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Residential solar photovoltaic (PV) systems are becoming more popular in residential households and contribute to a higher use of renewable energy in Germany. Homeowners are increasingly motivated to increase solar self-consumption and self-sufficiency of their solar PV systems to save costs and reduce their CO2 footprint.

Home energy management systems have been identified in previous research as a solution to improve the self-consumption of solar PV systems. However, studies covering home energy management systems and testing methods were rarely executed in an experimental demonstration to assess the technology's state of the art and maturity. So far, the existing research has not explored the practical behavior of systems with actual products or prototypes.

This thesis addresses this research gap by applying an experimental approach to assess the optimization performance of home energy management systems regarding solar self-consumption and self-sufficiency. This is achieved by the development of a test environment including a data collection method and test cases, a self-sufficiency and self-consumption assessment, and a device communication control characteristics exploration of a home energy management system on the market. The test environment includes a solar PV system, a variable load, and two different electric vehicle chargers connected to an electric vehicle.

Four different test cases and an experimental test method including a test environment to simulate household scenarios were presented. The test environment can simulate power flows and is able to measure power data and communication data between devices. The results from the self-consumption assessment vary with each test case between a ratio of 19.82 % and 72.2 %. Self-sufficiency shows overall high values between 92.23 % and 99.84 %. In contrast to prior research, the comparison to the benchmark case showed that in none of the four test cases, the home energy management system was able to optimize the self-consumption above the benchmark ratio.