## 4 Results
### Analysis and Discussion
Here, the black bar chart represents the power supply from the main grid, the light blue bar chart indicates the power of switchable loads, the light yellow bar chart shows the photovoltaic power generation, the green bar chart depicts the wind power generation, the blue bar chart is for the diesel engine's power generation, the red line chart represents the regulation power of controllable loads (including critical loads), the grey bar chart shows the power shedding of switchable loads, and the pink bar chart represents the battery's charging and discharging power. Positive values for the main grid power supply and battery discharging indicate power supply to the system/battery discharge, and negative values indicate selling power to the main grid/battery charging. From the results in Figure 3, it is evident that the management strategies under different objective preferences have significant differences. Strategy (a) represents the  
Figure 3: Management strategies under different objective preferences with three controllable loads. management strategy under the lowest dependence on the main grid, with the main grid supply power being noticeably the lowest and the grid dependence amounting to only USD 87.2 (for uniform comparison, all costs are calculated in U.S. dollars), but the system's electricity cost is USD 34,335.3, indicating that the system is primarily powered by diesel generation, renewable generations, and energy storage batteries. However, because the diesel generator's cost of generation is significantly higher than the electricity cost from the main grid, this leads to a noticeable increase in the system's total electricity cost. Conversely, strategy (d) shows a significant increase in the main grid supply power, with grid dependence at USD 2151.4 but at a considerably reduced cost (USD 18,040.3), indicating that utilizing relatively cheaper main grid supply can effectively reduce system costs, albeit at the expense of significant dependence on the main grid. The renewable energy generation situation under strategy (a) shows that around midnight, when photovoltaic cannot generate electricity and wind power is also low, but the base's critical loads still need to run, the designed algorithm prioritizes power supply from the main grid, followed by energy storage battery supply to meet the demand of critical loads; around noon, when renewable energy sources like photovoltaic and wind have sufficient generation and load demand decreases, the algorithm charges the energy storage battery to meet the potential high load demand later, showing the rationality of the method. It is worth noting that strategies (a) and (d) are the first and last on the Pareto front, representing management strategies under a single-objective preference, while (b) and (c) are two randomly selected strategies from the middle of the Pareto front, representing management strategies considering a balance between the two objectives. Therefore, it can be seen that the multi-objective optimization method designed in this paper can provide multiple management strategies under different objective preferences in a single run, thereby offering various choices for decision-makers, dynamically managing the system's energy storage, generation, load shedding, and load scheduling based on the available external power supply conditions. Figure 4 displays the management strategies under different objective preferences with four controllable loads, where (a-d) represent the strategies under various objective preferences. Compared to the scenario with three controllable loads shown in Figure 3, the addition of one more controllable load significantly changes the system's management mode. During the peak energy demand period of critical and controllable loads from 13:00 to 15:00, the management algorithm designed in this paper tends to ensure energy balance by supplying power through the energy storage system and shedding loads to meet the system's electricity demand.