With the increasing expansion of renewable energies, the demands placed on the German power grids are increasing many times over. The main reason for this increase is the power production from volatile and unpredictable sources like wind and sun. While grid operators will have to increase their investments in control technology and energy storage systems, private end consumers will have the responsibility to adapt their consumption behavior to the energy generation. This is the only way to achieve a long term, stable grid utilization without fossil fuels. In the beginning of the following bachelor thesis, basic terms, technologies and actors of the smart grid as well as the legal basics will be explained. This will be followed by an examination of projects that have already been carried out with regard to demand side management options. These are the MeRegio and eTelligence projects funded as a part of the German government´s E-Energy initiative. The main focus of the evaluation lies on the type of information and motivation provided to the end consumer. In both projects customers were to be encouraged to change their consumption behavior through dynamic tariffs and monetary incentives. In the eTelligence project, costumers were also given an extensive, personalized consulting system to support them in their energy-efficient behavior. Based on the findings from these two projects and the SmartER Game, supervised by the Institute of Numerical Methods and Informatics in Civil Engineering at the TU Darmstadt, a concept for increasing energy efficiency through the integration of smart grids and end consumer feedback was developed. A key problem of the evaluated projects is the strong decrease in the interaction rate with the feedback technology after an initial phase of motivation. To counteract this, the concept of this bachelor thesis discusses methods from the field of gamification as well as home automation systems. The aim of the concept is to support the consumer in his development into a smart user. A smart user is characterized by a reflective use of energy and the willingness to adapt his consumption behavior to the grid situation. To achieve this, a part of the concept was implemented in form of a demonstrator. The underlying basis for this demonstrator is a user-friendly, cross-platform Python-Flask web app in combination with the freely available electricity marked data from the SMARD platform (German Federal Network Agency). In order to visualize the grid utilization, a graphic to display the power generation and consumption values for the past 24 and upcoming four hours as well as an “energy traffic light” were implemented. In addition, a simple home managing system was created to help the user manage and control electronic devices. The process manager implemented for this purpose determines the optimal time to carry out the process based on the user inputs and the utilization forecast of the power grid. In combination with flexible tariffs an economic advantage for the end consumer can be created without the need of investing a lot of time or effort in adapting the personal behavior. This should increase the long-term motivation of the user to increase his energy efficiency. At the same time, automatic demand side management makes private households more predictable for grid operators and helps integrating them into the smart grid of the future.