## 1 Introduction
### Detailed System Performance Observations, Evaluation, and Analysis  
After configuring the microgrid connections, electric loads, storage system, and system management software in May 2019, a detailed case study of the system performance started, and the electric characteristics were monitored almost daily, at regular time intervals, and in varying weather conditions. The amounts of storage-ready electric energy generated by all four individual (differently-oriented) bundles of solar windows were monitored in different conditions. Energy losses at the microinverters and inside cabling would have amounted to several percent of the total generated energy, yet these were ignored and not monitored specifically. Regular system performance and electric output observations continued until the end of June 2019, resulting in obtaining a large dataset suitable for system performance characterization. Weather-dependent solar irradiation and cumulative daily solar exposure data were also collected (at the same times as the electric outputs) from the online live data broadcasts of nearby Wanneroo Weather Station operated by the Department of Primary Industries and Regional Development, Government of Western Australia [36]. Additional solar geometry-related data for the current (and local) Sun azimuth and Sun altitude angles at the times of data logging were recorded from SunCalc.org online solar astronomy calculator [37]. Figure 4 shows the dependencies of the generated electric power and stored energy on the time of day, measured over several sunny days in May and June of 2019. It is interesting to note the high consistency of the power generation on different sunny days, even measured weeks apart. The effects of variable weather conditions such as cloud cover are also seen in the graphs. Figure 4: \(Cont.\)  
It can also be noted from the data of Figure 4 that the time distribution of the power generation follows the \"bell curve\" shape well-known in conventional roof-based PV installations. This is despite the fact that this installation does not include any optimally-tilted, north-oriented roof sections, but rather is composed of an unequal number of PV generators placed into four deployment areas of substantially different geometric orientations, tilts, and shading exposure conditions. Also notable is the almost-linear time dependency of the stored electric energy, observed until late afternoons on sunny days. Considering that the sun-path geometry over the course of day involves large changes in both the azimuth and sun altitude angles, all occurring simultaneously with weather- and time-dependent irradiation intensity variations across all planes, these data confirm that all four main parts of this solar-window atrium provided important contributions to the daily energy generation function. Figure 5 shows the solar irradiation intensity dependencies of the output power (recorded on different sunny days during the study), and the dependency of stored electric energy on the total cumulative amount of incoming solar energy received during the day by each 1m\({}^{2}\) of horizontal (land) surface area. Both datasets are notable in terms of the data points clustering around nearly-linear function shapes. Since only the horizontal-plane solar irradiation intensity was measured by the weather station, and because most of the daily total energy was being generated by the eight vertically-mounted north-facing windows, the data trends seen in Figure 5a,b (and also in Figure 4b) confirm the relative insensitivity of the electric power output and energy storage rate on the geometry of sunlight incidence. This is because the transparent solar windows are of solar concentrator design type, which improves the angular stability of power generation compared to conventional PV panels. It can be noted from Figure 5a that the maximum output power readings have been recorded for moderate horizontal-plane solar irradiance values between 300-400 W/m\({}^{2}\).