Solar energy paper index
MAES AS A DATA-DRIVEN TRAINING PLATFORM: DAYLIGHT HIGH-LOAD OPERATION WITH PHOTOVOLTAIC SUPPORT
One-line summary
A solar energy research paper on MAES AS A DATA-DRIVEN TRAINING PLATFORM: DAYLIGHT HIGH-LOAD OPERATION WITH PHOTOVOLTAIC SUPPORT.
Engineering notes
Engineering notes will be added by the Power for Solar editorial team.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为光伏效率、钙钛矿太阳能电池、储能技术、太阳能热利用、BIPV、并网技术等高价值论文补充中文说明。
Original abstract
This paper presents a short experimental episode based on the MAES prototype - Mobile Module for Ensuring Energy Autonomy from Sustainable Sources, interpreted as a data- driven training platform for tactical energy autonomy [1]. The analysis goes one step further than previously published research by focusing on daylight operation under high three-phase load and significant photovoltaic contribution. During the analyzed interval, MAES supplied an AC load of approximately 11-12 kW, while the photovoltaic subsystem generated between 4.0 and 5.1 kW instantaneously. The measured data show that solar input reduced the battery discharge power from values close to 12 kW, typical for operation without photovoltaic production, to approximately 7.2-7.9 kW. The paper also integrates short-term energy balance screenshots, which indicate that cloudy days affected solar yield and reduced the expected photovoltaic contribution. The results confirm the usefulness of MAES as a living laboratory for military technical education and as a basis for further development of predictive autonomy models integrating load, PV production, battery state of charge and operational constraints.
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