This dissertation contains a strategy to minimize the non-technical electrical energy losses in an electrical distribution network. In order to develop the strategy, a model was constructed that simulates an electrical distribution network and includes different parameters that calculate the estimated technical losses in the electricity distribution network. The model was then used as the base to develop the strategy to minimize the electrical energy losses in an electrical distribution network. Increasing energy costs and environmentalists actions to protect the natural resources, force energy supply companies to conserve and reduce energy usage. Therefore the research focused on the reduction of electrical energy losses in distribution networks. The loss occurrences are divided into two categories: technical and non-technical losses. Reducing these losses ensure that the cost of electricity to customers will be reduced and in turn improve the efficiency of the distribution network. The model developed to calculate the non-technical losses in an electrical distribution network was tested at two different networks. Firstly at the University of Pretoria, where the network segment consisted of different network busses delivering electrical energy. Secondly results were obtained in a residential network of the Tshwane Metropolitan Council. In this network there was only one bus but various different time intervals were used to determine the time interval most suitable for determining the electrical energy losses in the electrical distribution network. The model was used primarily to quantify the technical losses as a base point towards determining the non-technical losses. Using the model one is able to forecast the technical energy losses of a section in the electricity distribution network and this enabled one to develop a strategy to minimize the energy losses in the distribution network. The model will enable municipalities or electricity distribution companies to estimate electrical energy losses in their electrical supply networks and facilitate the development of strategies to reduce electrical energy losses. / Dissertation (MEng (Electrical Engineering))--University of Pretoria, 2006. / Electrical, Electronic and Computer Engineering / unrestricted

Este trabalho apresenta um estudo de proteção de sobrecorrente de redes primárias aéreas de distribuição de energia elétrica através de uma abordagem probabilística. Abordagens convencionais para o problema de proteção de sobrecorrente não levam em conta a natureza probabilística das principais variáveis envolvidas: tipo da falta, localização da falta e impedância de defeito para faltas envolvendo a terra. Neste caso, por exemplo, torna-se muito difícil avaliar as conseqüências de situações nas quais a coordenação total entre os dispositivos não pode ser alcançada por alguma razão. A abordagem probabilística permite, por outro lado, quantificar o risco de não haver coordenação entre dois dispositivos de proteção adjacentes. Esta informação é extremamente valiosa para os engenheiros de proteção na fase de projeto da rede elétrica. No trabalho, a metodologia probabilística é apresentada em detalhe e sua aplicação é ilustrada através de alguns estudos de aplicação, nos quais procurou-se avaliar a influência dos principais parâmetros do modelo na coordenação dos dispositivos de proteção. / This work describes the study of distribution system overcurrent protection through a probabilistic approach. Conventional approaches for overcurrent protection do not consider the probabilistic nature of the main variables involved, such as fault location, fault type and fault impedance for faults involving the ground. In this case, for instance, it is very difficult to assess the impact of situations where full coordination cannot be attained for some reason. The probabilistic approach, on the other hand, allows quantifying the risk of two adjacent protective devices operating in a non-coordinated way. This information is extremely valuable for electrical engineers at design level. In this work, the proposed methodology is illustrated through a few detailed application studies, including various sensitivity analyzes for assessing the influence of model parameters on the coordination of protective devices.

Este trabalho apresenta um estudo de proteção de sobrecorrente de redes primárias aéreas de distribuição de energia elétrica através de uma abordagem probabilística. Abordagens convencionais para o problema de proteção de sobrecorrente não levam em conta a natureza probabilística das principais variáveis envolvidas: tipo da falta, localização da falta e impedância de defeito para faltas envolvendo a terra. Neste caso, por exemplo, torna-se muito difícil avaliar as conseqüências de situações nas quais a coordenação total entre os dispositivos não pode ser alcançada por alguma razão. A abordagem probabilística permite, por outro lado, quantificar o risco de não haver coordenação entre dois dispositivos de proteção adjacentes. Esta informação é extremamente valiosa para os engenheiros de proteção na fase de projeto da rede elétrica. No trabalho, a metodologia probabilística é apresentada em detalhe e sua aplicação é ilustrada através de alguns estudos de aplicação, nos quais procurou-se avaliar a influência dos principais parâmetros do modelo na coordenação dos dispositivos de proteção. / This work describes the study of distribution system overcurrent protection through a probabilistic approach. Conventional approaches for overcurrent protection do not consider the probabilistic nature of the main variables involved, such as fault location, fault type and fault impedance for faults involving the ground. In this case, for instance, it is very difficult to assess the impact of situations where full coordination cannot be attained for some reason. The probabilistic approach, on the other hand, allows quantifying the risk of two adjacent protective devices operating in a non-coordinated way. This information is extremely valuable for electrical engineers at design level. In this work, the proposed methodology is illustrated through a few detailed application studies, including various sensitivity analyzes for assessing the influence of model parameters on the coordination of protective devices.

The smooth and reliable operation of key infrastructure components like water distribution systems, electric power systems, and telecommunications is essential for a nation?s economic growth and overall security. Tragic events such as the Northridge earthquake and Hurricane Katrina have shown us how the occurrence of a disaster can cripple one or more such critical infrastructure components and cause widespread damage and destruction. Technological advancements made over the last few decades have resulted in these infrastructure components becoming highly complicated and inter-dependent on each other. The development of tools which can aid in understanding this complex interaction amongst the infrastructure components is thus of paramount importance for being able to manage critical resources and carry out post-emergency recovery missions. The research work conducted as a part of this thesis aims at studying the effects of fire (a calamitous event) on the electrical distribution network of a city. The study has been carried out on a test bed comprising of a virtual city named Micropolis which was modeled using a Geographic Information System (GIS) based software package. This report describes the designing of a separate electrical test bed using Simulink, based on the GIS layout of the power distribution network of Micropolis. It also proposes a method of quantifying the damage caused by fire to the electrical network by means of a parameter called the Load Loss Damage Index (LLDI). Finally, it presents an innovative graph theoretic approach for determining how to route power across faulted sections of the electrical network using a given set of Normally Open switches. The power is routed along a path of minimum impedance. The proposed methodologies are then tested by running numerous simulations on the Micropolis test bed, corresponding to different fire spread scenarios. The LLDI values generated from these simulation runs are then analyzed in order to determine the most damaging scenarios and to identify infrastructure components of the city which are most crucial in containing the damage caused by fire to the electrical network. The conclusions thereby drawn can give useful insights to emergency response personnel when they deal with real-life disasters.

This diploma thesis addresses the current analytical procedures and policies of renewable energy production in the Czech Republic and, mainly deals with the policy modifications that occurred between 2010 to 2012 which also influenced this policy. To give more explanation to the entire picture of the energetic situation in the Czech Republic we have to analyze the current potential situation of renewable and non renewable resources, the quality of electrical distribution network, the framework of available energy resources in the Czech Republic, the costs of producing energy and its impact on the environment. The current global trend in most developed countries is the development of renewable energy sources but, this is not the current case in the Czech Republic which has in its plans to reach its target set by the European Union for the year 2020 . But, instead the Czech Republic would like to set a different goal and decrease the use of renewable energy resources and increase the use of nuclear energy. The support of the analysis policy for renewable energy sources in the Czech Republic is measured in comparison with the European Union, the United States of America and the Peoples Republic of China. The main goal is to evaluate this policies support for renewable energy sources in the Czech Republic and for its possible improvement.

Les mutations observées sur le système électrique (production décentralisée, véhicules électriques, stockage, micro réseau...) font émerger des problématiques d'ordres économiques et techniques dans la gestion de ce dernier. Parmi eux, l'impact sur les niveaux de tension et de courant de neutre des réseaux de distribution. Le but de cette thèse est d'étudier des modèles probabilistes pour estimer ces impacts. L'incertitude sur la puissance PV produite et sur l'utilisation des VEs implique la nécessité de développer des modèles probabilistes de consommation et de production d'électricité. Deux modèles différents de production et de consommation ont été étudiés : L'un basé sur l'approximation de données historiques par une densité de probabilité, l'autre reposant sur la répartition des données en groupes définis par un profil type et une probabilité d'occurrence. Des techniques de load flow probabilistes ont été étudiées dans cette thèse pour prendre en compte l'effet intermittente de la production PV et l'incertitude sur la consommation. Une technique basée sur la méthode de simulation Monte Carlo, une deuxième basée sur l'approximation PEM et une dernière basée sur l'utilisation du clustering appelée méthode pseudo Monte Carlo. Après avoir comparé la pertinence des méthodes sur deux réseaux test, la méthode pseudo Monte Carlo est appliquée, pour son gain en temps de simulation et son adaptabilité, dans un cas d'application qui porte sur l'estimation de la probabilité de dépassement des limites du courant de neutre en fonction du déséquilibre de production PV installée. / The current changes on the electrical system bring out economic and technical issues in the management of the latter. Among these issues, the impact of distributed generation and VEs on the technical constraints of the distribution network. The aim of this thesis is to study probabilistic models to estimate the impacts of photovoltaic production and electrical vehicles on medium and low voltage distribution networks. Two different probabilistic models of production and consumption were studied : one based on the fitting of historical data by one probability density function, the other one based on the data clustered in groups defined by a standard profile and a probability of occurrence. Three probabilistic load flow technics have been studied in this thesis. The first is based on the Monte Carlo simulation method, the second is based on the PEM approximation method and the last, based on the use of clustering, is called pseudo Monte Carlo method.

Reliable electricity distribution systems are crucial; hence, the maintenance of such systems is highly important, and in Sweden strictly regulated. Poorly planned maintenance scheduling leads unnecessary driving which contributes to increased emissions and costs.  Maintenance planning is similar to the capacitated vehicle routing problem, CVRP, a combinatorial optimization problem. Each route has an origin location, in this case is the office of the maintenance worker. The origin is the starting and ending point of each route. In addition, conditions such as due date for inspection has an impact on how components in the network are prioritized. The maintenance planning problem is likely NP-hard.  Given the above, the aim for this study is to develop a heuristic algorithm that efficiently generates daily inspection schedules on a yearly basis. There are multiple tools and algorithms already developed to solve these kinds of problems, for example the Google’s OR-Tools library, which provide optimal or near optimal solutions to VRP problems. The time complexity of those tools makes them impractical to use when planning maintenance of electrical networks since they can contain many thousands of components i.e., nodes. The main aim of this study is to develop an algorithm that provides a solution good enough compared to the solutions computed by the tools mentioned above but with a lower time complexity.  In order to develop and test the algorithm an electrical distribution network data is required. Due to the sensitive nature of this data, a simulated network is generated in place of using real data. The simulated network is based on land use data from the city of Uppsala, Sweden, and is based on the spatial distribution of an existing electrical distribution network in Örebro, Sweden. The scheduling and routing algorithm developed works by dividing candidate nodes into subsets. The division is done by using Density-based spatial clustering of applications with noise (DBSCAN). The clustering is made by querying all objects that requires an inspection to be performed that year. As a post-processing step all noise points are appended to the closest neighboring cluster. Then a distance map is computed for the objects within each cluster. An inspection day route is computed by applying a greedy forward selection in each cluster, always selecting a random unvisited starting node until all nodes within the cluster has been visited. This is then repeated 100 times for each cluster, finally keeping the best iteration. The number of iterations is based on evaluating the gain per additional iteration which appear to be logarithmic. The greedy forward selection means that the algorithm has a linear time complexity after the clustering and distance map computation is done.  The algorithm is evaluated by comparing the total driving time for the computed route to the output routes of a modified Concorde TSP solution and the solution of Google’s VRP solver.  The results show that the algorithm performs better in areas with shorter average neighborhood distance and driving time of the output route decrease with higher number of iterations. Although the VRP based baselines methods return solutions with inspection routes that are roughly 25% shorter than the proposed method, for realistic problem sizes the proposed method uses less compute resources i.e., time and memory. Furthermore, while the proposed method has a linear time and space complexity whereas the baselines have exponential time complexity. Finally, the VRP based back-optimization solutions are not practical in real settings when inspection tasks are added / changed daily due to service tasks and unfinished routes or when the number of nodes is substantially larger than the roughly 1 000 nodes used in the evaluation.Due to the sensitive nature of electrical distribution data the performance of the algorithm could not be compared to actual maintenance schedules. But with all likelihood the computed schedules should be significantly more efficient than manually planned schedules. / Att ha pålitliga elnät är essentiellt för ett välfungerande samhälle därav är underhållet av sådana system av stor vikt och i Sverige strikt reglerat. Dåligt planerade besiktningar leder till onödig körning inom nätet vilket bidrar till ökade utsläpp och kostnader. Underhållsplanering liknar problemet, CVRP, ett kombinatoriskt optimeringsproblem. Varje rutt har en ursprungsplats, i detta fall är besiktningsmannens kontor. Kontoret är start- och slutpunkten för varje rutt. Dessutom har villkor som sista besiktningsdatum en inverkan på hur komponenter i nätet prioriteras. Underhållsplaneringsproblemet är sannolikt NP-svårt. Mot bakgrund av ovanstående är syftet med denna studie att utveckla en algoritm som effektivt genererar dagliga besiktningsscheman på årsbasis. Det finns redan flera verktyg och algoritmer som har utvecklats för att lösa den här typen av problem, till exempel Googles OR-Tools, som beräknar optimala eller nästan optimala lösningar på VRP-problem. Tidskomplexiteten hos dessa verktyg gör dem opraktiska att använda vid planering av underhåll av elnät eftersom dessa kan innehålla många tusen komponenter, dvs noder. Huvudsyftet med denna studie är att utveckla en algoritm som ger en lösning som är tillräckligt bra jämfört med de lösningar som beräknas av de verktyg som finns idag men med en lägre tidskomplexitet.För att utveckla och testa algoritmen krävs elnätsdata. På grund av denna datas känsliga natur genereras ett simulerat nätverk istället för att använda riktiga data. Det simulerade nätet är baserat på markanvändningsdata från Uppsala, Sverige, och på den rumsliga distributionen av ett befintligt eldistributionsnät i Örebro, Sverige. Schemaläggnings- och ruttalgoritmen som utvecklats fungerar genom att dela upp kandidatnoder i delmängder. Uppdelningen görs genom att använda densitetsbaserad spatial klustring (DBSCAN). Klustringen görs genom att välja ut alla objekt som behöver besiktigas det året. Som ett efterbehandlingssteg läggs alla bruspunkter till det närmaste intilliggande klustret. Sedan beräknas en distansmatris för objekten inom varje kluster. En besiktningsrutt beräknas genom att inom varje kluster alltid starta på en slumpmässig vald ej besökt startnod. Därefter väljs den närmsta nod tills alla noder inom klustret har besökts. Detta upprepas sedan 100 gånger för varje kluster, och slutligen behålls den bästa iterationen. Antalet iterationer baseras på att utvärdera förbättringen per ytterligare iteration - som verkar vara logaritmisk. Det här innebär att algoritmen har en linjär tidskomplexitet efter att klustringen och beräkningen av distansmatrisen har genomförts. Algoritmen utvärderas genom att jämföra den totala körtiden för den beräknade rutten med rutterna för en modifierad Concorde TSP-lösning och lösningen från Googles VRP-solver. Resultaten visar att algoritmen presterar bättre i områden med kortare genomsnittligt avstånd mellan noderna och körtiden för besiktningsrutterna minskar med ett högre antal iterationer. Även om de existerande VRP-algoritmerna returnerar lösningar med besiktningsrutter som är cirka 25 % kortare än den föreslagna metoden, så är dessa inte realistiska att använda när antalet noder närmar sig de av ett riktigt elnät.Dessutom, medan den föreslagna metoden har en linjär tids-och rymdkomplexitet medan de existerande VRP-algoritmerna har en exponentiell tidskomplexitet. Slutligen är de VRP-baserade algoritmerna inte praktiska i verkligheten när besiktningar läggs till eller ändras eller när antalet noder är avsevärt större än de cirka 1 000 noder som används i utvärderingen. På grund av den känsliga karaktären hos elnätsdata kunde algoritmens prestanda inte jämföras med faktiska besiktningsscheman. Men med all sannolikhet borde de beräknade besiktningsschemana vara betydligt effektivare än manuellt planerade scheman.