<p>More stringent requirements on nitrogen removal from wastewater are the motivation for this thesis. In order to improve treatment results and enhance cost-efficient operation of wastewater treatment plants, model based control strategies are presented.</p><p>A Java based simulator for activated sludge processes (JASS) is presented. The graphical user interface, educational experiences and implemented control strategies are discussed.</p><p>Controlling the addition of an external carbon source is the next topic discussed. A simple model based feedforward controller is derived and evaluated in a simulation study. The controller attenuates process disturbances quickly. Further, two feedforward controllers for adjusting the aeration volume in activated sludge processes are derived. The aim of the volume control strategies was to efficiently dampen the impact of process disturbances without using an excessively high dissolved oxygen concentration. The simulation results are promising and show that the aeration volume may be a feasible control variable.</p><p>A linearisation method for static input non-linearities is presented. The method gives essentially the same result as the existing standard method, but possesses some implementational advantages. The method is used to linearise the non-linear oxygen transfer function of an activated sludge process in an application study.</p><p>Multivariable interactions in a process model describing nitrate removal in an activated sludge process are studied using the well known RGA method as well as a relatively novel tool based on Hankel norms. The results of the analysis are compared to conclusions drawn from common process knowledge and are used to design a multivariable control strategy. It was found that process disturbances may be rejected faster using multivariable control.</p><p>Finally, the operational costs of the denitrification process are investigated and visualised graphically. Cost optimal regions are found by a numerical grid search. Procedures for controlling the denitrification process in a cost-efficient way are described.</p>

Many control systems of practical importance are multivariable. In such systems, each manipulated variable (input signal) may affect several controlled variables (output signals) causing interaction between the input/output loops. For this reason, control of multivariable systems is typically much more difficult compared to the single-input single-output case. It is therefore of great importance to quantify the degree of interaction so that proper input/output pairings that minimize the impact of the interaction can be formed. For this, dedicated interaction measures can be used. The first part of this thesis treats interaction measures. The commonly used Relative Gain Array (RGA) is compared with the Gramian-based interaction measures the Hankel Interaction Index Array (HIIA) and the Participation Matrix (PM) which consider controllability and observability to quantify the impact each input signal has on each output signal. A similar measure based on the <img src="http://www.diva-portal.org/cgi-bin/mimetex.cgi?%5Cmathcal%20H_2" /> norm is also investigated. Further, bounds on the uncertainty of the HIIA and the PM in case of uncertain models are derived. It is also shown how the link between the PM and the Nyquist diagram can be utilized to numerically calculate such bounds. Input/output pairing strategies based on linear quadratic Gaussian (LQG) control are also suggested. The key idea is to design single-input single-output LQG controllers for each input/output pair and thereafter form closed-loop multivariable systems for each control configuration of interest. The performances of these are compared in terms of output variance. In the second part of the thesis, the activated sludge process, commonly found in the biological wastewater treatment step for nitrogen removal, is considered. Multivariable interactions present in this type of bioreactor are analysed with the tools discussed in the first part of the thesis. Furthermore, cost-efficient operation of the activated sludge process is investigated.

L'objectif de cette thèse est de présenter de nouveaux algorithmes de placement de machines virtuelles (VMs) à fin d’optimiser le coût et les émissions de carbone dans les Clouds distribués. La thèse se concentre d’abord sur la rentabilité des Clouds distribués, et développe ensuite les raisons d’optimiser les coûts ainsi que les émissions de carbone. La thèse comprend deux principales parties: la première propose, développe et évalue les algorithmes de placement statiques de VMs (où un premier placement d'une VM détient pendant toute la durée de vie de la VM). La deuxième partie propose des algorithmes de placement dynamiques de VMs où le placement initial de VM peut changer dynamiquement (par exemple, grâce à la migration de VMs et à leur consolidation). Cette thèse comprend cinq contributions. La première contribution est une étude de l'état de l'art sur la répartition des coûts et des émissions de carbone dans les environnements de clouds distribués. La deuxième contribution propose une méthode d'allocation des ressources, appelée NACER, pour les clouds distribués. L'objectif est de minimiser le coût de communication du réseau pour exécuter une tâche dans un cloud distribué. La troisième contribution propose une méthode de placement VM (appelée NACEV) pour les clouds distribués. NACEV est une version étendue de NACER. Tandis que NACER considère seulement le coût de communication parmi les DCs, NACEV optimise en même temps les coûts de communication et de calcul. Il propose également un algorithme de cartographie pour placer des machines virtuelles sur des machines physiques (PM). La quatrième contribution présente une méthode de placement VM efficace en termes de coûts et de carbone (appelée CACEV) pour les clouds distribués verts. CACEV est une version étendue de NACEV. En plus de la rentabilité, CACEV considère l'efficacité des émissions de carbone pour les clouds distribués. Pour obtenir une meilleure performance, la cinquième contribution propose une méthode dynamique de placement VM (D-CACEV) pour les clouds distribués. D-CACEV est une version étendue de notre travail précédent, CACEV, avec des chiffres supplémentaires, une description et également des mécanismes de migration de VM en direct. Nous montrons que notre mécanisme conjoint de réallocation-placement de VM peut constamment optimiser à la fois le coût et l'émission de carbone dans un cloud distribué / Virtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud

The choice of heating system in new residential buildings has a significant effect onthe total life cycle-cost. Rising energy prices and tougher energy demands for newbuildings creates incentive for energy- and cost-efficient solutions. The purpose ofthis project is therefore to investigate how the choice and sizing of a heating systemin a building can be performed with focus on cost-efficiency. The project is conducted as a case study on a residential building during the buildingphase on behalf of INTEC Dalarna AB, a technical engineering company. The project aim is to answer the following questions: – What heating system of district heating, ground source heat pumps or air towater heat pumps is the most cost-effective for a new residential building inthe middle of Sweden? – Is there a specific combination of a heat pump of arbitrary size and peak heating system that is particularly advantageous for the building? – Is IDA ICE suitable for simulation of energy use in buildings with heatpumps? – Does high energy-efficiency also mean high cost-efficiency for the building? The questions will be answered with building simulation software IDA Indoor Climate and Energy along with capital budgeting. The capital budgeting will be performed with net present value and payoff period for the heat pumps over choosingdistrict heating. The results of the project show that a system with ground source heat pumps with acapacity of 50 percent of the annual peak heat demand and electricity for peak loadsis the most cost-efficient option for the building. However, the most energy efficient option is a ground source heat pump with a capacity of 50 percent of the annual peak heat demand with district heating for peak loads. The project also shows that IDA ICE is suitable for simulating the performance of heat pumps in buildings.The conclusion is that a smaller system of ground source is more cost-efficient forthe building, and that the most energy efficient option is not always equal to themost cost-efficient over time.

No description available.

In Sweden housing shortage is a rising issue. Within a ten year period scientists predict that the Swedish population will increase from 10 to approximately 11 million people. Due to this increase in the Swedish population, the production of multi-dwelling buildings should be expanding, though instead building development is now decreasing. The Swedish government recently stated upon a climate strategy, to have no excessive emissions of greenhouse gases until the year of 2045. Regarding this climate strategy and the increasing need for housing, the need to build time-efficient, low cost buildings that have minimal environmental impact is in a greater demand than ever before. The purpose of this degree project is to elucidate the environmental effects, costs and assembly time for multi-dwelling buildings with prefabricated wooden and concrete frames. The study, based on literature and interviews, displays that prefabricated cross-laminated timber frames are more expensive than prefabricated concrete frames. However, choosing a timber frame does not necessarily result in a higher production cost compared to a concrete frame. Due to the dehydration time with concrete frames, wooden frames are almost 20 % more time efficient to assemble. Although wooden frames take less time to assemble, they often need more post-production work to withhold quality demands in comparison to concrete frames. The difference in environmental effect between the two materials is significant. Wood is an organic and renewable material and therefore has a low environmental impact. Concrete, which is a non-renewable material, has a higher environmental impact because of its cement component. Today 90 % of the newly developed multi-dwelling buildings are constructed with concrete. To reach the climate strategy in 2045, an increase of wooden constructions is one solution to lower the greenhouse gas emissions. Regarding that most of today’s construction building companies are using concrete as their primary frame material, this way of construction will have to change. Due to this future change, a decisionmaking model for selecting framework material has been developed. The model aims to guide clients and construction companies in an early process to get a first indication on what type of material that would be most beneficial to use in a project. The model is based on three different key factors; environmental effect, investment cost and time. When using the model, these key factors will be compared to each other and prioritized in a hierarchy setting. The outcome specifies the most preferable material to use in a project.

To reach the EU directives and Sweden ́s energy- and climate goals, there is a needto implement new innovative- and technical solutions in each sector. The Swedishgovernment predicts that the buildings sectors energy demand could be reduced byrenovating the existing building stock. The research examines the opportunities to implement indoor design solutionsassociated with an energy renovation measure of an existing single-family house inSweden. The research will cover a broader picture of the concept's feasibility-, addedvalues, and financial cost and benefits. This will be done within the requirements ofthe current building regulations on altering an existing building in Sweden 2021. The research outcome showed that implementing the design solution concept willconstitute a financial benefit on energy renovation measure ́s payback time. Theresult showed that one of the suggested design concepts with the energy renovationmeasures would have a payback time of 8.5 years. Besides, implementing the designsolution concept predicts several beneficial added values, e.g., environment, buildingdesign and society.