In smart energy systems, load curve refers to the time series reported by smart meters, which indicate the energy consumption of customers over a certain period of time. The widespread use of load curve (data) in demand side management and demand response programs makes it one of the most important resources. To capture the load behavior or energy consumption patterns, load curve modeling is widely applied to help the utilities and residents make better plans and decisions. In this dissertation, with the help of load curve modeling, we focus on data-driven solutions to three load monitoring problems in different scenarios of smart energy systems, including residential power systems and datacenter power systems and covering the research fields of i) data cleansing, ii) energy disaggregation, and iii) fine-grained power monitoring. First, to improve the data quality for load curve modeling on the supply side, we challenge the regression-based approaches as an efficient way to load curve data cleansing and propose a new approach to analyzing and organizing load curve data. Our approach adopts a new view, termed portrait, on the load curve data by analyzing the inherent periodic patterns and re-organizing the data for ease of analysis. Furthermore, we introduce strategies to build virtual portrait datasets and demonstrate how this technique can be used for outlier detection in load curve. To identify the corrupted load curve data, we propose an appliance-driven approach that particularly takes advantage of information available on the demand side. It identifies corrupted data from the smart meter readings by solving a carefully-designed optimization problem. To solve the problem efficiently, we further develop a sequential local optimization algorithm that tackles the original NP-hard problem by solving an approximate problem in polynomial time. Second, to separate the aggregated energy consumption of a residential house into that of individual appliances, we propose a practical and universal energy disaggregation solution, only referring to the readily available information of appliances. Based on the sparsity of appliances' switching events, we first build a sparse switching event recovering (SSER) model. Then, by making use of the active epochs of switching events, we develop an efficient parallel local optimization algorithm to solve our model and obtain individual appliances' energy consumption. To explore the benefit of introducing low-cost energy meters for energy disaggregation, we propose a semi-intrusive appliance load monitoring (SIALM) approach for large-scale appliances situation. Instead of using only one meter, multiple meters are distributed in the power network to collect the aggregated load data from sub-groups of appliances. The proposed SSER model and parallel optimization algorithm are used for energy disaggregation within each sub-group of appliances. We further provide the sufficient conditions for unambiguous state recovery of multiple appliances, under which a minimum number of meters is obtained via a greedy clique-covering algorithm. Third, to achieve fine-grained power monitoring at server level in legacy datacenters, we present a zero-cost, purely software-based solution. With our solution, no power monitoring hardware is needed any more, leading to much reduced operating cost and hardware complexity. In detail, we establish power mapping functions (PMFs) between the states of servers and their power consumption, and infer the power consumption of each server with the aggregated power of the entire datacenter. We implement and evaluate our solution over a real-world datacenter with 326 servers. The results show that our solution can provide high precision power estimation at both the rack level and the server level. In specific, with PMFs including only two nonlinear terms, our power estimation i) at the rack level has mean relative error of 2.18%, and ii) at the server level has mean relative errors of 9.61% and 7.53% corresponding to the idle and peak power, respectively. / Graduate / 0984 / 0791 / 0800 / tangguo1999@gmail.com

L’évolution de la consommation électrique est un point clé pour les choix à venir, tant pour les moyens de production d’électricité, que pour le dimensionnement du réseau à toutes ses échelles. Aujourd’hui, ce sont majoritairement des modèles statistiques basés sur les consommations passées et des tendances démographiques ou économétriques qui permettent de prédire cette consommation. Dans le contexte de la transition énergétique, des changements importants sont en cours et à venir, et la consommation future ne sera certainement pas une continuation des tendances passées. Modéliser ces changements nécessite une modélisation fine de type bottom-up de chaque contributeur de la consommation électrique. Ce type de modèle présente des challenges de modélisation, car il nécessite un grand nombre de paramètres d’entrée qui peuvent difficilement être renseignés de façon réaliste à grande échelle. En même temps, les données et informations de tout type n’ont jamais été autant disponibles. Cela représente à la fois un atout pour la modélisation, mais aussi une difficulté importante notamment à cause de l’hétérogénéité des données. Dans ce contexte, cette thèse présente une démarche de construction d’un simulateur de consommation électrique bottom-up capable de simuler différentes alternatives énergétiques à l’échelle de la France. Un travail de recensement, de classification et d’association des bases de données pour expliquer la consommation électrique a d’abord été mené. Ensuite, le modèle de consommation électrique a été présenté ; il a été validé et calibré sur une grande quantité de mesures de consommation électrique des départs HTA fournie par Enedis. Ce modèle a enfin pu être utilisé pour simuler différentes alternatives énergétiques afin d’aider au dimensionnement du réseau de distribution. / Future trend of electricity demand is a key point for sizing both the electricity network and the power plants. In order to forecast future electricity demand, current models mostly use statistical approaches based on past demand measurements and on demographic and economic trends. Because of current context of energy transition which comes along with important changes, future electricity demand is not expected to be similar to past trends. Modeling these changes requires a bottom-up modeling of each contributor to electricity demand. This kind of model is challenging because of the large number of input data required. At the same time, data and information are more and more available. Such availability can be considered both as an asset for modeling and as an important issue because of data heterogeneity. In this context, this dissertation offers an approach to build a bottom-up load curve simulator which enables to simulate prospective scenarii at the scale of France country. Firstly, an assessment, classification, and matching of the large databases explaining the electricity demand have been performed. Then, the electricity demand model has been presented. It has been validated and calibrated on Enedis’ large volumes of electricity demand measurements of medium voltage feeders. Finally, this model has been used to simulate several prospective scenarii in order to improve the electricity distribution network sizing.

Este trabalho tem por objetivo propor uma nova metodologia para o cálculo das perdas técnicas de energia e demanda por segmento do sistema de distribuição. As perdas técnicas foram divididas em oito segmentos: medidor de energia, ramal de ligação, rede secundária, transformador de distribuição, rede primária, subestação de distribuição, sistema de alta tensão e outros. Neste último segmento, foram incorporadas as parcelas referentes a equipamentos (capacitores, reguladores de tensão, etc), perdas em conexões, corrente de fuga em isoladores, etc. Desenvolveu-se um sistema computacional, para uso em microcomputador, que conta com dois módulos principais. O primeiro módulo destina-se ao cálculo das perdas técnicas em redes específicas. O cálculo é feito de forma hierárquica, por exemplo, selecionada uma subestação específica, são calculadas as perdas na subestação e em todos os componentes a jusante (redes primárias, transformadores de distribuição, redes secundárias, ramais de ligação e medidores de energia). As perdas técnicas, em termos de energia e demanda, são obtidas por meio de cálculo elétrico específico para os segmentos envolvidos, com a utilização dos dados cadastrais da rede, dados de faturamento e curvas de carga típicas por classe de consumidor e tipo de atividade desenvolvida. Com a aplicação deste módulo para todo o sistema da empresa, ou para uma parcela representativa, obtém-se um índice percentual de perda de energia para cada segmento. Estes índices são transferidos para o segundo módulo, que tem por objetivo efetuar o balanço de energia do sistema. A partir dos dados de energia nos pontos de suprimento, da energia total faturada mensalmente e dos índices de perdas por segmento, são obtidos os montantes de energia de perdas em cada segmento do sistema e uma avaliação das perdas não técnicas. O trabalho ainda apresenta um exemplo de aplicação, em sistema de distribuição real, mostrando os resultados obtidos, e termina apresentando as principais vantagens da metodologia. Os resultados obtidos com a nova metodologia são comparados com os resultados obtidos com outras metodologias. / This work focuses on the development of a new methodology for calculating technical losses within the different segments of the electric distribution system. In order to evaluate technical losses the electrical system was divided into eight segments: energy meter, customer connections, secondary feeder, distribution transformer, primary feeder, distribution substation, high voltage system and another segment that represents other technical losses. The latter comprises losses in equipment such as capacitors and voltage regulators as well as losses in electric connections, isolators, etc. A computational system was developed and it comprises two modules. The first one is intended to calculate technical losses in specific networks. The calculation is made in a hierarchical manner. If a distribution substation is selected for the calculation, the losses in that substation and the losses in all components downstream are calculated. The technical losses, in terms of energy and demand, are obtained by utilizing network topological data, consumed energy data and typical load curves per customer class and activity type. An energy losses index, calculated as a percentage of the supplied energy, is obtained for each segment by applying this module to the entire utility’s power system or in a representative part of it. These values are transferred to the second module, which has the objective of determining the overall energy balance. Technical and non-technical losses, in terms of energy, in each segment are obtained by utilizing the total amount of energy supplied to the system, energy consumed and energy losses indices per segment. This work shows the results obtained by applying the computational tool to a real distribution system. Such results are compared with the ones obtained by using other methodologies, and the main advan ages of this new methodology are outlined.

Este trabalho tem por objetivo propor uma nova metodologia para o cálculo das perdas técnicas de energia e demanda por segmento do sistema de distribuição. As perdas técnicas foram divididas em oito segmentos: medidor de energia, ramal de ligação, rede secundária, transformador de distribuição, rede primária, subestação de distribuição, sistema de alta tensão e outros. Neste último segmento, foram incorporadas as parcelas referentes a equipamentos (capacitores, reguladores de tensão, etc), perdas em conexões, corrente de fuga em isoladores, etc. Desenvolveu-se um sistema computacional, para uso em microcomputador, que conta com dois módulos principais. O primeiro módulo destina-se ao cálculo das perdas técnicas em redes específicas. O cálculo é feito de forma hierárquica, por exemplo, selecionada uma subestação específica, são calculadas as perdas na subestação e em todos os componentes a jusante (redes primárias, transformadores de distribuição, redes secundárias, ramais de ligação e medidores de energia). As perdas técnicas, em termos de energia e demanda, são obtidas por meio de cálculo elétrico específico para os segmentos envolvidos, com a utilização dos dados cadastrais da rede, dados de faturamento e curvas de carga típicas por classe de consumidor e tipo de atividade desenvolvida. Com a aplicação deste módulo para todo o sistema da empresa, ou para uma parcela representativa, obtém-se um índice percentual de perda de energia para cada segmento. Estes índices são transferidos para o segundo módulo, que tem por objetivo efetuar o balanço de energia do sistema. A partir dos dados de energia nos pontos de suprimento, da energia total faturada mensalmente e dos índices de perdas por segmento, são obtidos os montantes de energia de perdas em cada segmento do sistema e uma avaliação das perdas não técnicas. O trabalho ainda apresenta um exemplo de aplicação, em sistema de distribuição real, mostrando os resultados obtidos, e termina apresentando as principais vantagens da metodologia. Os resultados obtidos com a nova metodologia são comparados com os resultados obtidos com outras metodologias. / This work focuses on the development of a new methodology for calculating technical losses within the different segments of the electric distribution system. In order to evaluate technical losses the electrical system was divided into eight segments: energy meter, customer connections, secondary feeder, distribution transformer, primary feeder, distribution substation, high voltage system and another segment that represents other technical losses. The latter comprises losses in equipment such as capacitors and voltage regulators as well as losses in electric connections, isolators, etc. A computational system was developed and it comprises two modules. The first one is intended to calculate technical losses in specific networks. The calculation is made in a hierarchical manner. If a distribution substation is selected for the calculation, the losses in that substation and the losses in all components downstream are calculated. The technical losses, in terms of energy and demand, are obtained by utilizing network topological data, consumed energy data and typical load curves per customer class and activity type. An energy losses index, calculated as a percentage of the supplied energy, is obtained for each segment by applying this module to the entire utility’s power system or in a representative part of it. These values are transferred to the second module, which has the objective of determining the overall energy balance. Technical and non-technical losses, in terms of energy, in each segment are obtained by utilizing the total amount of energy supplied to the system, energy consumed and energy losses indices per segment. This work shows the results obtained by applying the computational tool to a real distribution system. Such results are compared with the ones obtained by using other methodologies, and the main advan ages of this new methodology are outlined.

La problématique développée dans la thèse est d'estimer, dans une démarche prospective et dans un but d'anticipation, les impacts en puissance induits par les ruptures technologiques et comportementales qui ne font pas aujourd'hui l'objet de mesures dans les panels. Pour évaluer les modifications sur les appels de puissance du parc résidentiel engendrées par ces profondes transformations,un modèle paramétrique, bottom-up, techno-explicite et agrégatif est donc nécessaire. Celui-ci serait donc destiné à la reconstitution, de manière non tendancielle, de la courbe de charge électrique résidentielle. Il permettrait ainsi de conduire la simulation de différents scénarios d'évolution contrastés. L'élaboration d'un tel modèle constitue le sujet de ce doctorat.Pour répondre à cette problématique, nous proposons une méthode conceptuelle originale de reconstitution de courbe de charge. Sa mise en application centrée sur la génération de foisonnement d'origine comportementale a conduit à la modélisation d'un certain nombre de concepts. Ce travail a abouti à l'élaboration d'un algorithme stochastique destiné à représenter le déclenchement réalistedes appareils domestiques. Différents cas d'application ont pu être testés et les résultats en puissance ont été étudiés. Plus particulièrement pour analyser le foisonnement visible à un niveau agrégé, nous avons mis en place une méthodologie nouvelle basée sur une distance adaptée aux courbes de charge. Finalement, nous avons cherché à identifier des comportements réels d'usage des appareils. Pour cela, nous avons conduit différents travaux de classification de courbes de charge. / In this dissertation, we focus on the estimation of the impacts in terms of power demand caused by the technological and behavioural breaks that will affect the domestic sector in the future. These deep changes are not measured in the existing panels and the estimation is required for prospective (long-term) studies. To evaluate the very likely modifications of the domestic power demand that will follow previous influences, a bottom-up, technically-explicit and aggregative model is needed. This one aims at reconstituting the electric residential load curve according to a non-trending manner. Thanks to it, various evolution scenarios can be simulated. The purpose of this PhD is the elaboration of such a model.A functional analysis was carried out to build up a new method to reconstitute the domestic electric load curve. Since the clarifying of the diversity represents one of the key points of our research, we decided to begin the modelling task with focus on it. More precisely, we elaborated a stochastic algorithm whose purpose is the realistic starting of domestic appliances. Some application cases have been tested. We studied the diversity affecting aggregated power demand and we propose a new methodology able to visualise and to analyse it. This method is based on a distance adapted to the load curve. Finally we tried to identify human behaviour concerning the use of appliances thanks to load curve classifications.

Il est primordial, pour un distributeur d’énergie électrique, d’obtenir des estimations précises de la demande en énergie de leurs réseaux. Des outils statistiques tels que des profils de consommation électrique offrent des estimations de qualité acceptable. Ces profils ne sont cependant généralement pas assez précis, car ils ne tiennent pas compte de l’influence de facteurs tels que la présence de chauffage électrique ou le type d’habitation. Il est néanmoins possible d’obtenir des profils précis en utilisant uniquement les historiques de consommations d’énergie des clients, les mesures desdéparts 20kV, et un algorithme génétique de séparation de sources. Un filtrage et un prétraitement des données a permis de proposer à l’algorithme génétique de séparation de sources des données adaptées. La séparation de sources particulièrement bruitées est résolue par un algorithme génétique complètement parallélisé sur une carte GPGPU. Les profils de consommation électrique obtenus correspondent aux attentes initiales, et démontrent une amélioration considérable de la précision des estimations de courbes de charge de départs 20kV et de postes de transformation moyenne tension-basse tension. / Precise estimations of the energy demand of a power network are paramount for electrical distribution companies. Statistical tools such as load profiles offer acceptable estimations. These load profiles are, however, usually not precise enough for network engineering at the local level, as they do not take into account factors such as the presence of electrical heating devices or the type of housing. It is however possible to obtain accurate load profiles with no more than end user energy consumption histories, 20kV feeder load measurements, a blind source separation and a genetic algorithm. Filtering and preliminary treatments performed on the data allowed the blind source separation to work with adequate information. The blind source separation presented in this document is successfully solved by a completely parallel genetic algorithm running on a GPGPU card. The power load profiles obtained match the requirements, and demonstrate a considerable improvement in the forecast of 20kV feeder as well as MV substation load curves.

A three-phase power supply is a de facto standard when selecting a power supply to homes in Sweden, regardless of whether it is flat with low energy consumption or a house with electric heating. This project aims to determine the advantages and disadvantages of using a three-phase supply compared to a single-phase supply to homes. This thesis starts with a historical literature review to find answers to why a three-phase supply is a de facto standard in Sweden. Single-phase and threephase supplies to homes were compared by creating an electrical circuit model that used actual household load profiles. The load profiles were taken from a study that measured the power consumption in 400 Swedish homes. Two houses and four flats from that study was selected as input data to the circuit model. Each house was modelled as both single-phase and three-phase. The power losses in the supply conductors from the power meter to the homes distribution panel was calculated. The selectivity between the main fuses and Miniature Circuit Breakers (MCB) was also investigated by comparing the let-through energy of MCBs and pre-arcing energy of fuses. The results from the historical review indicate that one of the reasons that three-phase supplies became the de facto standard is that Sweden implemented a new tariff system. All the customers with low power consumption were placed in the 16 A main fuse category, and the network fee was the same for single-phase and threephase the previous system had a higher price for three-phase. The power losses in single-phase supplies and three-phase supplies with a similar total conductor area were compared. The results that a three-phase supply had lower losses in all the cases, even though the loads were mostly 230 V loads and not perfectly balanced between the phases. A three-phase supply is preferable over a single-phase supply if the home has high energy consumption. However, a single-phase supply might be a good option if the home has a low to moderate energy consumption. The reason for this is that the losses are only slightly higher in absolute terms, and a single-phase supply enables a higher main fuse rating for the supplies total cross-section, and it is, therefore, easier to coordinate the downstream protective devices / Att använda sig av trefasmatningar till bostäder är en de facto-standard i Sverige, oavsett om det är en lägenhet eller en eluppvärmd villa så väljs nästan alltid en trefastmatning. I det här projeket undersöks anledningar till att trefasmatningar är de facto-standarden i svenska bostäder. Målet med projektet är även att undersöka fördelar och nackdelar med trefasmatning och enfasmatning jämfört med varandra vid matning av bostäder Rapporten inleds med en litteratur studie vars syfte var att ta reda på historiska händelser som kan lett till att trefas blev standarden för matning av bostäder. För att jämföra trefasmatning och enfasmatning av bostäder så användes en elkrets av bostäder som använde effektförbrukning från en studie som har samlat in mätvärden för förbrukningen i 400 svenska hushåll. Två villor och fyra lägenheter undersöktes. Elkretsen användes sedan för att beräkna förluster i kablaget mellan elmätaren och elcentralen, varje bostad undersöktes både med enfasmatning och trefasmatning. Selektiviteten mellan huvudsäkringar och dvärgbrytare på utgående grupper undersöktes för felförlopp och överlast. Litteraturstudien visade tecken på att införandet av säkringstariffen 1963 kan ha gjort så att trefasmatningar blev de facto-standarden i Sverige. När säkringstariffen implementerades placerades samtliga kunder med lågförbrukning in 16 A säkrings kategorin, oavsett om de hade ett trefasabonnemang eller enfasabonnemang. Vilket gjorde att nätavgiften var densamma för enfas och trefas, tidigare var det billigare med enfas. Resultaten från undersökningen av ledningsförluster visade att trefasmatningen gav lägre förluster, även fast de mesta av lasterna var enfaslaster och inte perfekt balanserade. Resultaten visar att en trefasmatning är ett bättre val om bostaden har en hög energiförbrukning. Resultaten visar även att en enfasmatning kan vara ett bättre val om bostaden har låg energiförbrukning eftersom den totala mängden energi som går förlorad är låg i båda fallen. Eftersom en enfasmatning gör det möjligt att ha en högre huvudsäkring än en trefasmatning med samma totala ledararea, vilket gör att det är lättare att koordinera huvudsäkringen gruppledningarnas dvärgbrytare.

Transportsektorn står i dagsläget för cirka en tredjedel av alla växthusgasutsläpp inom Sverige. För att arbeta i linje med Parisavtalet har Sveriges riksdag därmed beslutat att dessa utsläpp ska minska med 70 procent fram till år 2030, relativt de nivåer som uppmättes år 2010. För att uppnå målet och klara klimatomställningen, arbetar man bland annat med att påskynda elektrifieringen av transporter. Detta skulle kunna innebära stora utmaningar för det svenska elnätet, eftersom man inte byggt ut ledningar i samma takt som elbehovet har ökat. I Stockholm har det därför uppstått kapacitetsbrist, som innebär att man inte kan tillgodose regionen med el vid alla tidpunkter under året. Samtidigt kommer man inte kunna bygga ut nya ledningar till Stockholm förrän vi når cirka år 2030.  Syftet med denna studie, är att undersöka hur elektrifieringen av personbilsflottan kan komma att påverka regionnätet i Stockholm år 2030, där det redan idag råder kapacitetsbrist. Metoden som används är baserad på scenariometodik där både kvantitativa och kvalitativa data används för att konstruera två olika huvudscenarion, ett lågscenario där personbilsflottan elektrifieras långsamt och ett högscenario där personbilsflottan elektrifieras snabbt. Genom att utforska hur elbehovet skulle kunna utvecklas fram till år 2030 på timbasis för dessa scenarion, görs en uppskattning över hur många timmar om året som det skulle kunna råda kapacitetsbrist, samt hur stor effektbristen blir vid dessa tillfällen, om allt elbehov ska kunna tillgodoses. Vidare undersöks om även flexibilitetsresurser i hemmaladdningen, kan påverka hur många timmar det råder kapacitetsbrist och hur korrelation ser ut mellan antalet laddbara bilar och kapacitetsbrist.  Resultatet från studien visar att elektrifieringen av personbilsflottan kan leda till stora ansträngningar på elnätet om användare laddar utifrån egna preferenser och därmed okontrollerat, eftersom laddningen sannolikt sammanfaller med tider på dygnet när elbehovet redan är som störst. Vidare ökar antalet timmar med kapacitetsbrist proportionellt mot hur många personbilar som elektrifieras. När flexibilitetsresurser integreras i hemmaladdningen, minskar ansträngningen på elnätet dock betydligt. Att öka incitamenten för att människor ska ändra sina beteenden gällande laddning, kan därmed positiva effekter på elnätet. Men även om flexibilitetresurser integreras i hemmaladdningen, på det sätt som har antagits genomföras i denna studie, visar resultatet att det fortfarande kan uppstå kapacitetsbrist. Det finns därmed fortfarande en risk för att elektrifieringen av personbilsflottan skulle kunna försenas. / The transport sector currently accounts for about a third of all greenhouse gas emissions in Sweden. To work in line with the Paris Agreement, it has thus been decided that these emissions should be reduced by 70 percent by 2030, relative to the levels measured in 2010. To achieve this goal and cope with climate change, the Swedish parliament is, among other things, currently working towards accelerating the electrification of transports. This, in turn, could result in major challenges for the Swedish electricity grid, as power lines have not been expanded at the same rate as the need for electricity has increased. In Stockholm, it has become a problem with a lack of capacity, which means that it is not possible to satisfy the region with electricity at all times of the year. Meanwhile, it will not be possible to expand new power lines to Stockholm until we reach around the year 2030.  The purpose of this study is to investigate how the electrification of the passenger car fleet could affect the regional network in Stockholm when we reach the year 2030. The method that has been used is based on scenario methodology where both quantitative and qualitative data has been used to construct two different main scenarios. Firstly, a low scenario was constructed, where the passenger car fleet is electrified slowly, and secondly, a high scenario was constructed where the passenger car fleet is electrified rapidly. By examining how the electricity demand could develop until the year 2030 on an hourly basis for these two scenarios, an estimate is made of how many hours a year there could be a lack of capacity and how large the power shortage would be on these occasions if all the electricity demand is to be satisfied. Furthermore, it is also investigated whether flexible resources in the home-charging of electric vehicles can affect how many hours there could be a lack of capacity and what the correlation looks like between the number of electric vehicles and lack of capacity.  The result from the study shows that the electrification of the passenger car fleet can lead to a congested electricity grid if users charge their cars uncontrolled. This, as the charge is likely to coincide with times of the day when the electricity demand already is great. Furthermore, the number of hours with a lack of capacity increases in proportion to the number of passenger cars that are electrified. When flexible resources are integrated into the home-charging, the effort on the power grid is significantly reduced. Increasing the incentives for people to change their behaviours about charging can thus have positive effects on the electricity grid. However, even if flexible resources are integrated into the home charging system, the way it is assumed to be implemented here, the result shows that there may still be a lack of capacity. There is thus still a risk that the electrification of the passenger car fleet will be delayed.

Kenntnisse über das prinzipielle Verhalten der Lasten und deren Benutzung durch die Endabnehmer sind im Wesentlichen vorhanden. Viele der aktuell notwendigen Untersuchungen benötigen jedoch Zeitreihen elektrischer Lasten, sogenannte Lastgänge. Mit der Synthese von Zeitreihen elektrischer Lasten können unter Berücksichtigung verschiedenster Anforderungen Lastgänge aufgebaut werden, wobei in dieser Arbeit der Fokus auf Haushaltsabnehmer liegt. Wichtige Eingangsdaten für die Lastgangsynthese sind die technischen Kenngrößen der elektrischen Geräte und die sozialen Kennzahlen zur Benutzung der Geräte durch die Endabnehmer. Anhand dieser Eingangsdaten wird die Lastgangsynthese durchgeführt und werden Anwendungsbeispiele dargestellt. Die Entwicklung von klassischen Versorgungsnetzen hin zu aktiven Verteilungsnetzen ist bedingt durch neue Verbraucher, wie Wärmepumpen, Elektroautos, sowie vielen dezentralen Erzeugungsanlagen. Speziell die fluktuierende Einspeisung durch Photovoltaik-Anlagen ist Anlass zur Forderung nach einem Verbrauchs- und Lastmanagement. Mit dem Verbrauchsmanagement wird die Last an die Einspeisung angepasst und das Lastmanagement berücksichtigt zusätzlich die Versorgungssituation des Netzes. Für die Lastgangsynthese werden die Haushaltsgeräte in fünf Geräteklassen unterteilt, für die spezifische Kennzahlen aus technischer und sozialer Sicht angegeben werden. Diese Kennzahlen sind Leistung pro Gerät oder Energieverbrauch pro Nutzung sowie Ausstattungsgrade, Benutzungshäufigkeiten und Zeiten für das Ein- und Ausschalten der Geräte. Damit wird ein neuer Ansatz gewählt, welcher nicht mehr auf die detaillierte Beschreibung des Bewohnerverhaltens beruht, da die Datenbereitstellung dafür äußerst schwierig war und ist. Vorzugsweise in Niederspannungsnetzen sind mit synthetischen Zeitreihen umfangreiche und umfassende Untersuchungen realisierbar. Es gibt verschiedenste Möglichkeiten, die Zeitreihen zusammenzustellen. Mit Lastgängen je Außenleiter können beispielsweise unsymmetrische Zustände der Netze analysiert werden. Zudem können auch Lastgänge für Geräte bzw. Gerätegruppen erstellt werden, welche für Potenzialanalysen des Verbrauchsmanagement essenziell sind. Der wesentliche Unterschied besteht darin, dass viele Berechnungen nicht mehr auf deterministische Extremwerte beruhen, sondern die stochastischen Eigenschaften der Endabnehmer mit den resultierenden Lastgängen berücksichtigt werden. / Distributed generation and novel loads such as electric vehicles and heat pumps require the development towards active distribution networks. Load curves are needed for the appropriate design process. This thesis presents a feasible and expandable synthesis of load curves, which is performed exemplary on residential customers with a period under review of 1 year and time steps of as little as 30 s. The data is collected for up-to-date appliances and current statics examining the way of life. The main focus lies on the input data for the synthesis and distinguishes between technical and social factors. Some thirty home appliances have been analyzed and are classified into five appliance classes by incorporating switching operations and power consumptions. The active power is the key figure for the technical perspective and the data is derived from manufacturer information. For the social perspective six different customer types are defined. They differ in sizes of household and housekeeping. The social key figures are appliance penetration rate and depending on the appliance class the turn-on time, turn-off time, operating duration or cycle duration. The elaborated two-stage synthesis is efficiently implemented in Matlab®. First, artificial load curves are created for each appliance of the households under consideration of the appliance class. In the second step, the individual load curves of the appliances are combined to load curves per line conductor. The algorithms have been validated in the implementation process by retracing the input data in the load curves. Also, the feasibility of the results is shown by comparing the key figures maximum load and power consumption to data in literature. The generated load curves allow for unsymmetrical calculations of distribution systems and can be used for probabilistic investigations of the charging of electric vehicles, the sizing of thermal storage combined with heat pumps or the integration of battery storage systems. A main advantage is the possibility to estimate the likelihood of operating conditions. The enhancement to further appliances and the changeability of the input data allows for versatile further possible investigations.

Kenntnisse über das prinzipielle Verhalten der Lasten und deren Benutzung durch die Endabnehmer sind im Wesentlichen vorhanden. Viele der aktuell notwendigen Untersuchungen benötigen jedoch Zeitreihen elektrischer Lasten, sogenannte Lastgänge. Mit der Synthese von Zeitreihen elektrischer Lasten können unter Berücksichtigung verschiedenster Anforderungen Lastgänge aufgebaut werden, wobei in dieser Arbeit der Fokus auf Haushaltsabnehmer liegt. Wichtige Eingangsdaten für die Lastgangsynthese sind die technischen Kenngrößen der elektrischen Geräte und die sozialen Kennzahlen zur Benutzung der Geräte durch die Endabnehmer. Anhand dieser Eingangsdaten wird die Lastgangsynthese durchgeführt und werden Anwendungsbeispiele dargestellt. Die Entwicklung von klassischen Versorgungsnetzen hin zu aktiven Verteilungsnetzen ist bedingt durch neue Verbraucher, wie Wärmepumpen, Elektroautos, sowie vielen dezentralen Erzeugungsanlagen. Speziell die fluktuierende Einspeisung durch Photovoltaik-Anlagen ist Anlass zur Forderung nach einem Verbrauchs- und Lastmanagement. Mit dem Verbrauchsmanagement wird die Last an die Einspeisung angepasst und das Lastmanagement berücksichtigt zusätzlich die Versorgungssituation des Netzes. Für die Lastgangsynthese werden die Haushaltsgeräte in fünf Geräteklassen unterteilt, für die spezifische Kennzahlen aus technischer und sozialer Sicht angegeben werden. Diese Kennzahlen sind Leistung pro Gerät oder Energieverbrauch pro Nutzung sowie Ausstattungsgrade, Benutzungshäufigkeiten und Zeiten für das Ein- und Ausschalten der Geräte. Damit wird ein neuer Ansatz gewählt, welcher nicht mehr auf die detaillierte Beschreibung des Bewohnerverhaltens beruht, da die Datenbereitstellung dafür äußerst schwierig war und ist. Vorzugsweise in Niederspannungsnetzen sind mit synthetischen Zeitreihen umfangreiche und umfassende Untersuchungen realisierbar. Es gibt verschiedenste Möglichkeiten, die Zeitreihen zusammenzustellen. Mit Lastgängen je Außenleiter können beispielsweise unsymmetrische Zustände der Netze analysiert werden. Zudem können auch Lastgänge für Geräte bzw. Gerätegruppen erstellt werden, welche für Potenzialanalysen des Verbrauchsmanagement essenziell sind. Der wesentliche Unterschied besteht darin, dass viele Berechnungen nicht mehr auf deterministische Extremwerte beruhen, sondern die stochastischen Eigenschaften der Endabnehmer mit den resultierenden Lastgängen berücksichtigt werden. / Distributed generation and novel loads such as electric vehicles and heat pumps require the development towards active distribution networks. Load curves are needed for the appropriate design process. This thesis presents a feasible and expandable synthesis of load curves, which is performed exemplary on residential customers with a period under review of 1 year and time steps of as little as 30 s. The data is collected for up-to-date appliances and current statics examining the way of life. The main focus lies on the input data for the synthesis and distinguishes between technical and social factors. Some thirty home appliances have been analyzed and are classified into five appliance classes by incorporating switching operations and power consumptions. The active power is the key figure for the technical perspective and the data is derived from manufacturer information. For the social perspective six different customer types are defined. They differ in sizes of household and housekeeping. The social key figures are appliance penetration rate and depending on the appliance class the turn-on time, turn-off time, operating duration or cycle duration. The elaborated two-stage synthesis is efficiently implemented in Matlab®. First, artificial load curves are created for each appliance of the households under consideration of the appliance class. In the second step, the individual load curves of the appliances are combined to load curves per line conductor. The algorithms have been validated in the implementation process by retracing the input data in the load curves. Also, the feasibility of the results is shown by comparing the key figures maximum load and power consumption to data in literature. The generated load curves allow for unsymmetrical calculations of distribution systems and can be used for probabilistic investigations of the charging of electric vehicles, the sizing of thermal storage combined with heat pumps or the integration of battery storage systems. A main advantage is the possibility to estimate the likelihood of operating conditions. The enhancement to further appliances and the changeability of the input data allows for versatile further possible investigations.