Harmonic propagation studies of public distribution networks require accurate models of aggregate residential customers (groups of customers) that simulate the harmonic emission of the multitude of household appliances in the network. Most of the present models were developed with the component-based approach, where models of individual household appliances are combined to build the model of multiple customers. This approach requires high amount of input data, like models of individual household appliances and detail information of customer behavior and device composition, which is usually not easy to acquire. However, with the increasing number of PQ-analyzers in the networks, the measurement-based approach is now more and more considered for the modeling of aggregate customers. The measurement-based approach uses measurements of the network in combination with top-down methodologies to obtain models of the aggregate customers. Compared to the component-based approach it has several advantages, like inherent consideration of the real operating changes of the individual household appliances, variation of customer behavior, effect of line impedances, cancellation and attenuation effects, etc. This thesis presents the development of a time-series stochastic model of the low-order harmonic emission of aggregate residential customers based on a top-down measurement-based approach. The model represents the daily variation of the harmonic magnitudes and phase angles. Besides, the model includes the representation of the harmonic unbalances, which is of great importance for the proper analysis of harmonic propagation in medium-voltage networks. The model is parametrized for German networks, but the methodology can be applied to find the models of other regions or countries.

Harmonic propagation studies of public distribution networks require accurate models of aggregate residential customers (groups of customers) that simulate the harmonic emission of the multitude of household appliances in the network. Most of the present models were developed with the component-based approach, where models of individual household appliances are combined to build the model of multiple customers. This approach requires high amount of input data, like models of individual household appliances and detail information of customer behavior and device composition, which is usually not easy to acquire. However, with the increasing number of PQ-analyzers in the networks, the measurement-based approach is now more and more considered for the modeling of aggregate customers. The measurement-based approach uses measurements of the network in combination with top-down methodologies to obtain models of the aggregate customers. Compared to the component-based approach it has several advantages, like inherent consideration of the real operating changes of the individual household appliances, variation of customer behavior, effect of line impedances, cancellation and attenuation effects, etc. This thesis presents the development of a time-series stochastic model of the low-order harmonic emission of aggregate residential customers based on a top-down measurement-based approach. The model represents the daily variation of the harmonic magnitudes and phase angles. Besides, the model includes the representation of the harmonic unbalances, which is of great importance for the proper analysis of harmonic propagation in medium-voltage networks. The model is parametrized for German networks, but the methodology can be applied to find the models of other regions or countries.