Use of computationally generated thermal energy
In one aspect, a computing device-implemented method includes receiving at least one triggering event signal from one or more components of a heat recovery system. The method also includes determining, based in part on the at least one triggering event signal, a computation workload assignment to be executed on one or more computation devices. The method further includes sending one or more command signals to the one or more computation devices. The one or more command signals include a portion of the computation workload assignment for execution by the one or more computation devices. The method also includes initiating capture of heat energy to be stored in one or more heat reservoirs, the heat energy being generated by the one or more computation device based upon the computation workload assignment.
1. A computing device-implemented method comprising:
predictively determining a demand for thermal energy;
determining a computation workload assignment to be executed on one or more computation devices having a machine learning capability;
sending one or more command signals to the one or more computation devices, wherein the one or more command signals include a portion of the computation workload assignment for execution by the one or more computation devices; and
initiating capture of thermal energy to be stored in one or more thermal energy reservoirs for satisfying the predicted thermal energy demand, the thermal energy being generated by the one or more computation devices based upon the computation workload assignment.
2. The computing device-implemented method in claim 1 , wherein the one or more command signals include information that represents type, size and execution speed of the portion of the computation workload assignment.
3. The computing device-implemented method of claim 1 , wherein the one or more command signals include a request for thermal energy generation information from the one or more computation devices.
4. The computing device-implemented method of claim 1 , further comprising using the captured thermal energy in one or more building end use systems.
5. The computing device-implemented method of claim 1 , wherein the one or more thermal energy reservoirs include a casing made of one or more phase change material.
6. The computing device-implemented method of claim 1 , wherein the one or more computation devices include a casing made of one or more phase change material.
7. The computing device-implemented method in claim 1 , wherein the thermal energy recovery system comprises a cooling system.
8. The computing device-implemented method in claim 1 , wherein the predictive determination is performed by the one or more computation devices at a thermal energy recovery site.
9. The computing device-implemented method in claim 1 , wherein the predictive determination is performed in a distributed manner.
10. The computing device-implemented method of claim 1 , wherein the computing device is one of the one or more computation devices.
11. The computing device-implemented method of claim 1 , wherein determining the computation workload assignment comprises predictively determining the computation workload assignment.
12. The computing device-implemented method of claim 1 , wherein the computing device uses cryptographic tokens to define a decentralized entity.
13. A system comprising:
a computing device comprising:
a memory configured to store instructions; and
a processor to execute the instructions to perform operations comprising:
predictively determining a demand for thermal energy;
determining a computation workload assignment to be executed on one or more computation devices having a machine learning capability;
sending one or more command signals to the one or more computation devices, wherein the one or more command signals include a portion of the computation workload assignment for execution by the one or more computation devices; and
initiating capture of thermal energy to be stored in one or more thermal energy reservoirs for satisfying the predicted thermal energy demand, the thermal energy being generated by the one or more computation devices based upon the computation workload assignment.
14. The system of claim 13 , wherein the one or more command signals include information that represents type, size and execution speed of the portion of the computation workload assignment.
15. The system of claim 13 , wherein the one or more command signals include a request for thermal energy generation information from the one or more computation devices.
16. The system of claim 13 , further comprising using the captured thermal energy in one or more building end use systems.
17. The system of claim 13 , wherein the one or more thermal energy reservoirs include a casing made of one or more phase change material.
18. The system of claim 13 , wherein the one or more computation devices include a casing made of one or more phase change material.
19. The system of claim 13 , wherein the thermal energy recovery system comprises a cooling system.
20. The system of claim 13 , wherein the predictive determination is performed by the one or more computation devices at a thermal energy recovery site.
21. The system of claim 13 , wherein the predictive determination is performed in a distributed manner.
22. The system of claim 13 , wherein the computing device is one of the one or more computation devices.
23. One or more non-transitory computer readable media storing instructions that are executable by a processing device, and upon such execution cause the processing device to perform operations comprising:
predictively determining a demand for thermal energy;
determining a computation workload assignment to be executed on one or more computation devices having a machine learning capability;
sending one or more command signals to the one or more computation devices, wherein the one or more command signals include a portion of the computation workload assignment for execution by the one or more computation devices; and
initiating capture of thermal energy to be stored in one or more thermal energy reservoirs for satisfying the predicted thermal energy demand, the thermal energy being generated by the one or more computation devices based upon the computation workload assignment.
24. The non-transitory computer readable media of claim 23 , wherein the one or more command signals include information that represents type, size and execution speed of the portion of the computation workload assignment.
25. The non-transitory computer readable media of claim 23 , wherein the thermal energy recovery system comprises a cooling system.
26. The non-transitory computer readable media of claim 23 , wherein the predictive determination is performed by the one or more computation devices at a thermal energy recovery site.
27. The non-transitory computer readable media of claim 23 , wherein the predictive determination is performed in a distributed manner.
28. The non-transitory computer readable media of claim 23 , wherein the computing device is one of the one or more computation devices.