*2.1. Conceptual System and Experimental Set-Up*

The system being studied consists of a set of PV panels, residential electrical load, a vanadium flow battery system and a charge controller power electronics module to link the three. The conceptual model is shown in Figure 1a. At every instant of time, the charge controller determines the residential load, assesses the available power output from the PV panels and the state of charge of the battery and aims to serve the load demand from PV to the extent possible. When this is not feasible, it attempts to source power from the battery to meet the demand may be partly or fully. Any excess power from the PV will be sent to the battery to the extent possible. The charge controller will, in practice, regulate the power drawn from the PV panels to meet the combined demand from residential load and battery charging. It will also regulate the power going to (and coming from) the battery by operating the latter within its safe operating voltage window. The present study deals with the VRFB system only, and the roles of load, PV panels and power electronics module are taken over by a battery charger (Bitrode Model), as shown in Figure 1b. The time-wise continuous load and PV output profiles are replaced by discrete time steps (of 11 min) during which the power going to or coming from the battery is held constant, subject to the battery lying within its pre-set voltage limits. The battery power is the difference between the PV output and the load, both averaged over the 11-min interval. The battery power may be positive (when the PV output is higher than the load) or negative (when the load is higher than the PV). At the end of the time step (of 11 min), the power is held at zero for one minute so as to measure the open circuit voltage (OCV) of the battery which is used to monitor its state of charge (SoC).Each experiment simulated the continuous running of the VRFB system over a seven-day period with natural variations of solar irradiations and residential power demand incorporated into the profiles. Setting up of these profiles is discussed below.

## *2.2. Construction of PV Output Profile*

A number of factors such as time of the day, location of PV, season of the year, atmospheric conditions, cell temperature, etc. influence solar insolation at a particular point of time and location. In order to get a realistic simulation of these natural factors in the PV output, solar insolation was simulated using the NREL software SAM for the year 2019 and was compared with global horizontal irradiation (GHI) data for a solar park site in Tumkur, Karnataka, India obtained from Meteonorm 7.0 database [32]. Weekly variation from the first method was found to be between 6.7 and 3.3 kWh/m2 while that from the latter was between 7.7 and 1.98 kWh/m2 over a week in the month of June. In view of the fairly good agreement between the two, seven successive days of insolation data from Meteonorm 7.0 database was chosen to construct the PV output profile for the present study. These give only the total PV output over the day. In order to get a minute-by-minute variation, measurements were carried out over several days using a set of WAAREE WS-325 solar PV panels. These profiles were then normalized by dividing the instantaneous

output power by the maximum daily output over all these days. These normalized profiles would then show how insolation might vary over the day so as to give a total daily output which would be less than the expected (clear day) value. These normalized profiles were then used to create a minute-by-minute profile of PV output over seven consecutive days such that their daily output agreed with that obtained from the Meteonorm database [32]. Figure 2a shows the modeled instantaneous PV output over seven consecutive days in the month of June. Salient numerical values of this output profile are listed in Table 1. It can be seen that the peak to average ratio of solar power is rather high at about 3.

**Figure 1.** (**a**) Schematic diagram of the solar PV-flow battery-residential load integrated system. (**b**) Modelled system for the experimental study.
