A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems

Due to its practical importance and inherent complexity, the optimisation of distribution networks for supplying drinking water has been the subject of extensive study for the past 30 years. The optimization is governed by sizing the pipes in the water distribution network (WDN) and / or optimises specific parts of the network such as pumps, tanks etc. or try to analyse and optimise the reliability of a WDN. In this thesis, the author has analysed two different WDNs (Anytown City and Cabrera city networks), trying to solve and optimise a multi-objective optimisation problem (MOOP). The main two objectives in both cases were the minimisation of Energy Cost (€) or Energy consumption (kWh), along with the total Number of pump switches (TNps) during a day. For this purpose, a decision support system generator for Multi-objective optimisation used. Its name is GANetXL and has been developed by the Center of Water System in the University of Exeter. GANetXL, works by calling the EPANET hydraulic solver, each time a hydraulic analysis has been fulfilled. The main algorithm used, was a second-generation algorithm for multi-objective optimisation called NSGA_II that gave us the Pareto fronts of each configuration. The first experiment that has been carried out was the network of Anytown city. It is a big network with a pump station of four fixed speed parallel pumps that are boosting the water dynamics. The main intervention was to change these pumps to new Variable speed driven pumps (VSDPs), by installing inverters capable to diverse their velocity during the day. Hence, it’s been achieved great Energy and cost savings along with minimisation in the number of pump switches. The results of the research are thoroughly illustrated in chapter 7, with comments and a variety of graphs and different configurations. The second experiment was about the network of Cabrera city. The smaller WDN had a unique FS pump in the system. The problem was the same as far as the optimisation process was concerned, thus, the minimisation of the energy consumption and in parallel the minimisation of TNps. The same optimisation tool has been used (GANetXL).The main scope was to carry out several and different experiments regarding a vast variety of configurations, using different pump (but this time keeping the FS mode), different tank levels, different pipe diameters and different emitters coefficient. All these different modes came up with a large number of results that were compared in the chapter 8. Concluding, it should be said that the optimisation of WDNs is a very interested field that has a vast space of options to deal with. This includes a large number of algorithms to choose from, different techniques and configurations to be made and different support system generators. The researcher has to be ready to “roam” between these choices, till a satisfactory result will convince him/her that has reached a good optimisation point.

Contributo dell'algoritmo euristico ghest nella caratterizzazione energetica di una rete di distribuzione idrica

Un sistema di distribuzione idropotabile (Water Distribution Network -WDN), data la sua complessità strutturale e funzionale, per l' ordinario esercizio richiede elevati quantitativi di energia. L'attuale trend tecnico/scientifico incoraggia la loro gestione e progettazione nell'ottica di un generale risparmio di energia che, oltre ad un indiscusso vantaggio economico, implica sopratutto una razionalizzazione dell'impiego di risorsa idrica. Questo è il contesto scientifico/culturale in cui il presente elaborato si colloca. Nello specifico, ci si propone la caratterizzazione energetica di la rete di distribuzione idrica Cabrera_network.(rivisitazione della rete presentata da E.Cabrera e M.Pardo nel loro studio del 2010) . Si sono quindi qualificati i legami tra i consumi energetici ed aspetti, quali: dimensionamento dei condotti, perdite idriche, tipologia di pompa centrifuga sfruttata e livello idrico massimo del serbatoio di compenso. Ciò è stato esplicato in due fasi di analisi. In una primo momento, si sono impiegati strumenti classi quali il simulatore idraulico Epanet2 e i fogli di calcolo Excel. In un secondo momento, il problema dell'ottimizzazione energetica della rete è stato risolto a mezzo l'algoritmo euristico GHEST. Al di là delle specifiche conclusioni, cui si rinvia, l'elaborato consente di cogliere un più generale profilo di ordine metodologico: l'importanza di una visione d'insieme del problema energetico in un sistema di distribuzione idropotabile, dalla quale, nel caso di specie, emerge che la scelta più ragionevole, al fine dell'ottimizzazione energetica, consiste nell'individuazione del più idoneo modello di pompa alimentante la rete. Per poi, data l'onere progettuale e applicativo che comporta, provvedere al reinvestimento dei capitali risparmiati in attività volte alla riduzione delle perdite idriche. Sono questi infatti, i due aspetti che più incidono sui consumi energetici nel caso di studio.

Design and implementation of a testbed for data distribution management

Data Distribution Management (DDM) is a core part of High Level Architecture standard, as its goal is to optimize the resources used by simulation environments to exchange data. It has to filter and match the set of information generated during a simulation, so that each federate, that is a simulation entity, only receives the information it needs. It is important that this is done quickly and to the best in order to get better performances and avoiding the transmission of irrelevant data, otherwise network resources may saturate quickly. The main topic of this thesis is the implementation of a super partes DDM testbed. It evaluates the goodness of DDM approaches, of all kinds. In fact it supports both region and grid based approaches, and it may support other different methods still unknown too. It uses three factors to rank them: execution time, memory and distance from the optimal solution. A prearranged set of instances is already available, but we also allow the creation of instances with user-provided parameters. This is how this thesis is structured. We start introducing what DDM and HLA are and what do they do in details. Then in the first chapter we describe the state of the art, providing an overview of the most well known resolution approaches and the pseudocode of the most interesting ones. The third chapter describes how the testbed we implemented is structured. In the fourth chapter we expose and compare the results we got from the execution of four approaches we have implemented. The result of the work described in this thesis can be downloaded on sourceforge using the following link: https://sourceforge.net/projects/ddmtestbed/. It is licensed under the GNU General Public License version 3.0 (GPLv3).

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.