Analysis Results of Simulating KIT.TC2.TS1 (Electrical Peak Shaving BESS Sizing)

Analysis Result Description

The purpose of the test is to optimize the size of the battery and to investigate the role of the battery in our local energy system. With the optimization result of the three different scenarios under test, we find out when a battery is necessary and valuable.

• In Scenario 1, the price related to PV and battery system dominate the total cost. The objective function of battery size is monotonically increasing. Therefore, the optimized battery size in this case is 0. The result indicates that from a purely economic perspective considering the present status, using electricity directly from the grid without battery storage is more cost-effective. One possible reasons for this unexpected result is the high cost of the batteries and PV system. According to the proportion of components in the objective function, the power price and self-consumed tax are less influential. The electricity cost drops as the battery size increase and then reaches a steady state. The cost and feed-in income of the system both increase with system size, but the income is less due to a smaller slope and self-consumption at the beginning. We might improve the PV outcome by adding PV peak power with a given battery capacity. However, we want to make the most of renewable energy instead of having too much surplus renewable generation. The target of SmILES project is to maximize the renewable share, which can be indicated as self-sufficiency in the PV battery system. A test on similar PV battery system have illustrated the relationship between battery size, PV size and self-sufficiency performance as shown in Figure 8 [1]. Considering our assumption of specific costs are close, the constraint for the PV power is a reasonable setting to get higher degree of self-sufficiency, but it also limit the possible improvement with extra PV or battery. Another most likely reason is that the 2014 version of Renewable Energy Sources Act (EEG) and its latest update in 2017 attempt to both support and restrict the growth in PV capacity. As can be seen from Figure 9 [7], the feed in tariff for new PV system has been significantly cut. Meanwhile, the electricity price is rising gradually. The combined effect is that the newly installed PV system is not sufficient to cover the system cost.
• In Scenario 2, the costs of PV and battery systems are significantly reduced. Therefore, the sum of cost reduction related to electricity load and feed-in income of PV generation is possible to compensate the costs of the system with suitable battery and PV size.
• Scenario 3, the cost of CO2 is very expensive as shown in Figure 10. This makes it particularly valuable to reduce the electricity consumption from the grid. As the result, there is also an optimal point for our decision variable to minimize the total cost.