doktorska disertacija
Mihael Kasaš (Author), Zorka Novak-Pintarič (Mentor), Zdravko Kravanja (Co-mentor)

Abstract

Disertacija obravnava vključevanje dejavnikov operabilnosti, kot so fleksibilnost ter obratovalna, okoljska in ekonomska učinkovitost, v načrtovanje kemijskih procesov z matematičnim programiranjem. V prvem delu jerazvita metoda za testiranje podrobnosti, in ustreznosti modeliranja procesnih shem glede na generiranje ustreznih kompromisov med vloženimi sredstvi in ustvarjenim denarnim tokom. Metoda analizira funkcijo denarnega toka v odvisnosti od naložbe, njen odvod in razlike med optimalnimi rešitvami,dobljenimi z različnimi ekonomskimi kriteriji, kot so stroški, dobiček, neto sedanja vrednost, doba vračanja, interna stopnja donosnosti itd.Ustrezni modeli procesov izkazujejo monotono naraščajočo funkcijo denarnihtokov in položno krivuljo odvoda. Optimalne rešitve takšnih modelov, dobljene z različnimi namenskimi funkcijami, se med seboj bistveno razlikujejo. Modeli z neustrezno stopnjo natančnosti izkazujejo unimodalno funkcijo denarnega toka, strm odvod in majhne razlike med optimalnimi rezultati. V disertaciji je prikazano, da se optimalni rezultati, dobljenimi zrazličnimi ekonomskimi kriteriji, razlikujejo ne le po ekonomskih kazalcih, temveč tudi po obratovalni učinkovitosti in okoljskih kazalcih. S kvantitativnimi kriteriji, kot sta dobiček in stroški, dosežemo ob višji investiciji obratovalno učinkovitejše in okoljsko manj obremenjujoče procese znižjo donosnostjo. Kvalitativni kriteriji, kot sta interna stopnja donosnostiin doba vračanja, generirajo procese z manj učinkovito izrabo virov in višjo donosnostjo ob nižji naložbi. Neto sedanja vrednost vzpostavlja najustreznejše kompromise med ekonomsko, obratovalno in okoljsko učinkovitostjo optimalnih procesov pri enokriterijskem optimiranju. Natančnejši vpogled v kompromise med omenjenimi učinkovitostmi daje večkriterijsko optimiranje, pri čemer je v disertaciji prikazano, da različni ekonomski kriteriji glede na izbrani okoljski kriterij generirajo množice nedominantnih (Pareto) rešitev, ki se razlikujejo po območju vrednosti ter po najnižji in najvišji dosegljivi vrednosti posameznega kriterija. V drugem deludisertacije je predstavljena strategija za načrtovanje fleksibilnih procesnih shem z velikim številom negotovih parametrov. Osnovna matematična formulacija temelji na dvostopenjskem stohastičnem problemu z rekurzom, ki je spremenjen v znatno reduciran deterministični ekvivalent. Ta je rešen v majhnimnožici kritičnih točk, medtem ko je pričakovana vrednost namenske funkcije ocenjena z eno samo točko, tj. nominalno ali centralno bazno točko. Za zmanjšanje števila scenarijev smo razvili dve metodi: metodo z analizo občutljivosti vpliva negotovih parametrov na prvostopenjske spremenljivke in namensko funkcijo, ter dvonivojsko metodo, ki uporablja možnost programa GAMS za vključitev zunanjih funkcij v optimiranje. Rezultati primerov kažejo, da jemogoče s predlaganimi pristopi generirati fleksibilne rešitve z bistveno zmanjšanim računalniškim naporom tudi za primere z do 100 negotovimi parametri.

Keywords

kemijska procesna tehnika;matematična optimizacija;modeliranje;ekonomska namenska funkcija;operabilnost;učinkovitost;negotovost;dvostopenjsko stohastično programiranje;algoritem WAR;večkriterisko optimiranje;

Data

Language: Slovenian
Year of publishing:
Source: [Maribor
Typology: 2.08 - Doctoral Dissertation
Organization: UM FKKT - Faculty of Chemistry and Chemical Engineering
Publisher: M. Kasaš]
UDC: 66.02:519.61/.64(043.3)
COBISS: 16527638 Link will open in a new window
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Other data

Secondary language: English
Secondary title: Designing operable processes with mathematical programming
Secondary abstract: This dissertation deals with the integration of the operability topics, such as the flexibility, and the operational, environmental and economic efficiencies, into chemical process design by means of mathematical programming. In the first part, the method was developed for testing the accuracy, complexity, and adequacy of process flow sheets modelling regarding the embedded trade-offs between the invested funds and generated cash flows. This method analyses the cash flow function vs. investment, its derivative, and the differences between optimum solutions obtained by different economic criteria, such as the total annual cost, the profit, the net present value, the payback time, the internal rate of return etc. Suitable process models generate concave monotonically increasing cash flow functions, and flat derivative curves. Optimal designs of such models are substantially different when using different economic objectives. On the contrary, those process models with inappropriate level of accuracy produce unimodal cash flow function with steep derivative, and small differences between optimal results.It is shown that those optimal results obtained by different economic criteria differ not only in the economic indicators but also in the operational efficiency and environmental indicators. Quantitative criteria, such as the profit and costs, generate more expensive yet operationally more efficient, and environmentally less harmful processes at lower profitability. Qualitative criteria, such as the internal rate of return and payback time, produce processes with less efficient usage of resources at higher profitability, and lower investment cost. The net present value generates the compromise solutions regarding the economic, operational, and environmental efficiencies of optimal processes during the single-objective optimization. Multi-objective optimization, however, could provide more precise insight intothe trade-offs among the above mentioned efficiencies. It is shown in thisdissertation that various economic criteria, with regard to the selected environmental criterion, generate the sets of nondominant (Pareto) solutions, which differ in the range of values as well as in the lowest and highest attainable values of particular objective. In the second part of dissertation, a strategy is presented for flexible process flow sheets design with a large number of uncertain parameters. The mathematical formulation is based on the two-stage stochastic problem with recourse, and its transformation into the significantly reduced deterministic equivalent. The latter is solved over the reduced set of critical points, while the expected objective value is approximated in one single point, i.e. the nominal point orthe Central Basic Point. Two methods for scenario reduction were developed: the sensitivity analysis of uncertain parametersć influences on the first-stage variables and the objective function, and the two-level method, which combines GAMS optimization program with the external functions. The results of the examples show that flexible solutions can be generated by usingthe proposed methods at significantly reduced computational effort, even for problems with up to 100 uncertain parameters.
Secondary keywords: chemical process engineering;mathematical optimization;modelling;economic objective function;operability;efficiency;uncertainty;two stage stochastic programming;WAR algorithm;multicriteria optimization;Kemijska procesna tehnika;Disertacije;Optimizacija;Modeliranje;
URN: URN:SI:UM:
Type (COBISS): Dissertation
Thesis comment: Univ. Maribor, Fak. za kemijo in kemijsko tehnologijo
Pages: XIX, 143 str.
Keywords (UDC): applied sciences;medicine;technology;uporabne znanosti;medicina;tehnika;chemical technology;chemical and related industries;kemijska tehnologija;kemijske in sorodne industrije;chemical processing operations and equipment in general;kemijska procesna tehnika in oprema na splošno;mathematics;natural sciences;naravoslovne vede;matematika;mathematics;matematika;computational mathematics;numerical analysis;računska matematika;numerična analiza;
ID: 1027031