250 350 300 400 450 150 200 100
Wind energy (kWh) Wave energy (kWh) Solar energy (kWh)
34.9433 100.027
33.2397 91.4867
31.2308 82.6235
28.4734 73.9121
65.9216
57.9323
49.7464
41.4836
33.0946
253.351
215.31
166.169
141.355
121.987
122.933
123.449
129.562
50
88.6755 105.946 118.536
51.8531
0
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Jan
Dec
50 70 60 80 90 30 40 10 20
8.25051
8.86319
8.54012
8.36305
8.71145
51.8531
8.8893
49.1409
17.2704 12.5905 7.5917
38.0405
7.99048 11.7928
36.8225
7.9893 6.11309
24.8141
8.38902 8.26283 8.18588
0
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
100
13.29
14.77
17.69
17.65
24.01
30.38
32.1
80
34.83
45.13
7.6
53.95
66.11
64.54
10.6
60
14.67
13.76
83.56
20.33
81.88
77.7
78.78
40
68.39
23.86
59.02
53.23
51.41
20
28.08
29.72
34.53
22.19
7.39
0
Jan
Feb
Mar
Apr
May
June
July
Aug
Sept
Oct
Nov
Dec
Figure 2 Monthly analysis of the cumulated energy production, the monthly energy production and the monthly repatriation of energy sources
several sources can be used, such as wind turbines, solar panels, wave converters. These energy sources can be combined to improve performance and reliability. However, the energy produced fluctuates due to uncontrollable conditions and does not correspond continuously to the power demand. Energy storage is, therefore, mandatory. Using water electrolysis, this energy can be stored as hydrogen. Since hydrogen has a low density in ambient conditions, it is compressed before storage in high-pressure tanks. When the power demand exceeds the power produced by the solar panels, the wind turbine and the wave converter, a fuel cell generates the surplus electric power. This kind of system involves a multitude of complex physics. That is a typical case where a system model (see Figure 1 ) can help better understand physical phenomenon and interactions between various subsystems and components. Hence, evaluating virtual design options makes it possible to better size components, integrate them in the best architecture and better
control them to select the right design on the first attempt. Off-the-shelf and validated models of the system simulation software tools are based on lumped parameters. So simulations can precede the detailed design of the components and be performed very early in the system design stages. Moreover, that makes simulation run very fast, enabling you to evaluate many configurations and scenarios, including ones with long time-range simulations. Further into the project, when the subsystems are better defined, models can still be refined, integrating more physics and capturing more dynamics. That makes it possible to improve simulation accuracy, allowing you to focus more on the component’s design. The application case of this article is based on the following assumptions regarding the definition of the system: • Wind turbines: Wind turbines have a 50 m radius. Their pitch is controlled, depending on the wind orientation. The wind orientation is variable.
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