In recent years, water utilities have placed a greater emphasis on the reliability and resilience of their water distribution networks. This focus has increased due to the continuing aging of such infrastructure and the potential threat of natural or man-made disruptions. As a result, water utilities continue to look for ways to evaluate the resiliency of their systems with a goal of identifying critical elements that need to be reinforced or replaced. The simulation of pipe breaks in water reliability studies is traditionally modeled as the loss of a single pipe element. This assumes that each pipe has an isolation valve on both ends of the pipe that can be readily located and operated under emergency conditions. This is seldom the case. The proposed methodology takes into account that multiple pipes may be impacted during a single failure as a result of the necessity to close multiple isolation valves in order to isolate the “segment” of pipes necessary to contain the leak. This document presents a simple graphical metric for use in evaluating the performance of a system in response to a pipe failure. The metrics are applied to three different water distribution systems in an attempt to illustrate the fact that different pipe segments may impact system performance in different ways. This information is critical for use by system managers in deciding which segments to prioritize for upgrades or replacement.

This thesis investigates methodologies for valuing the flexibility of demand-side response (DSR) in its ability to respond to future uncertainties. The ability to quantify this flexibility is especially important for energy systems investments given their large and irreversible capital costs. The consideration of uncertainty in electricity markets and energy networks requires solutions that allow decision makers to quickly respond to unexpected events, such as extreme short-term electricity price variations in an operational setting, or incorrect long-term demand projections in planning. This uncertainty, coupled with the irreversibility of energy network investments, results in the need for viable 'wait-and-see' investment strategies that can help hedge electicity price risk in the short-term while hedging planning risk in the long-term, until at least some, if not all, uncertainty is resolved. In both cases, this leads to an added value in the case of temporary flexible investment options like DSR, which may otherwise be considered unattractive under a deterministic analysis setting. A number of significant contributions to power systems research are offered in this work, focusing on valuation methods for quantifying the flexibility value of DSR under both short-term and long-term uncertainty. The first outcome of this research is an extensive review of current real options (RO) methods that clarifies the assumptions and utilization of RO for decision-making in engineering applications. It suggests that many of the assumptions used contribute to a misuse of the models when applied to physical systems. A framework for investing under uncertainty is proposed, where the methodologies, steps, inputs, assumptions, limitations and advantages of different RO models are described so as to offer a practical guide to decision makers for selecting the most appropriate RO model for their valuation purposes. The second outcome is the design of a probabilistic RO framework and operational model for DSR that quantifies its benefits as an energy service for hedging different market price risks. A mathematical formulation for applying “real options thinking” is presented that provides decision makers with a means of quantifying the value of DSR when both operational and planning decisions are subject to uncertainty. In particular, DSR contracts can have tremendous value as an arbitrage or portfolio-balancing tool, helping hedge almost entirely electricity price risk in day-ahead and real-time markets, especially when prices are highly volatile. This value is quantified using a novel RO framework that frees the decision maker from the assumptions needed in financial option models. A new load forecasting and price simulation model is also developed to forecast load profiles and simulate new price series with different average values, higher volatilities and extreme price spikes to represent potential future market scenarios and to determine under which conditions DSR has the most value. The valuation of a DSR investment is then presented to show how the physical characteristics of a system, in this case the physical load recovery effect of loads after a DSR activation, can tremendously affect the profitability of an investment when uncertainty is taken into account. The third outcome of this work is the development of a complete, general and practical tool for making long-term multi-staged investment decisions in future power networks under multiple uncertainties. It is argued throughout this work that many of the current methods are either unsuitable for long-term investment valuation or are too complex for practical application and implementation at the industry level. A strategic spreadsheet-based tool for making long-term investment decisions under uncertainty is therefore created and tested in collaboration with industry for solving real network planning problems.

La distribution reste le segment du secteur de l’électricité le moins étudié. Mais les débats s’animent autour d’elle depuis deux ou trois ans quant aux changements structurels possibles du fait notamment de l’émergence amorcée ou annoncée des smart technologies: ils pourraient en effet remettre en cause dans les prochaines années les modèles d’affaires actuels des GRD et leur mode de régulation. Mais de nombreuses incertitudes pèsent sur leurs choix d’investissements. La thèse vise à anticiper les évolutions des modèles d’affaires des GRD en Europe à l’horizon 2030 en tenant compte des paramètres technologiques, macroéconomiques et géographiques. Elle propose une vision théorique et analytique originale, en introduisant tout d’abord la notion de « technologies à potentiel naturel » pour étudier le développement optimal de différentes technologies par contexte géographique et par scénario de référence. A partir de ces résultats, elle définit alors différentes évolutions possibles des activités de la distribution. Le croisement de ces futurs avec les différentes stratégies d’investissement envisageables pour les GRD permet de définir les futurs modèles d’affaires des GRD européens en fonction des combinaisons de smart technologies déployées et des contextes géographiques contrastés. Dans sa dernière partie, la thèse s’intéresse tout particulièrement aux changements prévisibles dans la relation GRD / régulateur sectoriel via une formalisation par la théorie des jeux. Enfin, en s’appuyant notamment sur les études théoriques de Brian Arthur, la thèse identifie les différents effets lock-in qui pourraient entraver l’émergence des smart technologies et les solutions possibles / Distribution activities have been the least studied domain of the electricity sector; over the last few years though, strong debates emerged with regards to the future. Indeed, this activity might soon undergo some deep structural changes, particularly as smart technologies are deployed: theses technologies could strongly impact the current business cases of the DSOs, along with the regulation now in effect, at a time when numerous uncertainties weigh on the distributors choices of investments. This thesis investigates the distributors’ business models evolutions in Europe for the next 20 years, based on technological, macroeconomic and geographical parameters. It proposes an original approach, both theoretical and analytical, to better understand the future world of DSOs. At first, it introduces the notion of “technologies with natural potential” in order to study the optimal development of the different technologies, by geographical context and macroeconomic scenarios. From these results, it then defines various possible evolutions of the distribution activities. Crossing these futures with the various possible investment strategies for the DSOs makes it possible to define the future business models of the European DSOs, according to various combinations of smart technologies displayed and contrasted geographical contexts. In its last part, the thesis studies the predictable changes in the relation DSO / regulator, using a formalization based on the Games Theory; this work is complemented by identifying the different lock-in effects (using the approach described in Brian Arthur’s studies) that could hinder the emergence of smart technologies, and the possible solutions

<p>U disertaciji je predložen algoritam za proračun kratkih spojeva zasnovan na korelisanim intervalima. U savremenim distributivnim mrežama postoje različiti tipovi generatora koji proizvode električnu energiju iz energije obnovljivih izvora. Za takve generatore, kao i za potrošače, karakteristično je to što je njihova proizvodnja i potrošnja neizvesna. Predloženi algoritam u disertaciji uvažava te neizvesnosti, kao i korelacije između navedenih elemenata. Neizvesnosti su modelovane intervalima i direktno su uvažene u predloženom algoritmu za proračun kratkih spojeva. Algoritam je prvenstveno razvijen za proračun kratkih spojeva savremenih distributivnih mreža sa velikim brojem distribuiranih generatora i potrošača. NJime je moguće proračunavati režime sa kratkim spojevima distributivnih mreža velikih dimenzija, što je numerički verifikovano u disertaciji. Predloženim algoritmom se dobija režim distributivne mreže sa kratkim spojem koji je realističniji od režima dobijenih algoritmima sa determinističkim pristupom. Proračuni kao što su: koordinacija, podešenje i provera osetljivosti relejne zaštite, provera kapaciteta prekidača i osigurača, lokacija kvara itd. mogu na osnovu realističnijeg režima, dobijenog predloženim algoritmom, da daju kvalitetnije rezultate, što je numerički potvrđeno na primeru koordinacije prekostrujne zaštite</p> / <p>In this dissertation an algorithm for correlated intervals-based short-circuit calculation is<br />proposed. In modern distribution networks there are various types of generators that produce<br />electric energy from renewable energy resources. For these generators, as well as loads, uncertain<br />production and consumption is characteristic. The proposed algorithm in the dissertation deals<br />with above-mentioned uncertainties, as well as correlations among them. The uncertainties are<br />modeled with intervals and directly taken into account in the proposed algorithm for short-circuit<br />calculation. The algorithm is primarily developed for short-circuit calculation in modern<br />distribution networks with a great number of distributed generators and consumers. The proposed<br />algorithm enables calculation of short circuits states of large-scale distribution networks, which is<br />numerically verified in the dissertation. The proposed algorithm provides short circuit state of<br />distribution network which is more realistic than the one obtained with algorithms with<br />deterministic approach. Calculations such as: coordination, settings and sensitivity check of relay<br />protection, breaker and fuse capacity check, fault location, etc. can give better results, on the basis<br />of the more realistic state obtained by the proposed algorithm for short circuit calculation, which<br />is numerically confirmed by the example of coordination of overcurrent protection.</p>

Afin de maintenir une bonne qualité de l’électricité, les gestionnaires de réseaux doivent maintenir les niveaux de tension harmonique en-dessous de certaines limites spécifiées dans les normes. Les niveaux de tension harmonique résultent des équipements non-linéaires présents dans les installations, qui injectent des courants harmoniques sur le réseau.Dans ce but, une solution consiste à appliquer des limites d’émission à ces installations. Les gestionnaires de réseaux ont besoin pour cela d’un indicateur fiable pour évaluer le niveau d’émission harmonique d’une installation.Dans ce cadre, nous nous sommes tout d’abord intéressés aux différentes méthodes existantes, que nous avons appliqué sur des cas de réseaux simplifiés afin de les évaluer sur plusieurs critères. Nous avons ainsi identifié dans un premier temps les définitions qui répondent le mieux à notre besoin ainsi que leurs limites restectives. Dans un deuxième temps, nous avons amélioré une des définitions retenues en proposant une nouvelle solution : la définition “quatre quadrants”.Cette nouvelle définition permet d’évaluer le courant harmonique émis par une installation sur le réseau en se basant sur les mesures de la tension et du courant au point de livraison de l’installation. Son principal intérêt par rapport aux méthodes existantes est de mieux identifier les installations moyennement perturbatrices sur le réseau. Ce point a été validé en simulation sur un réseau dérivé du benchmark CIGRE. / In order to maintain good power quality, Distribution Systems Operators (DSOs) must keep harmonic voltage levels under limits specified in standards. These harmonic voltages result from non-linear equipment connected in installations, which inject harmonic currents into networks.A possible solution to solve this problem consists to implement emission limits per installation. In order to apply these limits, DSOs need to have an accurate and reliable indicator to assess the harmonic emission of an installation.In this context, we studied different methods from the literature. We implemented each of them on several simplified distribution networks in order to evaluate them on several criteria. First, we identified the most interesting definitions from the literature, and emphasized their respective theorical limits. Then, we improved one of these definitions by proposing a new solution: the “four-quadrants” definition.This new definition is able to assess the harmonic current injected by an installation into the network by using current and voltage measurements at the point of common coupling of this installation. Its main advantage in comparison to other methods is a better detection of “medium” disturbing installations over the network. This advantage has been confirmed by implementing the proposed solution in simulation on a distribution network derived from the CIGRE benchmark.

Distribution load flow and state estimation are two important functions in distribution energy management systems (DEMS) and advanced distribution automation (ADA) systems. Distribution load flow analysis is a tool which helps to analyze the status of a power distribution system under steady-state operating conditions. In this research, an effective and comprehensive load flow algorithm is developed to extensively incorporate the distribution system components. Distribution system state estimation is a mathematical procedure which aims to estimate the operating states of a power distribution system by utilizing the information collected from available measurement devices in real-time. An efficient and computationally effective state estimation algorithm adapting the weighted-least-squares (WLS) method has been developed in this research. Both the developed algorithms are tested on different I testeeders and the results obtained are justified.

In electric power distribution systems, the major determinant in electricity supply strategy is the quantity of demand. Customers need to be accurately represented using updated nodal load information as a requirement for efficient control and operation of the distribution network. In Distribution Load Estimation (DLE), two major categories of data are utilized: historical data and direct real-time measured data. In this thesis, a comprehensive survey on the state-of-the-art methods for estimating loads in distribution networks is presented. Then, a novel method for representing historical data in the form of Representative Load Curves (RLCs) for use in realtime DLE is also described. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) is used in this regard to determine RLCs. An RLC is a curve that represents the behavior of the load during a specified time span; typically daily, weekly or monthly based on historical data. Although RLCs provide insight about the variation of load, it is not accurate enough for estimating real-time load. This therefore, should be used along with real-time measurements to estimate the load more accurately. It is notable that more accurate RLCs lead to better real-time load estimation in distribution networks. This thesis addresses the need to obtain accurate RLCs to assist in the decision-making process pertaining to Radial Distribution Networks (RDNs).This thesis proposes a method based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) architecture to estimate the RLCs for Distribution Networks. The performance of the method is demonstrated and simulated, on a test 11kV Radial Distribution Network using the MATLAB software. The Mean Absolute Percent Error (MAPE) criterion is used to justify the accuracy of the RLCs.

No / Due to high penetration of single-phase Photovoltaic (PV) cells into low voltage (LV) distribution networks, several impacts such as voltage unbalance, voltage rise, power losses, reverse power flow arise which leads to operational constraints violation in the network. In this paper, a time series Three Phase Optimal Power Flow (TPOPF) method is proposed to minimize the voltage unbalance in LV distribution networks with high penetration of residential PVs. TPOPF problem is formulated using the current injection method in which the PVs are modelled via a time-varying PV power profile with active and reactive power control. The proposed method is validated on a real LV distribution feeder. The results show that the reactive power management of the PVs helps mitigate the voltage unbalance significantly. Moreover, the voltage unbalance index reduced significantly compared to the case without voltage unbalance minimisation. / Innovate UK GCRF Energy Catalyst Pi-CREST project under Grant number 41358; British Academy GCRF COMPENSE project under Grant GCRFNGR3\1541; Mut’ah University, Jordan

Yes / The low voltage (LV) distribution network is the last stage of the power network, which is connected directly to the end user customers and supplies many dispersed small-scale loads. In order to achieve environmental targets and to address the energy shortage issue, governments worldwide increase the renewable energy sources (RES) into the electricity grid. In addition, different types of low carbon technologies (LCTs) such as electric vehicles (EVs) are becoming widely used. A significant portion of RES and LCTs is penetrated into the LV distribution network, which poses a wide range of challenges. In order to address these challenges, there is a persistent need to develop traditional planning and operation frameworks to cope with these new technologies. In this context, this paper provides a comprehensive review about planning, operation, and management of LV distribution networks. The characteristics, types, and topologies of LV distribution networks plus different aspects of operation and planning are investigated. An insightful investigation of the reasons impacts and mitigation of voltage and current unbalanced in LV networks is provided. Moreover, the main three-phase power flow techniques used to analyze the LV networks are analyzed.

Electric power distribution network is an important part of electrical power systems for delivering electricity to consumers. Electric power utilities worldwide are increasingly adopting the computer aided monitoring, control and management of electric power distribution systems to provide better services to the electrical consumers. Therefore, research and development activities worldwide are being carried out to automate the electric power distribution system. The power distribution system consists of a three-phase source supplying power through single-, two-, or three-phase distribution lines, switches, and transformers to a set of buses with a given load demand. In addition, unlike transmission systems, single-, two-, and three-phase sections exist in the network and single-, two-, and three-phase loads exist in the distribution networks. Further, most distribution systems are overhead systems, which are susceptible to faults caused by a variety of situations such as adverse weather conditions, equipment failure, traffic accidents, etc. When a fault occurs on a distribution line, it is very important for the utility to identify the fault location as quickly as possible for improving the service reliability. Hence, one of the crucial blocks in the operation of distribution system is that of fault detection and it’s location. The achievement of this objective depends on the success of the distribution automation system. The distribution automation system should be implemented quickly and accurately in order to isolate those affected branches from the healthy parts and to take alternative measures to restore normal power supply. Fault location in the distribution system is a difficult task due to its high complexity and difficulty caused by unique characteristics of the distribution system. These unique characteristics are discussed in the present work. In recent years, some techniques have been discussed for the location of faults, particularly in radial distribution systems. These methods use various algorithmic approaches, where the fault location is iteratively calculated by updating the fault current. Heuristic and Expert System approaches for locating fault in distribution system are also proposed which uses more measurements. Measurements are assumed to be available at the sending end of the faulty line segment, which are not true in reality as the measurements are only available at the substation and at limited nodes of the distribution networks through the use of remote terminal units. The emerging techniques of Artificial Intelligence (AI) can be a solution to this problem. Among the various AI based techniques like Expert systems, Fuzzy Set and ANN systems, the ANN approach for fault location is found to be encouraging. In this thesis, an ANN approaches with limited measurements are used to locate fault in long distribution networks with laterals. Initially the distribution system modeling (using actual a-b-c phase representation) for three-, two-, and single-phase laterals, three-, two-, and single- phase loads are described. Also an efficient three-phase load flow and short circuit analysis with loads are described which is used to simulate all types of fault conditions on distribution systems. In this work, function approximation (FA) is the main technique used and the classification techniques take a major supportive role to the FA problem. Fault location in distribution systems is explained as a FA problem, which is difficult to solve due to the various practical constraints particular to distribution systems. Incorporating classification techniques reduce this FA problem to simpler ones. The function that is approximated is the relation between the three-phase voltage and current measurements at the substation and at selected number of buses (inputs), and the line impedance of the fault points from the substation (outputs). This function is approximated by feed forward neural network (FFNN). Similarly for solving the classification problems such as fault type classification and source short circuit level classification, Radial Basis Probabilistic Neural Network (RBPNN) has been employed. The work presented in this thesis is the combinational use of FFNN and RBPNN for estimating the fault location. Levenberg Marquardt learning method, which is robust and fast, is used for training FFNN. A typical unbalanced 11-node test system, an IEEE 34 nodes test system and a practical 69- bus long distribution systems with different configurations are considered for the study. The results show that the proposed approaches of fault location gives accurate results in terms of estimated fault location. Practical situations in distribution systems such as unbalanced loading, three-, two-, and single- phase laterals, limited measurements available, all types of faults, a wide range of varying source short circuit levels, varying loading conditions, long feeders with multiple laterals and different network configurations are considered for the study. The result shows the feasibility of applying the proposed method in practical distribution system fault diagnosis.