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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Modelling the performance of an integrated urban wastewater system under future conditions

Astaraie Imani, Maryam January 2012 (has links)
The performance of the Integrated Urban Wastewater Systems (IUWS) including: sewer system, WWTP and river, in both operational control and design, under unavoidable future climate change and urbanisation is a concern for water engineers which still needs to be improved. Additionally, with regard to the recent attention around the world to the environment, the quality of water, as the main component of that, has received significant attention as it can have impacts on health of human life, aquatic life and so on. Hence, the necessity of improving systems performance under the future changes to maintain the quality of water is observed. The research presented in this thesis describes the development of risk-based and non-risk-based models to improve the operational control and design of the IUWS under future climate change and urbanisation aiming to maintain the quality of water in recipients. In this thesis, impacts of climate change and urbanisation on the IUWS performance in terms of the receiving water quality was investigated. In the line with this, different indicators of climate change and urbanisation were selected for evaluation. Also the performance of the IUWS under future climate change and urbanisation was improved by development of a novel non-risk-based operational control and design models aiming to maintain the quality of water in the river to meet the water quality standards in the recipient. This is initiated by applying a scenario-based approach to describe the possible features of future climate change and /or urbanisation. Additionally the performance of the IUWS under future climate change and urbanisation was improved by development of a novel risk-based operational control and design models to reduce the risk of water quality failures to maintain the health of aquatic life. This is initiated by considering the uncertainties involved with the urbanisation parameters considered. The risk concept is applied to estimate the risk of water quality breaches for the aquatic life. Also due to the complexity and time-demanding nature of the IUWS simulation models (which are called about the optimisation process), there is the concern about excessive running times in this study. The novel “MOGA-ANNβ” algorithm was developed for the optimisation process throughout the thesis to speed it up while preserving the accuracy. The meta-model developed was tested and its performance was evaluated. In this study, the results obtained from the impact analysis of the future climate change and urbanisation (on the performance of the IUWS) showed that the future conditions have potential to influence the performance of the IUWS in both quality and quantity of water. In line with this, selecting proper future conditions’ parameters is important for the system impact analysis. Also the observations demonstrated that the system improvement is required under future conditions. In line with this, the results showed that both risk-based and non-risk-based operational control optimisation of the IUWS in isolation is not good enough to cope with the future conditions and therefore the IUWS design optimisation was carried out to improve the system performance. The riskbased design improvement of the IUWS in this study showed a better potential than the non-risk-based design improvement to meet all the water quality criteria considered in this study.
2

Structural Studies On Bovine Pancreatic Phospholipase A2 And Proteins Involved In Molybdenum Cofactor Biosynthesis

Kanaujia, Shankar Prasad 10 1900 (has links) (PDF)
We have carried out structural studies on bovine pancreatic phospholipase A2 (BPLA2) and two proteins involved in molybdenum cofactor (Moco) biosynthesis pathway. In addition, molecular-dynamics simulations and other analyses have been performed to corroborate the findings obtained from the crystal structures. Crystal structures of the three active-site mutants (H48N, D49N and D49K) of BPLA2 were determined to understand the mechanism by which the mutant H48N is able to catalyze the reaction of phospholipid hydrolysis and to see the effect of the loss of Ca 2+ ion in the active site of D49N and D49K mutants. We found that Asp49 could possibly play the role of a general base instead of His48 in the case of the H48N mutant. In the case of D49N and D49K mutants, the active site of the enzyme is perturbed, whereas the overall tertiary structure of these mutants is intact. In addition, a total of 24 invariant water molecules were identified in all of the crystal structures of BPLA2 available in its archive, PDB. Out of these, four water molecules are essential for the catalytic activity, whereas, the remaining water molecules play a role in the stability of the enzyme. In addition, structural studies on two proteins MoaC and MogA involved in Moco biosynthesis pathway have been carried out. For the first time, crystal structure of MoaC bound with GTP molecule has been reported. The gene id TTHA0341, which is mentioned as MoaB in the CMR database, was annotated as MogA based the comparative analysis of sequences and structures (with the present work and the structures available in the literature). The role of N-and C-termini of MoaB and MogA proteins were proposed that these residues might stabilize the substrate and/or product molecule in the active site. In addition, the residues involved in the oligomerization are compared with MD simulations. The molecular docking studies show that MoaB proteins show more preference to GTP than ATP. The comparison of the two active (MPT and AMP-binding) sites revealed that MPT-binding site is preferred over AMP-binding site for nucleotide binding.
3

Multi-objective Control on Inverter-Based Microgrids

Gonzales Zurita, Óscar Omar 10 March 2024 (has links)
[ES] El aumento en el uso de combustibles fósiles para la generación de energía ha contribuido significativamente a la crisis del calentamiento global. Diferentes lugares alejados de la infraestructura eléctrica emplean generadores a base de gasolina que aumentan la contaminación ambiental. En este contexto, la introducción masiva de microrredes en la sociedad ha traído oportunidades para la generación de energía de forma distribuida, beneficiando a personas en todo el mundo. Por ejemplo, las microrredes pueden brindar electricidad a poblaciones vulnerables que viven en áreas remotas con acceso limitado a infraestructuras de transmisión y distribución. Además, las microrredes promueven el uso de recursos renovables, reduciendo el impacto ambiental en comparación con los métodos tradicionales de generación de electricidad, como las plantas de energía térmica o las instalaciones nucleares. Además, las microrredes permiten la generación de electricidad a pequeña escala, lo que permite que las familias logren la independencia energética y vendan el exceso de energía a la compañía eléctrica local. Cualquier inversor en una microrred necesita un algoritmo de control para realizar una regulación en bucle cerrado. En este contexto, el control por modos deslizantes de segundo orden es una estrategia de control robusta que ha ganado atención en las aplicaciones de inversores de microrredes. Mediante el uso de este enfoque, el inversor puede lograr un control preciso y rápido, incluso en presencia de incertidumbres y perturbaciones. El uso de estrategias de control robustas mejora la estabilidad y el rendimiento general del sistema de microrredes, asegurando una gestión de energía óptima. El proceso de ajuste es esencial para los algoritmos de control en bucle cerrado, ya que modifica la respuesta del controlador para alcanzar los objetivos de control. La optimización por enjambre de partículas (PSO por sus siglas en inglés) es un eficiente algoritmo de optimización empleado en controladores en lazo cerrado que puede resolver de manera efectiva problemas multi-objetivo formulados en una sola función de costo. Los parámetros de control del inversor de la microrred pueden ser optimizados mediante la utilización de PSO para lograr los objetivos deseados, ajustando de manera eficiente una estrategia de control. Para controladores por modos deslizantes, algunas estrategias de ajuste se basan en técnicas heurísticas. La función de costo única resuelve varios problemas en una microrred, pero existen dificultades cuando diferentes objetivos en un proceso no pueden ser mejorados simultáneamente debido a su relación conflictiva. Estrategias como Algoritmos Genéticos Multi-Objetivo (MOGA por sus siglas en inglés), Evolución Diferencial Multi-Objetivo (MODE por sus siglas en inglés) y Algoritmo Artificial de Ovejas Multi-Objetivo (MOASA por sus siglas en inglés), han demostrado su capacidad para mejorar el rendimiento del inversor mediante la optimización de objetivos conflictivos. Estos algoritmos pueden equilibrar de manera efectiva objetivos como la reducción del tiempo de respuesta y la minimización del sobreimpulso en la señal de salida del inversor. En consecuencia, el rendimiento general y la eficiencia de los inversores de la microrred pueden mejorar. La integración de algoritmos de control multi-objetivo en los inversores de la microrred tiene un gran potencial para abordar los desafíos de gestión de energía y optimizar el rendimiento. Los inversores de la microrred pueden lograr una mayor estabilidad, eficiencia y confiabilidad utilizando técnicas como el control por modos deslizantes de segundo orden y algoritmos de optimización como PSO, MOGA, MODE y MOASA. Al adoptar estos enfoques, se presenta una nueva metodología para un futuro energético más sostenible y resiliente, al tiempo que se mitigan los efectos adversos del calentamiento global causado por el consumo de combustibles fósiles en la generación convencional de energía. / [CA] L'augment en l'ús de combustibles fòssils per a la generació d'energia ha contribuït significativament a la crisi de l'escalfament global. Diferents llocs allunyats de la infraestructura elèctrica empleen generadors a base de gasolina que augmenten la contaminació ambiental. En aquest context, la introducció massiva de microxarxes a la societat ha comportat oportunitats per a la generació d'energia de forma distribuïda, beneficiant persones arreu del món. Per exemple, les microxarxes poden proporcionar electricitat a poblacions vulnerables que viuen en àrees remotes amb accés limitat a infraestructures de transmissió i distribució. A més, les microxarxes promouen l'ús de recursos renovables, reduint l'impacte ambiental en comparació amb els mètodes tradicionals de generació d'electricitat, com les plantes d'energia tèrmica o les instal·lacions nuclears. A més a més, les microxarxes permeten la generació d'electricitat a petita escala, la qual cosa permet que les famílies aconsegueixin la independència energètica i venguen l'excedent d'energia a la companyia elèctrica local. Qualsevol inversor en una microxarxa necessita un algoritme de control per a realitzar una regulació en bucle tancat. En aquest context, el control per modes lliscants de segon ordre és una estratègia de control robusta que ha guanyat atenció en les aplicacions d'inversors de microxarxes. Mitjançant l'ús d'aquest enfocament, l'inversor pot aconseguir un control precís i ràpid, fins i tot en presència d'incerteses i pertorbacions. L'ús d'estratègies de control robustes millora l'estabilitat i el rendiment general del sistema de microxarxes, assegurant una gestió d'energia òptima. El procés d'ajust és essencial pels algoritmes de control en bucle tancat, ja que modifica la resposta del controlador per a aconseguir els objectius de control. L'optimització per enjambre de partícules (PSO per les seues sigles en anglés) és un eficient algoritme d'optimització emprat en controladors en bucle tancat que pot resoldre de manera efectiva problemes multi-objectiu formulats en una sola funció de cost. Els paràmetres de control de l'inversor de la microxarxa poden ser optimitzats mitjançant l'utilització de PSO per a aconseguir els objectius desitjats, ajustant de manera eficient una estratègia de control. Per a controladors per modes lliscants, algunes estratègies d'ajust es basen en tècniques heurístiques. La funció de cost única resol diversos problemes en una microxarxa, però existeixen dificultats quan diferents objectius en un procés no poden ser millorats simultàniament a causa de la seua relació conflictiva. Estratègies com Algorismes Genètics Multi-Objectiu (MOGA per les seues sigles en anglés), Evolució Diferencial Multi-Objectiu (MODE per les seues sigles en anglés) i Algorisme Artificial de Xais Multi-Objectiu (MOASA per les seues sigles en anglés), han demostrat la seua capacitat per a millorar el rendiment de l'inversor mitjançant l'optimització d'objectius conflictius. Aquests algorismes poden equilibrar de manera efectiva objectius com la reducció del temps de resposta i la minimització del sobreguiny a la senyal de sortida de l'inversor. En conseqüència, el rendiment general i l'eficiència dels inversors de la microxarxa poden millorar. La integració d'algorismes de control multi-objectiu en els inversors de la microxarxa té un gran potencial per a abordar els desafiaments de gestió d'energia i optimitzar el rendiment. Els inversors de la microxarxa poden aconseguir una major estabilitat, eficiència i fiabilitat utilitzant tècniques com el control per modes lliscants de segon ordre i algorismes d'optimització com PSO, MOGA, MODE i MOASA. En adoptar aquests enfocaments, es presenta una nova metodologia per a un futur energètic més sostenible i resilient, al mateix temps que es mitiguen els efectes adversos de l'escalfament global causat pel consum de combustibles fòssils en la generació convencional d'energia. / [EN] The increase in fossil fuel usage for power generation has significantly contributed to the global warming crisis. Various remote areas, detached from electrical infrastructure, rely on gasoline-based generators that escalate environmental pollution. In this context, the widespread implementation of microgrids in society has brought forth opportunities for distributed energy generation, benefiting people worldwide. For instance, microgrids can provide electricity to vulnerable populations in remote areas with limited access to transmission and distribution infrastructures. Furthermore, these microgrids advocate for using renewable resources, diminishing environmental impact compared to traditional methods such as thermal power plants or nuclear facilities. Additionally, microgrids enable small-scale electricity generation, empowering families to achieve energy independence and sell surplus energy to local power companies. Any investor in a microgrid requires a closed-loop control algorithm. In this realm, the second-order sliding mode control is a robust strategy garnering attention in microgrid inverter applications. Through this approach, the inverter can achieve precise and rapid control despite uncertainties and disturbances. Using robust control strategies enhances microgrid systems' stability and overall performance, ensuring optimal energy management. Adjustment processes are pivotal for closed-loop control algorithms, modifying the controller's response to meet control objectives. Particle Swarm Optimization (PSO) is an efficient optimization algorithm employed in closed-loop controllers that can effectively solve multi-objective problems formulated in a single cost function. Control parameters of the microgrid inverter can be optimized using PSO to attain desired objectives, efficiently fine-tuning a control strategy. For sliding mode controllers, some adjustment strategies rely on heuristic techniques. While a single cost function resolves various issues within a microgrid, difficulties arise when different objectives in a process cannot be simultaneously improved due to conflicting relationships. Strategies like Multi-Objective Genetic Algorithms (MOGA), Multi-Objective Differential Evolution (MODE), and Multi-Objective Artificial Sheep Algorithm (MOASA) have proven their ability to enhance inverter performance by optimizing conflicting objectives. These algorithms effectively balance objectives like reducing response time and minimizing overshoot in the inverter's output signal. Consequently, the overall performance and efficiency of microgrid inverters can be enhanced. Integrating multi-objective control algorithms into microgrid inverters holds significant potential in addressing energy management challenges and optimizing performance. Microgrid inverters can achieve greater stability, efficiency, and reliability by utilizing second-order sliding mode control and optimization algorithms like PSO, MOGA, MODE, and MOASA. By embracing these approaches, a new methodology emerges for a more sustainable and resilient energy future while mitigating the adverse effects of global warming caused by conventional fossil fuel consumption in power generation. / Gonzales Zurita, ÓO. (2024). Multi-objective Control on Inverter-Based Microgrids [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203120

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