# Techno-Economic Analysis of the Peak Shifting Strategy Based on Time-of-Use Tariff for Cold Stores
## 4 Results and Discussion
### Comparison of Control Effects  
Figure 7 shows the comparison of cooling capacity supply between the original mode, Mode A, and Mode B on the first and third days. The solid black line represents the original mode, while the red and blue dashed lines represent Mode A and B, respectively. The cooling load of the cold stores will change chaotically and rapidly with the external environment, production conditions, etc. Under the original mode, the compressor unit runs at a low load for a long time, and this load may fluctuate with the cooling load, bringing additional energy waste and cost increases. The peak shifting results suggest that the compressor unit only operates during the valley period in Mode A and only in the valley and flat_1# periods in Mode B. Based on the reliable prediction of the cooling load, the operation of the compressor unit is switched to a high load and short time, enhancing the stability. By charging the storage during off-peak hours, the temperature of the warehouse can always be maintained within the appropriate range, so that no additional start-up of the compressor unit is required in both modes. It should be mentioned that while Mode A allows for complete shifting, it requires a larger capacity of the compressor unit, which may result in a potential initial cost increment. As a load-balancing solution, Mode B shifts the load to multiple suitable periods, which is also applicable to cases with a small unit capacity.  
The variation in the warehouse temperature on the first and third days is shown in Figure 8. Basically, the trends before and after optimization are similar, but most of the time, the optimized temperature is slightly lower than the original one. For Mode A, its warehouse temperature reaches its lowest point around 6-8 a.m. and rises slowly during the rest of the day. The temperature of Mode B is in between the original mode and Mode A during the valley period. The temperature curves of the two modes overlap at around 17:00 but still remain below the original mode. At the end of the day, the temperature of the two modes returns to a similar level to the original one. From the perspective of operation safety, the temperature fluctuations in the cold store are another important indicator of an optimization strategy. Mode A results in greater temperature fluctuations than Mode B. The maximum temperature difference of Mode A in two days was 0.35 \({}^{\circ}\)C and 0.38 \({}^{\circ}\)C, while that of Mode B was 0.18 \({}^{\circ}\)C and 0.20 \({}^{\circ}\)C which is only about half of that of Mode A, based on the original temperature curve. Objectively speaking, temperature fluctuations in both modes are quite limited, and thus, the dissipation before and after the adoption of the peak shifting strategy can be approximated to be identical, as mentioned earlier. This is mainly due to the large thermal inertia of the cold store, which can keep the core temperature of the product relatively stable when external factors change temporarily [23; 24].  
Figure 6: Errors between the test and predicted values.  
Figure 8: Comparison of the warehouse temperature on two representative days.  
Figure 7: Comparison of the cooling capacity on two representative days.