid in the sense that it contains both continuous and discrete input variables, which significantly complicates the design and implementation of control and optimisation solutions. This paper illustrates how the cost and energy consumption of a hybrid system can be reduced through the implementation of hybrid non-linear model predictive control (HNMPC) and economic HNMPC (EHNMPC). The results are compared to that of a base case and an Advanced Regulatory Control (ARC) case, showing that significant additional benefit may be achieved through the implementation of these advanced control and optimisation techniques. The paper further illustrates that additional capital is not necessarily required for the implementation of these techniques.The National Research Foundation of South Africa (Grant Number 90533).http://www.elsevier.com/locate/jprocont2018-05-30Electrical, Electronic and Computer Engineerin

Energy reduction for a dual circuit cooling water system using advanced regulatory control

Various process utilities are used in the petrochemical industry as auxiliary variables to facilitate the addition/removal of energy to/from the process, power process equipment and inhibit unwanted reaction. Optimisation activities usually focus on the process itself or on the utility consumption though the generation and distribution of these utilities are often overlooked in this regard. Many utilities are prepared or generated far from the process plant and have to be transported or transmitted, giving rise to more losses and potential inefficiencies. To illustrate the potential benefit of utility optimisation, this paper explores the control of a dual circuit cooling water system with focus on energy reduction subject process constraints. This is accomplished through the development of an advanced regulatory control (ARC) and switching strategy which does not require the development of a system model, only rudimentary knowledge of the behaviour of the process and system constraints. The novelty of this manuscript lies in the fact that it demonstrates that significant energy savings can be obtained by applying ARC to a process utility containing both discrete and continuous dynamics. Furthermore, the proposed ARC strategy does not require a plant model, uses only existing plant equipment, and can be implemented on control system hardware commonly used in industry. The simulation results indicate energy saving potential in the region of 30% on the system under investigation.http://www.elsevier.com/locate/apenergy2017-06-30hb2016Electrical, Electronic and Computer Engineerin

Fuel gas blending benchmark for economic performance evaluation of advanced control and state estimation

A simulation of a fuel gas blending process and its measurement system is proposed as a benchmark test case for advanced control and state estimation. The simulation represents an industrial facility and employs a well-established software environment. The objective is to maintain four controlled variables within specified bounds while minimizing an economic performance index. The controlled variables are the fuel gas pressure and three measures of gas quality. Six feed gas flow rates may be adjusted to achieve the objective. Each has a limited availability. The benchmark consists of three reproducible scenarios, each a 46-h period during which 23 discrete upsets occur and the feed gas compositions vary gradually with time. A benchmark multi-loop feedforward–feedback structure is described, tested, and compared to an estimate of optimal performance. The operating cost provided by the benchmark controller is from 1.19 to 1.71 times higher than the estimated minimum. Readers are challenged to download the simulation model, benchmark controller and estimated optimal performance from the URL given in this paper, and to devise case studies of advanced state estimation and control strategies to better the proposed benchmark controller.http://www.elsevier.com/locate/jprocontai201

Dynamic modelling of induced draft cooling towers with parallel heat exchangers, pumps and cooling water network

In the process industries, cooling capacity is an important enabler for the facility to manufacture on specification product. The cooling water network is an important part of the over-all cooling system of the facility. In this paper a cooling water circuit consisting of 3 cooling towers in parallel, 2 cooling water pumps in parallel, and 11 heat exchangers in parallel, is modelled. The model developed is based on first principles and captures the dynamic, non-linear nature of the plant. The modelled plant is further complicated by continuous, as well as Boolean process variables, giving the model a hybrid nature. Energy consumption is included in the model as it is a very important parameter for plant operation. The model is fitted to real industry data by using a particle swarm optimisation approach. The model is suitable to be used for optimisation and control purposes.The National Research Foundation of South Africa (Grant Number 90533).http://www.elsevier.com/locate/jprocont2019-08-01hj2018Electrical, Electronic and Computer Engineerin

Hybrid nonlinear model predictive control of a cooling water network

A Hybrid Nonlinear Model Predictive Control (HNMPC) strategy is developed for temperature control and power consumption minimisation of a cooling water network. The HNMPC uses a gradient descent optimisation algorithm for the continuous manipulated variables, and an enumerated tree traversal algorithm to control and optimise the Boolean manipulated variables. The HNMPC is subjected to disturbances similar to those experienced on a real plant, and its performance compared to a continuous Nonlinear Model Predictive Control (NMPC) and two base case scenarios. Power consumption is minimised, and process temperature disturbances are successfully rejected. Monetary benefits of the HNMPC control strategy are estimated.The National Research Foundation of South Africahttp://www.elsevier.com/locate/conengprac2021-04-01hj2020Electrical, Electronic and Computer Engineerin

Modelling control and optimisation of a dual circuit induced draft cooling water system

The operation of any petrochemical plant requires the transfer of energy to and from the process, movement of material through the process piping and vessels and suppression of unwanted reaction or combustion. This is mainly achieved through the use of utilities which serve as auxiliary variables in plant operation and include electricity, steam, cooling water, hydrogen, nitrogen, compressed air and fuel gas. These utilities have costs associated with them and it is therefore common practice to optimise on the use of these utilities. Other aspects to consider are the generation and transportation/ transmission of these utilities to the point of consumption. These areas have not received much attention historically mainly due to the large differences that existed between product prices and utility costs. Recently, there has been a revival in the focus on efficient operation fuelled by global economic turbulence, higher energy cost, stricter environmental policies, dwindling fossil fuel supplies and the threat of climate change. The losses encountered in the generation and transmission of utilities are in many cases substantial, especially in those utilities where releases to the atmosphere do not present significant safety or environmental risk such as compressed air, cooling water and steam systems. Also in many cases, the transmission distance is substantial which gives rise to more losses and inefficiencies. Furthermore, many electrical utility providers are using time-of-use electricity costs and maximum demand penalties. This necessitates scrutinising the exact time of consumption and peak consumption rather just the overall amount consumed. This study explores the potential benefits of utility control and optimisation from a supply/ generation point of view through the application of modern advanced control and optimisation techniques. The approach and results for a dual circuit cooling water system are illustrated. The cooling water system is an example of a hybrid system where both continuous and discrete input variables are present. This complicates the formulation of control and optimisation solutions. A model of the system is developed and verified using real plant data. To improve model accuracy, a parameter estimation exercise is performed using a genetic algorithm as the optimisation platform. Several control and optimisation schemes are then developed with varying degrees of complexity including advanced regulatory control (ARC), hybrid non-linear model predictive control (HNMPC) and economic hybrid non-linear model predictive control (EHNMPC). The ARC scheme uses classical advanced base layer control techniques, together with time and condition based switching logic, which do not require the use of a system model. The HNMPC and EHNMPC schemes make use of a system model in the formulation of the control solutions and use a genetic algorithm for optimisation. The model is then used to evaluate the performance of the control and optimisation techniques in several simulation studies by comparing the results to that of a base case study. The results indicate that substantial energy and cost savings may be achieved without the need to install additional plant equipment.Die suksesvolle bedryf van enige petro-chemiese aanleg is afhanklik van die oordrag van energie van en na die proses, beweging van materiaal deur die aanleg se pyp- en struktuurnetwerk en die onderdrukking van ongewensde reaksie of ontbranding. Hierdie doelwitte word hoofsaaklik bereik deur gebruik te maak van utiliteite wat as hulpveranderlikes dien en sluit onder andere elektrisiteit, stoom, verkoelingswater, waterstof, stikstof, saamgepersde lug en brandstofgas in. Daar is koste aan sulke utiliteitstrome verbonde en dit is daarom algemeen om die benutting daarvan te optimeer. Ander areas om in ag te neem, is die opwekking en vervoer van hierdie strome tot by die verbruikspunt. Hierdie areas het histories nie soveel aandag geniet nie, hoofsaaklik as gevolg van die groot verskille wat tussen produkpryse en utiliteitskoste bestaan het. As gevolg van die onstuimighede in die wêreldekonomie, hoër energiekoste, strenger omgewingswette, kwynende fossielbrandstofreserwes en drygende klimaatsverandering word daar egter tans nuwe klem op meer effektiewe aanlegsbedryf geplaas. Die verliese wat aangetref word in die opwekking en vervoer van utiliteite is in baie gevalle noemenswaardig, veral in gevalle waar verliese na die atmosfeer nie enige ware risiko s vir veiligheid of die omgewing inhou nie, byvoorbeeld in die geval van saamgepersde lug, verkoelingswater en stoom. In baie gevalle is die afstand waaroor die oordrag plaasvind groot wat verder tot verliese en ondoeltreffendheid bydra. Verder maak heelwat elektrisiteitsverskaffers deesdae gebruik van tyd-van-verbruik tariewe en maksimum aanvraag boetes, waar die hoeveelheid energie wat gebruik word nie die enigste faktor is wat in ag geneem moet word nie, maar ook wanneer die energie gebruik word. Hierdie studie ondersoek die moontlike voordele verbonde aan die beheer en optimering van utiliteite uit n opwekkings- en oordragsoogpunt, deur gebruik te maak van moderne beheeren optimeringstegnieke. Die benadering en resultate word geïllustreer deur die toepassing daarvan op n dubbel-baan verkoelingswaterstelsel. Die verkoelingswaterstelsel is n voorbeeld van n hibriede stelsel waar beide diskrete en kontinue insetveranderlikes teenwoordig is, wat die formulering van beheer- en optimeringsoplossings kompliseer. n Model van die stelsel word ontwerp en geverifieer deur gebruik te maak van ware aanlegdata. Ten einde die model se akkuraatheid te verbeter word n genetiese algoritme gebruik in n parameterpassingsoefening. Verskeie beheer- en optimeringskemas word dan ontwikkel met wisselende grade van kompleksiteit, insluitend gevorderde regulerende beheer, hibriede nie-lineêre model voorspellende beheer en ekonomiese hibriede nie-lineêre model voorspellende beheer. Die gevorderde regulerende beheer maak gebruik van klassieke gevorderde basisvlak beheer tegnieke, tesame met tyd- en voorwaarde-afhanklike skakelingslogika, wat nie die ontwikkeling van n stelselmodel benodig nie. Die hibriede nie-lineêre model voorspellende beheer en ekonomiese hibriede nie-lineêre model voorspellende beheer skemas maak gebruik van n stelselmodel in die formulering van die beheeroplossing en gebruik n genetiese algoritme vir optimering. Die model word daarna gebruik om die prestasie van die verskillende beheer- en optimeringstegnieke te evalueer in n verskeidenheid van simulasiestudies deur die resultate te vergelyk met die van n basisgeval. Die resultate dui daarop dat n noemenswaardige energieen kostebesparing bewerkstellig kan word sonder dat addisionele toerusting geïnstalleer hoef te word.Thesis (PhD)--University of Pretoria, 2015.tm2016Electrical, Electronic and Computer EngineeringPhDUnrestricte

Modelling of a dual circuit induced draft cooling water system for control and optimisation purposes

The successful operation of any petrochemical plant is dependent on the use of several utilities whichmay include electricity, steam, compressed air, cooling media, refrigeration media, nitrogen, condensateand fuel gas. These utilities form a significant portion of the fixed cost associated with running a plant.Utility optimisation has not received much attention until recently, driven by rising energy costs, stricterenvironmental policies, more competitive markets, and the threat of climate change. The generation,preparation, and transportation of utilities require energy and therefore should be optimised to reducelosses and improve operating efficiency. One example of such a utility is a cooling water system. Thispaper describes the modelling of a dual circuit induced draft cooling water system for control and opti-misation purposes. The derived model is verified with plant data indicating promising results. The modelis represented in a steady-state algebraic form as well as a dynamic state-space form. This provides aconvenient basis for simulation studies and controller/optimiser design.http://www.elsevier.com/locate/jproconthb201

Modelling, validation, and control of an industrial fuel gas blending system

In industrial fuel gas preparation, several compositional properties must be controlled within specified limits. This allows client plants to burn the gas safely and with consistent heat production. The variables to be controlled are the higher heating value (HHV), Wobbe index (WI), flame speed index (FSI), and header pressure. A plant in which six feed gasses are blended is considered. Four of the feeds are well-defined makeup streams (costly but always available) and the other two are byproducts that would otherwise be flared. The six feed rates comprise the manipulated variables (MVs) used to regulate the four controlled variables (CVs) while minimising the cost of the gas blend. The control system must compensate for feed composition and fuel gas demand variability. The development and validation of an industrial fuel gas header model is described, followed by a simulation study comparing three Model Predictive Control (MPC) strategies. It is shown that when iterative linearisation is used to update the prediction model and real-time optimisation (RTO) is used to update the CV and MV targets used in the MPC cost function, the plant is driven reliably to the optimal steady-state.ai201