The market for microinverters is growing, especially in Europe. Driven by the strongly rising prices for electricity, many small photovoltaic energy systems are being installed. Since monitoring for these plants is often quite costly, their yields are often not logged. Since 2014, microinverters have been studied at the University of Paderborn. The investigations are divided into indoor and outdoor tests. In the indoor area conversion efficiencies as a function of load have been measured with high accuracy and ranked according to Euro- and CEC weightings. In the outdoor laboratory, the behavior in the real world is tested. Energy yields have been measured outdoors via identical and calibrated crystalline silicon PV modules. Here, the investigations were carried out with modules of the power of 215 Wp until the year 2020. Because of the increasing module power nowadays, modules with an output of 360 Wp are now being used. To assess the influence of PV module size, two extremes have been investigated: A rather small module with 215 Wp - as it has been used 10 years ago, and a brand-new module (2021) offering 360 Wp. Both types of modules contain 60 solar cells in series connection. Appling the low-power modules, the challenge for the different micro-inverters has been during weak-light conditions, using the high-power modules, some inverters temporarily reach their power limits and yield is reduced. A method using a reference configuration of inverter & module and a linear equation resulting in the actual yield, any module & inverter configuration can be characterized by just the two coefficients.

This paper provides a hybrid energy system model created in Matlab/Simulink which is based on photovoltaics as its main energy source. The model includes a hybrid energy storage which consists of a short-term lithium-ion battery and hydrogen as long-term storage to ensure autonomy even during periods of low PV production (e.g., in winter). The sectors heat and electricity are coupled by using the waste-heat generated by production and reconversion of hydrogen through an electrolyser respectively a fuel cell. A heat pump has been considered to cover the residual heat demand (for well insulated homes). Within this paper a model of the space heating system as well as the hot water heating system is presented. The model is designed for the simulation and analysis of a whole year energy flow by using a time series of loads, weather and heat profiles as input. Moreover, results of the energy balance within the energy system by simulation of a complete year by varying the orientation (elevation and azimuth) of the PV system and the component sizing, such as the lithium-ion battery capacity, are presented. It turned out that a high amount of heating energy can be saved by using the waste heat generated by the electrolyser and the fuel cell. The model is well suited for the analysis of the effects of different component dimensionings in a hydrogen-based energy system via the overall energy balance within the residential sector.

Access to precise meteorological data is crucial to be able to plan and install renewable energy systems such as solar power plants and wind farms. In case of solar energy, knowledge of local irradiance and air temperature values is very important. For this, various methods can be used such as installing local weather stations or using meteorological data from different organizations such as Meteonorm or official Deutscher Wetterdienst (DWD). An alternative is to use satellite reanalysis datasets provided by organizations like the National Aeronautics and Space Administration (NASA) and European Centre for Medium-Range Weather Forecasts (ECMWF). In this paper the “Modern-Era Retrospective analysis for Research and Applications” dataset version 2 (MERRA-2) will be presented, and its performance will be evaluated by comparing it to locally measured datasets provided by Meteonorm and DWD. The analysis shows very high correlation between MERRA-2 and local measurements (correlation coefficients of 0.99) for monthly global irradiance and air temperature values. The results prove the suitability of MERRA-2 data for applications requiring long historical data. Moreover, availability of MERRA-2 for the whole world with an acceptable resolution makes it a very valuable dataset.

Efficiencies and energy yields of microinverters available on the market during 2014‒2021 have been measured, compared, and ranked. Conversion efficiencies as a function of load have been measured indoors with high accuracy and ranked according to Euro- and CEC weightings. Energy yields have been measured outdoors via identical and calibrated crystalline silicon PV modules of 215 Wp (until 2020) and 360 Wp (starting 2021). Inverters with two inputs have been fed by two of those modules. DC input, AC power output and energy yield of each microinverter have been recorded by individual calibrated electricity meters. CEC and EU efficiency rankings have been computed and compared. To assess the influence of PV module size, two extremes have been investigated: A rather small module with 215 Wp - as it has been used 10 years ago, and a brand-new module (2021) offering 360 Wp. Both types of modules contain 60 solar cells in series connection. Appling the low-power modules, the challenge for the different micro-inverters has been during weak-light conditions, using the high-power modules, some inverters temporarily reach their power limits and yield is reduced. A method using a reference configuration of inverter & module and a linear equation y = ax + b resulting in the actual yield, any module & inverter configuration can be characterized by just the coefficients a and b.

With its growing population and industrialization, DREs, and solar technologies in particular, provide a sustainable means of bridging the current energy deficit in Africa, increasing supply reliability and meeting future demand. Data acquisition and data management systems allow real time monitoring and control of energy systems as well as performance analysis. However commercial data acquisition systems often have cost implications that are prohibitive for small PV systems and installations in developing countries. In this paper, a multi-user, multi-purpose microgrid database system is designed and implemented. MAVOWATT 270 power quality analyzers by GOSSEN METRAWATT, raspberry pi modules and sensors are used for measuring, recording and storing electrical and meteorological data in East Africa. Socio-economic data is also stored in the database. The designed system employs open source software and hardware solutions which are best suited to developing regions like East Africa due to the lower cost implications. The expected results promise a comprehensive database covering different electro-technical and socio-economic parameters useful for optimal design of microgrid systems.

Efficiencies and energy yields of microinverters available on the market during 2014‒2020 have been measured, compared, and ranked. Conversion efficiencies as a function of load have been measured indoors with high accuracy and ranked according to Euro- and CEC weightings. Energy yields have been measured outdoors via identical and calibrated crystalline silicon PV modules of 215 Wp each. Inverters with two inputs have been fed by two of those modules. DC input, AC power output and energy yield of each micro-inverter have been recorded by individual calibrated electricity meters. Apparently, some inverters have been optimized for high irradiance levels and ranked better at the CEC efficiency ranking, others performed very well also at low irradiance levels, thus ranking higher at in the EU efficiency ranking. Efficiency ranks are slightly deviating from rankings by energy yield measurements. At one inverter, a slow MPPT algorithm that barely could follow quickly changing irradiance levels is most probably responsible for this effect. Another inverter switched off for a while after operation at high power, another one failed permanently. Apparently, some inverters are been optimized to show excellent datasheet ratings for EU- or CEC- efficiency. On the other hand, two inverters (each featuring two inputs) did not show an outstanding performance at the EU- and CEC-ratings but achieved leading ranks for AC energy yields. For the customer, AC yield is a major performance indicator of a microinverter and should be included in the datasheet.

To provide a simple instrument to operate residential Load-Shifting or Demand-Side-Management systems, the measurement of the actual grid frequency seems to be an appropriate method. Due to the present inflexibility and the lack of sufficient throttling capabilities of lignite and nuclear power plants, a surplus of electricity generation occurs during periods of high wind and solar power generation. While the specific CO2- emission is decreasing then ‒ due to the increased share of Renewables, the grid frequency is increasing (to a certain limit). Using the grid frequency as an indicator to switch-on and off certain loads (loads that do not require power permanently (e.g. dishwashers, washing machines, dryers, fridges and freezers, heaters) could provide a simple, inexpensive demand-side management indicator to lower specific CO2‒emssions and costs (if a dynamic consumption tariff is available). To check the truthfulness of that hypothesis, the grid and frequency data of the German grid of the year 2018 have been collected and a the correlation between grid frequency, power surplus, share of renewables vs. CO2-contents and price at the European energy exchange (EEX) have been calculated. The results show: Correlation between frequency and share of renewables is quite low (r = 0.155) due to the fact that primary grid control quickly compensates deviations from the 50 Hz nominal frequency. There is a good anti-correlation (r = - 0.687) between the EEX‒prices and the share of renewables in the grid. Over the years, correlation between electricity trading prices (EEX) and CO2 emissions is quite good (r =0.665), within the one year (2018) that correlation almost doesn’t exist, possibly due to the inflexibility of the bulky lignite power plants that even operate at negative prices.

Due to the strong reduction of PV prices, storage plays a dominating role in overall system costs. A steeper elevation angle would result in a more balanced seasonal PV yield, at the cost of PV yield reductions during summer, but allowing reduced storage capacities. Additionally, the effect of a single-axis tracking system has been investigated, generating more electricity during the morning and evening hours, thus reducing daily storage requirements. The necessary PV size and storage capacities required for the German energy supply (1,500 TWh after electrification of all sectors) via 100% renewable energies and a 50% solar share have been calculated via the HOMER Pro software, considering the bridging of periods of "dark lulls“ in winter, using costs of 2030 (Table 1). Results: The increase of module elevation angles above the typical 30° leads to a reduction of investment and supply costs. The optimum is reached at a cost reduction of -1.5% for an elevation angle at the latitude of the installation site. An explanation is that high elevation angles are favorable for clear winter days, but not at all for the critical days with diffuse irradiance only, so the battery capacity must be increased. For the same reason, tracking systems do not offer any cost advantage (at least for the ones without an option for horizontal positioning during diffuse days).

During comparative measurements of different PV microinverters, two yield issues came up that could not be explored via conventional efficiency measurements, but do have a significant impact on electrical energy yield: First category of issues are either sluggish or nervously acting maximum–power–point–tracking devices, which lead to reduced energy yields. The other category of issues is thermal: As a first explanation for observed reduced energy yields, it has been assumed that the conversion efficiency degrades at higher operating temperatures. This matter has been investigated in this article: A change in conversion efficiency could not be observed for elevated operation temperatures up to 50°C, despite high-precision and repeated measurements. But it was found that some inverters temporarily interrupted (or entirely stopped) operation after long periods of running at high temperatures. Also, a reduction in potential maximum power output has been detected for those inverters. Summarizing: With a high degree of certainty it can be stated that those reported yield losses have been caused by the temporary shutdowns and power limitations of the inverters.

Due to the present inflexibility and the lack of sufficient throttling capabilities of lignite and nuclear power plants, a surplus of electricity generation occurs during periods of high wind and solar power generation in the German electricity grid. While the specific CO2-emission is decreasing then - due to the increased share of Renewables, the grid frequency should be increasing (to a certain limit). Using the grid frequency as an indicator to switch-on and -off certain loads (loads that do not require power permanently (e.g. dishwashers, washing machines, dryers, fridges and freezers, heaters) could provide a simple, inexpensive demand-side-management indicator to lower specific CO2-emissions and costs (if a dynamic consumption tariff is applied). To check the truthfulness of that hypothesis, the grid and frequency data of the German grid of the year 2018 have been collected and the correlations between grid frequency, share of renewables, CO2-contents, and actual price at the European energy exchange (EEX) have been calculated. The results show: Correlation between grid frequency and the share of renewables is quite low (r=0.155) due to the fact that primary grid control quickly compensates deviations from the 50 Hz nominal frequency. As expected, there is a good anti-correlation (r=-0.687) between the EEX-prices and the share of renewables in the grid. Over the years, correlation between electricity trading prices (EEX) and CO2 emissions is quite good (r=0.665), within the one year (2018) that correlation almost doesn't exist, possibly due to the inflexibility of the bulky lignite baseload power plants that even operate at negative prices.

To compare efficiency and yield of many micro-inverters available on the world market in 2014-2020, an in- and outdoor test laboratory at the University of Paderborn has been set up. The inverters have been fed by identical and calibrated crystalline silicon PV modules of 215 Wp. To monitor accurately DC input, AC power output and energy yield, each of the micro-inverters has been equipped with a calibrated electricity meter. For micro-inverters requiring control units for grid-feeding that has been acquired also. The comparison covers efficiency-load characteristics as well as electrical energy yields. Purchase costs vary considerably between the models in comparison, sometimes inverter costs are higher than module costs, particularly if an additional grid-connection or interface device is needed for operation. The weighted conversion efficiency according to EU and CEC standards has been measured and calculated. While some inverters have been optimized for high irradiance levels, they ranked better at the CEC efficiency, others performed very well also for low irradiance levels, thus ranking higher at in the EU-efficiency tables. These results are deviating from the actual energy yield measurements, which show a slightly different ranking. At one inverter, an accurate, but very slow MPPT algorithm that barely could follow quickly changing irradiance levels could be the reason for this effect. Another inverter switched off after operation at high power output for a while. Apparently, some inverters are been optimized to show excellent EU and CEC efficiency ratings. Two of the inverters featuring two inputs did not show an exceptional performance at the EU- and CEC-ratings, but they achieved top ranks at the AC energy yield for the first years. For the customer, the AC yield is a major performance indicator of any microinverter and should be included in the datasheet.