Due to the increasing installation of decentralized generation units and the increasing demand of electrical power on distribution level the low voltage grids in Europe are facing different problems, e.g. deviations of the permitted voltage range or local inner overloads of the grid equipment. To overcome these problems a self-sustaining monitoring and control system for low voltage grids has been developed, which monitors the actual power flow situation and controls individual decentralized generation units and consumer loads if necessary. In this context new approaches for power flow calculation and control intelligence are inevitable. This paper describes a newly developed power flow algorithm to be used for online-monitoring of the grid state. In case of critical grid states identified by this power flow algorithm a control intelligence determines and executes possible strategies for elimination of the critical grid state. The developed algorithms have been tested and validated in comprehensive scenarios in consideration of plausibility, calculation speed and reliability of the results.

The ongoing shift towards a more decentralized and renewable energy system in Germany requires extensive modifications to existing grids and their operating principlesespecially at the distribution level. Furthermore, the integration of e-mobility will have a significant effect on distribution grids. Smart distribution systems are one way of handling these new supply scenarios. Hence, a self-sustaining monitoring and control system for LV-grids has been developed. It monitors the power flow situation and is able to control the grid if necessary. The system has been implemented in four LV-grids in Germany. The present paper describes the automation system and our initial experience with this smart grid approach.

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

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Not all urban low-voltage grids will be able to integrate new loads such as charging infrastructure for electric mobility or electrical heat pumps into existing structures without further measures. Therefore, this article analyzes to what extent load management is more cost-effective than conventional grid expansion. Methodically, the different load types are first apportioned from country to grid-level on the basis of different parameters. Subsequently, both conventional grid planning as a reference variant and innovative grid planning with different variants of load management are carried out. As a result, it can be summarized that the future success of load management is strongly dependent on its costs and whether the necessary information and communication technology is already deployed in the grids. Regardless of the costs, there is also considerable potential for savings in conventional grid expansions.

This paper describes new planning principles for rural low voltage networks, which have to be significantly expanded due to the required integration of distributed energy resources. The planning principles focus on the optimized use of innovative technologies (like feed-in management and voltage controller) in order to lower the total costs of necessary network reinforcement. In order to derive these planning principles technical and economical results of multiple concrete and representative low voltage distribution networks are compared. By means of cluster analyses, dependencies between the supply tasks and the most suitable innovative technologies are examined. As a result 6 planning principles are presented and discussed as a basis for a company-specific strategic orientation for planning of low voltage networks.

Due to the increasing installation of decentralized generation units and the increasing demand of electrical power on distribution level the low voltage grids in Germany are facing different problems, e.g. deviations of the permitted voltage range or local inner overloads of the grid equipment. To overcome these problems a self-sustaining monitoring and control system for low voltage grids has been developed, which monitors the actual power flow situation and controls individual decentralized generation units and consumer loads if necessary. The control system has been implemented into several low voltage grids in Germany. This paper describes first practical experience with the developed smart grid approach.

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