Eine angemessene Qualität der Elektroenergie ist Grundvoraussetzung für den störungsfreien Betrieb aller angeschlossenen Geräte und Anlagen und spielt in den Verteilungsnetzen moderner Industriegesellschaften wie Deutschland eine zentrale Rolle. Die Elektroenergiequalität (EEQ) wird in Strom- und Spannungsqualität unterteilt. Während die Stromqualität maßgeblich im Verantwortungsbereich der Hersteller von Geräten und Anlagen liegt, sind für die Sicherung einer angemessenen Spannungsqualität im Wesentlichen die Netzbetreiber verantwortlich. Durch die technische Weiterentwicklung bspw. neuer Gerätetechnologien und die zunehmende Integration dezentraler Erzeugungsanlagen wie Photovoltaikanlagen ist zu erwarten, dass die EEQ auch künftig weiter an Bedeutung gewinnt. Die EEQ im Niederspannungsverteilungsnetz ist abhängig von Ort und Zeit und wird durch verschiedene Qualitätskenngrößen beschrieben. Die örtliche und zeitliche Abhängigkeit resultieren aus einer Vielzahl verschiedener Einflussfaktoren, welche sich entweder der elektrischen oder der nicht-elektrischen Umgebung des betrachteten Verteilungsnetzes zuordnen lassen. Die elektrische Umgebung wird durch die Art und Anzahl angeschlossener Verbraucher bzw. Erzeuger (Abnehmer- bzw. Erzeugerstruktur) sowie Struktur und technische Parameter des Verteilungsnetzes (Netzstruktur) bestimmt. Die nicht-elektrische Umgebung umfasst u.a. Einflüsse der klimatischen Umgebung wie bspw. Temperatur oder Globalstrahlung. Ziel dieser Arbeit ist die systematische Identifikation korrelativer Zusammenhänge zwischen den genannten Umgebungseinflüssen und der EEQ sowie deren Quantifizierung auf Basis geeigneter Indizes und Kenngrößen. Die Ergebnisse der Arbeit helfen grundlegende Prinzipien der Ausprägung der Elektroenergiequalität im öffentlichen Verteilungsnetz besser zu verstehen sowie die Verteilungsnetze im Hinblick auf die Elektroenergiequalität zu charakterisieren und zu klassifizieren. Analog zu den Standard-Lastprofilen erfolgt die Definition von Standard-Qualitätsprofilen. / Power quality levels in public low voltage grids are influenced by many factors which can either be assigned to the electrical environment (connected consumers, connected genera-tion, network characteristics) or to the non-electrical environment (e.g. climatic conditions) at the measurement site. Type and amount of connected consumers (consumer topology) are expected to have a very high impact on power quality (PQ) levels. The generation topology is characterized by number and kind of equipment and generating installations like photovoltaic systems which are connected to the LV grid. The electrical parameters of the grid define the network topology. The parameters which are most suitable to describe each of the three topologies and the climatic environment will be identified. Voltage and current quality in public low voltage (LV) grids vary depending on location and time. They are quantified by a set of different parameters which either belong to events (e.g. dips) or to variations (e.g. harmonics). This thesis exclusively addresses continuous parameters describing variations. Continuous phenomena like harmonics are closely linked to an one-day-cycle which implies a more or less periodic behavior of the continuous power quality parameters. Consumer topologies such as office buildings or residential areas differ in their use of equipment. Time series analysis is used to distinguish between different consumer topologies and to identify characteristic weeks. The clustering of one-day time series is applied to identify characteristic days within the weeks of certain topologies. Based on the results, emission profiles for certain current quality parameters of different consumer topologies will be defined. Due to the characteristic harmonic current emission of certain consumer topologies which represents the typical user behaviour a classification system is developed. It is used to automatically classify the emission profiles of harmonic currents for unknown measurements and to estimate a likely consumer topology. A classification measure is introduced in order to identify unusual or false classified emission profiles. The usage behaviour of equipment by customers usually varies over the year. Subsequently, the levels of PQ parameters like harmonics may show seasonal variations which are identified by using newly defined parameters. The introduction of new device technologies on a large scale like the transition from incandescent to LED lamps might result in long-term changes to the levels of PQ parameters (e.g. harmonics). The analysis of the long-term behavior (trend) will be applied in order to quantify global trends (looking on the measurement duration as a whole) and local trends (looking on individual segments of the whole time series).

Controlling the balance of production and consumption of electricity will become increasingly challenging as the transport sector gradually converts to electric vehicles along with a growing share of wind power in the Swedish electric power system. This puts greater demand on resources that maintain the balance to ensure stable grid operation. The balancing act is called frequency regulation which historically has been performed almost entirely by hydropower. As the power production becomes more intermittent with renewable energy sources, frequency regulation will need to be performed in higher volumes on the demand side by having a more flexible consumption. In this report, the electrification of 17 buses Svealandstrafiken bus depot in Västerås has been studied. The aim has been to assess different charging strategies to efficiently utilize the available time and power but also to investigate if Svealandstrafiken can participate in frequency regulation. A smart charging model was created that demonstrated how smart charging can be implemented to optimize the charging in four different cases. The simulated cases were: charging with load balancing, reduced charging power, frequency regulation, and electrifying more buses. The results show that the power capacity limit will be exceeded if the buses are being charged directly as they arrive at the depot and without scheduling the charging session. By implementing smart charging, Svealandstrafiken can fully charge the 17 buses within the power capacity limit of the depot with 82 minutes to spare. By utilizing this 82-minute margin in the four different charging strategies, it was found that Svealandstrafiken can save 88 200SEK per year by load balancing, save 30 000 SEK per year by reducing the charging power by 10 %, earn 111 900 SEK per year by frequency regulation or electrify five more buses. Reducing the charging power may also increase the lifetime of the batteries but quantifying this needs further studies. Conclusively, there is economic potential for Svealandstrafiken for implementing smart charging.