@inproceedings{24550,
  abstract     = {{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.}},
  author       = {{Krauter, Stefan and Bendfeld, Jörg}},
  booktitle    = {{Proceedings of the 38th European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC 2021)}},
  isbn         = {{3-936338-78-7}},
  keywords     = {{AC-modules, Microinverter, Power Conditioning, Efficiency, Yield, PV module size, saturation, performance}},
  pages        = {{659 -- 663}},
  title        = {{{Module-Inverters (Microinverters): Influence of Module Size on Conversion Efficiencies and Energy Yields}}},
  doi          = {{10.4229/EUPVSEC20212021-4CO.3.4}},
  year         = {{2021}},
}

@inproceedings{18387,
  abstract     = {{ 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.}},
  author       = {{Krauter, Stefan and Bendfeld, Jörg}},
  booktitle    = {{Proceedings of the EU PVSEC 2020 }},
  issn         = {{3-936338-73-6}},
  keywords     = {{AC-modules, Microinverter, Power Conditioning, Thermal Performance, Ventilation, Stability, Efficiency, Yield}},
  location     = {{online}},
  pages        = {{1179 -- 1180}},
  title        = {{{Elevated Temperatures Affecting Efficiency, Overall Performance and Energy Yield of PV Microinverters}}},
  doi          = {{10.4229/EUPVSEC20202020-4AV.3.6}},
  year         = {{2020}},
}

@inproceedings{16899,
  abstract     = {{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.}},
  author       = {{Krauter, Stefan and Bendfeld, Jörg}},
  booktitle    = {{Proceedings of the 47th IEEE Photovoltaic Specialists Conference (PVSC 47) JUNE 15 - AUGUST 21, 2020 VIRTUAL MEETING}},
  issn         = {{ 0160-8371}},
  keywords     = {{yield, AC, micro-inverter, MPPT, CEC rating, EU efficiency, Photovoltaic, Solar}},
  location     = {{VIRTUAL MEETING}},
  pages        = {{1429--1432}},
  publisher    = {{IEEE}},
  title        = {{{Comparison of Microinverters: Update on Rankings of Conversion Efficiencies and Energy Yields}}},
  doi          = {{10.1109/PVSC45281.2020.9300953}},
  year         = {{2020}},
}

@inproceedings{9760,
  abstract     = {{Self-optimizing systems are able to adapt their behavior autonomously according to their current self-determined objectives. Unforeseen influences could lead to dependability-critical behavior of the system. Methods are required which secure self-optimizing systems during operation. These methods to increase the dependability of the system should already be taken into consideration in the design process. This paper presents a guideline for the dependability-oriented design of self-optimizing systems, which integrates established classical methods like failure mode and effects analysis as well as methods based on self-optimization. On the one hand self-optimization is used to increase the dependability of the system by integrating objectives like safety, availability, and reliability to the objectives of the system. On the other hand methods are required to ensure the self-optimization itself. As basis for this guideline serves the principle solution of the system. The six phases of the guideline extend the design process and lead to an enhanced principle solution. Additionally, the guideline illustrates phases to implement and validate the self-optimizing system. The proposed guideline is applied to an innovative rail-bound vehicle, called RailCab, which is equipped with self-optimizing function modules.}},
  author       = {{Sondermann-Wölke, Christoph and Hemsel, Tobias and Sextro, Walter and Gausemeier, Jürgen and Pook, Sebastian}},
  booktitle    = {{Industrial Informatics (INDIN), 2010 8th IEEE International Conference on}},
  keywords     = {{RailCab, dependability-critical behavior, dependability-oriented design, failure mode, rail-bound vehicle, secure self-optimizing systems, self-optimizing function modules, optimisation, railways, self-adjusting systems}},
  pages        = {{739 --744}},
  title        = {{{Guideline for the dependability-oriented design of self-optimizing systems}}},
  doi          = {{10.1109/INDIN.2010.5549490}},
  year         = {{2010}},
}

@inproceedings{9742,
  abstract     = {{New mechatronic systems, called self-optimizing systems, are able to adapt their behavior according to environmental, user and system specific influences. Self-optimizing systems are complex and due to their non-deterministic behavior comprise hidden risks, which cannot be foreseen in the design phase of the system. Therefore, this paper presents modifications of the current condition monitoring policy, to be able to cope with this new kind of systems. Beside avoiding critical situations evoked by self-optimization, the proposed concept uses self-optimization to increase the dependability of the system. In this case, the concept is applied to the active guidance module of an innovative rail-bound vehicle.}},
  author       = {{Sondermann-Wölke, Christoph and Sextro, Walter}},
  booktitle    = {{Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns, 2009. COMPUTATIONWORLD '09. Computation World:}},
  keywords     = {{condition monitoring, mechatronic systems, rail bound vehicle, rail guidance module, self-optimization, self-optimizing function modules, condition monitoring, mechatronics, railway rolling stock, self-adjusting systems}},
  pages        = {{15 --20}},
  title        = {{{Towards the Integration of Condition Monitoring in Self-Optimizing Function Modules}}},
  doi          = {{10.1109/ComputationWorld.2009.47}},
  year         = {{2009}},
}