Biomass for Energy Country Specific Show Case Studies

In many domestic and industrial processes, vast percentages of primary energy are produced by the combustion of fossil fuels. Apart from diminishing the source of fossil fuels and the increasing risk of higher costs and energy security, the impact on the environment is worsening continually. Renewables are becoming very popular, but are, at present, more expensive than fossil fuels, especially photovoltaics and hydropower. Biomass is one of the most established and common sources of fuel known to mankind, and has been in continuous use for domestic heating and cooking over the years, especially in poorer communities. The use of biomass to produce electricity is interesting and is gaining ground. There are several ways to produce electricity from biomass. Steam and gas turbine technology is well established but requires temperatures in excess of 250 °C to work effectively. The organic Rankine cycle (ORC), where low-boiling-point organic solutions can be used to tailor the appropriate solution, is particularly successful for relatively low temperature heat sources, such as waste heat from coal, gas and biomass burners. Other relatively recent technologies have become more visible, such as the Stirling engine and thermo-electric generators are particularly useful for small power production. However, the uptake of renewables in general, and biomass in particular, is still considered somewhat risky due to the lack of best practice examples to demonstrate how efficient the technology is today. Hence, the call for this Special Issue, focusing on country files, so that different nations’ experiences can be shared and best practices can be published, is warranted. This is realistic, as it seems that some nations have different attitudes to biomass, perhaps due to resource availability, or the technology needed to utilize biomass. Therefore, I suggest that we go forward with this theme, and encourage scientists and engineers who are researching in this field to present case studies related to different countries. I certainly have one case study for the UK to present

Soft-sensor design and dynamic model development for a biomass combustion power plant

From a system theory perspective, a biomass power plant is a nonlinear, coupled multivariate system with multiple inputs (fuel feed, air supply, grate speed) and multiple outputs (gas temperature, oxygen concentration, steam generated), where the different process input-output relationships are difficult to understand due to the large disturbances acting on the combustion process, which emanate mainly from the varying calorific value of fuel delivered to the furnace. Hence, any attempt to maintain stable operating conditions and to design or improve the control strategy being employed will lead to suboptimal solutions, which may jeopardize the commercial character of the combustion site. One possible way to handle such a situation is by improving the combustion performance using advanced model-based control strategies for this aim to further ameliorate the economical aspect of the power plant, while adhering to stringent emission standards. These control techniques explicitly incorporate the available process knowledge, which is represented in terms of an available mathematical model, used by the controller to compute the best control actions to fulfill the multiple conflicting goals in the plant. Therefore, mathematical modeling will be carried out to derive a suitable dynamic model of the power plant. The model is extended by designing a soft-sensor which estimates the energy content of fuel mix.Aus systemetheoretischer Perspektive ist ein Biomassekraftwerk ein nichtlineares, verkoppeltes Mehrgr¨oßensystem mit mehreren Eing¨angen (Brennstoffzufuhr, Luftzufuhr, Rostgeschwindigkeit) und mehreren Ausg¨angen (Gastemperatur, Sauerstoffkonzentration, erzeugter Dampfmenge). Dabei werden die unterschiedlichen Beziehungen zwischen Prozesseing¨angen und -ausg¨angen von großen St¨orungen ¨uberlagert, die haupts¨achlich vom variierenden Heizwert der in den Ofen gelieferten Biomasse herr¨uhren. Deshalb wird jeder Versuch, stabile Betriebsbedingungen aufrechtzuerhalten und die eingesetzte Regelstrategie zu verbessen, zu suboptimalen L¨osungen f¨uhren, die den kommerziellen Nutzen des Kraftwerks gef¨ahrden k¨onnen. Eine L¨osungsm¨oglichkeit ist die Verbesserung der Verbrennungsleistung unter Verwendung h¨oherer modellbasierter Regelungsstrategien, um den wirtschaftlichen Aspekt des Kraftwerks unter Einhaltung strikter Emissionsnormen weiter zu verbessern. Diese Strategien integrieren explizit das verf¨ugbare Prozesswissen, das durch ein verf¨ugbares mathematisches Modell repr¨asentiert wird, das vom Regler verwendet wird, um die besten Steuerungsaktionen zu berechnen, die die vielf¨altigen konkurrierenden Ziele in der Anlage erf¨ullen. Daher wird eine mathematische Modellierung durchgef¨uhrt, um ein geeignetes dynamisches Modell des Kraftwerks abzuleiten. Das Modell wird um einen Softsensor erweitert, der den Energiegehalt des Brennstoffs sch¨atzt

Fault-tolerant model predictive control (FTMPC) for the BioGrate boiler

Peer reviewe

Vikasietoinen malliprediktiivinen säätö (FTMPC) BioGrate-kattilalle

Climate change and environmental concerns are forcing process industries to increase the share of sustainable resources in energy production. The utilization of biomass receives an increasing attention as a replacement for fossil fuels due to its wide availability and sustainability. However, the unpredictable variability of biomass properties, including moisture content, composition and heating value, results in disturbances, faults, and failures during the power plant operation, which creates additional barriers for a wider utilization of biomass.  This thesis focusses on the development of a fault tolerant model predictive control (FTMPC) scheme that addresses the challenges associated with the biomass utilization for power production in BioGrate boilers. The novelty of this scheme lies in the integration of soft-sensors measuring the unpredictable biomass properties with a fault accommodation mechanism.  The effectiveness of the developed FTMPC scheme is successfully tested with a dynamic simulator of the BioGrate boiler. This simulator is constructed using the industrial test data from the BioPower 5 CHP plant. In addition, industrial tests, conducted to evaluate the performance of the developed soft-sensors, confirm the prediction accuracy of the fuel moisture content and combustion power in the furnace. Subsequently, the economic evaluation of the soft-sensors integrated FTMPC scheme is presented.Ilmastonmuutos ja ympäristökysymykset pakottavat prosessiteollisuutta kasvattamaan kestävien luonnonvarojen osuutta energiantuotannossa. Biomassa saa kasvavaa huomiota korvaavana vaihtoehtona fossiilisille polttoaineaineille johtuen sen hyvästä saatavuudesta ja hiilineutraalisuudesta. Kuitenkin biomassan ominaisuuksien arvaamaton vaihtelu, mukaan lukien kosteus, koostumus ja lämpöarvo, johtaa häiriöihin, vikoihin ja toimintahäiriöihin laitoksen operoinnissa, mikä luo esteitä biomassan laajemmalle hyödyntämiselle.  Tämä väitöskirja keskittyy vikasietoisen malliprediktiivisen säätö (FTMPC) -järjestelmän kehittämiseen ottaen huomioon haasteet biomassan hyödyntämisessä energiantuotannossa BioGrate-kattiloilla. Uutta tässä järjestelmässä on soft-sensorien integrointi mittaamaan biomassan vaihtelevia ominaisuuksia yhdessä vikasietoisen menetelmän kanssa.  Kehitetyn FTMPC-järjestelmän tehokkuus on testattu käyttäen BioGrate-kattilan dynaamista simulaattoria, joka on tehty käyttäen hyväksi BioPower 5 CHP -laitoksen teollisia mittauksia. Lisäksi, teollisuudessa suoritetut koetulokset, joita käytettiin kehitettyjen soft-sensorien suorituskyvyn arvioimiseen vahvistavat, että polttoaineen kosteus ja palamisteho voidaan ennustaa hyvällä tarkkuudella. Tämän lisäksi kehitetyn FTMPC-järjestelmän taloudellinen merkitys on arvioitu väitöskirjassa