4.4.2. Time-Of-Use Prices

This experiment, conducted on 15 May 2020, tested the response of SPO to the winter TOU rates of the B19 tariff [85]. This tariff contains time of use based energy prices and demand charges. Figure 9a shows the solar irradiance, demand and energy charges. The peak price window for both demand and energy charges are from 16:00 to 21:00 Figure 9b shows the battery and net load responses, controlled by the SPO. Figure 9c shows the HVAC zone setpoints that were generated by SPO and the actual temperatures for these two zones (gaps in the chart are due to missing data, where the thermostats temporarily lost network connection).

In response to the peak prices, the battery began to charge quite late until the PV generation began to ge<sup>t</sup> online and charged up to its maximum of 95% of its capacity right before 16:00 and started to discharge until 21:00, the end of the peak period. The HVAC systems started pre-cooling very early at around 07:00 Then, it started to increase the indoor temperatures once the battery began to charge. During the beginning hours of the peak period, the temperatures were maintained as high to reduce the HVAC load. Then, the HVAC west began to cool down the space as the accumulated penalty of deviating from the setpoint began to ge<sup>t</sup> high. With regards to the refrigeration systems, there were still hardly any periods when the temperatures were allowed to rise, but they always remained within the limits.

Table 4 compares total electricity costs incurred in these 24 hour for the SPO optimized building against the building's baseline load for this day (shown in Figure 9b). The energy cost is calculated as described in the previous experiment and it can be seen that SPO was able to save 10.33% of the total energy cost. Calculating the total demand cost and the subsequent savings is slightly more complicated. The total demand cost is the sum of the demand costs across all the different TOU rate periods (e.g., 16:00–21:00). The maximum load (load refers to the 15-min average power consumption) for each rate period across the whole billing cycle (typically monthly), or, in this case, the whole day, multiplied by the corresponding demand charge is the demand cost for that period. This introduces the caveat that the demand cost shown in Table 4 might not be the final demand cost for the full billing cycle. Hence, for the purposes of evaluating this experiment, the billing cycle is assumed to be one day. Under this assumption, SPO reduced the total demand cost by \$21.13. For a realistic billing cycle of a month, through continuous peak demand managemen<sup>t</sup> by SPO, much higher demand cost savings can be accrued.


**Table 4.** Comparison of estimated costs for energy and demand between SPO and Baseline controls.

**Figure 9.** (**a**) SPO's response to a TOU tariff with both demand charges and energy costs and varying solar irradiance. (**b**) The battery is used effectively for reducing net load during peak price hours. (**c**) SPO changes the thermostat setpoints to vary the zone temperature. Preferred temperatures: 20.56 ◦C (69 ◦F) for the West Zone and 21.67 ◦C (71 ◦F) for the East Zone.

## 4.4.3. Demand Limiting Event

Demand limiting "refers to shedding loads when pre-determined peak demand limits are about to be exceeded ... and this is typically done to flatten the load shape when the pre-determined peak is the monthly peak demand" [98]. Coordinated load limiting efforts across multiple buildings helps to reduce the stress on the utility during peak hours.

An experiment was conducted in May 2020 to test the response of SPO to a demand-limiting signal. The signal constrained demand to 26 kW from 06:00 to 08:00., given that minimum baseline load during this period is 32.9 kW. Figure 10a depicts the response of SPO: the building reduced its average power consumption at 06:00 to 26.30 kW from 32 kW at 05:30. Figure 10b shows that this was achieved by reducing in the power consumption of the two HVAC units from 06:00 (in yellow and

orange) and a drop in power consumption of the freezer unit at 07:30. However, the battery state of charge remained nearly flat throughout the event as SPO decided not to employ the battery during it. This is evidence of SPO's intelligent load control capabilities as it is able to coordinate the controllable load without depending on the battery to handle grid signals.

**Figure 10.** (**a**) Reduction in net load during a 26 kW demand limiting grid signal from 06:00 to 08:00 (**b**) Breakdown of controlled loads; HVAC and freezer loads cause the decrease in net load consumption; the battery was not used during this event.
