Data-analysis-based control of floating solar array location
A data-analysis-based process of controlling a floating solar array location is provided. The process includes providing data analysis-based control of location of the floating solar array on water within a geographical area. The floating solar array has a propulsion system coupled to the floating solar array to facilitate relocating of the floating solar array. The control is configured to identify, using one or more machine learning prediction models, a region of a plurality of regions of the geographical area which meets, for a forecasted time period, a predefined criteria for harvesting energy from the floating solar array. Further, the control is configured to initiate, using the propulsion system, dynamic relocating of the floating solar array to the identified region of the geographical area to facilitate solar energy harvesting from the floating solar array for the forecasted time period.
1 . A computer-implemented method of facilitating solar energy harvesting, the computer-implemented method comprising:
providing data analysis-based control of location of a floating solar array on water within a geographical area, the floating solar array having a propulsion system coupled thereto to facilitate relocating of the floating solar array, the control being configured to:
predictively identify, using one or more machine learning prediction models, a water region of a plurality of water regions of the geographical area which meets, for a forecasted time period, a predefined criteria for harvesting energy from the floating solar array; and
initiate, using the propulsion system, dynamic relocating of the floating solar array to the identified water region of the geographical area to facilitate solar energy harvesting from the floating solar array for the forecasted time period.
2 . The computer-implemented method of claim 1 , wherein the control is further configured to predictively identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, determining potential solar energy generation of the floating solar array if relocated to another water region of the plurality of water regions of the geographical area for the forecasted time period.
3 . The computer-implemented method of claim 2 , wherein the control is further configured to identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, predicting energy loss in relocating the floating solar array to the other water region of the plurality of water regions, wherein net energy harvesting potential of the other water region includes the determined potential solar energy generation of the floating solar array in the other water region reduced by the predicted energy loss in relocating the floating solar array to the other water region.
4 . The computer-implemented method of claim 3 , wherein the predicting energy loss in relocating the floating solar array to the other water region of the plurality of water regions includes predicting energy to be consumed by the propulsion system of the floating solar array in relocating the floating solar array to the other water region.
5 . The computer-implemented method of claim 4 , wherein the predicting energy loss in relocating the floating solar array to the other water region of the plurality of water regions further includes predicting energy to be consumed by an anchor system of the floating solar array in relocating the floating solar array to the other water region.
6 . The computer-implemented method of claim 3 , wherein predicting energy loss in relocating the floating solar array to the other water region of the plurality of water regions comprises predicting floating solar array efficiency loss based on a water temperature change with relocating the floating solar array to the other water region.
7 . The computer-implemented method of claim 1 , wherein the control is further configured to identify, based on data analysis, one or more predicted cloud-shadow-free water regions of the plurality of water regions of the geographical area for the forecasted time period, the identified region being one predicted cloud-shadow-free water region of the one or more predicted cloud-shadow-free water regions of the plurality of water regions of the geographical area.
8 . The computer-implemented method of claim 7 , wherein identifying the one or more predicted cloud-shadow-free water regions for the forecasted time period includes:
data-analysis-based analyzing of one or more satellite images to identify cloud positions relative to the geographical area;
data-analysis-based determining of cloud-shadow paths across the geographical area for the forecasted time period; and
identifying the one or more predicted cloud-shadow-free water regions of the geographical area for the forecasted time period based on the data-analysis-based analyzing of the one or more satellite images and the data-analysis-based determining of cloud-shadow paths across the geographical area.
9 . A computer system for facilitating solar energy harvesting, the computer system comprising:
a memory; and
at least one processor in communication with the memory, wherein the computer system is configured to perform a method, the method comprising:
providing data analysis-based control of location of a floating solar array on water within a geographical area, the floating solar array having a propulsion system coupled thereto to facilitate relocating of the floating solar array, the control being configured to:
predictively identify, using one or more machine learning prediction models, a water region of a plurality of water regions of the geographical area which meets, for a forecasted time period, a predefined criteria for harvesting energy from the floating solar array, wherein the predefined criteria comprises, for the forecasted time period, an optimal net energy harvesting potential for the floating solar array; and
initiate, using the propulsion system, dynamic relocating of the floating solar array to the identified water region of the geographical area to facilitate solar energy harvesting from the floating solar array for the forecasted time period.
10 . The computer system of claim 9 , wherein the control is further configured to predictively identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, determining potential solar energy generation of the floating solar array if relocated to another water region of the plurality of water regions of the geographical area for the forecasted time period.
11 . The computer system of claim 10 , wherein the control is further configured to identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, predicting anticipated energy loss in relocating the floating solar array to the other water region of the plurality of water regions, wherein net energy harvesting potential of the other water region includes the determined potential solar energy generation of the floating solar array in the other water region reduced by the predicted energy loss in relocating the floating solar array to the other water region.
12 . The computer system of claim 11 , wherein the predicting energy loss in relocating the floating solar array to the other water region of the plurality of regions includes predicting energy to be consumed by the propulsion system of the floating solar array in relocating the floating solar array to the other water region.
13 . The computer system of claim 12 , wherein the predicting energy loss in relocating the floating solar array to the other water region of the plurality of water regions further includes predicting energy to be consumed by an anchor system of the floating solar array in relocating the floating solar array to the other region.
14 . The computer system of claim 11 , wherein predicting energy loss in relocating the floating solar array to the other region of the plurality of water regions comprises predicting floating solar array efficiency loss based on a water temperature change with relocating the floating solar array to the other water region.
15 . A computer program product for facilitating solar energy harvesting, the computer program product comprising:
one or more computer-readable storage media and program instructions embodied therewith, the program instructions being readable by a processing circuit to cause the processing circuit to perform a method comprising:
providing data analysis-based control of location of a floating solar array on water within a geographical area, the floating solar array having a propulsion system coupled thereto to facilitate relocating of the floating solar array, the control being configured to:
predictively identify, using one or more machine learning prediction models, a water region of a plurality of water regions of the geographical area which meets, for a forecasted time period, a predefined criteria for harvesting energy from the floating solar array, wherein the predefined criteria comprises, for the forecasted time period, an optimal net energy harvesting potential for the floating solar array; and
initiate, using the propulsion system, dynamic relocating of the floating solar array to the identified water region of the geographical area to facilitate solar energy harvesting from the floating solar array for the forecasted time period.
16 . The computer program product of claim 15 , wherein the control is further configured to predictively identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, determining potential solar energy generation of the floating solar array if relocated to another water region of the plurality of water regions of the geographical area for the forecasted time period.
17 . The computer program product of claim 16 , wherein the control is further configured to identify the water region with the optimal net energy harvesting potential for the forecasted time period by, at least in part, predicting anticipated energy loss in relocating the floating solar array to the other water region of the plurality of water regions, wherein net energy harvesting potential of the other water region includes the determined potential solar energy generation of the floating solar array in the other water region reduced by the predicted energy loss in relocating the floating solar array to the other water region.