Identifikation und Quantifizierung korrelativer Zusammenhänge zwischen elektrischer sowie klimatischer Umgebung und Elektroenergiequalität

Dissertation, Technische Universität Dresden

Links

Qucosa

Keywords

Power Quality, Time Series Analysis

Abstract

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).