Improving energy and economic performances of a typical sugarcane factory through energy indicator development, set-point optimization, and optimal sensor placement

Date
2021-03
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: The volatile sugar markets and the recent recognition of bagasse as a key feedstock to produce biofuels and bioproducts have prompted a desire in the sugarcane industry to correct energy inefficiencies thereby allowing for additional revenue from increased surplus bagasse availability. However, the desire for improved energy efficiency is often beset by the lack of adequate measurements, imprecise measurements, budget constraints, and random variations in external process disturbances and market prices. In this regard, this study seeks to evaluate optimal control solutions that can be used to enhance the plant-wide monitoring and control of existing process operations in a typical sugarcane mill that processes 250 tonnes of sugarcane per hour. Objective 1 sought to identify the controlled variables (CVs) whose steady-state set-point deviations are associated with excess energy demands through energy indicator definition, sensitivity, and statistical analysis. An established sugarcane mill model was used to simulate the steady-state deviations of the CVs and to quantify their effect on energy usage based on defined energy indicators. Objective 2 entailed the use of Monte Carlo analysis to investigate the effect of process disturbances and market price variations on the steady-state factory control and net- revenue. Six disturbances were considered for simulation using the sugarcane mill model while the net revenue was defined in terms of raw materials cost and product revenue. From the observed steady-state deviations, set-point optimizing control (objective 3) was investigated for use in maximizing the net revenue by finding the optimal set-points for the CVs when disturbances and market prices vary. Fourteen CVs identified from objective 1 to have a large influence on energy consumption were used for set-point optimization. From objective 1, massecuite recycling was identified to result in excess energy demands and with set-point optimization, recycling was reduced by 23%. Surplus bagasse was increased by 8.5% with an acceptable 0.43% reduction in sugar yield and a 2.4% increase in net revenue. Nine CVs were identified to have optimal steady-state set-points that are insensitive to disturbance variations, thus allowing for simplified implementation of set-point optimization by keeping these CVs at constant set-points while re-optimizing for the remaining 5 CVs. The availability of precise measurements is crucial for effective automated control. Hence, the self-optimizing control concept was used to find an optimal linear combination of 41 CVs and their optimal sensor placement for use as constant CVs while eliminating the need for frequent online re-optimization when disturbances occur (objective 4). Optimality is defined as maximizing the net revenue by minimizing the total cost of purchasing the measuring instruments and the average revenue loss due to implementing the constant set-point policy rather than continuous real-time optimization. The cost of purchasing the sensor is normalized based on its expected lifespan. The attained optimal sensor placement has an average revenue loss of US$61.93/hr while the base case sensor placement loss is US$157.72/hr. The reduction in average revenue loss is attributed to 19 CVs for which the optimal sensor placement allocated more precise sensors compared to the base case sensor placement. The cost of purchasing the more precise sensors for these 19 CVs is US$2.73/hr. Overall, this study was able to successfully formulate strategies for enhanced process monitoring and control in sugarcane mills while contributing to the available literature.
AFRIKAANSE OPSOMMING: Die onbestendigde suikermarkte en die onlangse erkenning van bagasse as ’n sleutelfaktor vir die produksie van biobrandstowwe en bioprodukte het ’n begeerte in die suikerrietindustrie aangehits om energie-ondoeltreffendhede te korrigeer en daardeur addisionele inkomste uit verhoogde surplus bagasse se beskikbaarheid, toe te laat. Die begeerte vir verbeterde energiedoeltreffendheid word egter gereeld in beslag geneem deur die gebrek aan voldoende afmetings, onakkurate afmetings, begrotingsbeperkings, en lukrake variasies in eksterne prosessteuringe en markpryse. In hierdie verband poog hierdie studie om optimale beheeroplossings te evalueer wat gebruik kan word om die fabriekswye monitering en beheer van bestaande prosesbedrywighede in 'n tipiese suikerrietfabriek wat 250-ton suikerriet per uur verwerk, te verbeter. Doelwit 1 het probeer om die beheerde veranderlikes (CV’s) te identifiseer wat se bestendige toestand setpuntafwykings geassosieer word met oormaat energievereistes deur energie-indikatordefinisie, sensitiwiteit, en statistiese analise. ’n Gevestigde suikerrietaanlegmodel is gebruik om die bestendige toestand afwykings van die CV’s te simuleer en hul effek op energieverbruik te kwantifiseer gebaseer op gedefinieerde energie-indikators. Doelwit 2 het die gebruik van Monte Carlo-analise behels om die effek van prosessteuringe en markprysvariasies op die bestendige toestand fabrieksbeheer en netto opbrengs, te ondersoek. Ses steuringe is oorweeg vir simulasie deur die suikerrietmeulmodel te gebruik in terme van rou materiale se koste en produkinkomste. Van die waargenome bestendige toestandafwykings, is setpuntoptimeringsbeheer (doelwit 3) ondersoek vir gebruik in maksimering van die netto opbrengs deur die optimale setpunte vir die CV’s te vind wanneer steuringe en markpryse varieer. Veertien CV’s wat in doelwit 1 geïdentifiseer is wat ’n groot invloed op energieverbruik het, is gebruik vir setpuntoptimering. Uit doelwit 1, is massecuite-hersirkulasie geïdentifiseer om oormaat energievereistes tot gevolg te hê en met setpuntoptimering het hersirkulasie met 23% afgeneem. Surplus bagasse het met 8.5% verhoog met ’n aanvaarbare 0.43% afname in suikeropbrengs en ’n 2.4% verhoging in netto opbrengs. Nege CV’s is geïdentifiseer om optimale bestendige toestand setpunte te hê wat onsensitief is vir steuringvariasies, en het dus vereenvoudigde implementasie van setpuntoptimering toegelaat deur hierdie CV’s by konstante setpunte te hou terwyl die oorblywende vyf CV’s heroptimeer kon word. Die beskikbaarheid van presiese afmetings is krities vir effektiewe geoutomatiseerde beheer. Daarom is die self-optimeringsbeheerkonsep gebruik om ’n optimale liniêre kombinasie van 41 CV’s en hul optimale sensorplasing vir gebruik as konstante CV’s, te vind, terwyl die behoefte aan gereelde aanlyn heroptimering wanneer steuringe voorkom (doelwit 4), geëlimineer word. Optimaliteit is gedefinieer om die netto opbrengs te maksimeer deur die koste van instrumentasie en die gemiddelde inkomsteverlies te minimeer as gevolg van die implementering van konstante setpuntbeleid in plaas van die aaneenlopende intydse optimering. Die behaalde optimale sensorplasing het ’n gemiddelde inkomsteverlies van US$61.93/hr terwyl die basis-geval sensorplasing se verlies US$157.72/hr is. Die vermindering in gemiddelde inkomsteverlies word toegeskryf aan 19 CV’s waarvoor die optimale sensorplasing meer presiese sensors geallokeer het in vergelyking met basis-geval sensorplasing. Die koste van die presisie opgradering vir hierdie 19 CV’s is US$2.73/hr. Oor die algeheel het hierdie studie suksesvolle strategieë vir versterkte prosesmonitering en -beheer in suikerrietmeule geformuleer, terwyl dit tot die beskikbare literatuur bygedra het.
Description
Thesis (PhD)--Stellenbosch University, 2021.
Keywords
Sugarcane factories -- Energy consumption -- Evaluation, Sensor networks, Energy consumption -- Monitoring, Sugercane factories -- Cost effectiveness, Process control, UCTD
Citation