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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.

Adaptive water distribution system design under future uncertainty

Basupi, Innocent January 2013 (has links)
A water distribution system (WDS) design deals with achieving the desired network performance. WDS design can involve new and / or existing network redesigns in order to keep up with the required service performance. Very often, WDS design is expensive, which encourages cost effectiveness in the required investments. Moreover, WDS design is associated with adverse environmental implications such as greenhouse gas (GHG) emissions due to energy consumption. GHGs are associated with global warming and climate change. Climate change is generally understood to cause reduction in water available at the sources and increase water demand. Urbanization that takes into account factors such as demographics (population ageing, household occupancy rates, etc.) and other activities are associated with water demand changes. In addition to the aforementioned issues, the challenge of meeting the required hydraulic performance of WDSs is worsened by the uncertainties that are associated with WDS parameters (e.g., future water demand). With all the factors mentioned here, mitigation and adaptive measures are considered essential to improve WDS performance in the long-term planning horizon. In this thesis, different formulations of a WDS design methodologies aimed at mitigating or adapting the systems to the effects of future changes such as those of climate change and urbanization are explored. Cost effective WDS designs that mitigate climate change by reducing GHG emissions have been investigated. Also, water demand management (DM) intervention measures, i.e., domestic rainwater harvesting (RWH) systems and water saving appliance schemes (WSASs) have been incorporated in the design of WDSs in an attempt to mitigate, adapt to or counteract the likely effects of future climate change and urbanization. Furthermore, flexibility has been introduced in the long-term WDS design under future uncertainty. The flexible methodology is adaptable to uncertain WDS parameters (i.e., future water demand in this thesis) thereby improving the WDS economic cost and hydraulic performance (resilience). The methodology is also complimented by strategically incorporating DM measures to further enhance the WDS performance under water demand uncertainty. The new methodologies presented in this thesis were successfully tested on case studies. Finally, conclusions and recommendations for possible further research work are made. There are potential benefits (e.g., cost savings, additional resilience, and lower GHG emissions) of incorporating an environmental objective and DM interventions in WDS design. Flexibility and DM interventions add value in the design of WDSs under uncertainty.

Near real-time detection and approximate location of pipe bursts and other events in water distribution systems

Romano, Michele January 2012 (has links)
The research work presented in this thesis describes the development and testing of a new data analysis methodology for the automated near real-time detection and approximate location of pipe bursts and other events which induce similar abnormal pressure/flow variations (e.g., unauthorised consumptions, equipment failures, etc.) in Water Distribution Systems (WDSs). This methodology makes synergistic use of several self-learning Artificial Intelligence (AI) and statistical/geostatistical techniques for the analysis of the stream of data (i.e., signals) collected and communicated on-line by the hydraulic sensors deployed in a WDS. These techniques include: (i) wavelets for the de-noising of the recorded pressure/flow signals, (ii) Artificial Neural Networks (ANNs) for the short-term forecasting of future pressure/flow signal values, (iii) Evolutionary Algorithms (EAs) for the selection of optimal ANN input structure and parameters sets, (iv) Statistical Process Control (SPC) techniques for the short and long term analysis of the burst/other event-induced pressure/flow variations, (v) Bayesian Inference Systems (BISs) for inferring the probability of a burst/other event occurrence and raising the detection alarms, and (vi) geostatistical techniques for determining the approximate location of a detected burst/other event. The results of applying the new methodology to the pressure/flow data from several District Metered Areas (DMAs) in the United Kingdom (UK) with real-life bursts/other events and simulated (i.e., engineered) burst events are also reported in this thesis. The results obtained illustrate that the developed methodology allowed detecting the aforementioned events in a fast and reliable manner and also successfully determining their approximate location within a DMA. The results obtained additionally show the potential of the methodology presented here to yield substantial improvements to the state-of-the-art in near real-time WDS incident management by enabling the water companies to save water, energy, money, achieve higher levels of operational efficiency and improve their customer service. The new data analysis methodology developed and tested as part of the research work presented in this thesis has been patented (International Application Number: PCT/GB2010/000961).

A distributed computing architecture to enable advances in field operations and management of distributed infrastructure

Khan, Kashif January 2012 (has links)
Distributed infrastructures (e.g., water networks and electric Grids) are difficult to manage due to their scale, lack of accessibility, complexity, ageing and uncertainties in knowledge of their structure. In addition they are subject to loads that can be highly variable and unpredictable and to accidental events such as component failure, leakage and malicious tampering. To support in-field operations and central management of these infrastructures, the availability of consistent and up-to-date knowledge about the current state of the network and how it would respond to planned interventions is argued to be highly desirable. However, at present, large-scale infrastructures are “data rich but knowledge poor”. Data, algorithms and tools for network analysis are improving but there is a need to integrate them to support more directly engineering operations. Current ICT solutions are mainly based on specialized, monolithic and heavyweight software packages that restrict the dissemination of dynamic information and its appropriate and timely presentation particularly to field engineers who operate in a resource constrained and less reliable environments. This thesis proposes a solution to these problems by recognizing that current monolithic ICT solutions for infrastructure management seek to meet the requirements of different human roles and operating environments (defined in this work as field and central sides). It proposes an architectural approach to providing dynamic, predictive, user-centric, device and platform independent access to consistent and up-to-date knowledge. This architecture integrates the components required to implement the functionalities of data gathering, data storage, simulation modelling, and information visualization and analysis. These components are tightly coupled in current implementations of software for analysing the behaviour of networks. The architectural approach, by contrast, requires they be kept as separate as possible and interact only when required using common and standard protocols. The thesis particularly concentrates on engineering practices in clean water distribution networks but the methods are applicable to other structural networks, for example, the electricity Grid. A prototype implementation is provided that establishes a dynamic hydraulic simulation model and enables the model to be queried via remote access in a device and platform independent manner.This thesis provides an extensive evaluation comparing the architecture driven approach with current approaches, to substantiate the above claims. This evaluation is conducted by the use of benchmarks that are currently published and accepted in the water engineering community. To facilitate this evaluation, a working prototype of the whole architecture has been developed and is made available under an open source licence.

Studie propojení skupinových vodovodů Lanškroun a Letohrad / Study of Interconnection of Lanškroun and Letohrad Water Distribution Systems

Kubešová, Kateřina January 2020 (has links)
This diploma thesis describes study of interconnection of Letohrad and Lanškroun water distribution systems. The thesis contains an overview of legislative regulations and technical standards related to the construction, design and directional solution of water supply systems. Following that, there is the description of the current state of the affected water mains. Next part is the design of interconnection including hydraulic analysis in using Epanet 2.0 software. The study contains several variants of the solution. The economic assessment is included.

Desarrollo e implementación de algoritmos para la optimización energética en tiempo real de redes hidráulicas a presión

Alonso Campos, Joan Carles 20 January 2022 (has links)
[ES] El objetivo general de la presente Tesis es investigar metodologías que permitan obtener en tiempo real los parámetros de operación de redes hidráulicas a presión que minimicen el consumo y/o el coste energético, garantizando el cumplimiento de las condiciones de funcionamiento necesarias para una adecuada calidad del servicio. Al tratarse del ámbito de la operación diaria de la red, una de las condiciones indispensables que deben reunir los métodos de optimización es una respuesta lo suficientemente rápida como para que no solo se pueda disponer de las soluciones más convenientes en el momento de ejecutar las consignas de operación, sino que además se habilite un procedimiento flexible que permita dar respuesta a posibles cambios en las predicciones o eventos que puedan producirse. Se ha abordado de manera aislada la optimización energética de los subsistemas de transporte de agua y la de los subsistemas de distribución debido a las distintas características que se pueden observar en ellos. En la parte relativa a los subsistemas de distribución, particularizada al caso de un sistema de riego con bombeo directo a red, se han explorado los métodos metaheurísticos de optimización, realizando varias aportaciones originales orientadas a la mejora en la eficiencia computacional de los mismos, debido a la necesidad de obtener una respuesta rápida compatible con la toma de decisiones en tiempo real. En cuanto a los subsistemas de transporte, se ha explorado la aplicabilidad del método determinista de optimización por programación lineal, a la vista de las importantes ventajas que presenta respecto al resto de métodos generales de optimización. Asimismo, en el contexto de los subsistemas de transporte, se ha trabajado en la definición de una heurística basada en el cálculo del coste energético y/o económico del agua entregada en los puntos de consumo y almacenada en los depósitos intermedios, que ha permitido formular un algoritmo voraz para la optimización energética en cada instante de tiempo. Este método ha conseguido igualar el desempeño alcanzado mediante la programación lineal y se espera que ofrezca unas mejores capacidades en sistemas con un comportamiento marcadamente no lineal, así como también una mejor adaptación a problemas de optimización con la participación de energías renovables. / [CA] L'objectiu general de la present Tesi és la investigació de metodologies que permeten obtindre en temps real els paràmetres d'operació de xarxes hidràuliques a pressió que minimitzen el consum i/o el cost energètic, garantint el compliment de les condicions de funcionament necessàries per a una adequada qualitat del servei. En tractar-se de l'àmbit de l'operació diària de la xarxa, una de les condicions indispensables que han de reunir els mètodes d'optimització és una resposta prou ràpida com perquè no sols es puga disposar de les solucions més convenients en el moment d'executar les consignes d'operació, sinó que a més s'habilite un procediment flexible que permeta donar resposta a possibles canvis en les prediccions o esdeveniments que puguen produir-se. S'ha abordat de manera aïllada l'optimització energètica dels subsistemes de transport d'aigua i la dels subsistemes de distribució (reg per injecció directa) a causa de les diferents característiques que es poden observar en ells. En el treball amb els subsistemes de distribució s'han explorat les possibilitats que ofereixen els mètodes meta-heurístics d'optimització, realitzant diverses aportacions originals orientades a la millora en l'eficiència computacional dels mateixos a causa de la necessitat d'obtindre una resposta més ràpida que siga compatible amb la presa de decisions en temps real. Quant als subsistemes de transport, s'ha explorat l'aplicabilitat del mètode determinista d'optimització per programació lineal a la vista dels importants avantatges que presenta respecte a la resta de mètodes generals d'optimització. Així mateix, en el context dels subsistemes de transport, s'ha treballat en la definició d'una bona heurística basada en el càlcul del cost energètic i/o econòmic de l'aigua entregada en els punts de consum i en els dipòsits intermedis, que ha permés formular un mètode voraç per a l'optimització energètica en cada instant de temps. Aquest mètode ha aconseguit igualar l'acompliment aconseguit mitjançant la programació lineal i s'espera que oferisca unes millors capacitats en sistemes amb un comportament més marcadament no lineal, així com també una millor adaptació a problemes d'optimització amb participació d'energies renovables. / [EN] The general objective of this Thesis is the research of methodologies to obtain in real time the operating parameters of pressurized hydraulic networks that minimize energy consumption and/or cost, ensuring compliance with the operating conditions necessary for an appropriate quality of service. Since this is the field of daily network operation, one of the indispensable conditions that optimization methods must meet is a response fast enough so that not only the most convenient solutions are available at the time of executing the operating instructions, but also a flexible procedure is provided to allow a response to possible changes in the predictions or events that may occur. The energy optimization of the water transport subsystems and that of the distribution subsystems (direct injection irrigation) have been approached separately due to the different characteristics that can be observed in them. In the work with distribution subsystems, the possibilities offered by metaheuristic optimization methods have been explored, making several original contributions aimed at improving their computational efficiency due to the need to obtain a faster response that is compatible with real-time decision making. Regarding transport subsystems, the applicability of the deterministic method of optimization by linear programming has been explored in view of the important advantages it presents with respect to the rest of the general optimization methods. Also, in the context of transport subsystems, there has been a work on the definition of a good heuristic based on the calculation of the energy and/or economic cost of the water delivered at the consumption points and intermediate reservoirs, which has allowed to formulate a greedy method for energy optimization at each time instant. This method has been able to match the performance achieved by linear programming and is expected to offer better capabilities in systems with a more marked non-linear behaviour, as well as a better adaptation to optimization problems involving renewable energies. / Alonso Campos, JC. (2021). Desarrollo e implementación de algoritmos para la optimización energética en tiempo real de redes hidráulicas a presión [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/180389 / TESIS

Využití modelů neuronových sítí pro hodnocení kvality vody ve vodovodních sítích / Using Artificial Neural Network Models to Assess Water Quality in Water Distribution Networks

Cuesta Cordoba, Gustavo Andres January 2013 (has links)
A water distribution system (WDS) is based in a network of interconnected hydraulic components to transport the water directly to the customers. Water must be treated in a Water Treatment Plant (WTP) to provide safe drinking water to consumers, free from pathogenic and other undesirable organisms. The disinfection is an important aspect in achieving safe drinking water and preventing the spread of waterborne diseases. Chlorine is the most commonly used disinfectant in conventional water treatment processes because of its low cost, its capacity to deactivate bacteria, and because it ensures residual concentrations in WDS to prevent microbiological contamination. Chlorine residual concentration is affected by a phenomenon known as chlorine decay, which means that chlorine reacts with other components along the system and its concentration decrease. Chlorine is measured at the output of the WTP and also in several considered points within the WDS to control the water quality in the system. Simulation and modeling methods help to predict in an effective way the chlorine concentration in the WDS. The purpose of the thesis is to assess chlorine concentration in some strategic points within the WDS by using the historical measured data of some water quality parameters that influence chlorine decay. Recent investigations of the water quality have shown the need of the use of non-linear modeling for chlorine decay prediction. Chlorine decay in a pipeline is a complex phenomenon so it requires techniques that can provide reliable and efficient representation of the complexity of this behavior. Statistical models based on Artificial Neural Networks (ANN) have been found appropriated for the investigation and solution of problems related with non-linearity in the chlorine decay prediction offering advantages over more conventional modeling techniques. In this sense, this thesis uses a specific neural network application to solve the problem of forecasting the residual chlorine

Water Supply Infrastructure Modeling and Control under Extreme Drought and/or Limited Power Availability

January 2019 (has links)
abstract: The phrase water-energy nexus is commonly used to describe the inherent and critical interdependencies between the electric power system and the water supply systems (WSS). The key interdependencies between the two systems are the power plant’s requirement of water for the cooling cycle and the water system’s need of electricity for pumping for water supply. While previous work has considered the dependency of WSS on the electrical power, this work incorporates into an optimization-simulation framework, consideration of the impact of short and long-term limited availability of water and/or electrical energy. This research focuses on the water supply system (WSS) facet of the multi-faceted optimization and control mechanism developed for an integrated water – energy nexus system under U.S. National Science Foundation (NSF) project 029013-0010 CRISP Type 2 – Resilient cyber-enabled electric energy and water infrastructures modeling and control under extreme mega drought scenarios. A water supply system (WSS) conveys water from sources (such as lakes, rivers, dams etc.) to the treatment plants and then to users via the water distribution systems (WDS) and/or water supply canal systems (WSCS). Optimization-simulation methodologies are developed for the real-time operation of water supply systems (WSS) under critical conditions of limited electrical energy and/or water availability due to emergencies such as extreme drought conditions, electric grid failure, and other severe conditions including natural and manmade disasters. The coupling between WSS and the power system was done through alternatively exchanging data between the power system and WSS simulations via a program control overlay developed in python. A new methodology for WDS infrastructural-operational resilience (IOR) computation was developed as a part of this research to assess the real-time performance of the WDS under emergency conditions. The methodology combines operational resilience and component level infrastructural robustness to provide a comprehensive performance assessment tool. The optimization-simulation and resilience computation methodologies developed were tested for both hypothetical and real example WDS and WSCS, with results depicting improved resilience for operations of the WSS under normal and emergency conditions. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019

Studies On Application Of Control Systems For Urban Water Networks

Kumar, M Prasanna 05 1900 (has links)
Management and supply of water in an urban water distribution system is a complex process, which include various complexities like pressure variations across the network depending on topography, demand variations depending on customers’ requirement and unaccounted water etc. Applying automatic control methods to water distribution systems is a way to improve the management of water distribution. There have been some attempts in recent years to develop optimal control algorithms to assist in the operation of complex water distribution systems. The difficulties involved by these hydraulic systems such as non-linearity, and diurnal demand patterns make the choice of a suitable automatic control method a challenge. For this purpose, this study intends to investigate the applicability of different controllers which would be able to meet the targets as quickly as possible and without creating undue transients. As a first step towards application of different controllers, PD and PID linear controllers have been designed for pump control and valve control in water distribution systems. Then a Dynamic Inversion based nonlinear controller has been designed by considering the non-linearities in the system. Here, different cases considering the effects of initial conditions used, linearization methods used, time step used for integration and selection of gains etc., have been studied before arriving at best controller. These controllers have been designed for both the flow control problems and level control problems. It is found that Dynamic Inversion-based nonlinear controller outperforms other controllers. It is well known that the performance of controllers is much dependent on the tuning of the gains (parameters). Thus in this study various alternative techniques such as Ziegler--Nichols rules (ZNPID), Genetic algorithms (GAPID) and fuzzy algorithms (FZPID) have been studied and a comparative study has been made Although with all the three gain tuning methods, required states have reached their target values, but the responses vary much in reaching to final targets. The self-tuned FZPID controller outperforms other two controllers, especially with regard to overshoots and the time taken to tune the gains for each problem. Further, an optimal DI controller is developed for the over determined case with more controls and less targets. Energy loss is considered as an objective function and normal DI controller equations are considered as constraints. Hence, an attempt is made to reduce the energy minimization in water distribution system by formulating an optimal control problem using optimal Dynamic Inversion concept. Finally, leakage reduction model is developed based on excessive pressure minimization problem by locating valves optimally as well as by setting valves optimally. For this purpose, optimization problem is solved using Pattern search algorithms and hydraulic analysis is carried out using EPANET program.

Pump schedule optimisation techniques for water distribution systems

Bene, J. G. (József Gergely) 18 November 2013 (has links)
Abstract This thesis deals with the pump schedule optimisation of regional water distribution systems. The aims and the possible applications of the presented methods differ from each other; all of them are intended to solve a particular but realistic problem. The developed techniques use the capacity of the water reservoirs in order to find the optimal pump-schedule of the system. The optimisation task is always deterministic and discrete in time; the stochastic behaviour of the water consumptions is approximated by expected values. A so-called neutral genetic algorithm equipped with new constraint handling is presented first. The method is able to solve the scheduling problems of real-size and complex networks, e.g. the network of Budapest with coupled hydraulic simulations where both variable and fixed speed pumps are in the network. The results are compared to other ones obtained by widely used genetic algorithms and state-of-the-art general purpose optimisation solvers. A dynamic programming based method was also carried out which provides the global optimum of the so-called ’combinatorial’ pump scheduling problems. This modelling type is very common in the industry, which can be used if the operation points of the pumps take discrete values. The basic idea of the method is exploiting the ’permutational invariance’ of the model which results in a perfect discretisation of the state space without any loss of information. An approximate dynamic programming technique is also presented which solves the same type of problems as the formerly mentioned genetic algorithm does. The technique splits the water network model into smaller units, namely into the so-called well fields and the main distribution system. The state space of the main distribution system was further decreased while the quality of the results does not decay. A part of the test examples is the same as in the case of the former presented genetic algorithm; thus, the two methods can be compared. Finally, a small water network fed by a single variable speed pump was investigated. The presented methods are based on the minimisation of the specific energy consumption. The gained results are compared to ones obtained using a high-resolution discrete dynamic program. Novel optimisation techniques for water distribution network pump scheduling were developed in this work. A particular focus was put on the dynamics between pumping, water reservoirs, and water use. The work shows the applicability of the approach via numerous realistic simulation case studies. / Tiivistelmä Työ käsittelee alueellisten vedenjakelujärjestelmien pumppauksen aikataulutuksen optimointia. Esitettyjen menetelmien tavoitteet ja mahdolliset sovellukset poikkeavat toisistaan. Kaikki on kuitenkin tarkoitettu tiettyjen todellisten ongelmien ratkaisemiseen. Kehitetyt tekniikat käyttävät vesivarastojen kapasiteettia optimaalisen pumppausohjelman löytämiseksi. Jokainen optimointitehtävä on aikadiskreetti ja deterministinen, vedenkulutuksen stokastista käyttäytymistä on approksimoitu odotusarvoilla. Ensimmäiseksi työssä esitetään ns. neutraaleja geneettisiä algoritmeja varustettuna rajoitusten käsittelyllä. Menetelmällä voidaan ratkaista skedulointiohjelmia reaalimittakaavaisille ja monimutkaisille verkostoille (esim. Budapestin verkosto varustettuna hydraulisilla simuloinneilla, sekä muuttuvanopeuksisilla että vakionopeuksisilla verkoston pumpuilla). Tuloksia verrataan toisiin yleisesti käytössä olevilla geneettisillä algoritmeilla saatuihin, sekä johtavilla yleiskäyttöisillä optimointitekniikoilla saatuihin tuloksiin. Työssä käytettiin myös dynaamiseen ohjelmointiin pohjaavaa menetelmää, jolla saadaan globaali optimi ns. "kombinatoorisille" pumppauksen aikataulutusongelmille. Tällainen mallinnustapa on hyvin yleistä teollisuudessa. Sitä voidaan käyttää, jos pumppujen toimintapisteet saavat diskreettejä arvoja. Menetelmän perusajatuksena on "permutationaalisen invarianssin" hyväksikäyttäminen, josta seuraa tila-avaruuden virheetön diskretointi ilman informaation häviämistä. Työssä esitellään myös approksimoidun dynaamisen ohjelmoinnin tekniikka, jonka avulla voidaan ratkaista samantyyppisiä ongelmia kuin yllämainituilla geneettisillä algoritmeilla. Tämä tekniikka jakaa vesijohtoverkoston mallin pienempiin yksiköihin: lähdekenttiin ja pääjakeluverkostoon. Pääjakeluverkoston tila-avaruutta voitiin edelleen pienentää ilman, että tulosten laatu heikkeni. Osa käsitellyistä esimerkkitapauksista on samoja kuin edellämainittujen geneettisten algoritmien osalla, joten tuloksia voidaan verrata. Lopuksi tutkittiin pienen muuttuvanopeuksisella pumpulla syötetyn vesijohtoverkoston toimintaa. Esitetyt menetelmät perustuvat ominaisenergiankulutuksen minimointiin. Saatuja tuloksia verrataan korkearesoluutioisella diskreetillä dynaamisella ohjelmoinnilla saatuihin tuloksiin. Työssä kehitettiin uusia optimointitekniikoita vedenjakelujärjestelmien pumppauksen aikataulutuksen optimintiin. Erityisesti työssä keskityttiin pumppauksen, vesitornien ja kuluttajien käyttäytymisen väliseen dynamiikkaan. Työssä osoitettiin tekniikoiden toimivuus realististen esimerkkisimulointien avulla. / Kivonat Jelen doktori disszertáció regionális ivóvízellátó-hálózatok üzemvitel-optimalizációjával foglalkozik. A bemutatott módszerek alkalmazhatósági köre rendszerint eltér egymástól, mindegyik egy-egy speciális, de a való életben is előforduló problémára kíván megoldást nyújtani. A kidolgozott módszerek a medencék tárolókapacitását kihasználva, az optimális szivattyú-menetrendet keresve kívánják megtalálni az adott vízműhálózat üzemviteloptimumát. Az optimalizáció egy időben diszkrét, ugyanakkor determinisztikus feladat megoldását igényli, a vízfogyasztások sztochasztikus viselkedését a várható értékekkel közelítettem. Elsőként egy új mellékfeltétel-kezeléssel ellátott, ún. neutrális genetikus algoritmus bemutatása a cél. A kidolgozott módszer alkalmas nagy, valós méretű (pl. Budapest) és bonyolultságú (kapcsolt hidraulikai szimulációk, frekvenciaváltós és direkt szivattyúk a hálózatban) ivóvízhálózatok napi üzemvitel optimalizálására. Az eredményeket más genetikus algoritmusokkal és a világ élvonalába tartozó, de általános célú optimalizációs módszerekkel hasonlítottam össze. Kidolgozásra került egy dinamikus programozás alapú, a valós, globális optimumot adó módszer is. Az algoritmus a gyakorlatban elterjedt, ún. "kombinációs" hálózatként modellezhető vízműhálózat típusokra alkalmazható, ahol a szivattyúk munkapontjai diszkrét értékek. A megoldás alapját az ún. "permutációs invariancia" jelensége adja, mely lehetővé teszi az állapottér információveszteség nélküli, tökéletes diszkretizációját. Egy, a korábban bemutatott genetikus algoritmuséhoz hasonló problémakört megoldó, de közelítő dinamikus programozás alapú módszer is bemutatásra kerül. Az algoritmus a hálózat kisebb részegységekre (víztermelő területekre és fő elosztó hálózatra) való felbontásával és a fő elosztó hálózat állapotterének önkényes, de a megoldás jóságán jelentősen nem rontó csökkentésével éri el a program futtatásához szükséges számítási igény csökkentését. A tesztfeladatok egy része megegyezik a genetikus algoritmus tesztfeladataival, így azok közvetlenül összehasonlíthatóak. Végül bemutatásra kerül egy kisméretű, mindössze egy darab változtatható fordulat- számú szivattyúval táplált rendszer energetikai vizsgálata. Az itt bemutatott módszerek mind a fajlagos energiafelhasználás minimalizálásán alapulnak. Az eredményeket egy nagyfelbontású dinamikus programozás alapú módszerhez hasonlítottam.

Energy Optimization Strategy for System-Operational Problems

Al-Ani, Dhafar S. 04 1900 (has links)
<ul> <li>Energy Optimization Stategies</li> <li>Hydraulic Models for Water Distribution Systems</li> <li>Heuristic Multi-objective Optimization Algorithms</li> <li>Multi-objective Optimization Problems</li> <li>System Constraints</li> <li>Encoding Techniques</li> <li>Optimal Pumping Operations</li> <li>Sovling Real-World Optimization Problems </li> </ul> / <p>The water supply industry is a very important element of a modern economy; it represents a key element of urban infrastructure and is an integral part of our modern civilization. Billions of dollars per annum are spent internationally in pumping operations in rural water distribution systems to treat and reliably transport water from source to consumers.</p> <p>In this dissertation, a new multi-objective optimization approach referred to as energy optimization strategy is proposed for minimizing electrical energy consumption for pumping, the cost, pumps maintenance cost, and the cost of maximum power peak, while optimizing water quality and operational reliability in rural water distribution systems. Minimizing the energy cost problem considers the electrical energy consumed for regular operation and the cost of maximum power peak. Optimizing operational reliability is based on the ability of the network to provide service in case of abnormal events (e.g., network failure or fire) by considering and managing reservoir levels. Minimizing pumping costs also involves consideration of network and pump maintenance cost that is imputed by the number of pump switches. Water quality optimization is achieved through the consideration of chlorine residual during water transportation.</p> <p>An Adaptive Parallel Clustering-based Multi-objective Particle Swarm Optimization (APC-MOPSO) algorithm that combines the existing and new concept of Pareto-front, operating-mode specification, selecting-best-efficiency-point technique, searching-for-gaps method, and modified K-Means clustering has been proposed. APC-MOPSO is employed to optimize the above-mentioned set of multiple objectives in operating rural water distribution systems.</p> <p>Saskatoon West is, a rural water distribution system, owned and operated by Sask-Water (i.e., is a statutory Crown Corporation providing water, wastewater and related services to municipal, industrial, government, and domestic customers in the province of Saskatchewan). It is used to provide water to the city of Saskatoon and surrounding communities. The system has six main components: (1) the pumping stations, namely Queen Elizabeth and Aurora; (2) The raw water pipeline from QE to Agrium area; (3) the treatment plant located within the Village of Vanscoy; (4) the raw water pipeline serving four major consumers, including PCS Cogen, PCS Cory, Corman Park, and Agrium; (5) the treated water pipeline serving a domestic community of Village of Vanscoy; and (6) the large Agrium community storage reservoir.</p> <p>In this dissertation, the Saskatoon West WDS is chosen to implement the proposed energy optimization strategy. Given the data supplied by Sask-Warer, the scope of this application has resulted in savings of approximately 7 to 14% in energy costs without adversely affecting the infrastructure of the system as well as maintaining the same level of service provided to the Sask-Water’s clients.</p> <p>The implementation of the energy optimization strategy on the Saskatoon West WDS over 168 hour (i.e., one-week optimization period of time) resulted in savings of approximately 10% in electrical energy cost and 4% in the cost of maximum power peak. Moreover, the results showed that the pumping reliability is improved by 3.5% (i.e., improving its efficiency, head pressure, and flow rate). A case study is used to demonstrate the effectiveness of the multi-objective formulations and the solution methodologies, including the formulation of the system-operational optimization problem as five objective functions. Beside the reduction in the energy costs, water quality, network reliability, and pumping characterization are all concurrently enhanced as shown in the collected results. The benefits of using the proposed energy optimization strategy as replacement for many existing optimization methods are also demonstrated.</p> / Doctor of Science (PhD)

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