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 computer-implemented method comprising:
receiving, at a controller, first data indicative of renewable energy generated at a site, wherein the site comprises one or more building end use systems configured to consume energy;
predictively determining, by the controller, an energy demand of the one or more building end use systems;
determining, by the controller, a computational workload based on the first data and the predictively determined energy demand, wherein the computational workload is configured such that, when executed by one or more computational devices, the one or more computational devices generate energy to at least partially satisfy a predicted energy shortfall between (i) the renewable energy generated at the site and (ii) the predictively determined energy demand of the one or more building end use systems; and
transmitting, from the controller, the computational workload to the one or more computational devices for generating energy to at least partially satisfy the predicted energy shortfall.
2. The computer-implemented method of claim 1 , comprising receiving, at the controller, second data indicative of a utility grid condition of a utility grid servicing energy to the site.
3. The computer-implemented method of claim 2 , wherein the computational workload is further based on the second data such that, when executed by the one or more computational devices, the one or more computational devices generate energy to at least partially satisfy a predicted energy shortfall between (i) a combination of the renewable energy generated at the site and available energy from the utility grid and (ii) the predictively determined energy demand of the one or more building end use systems.
4. The computer-implemented method of claim 3 , wherein the second data indicative of the utility grid condition comprises data of at least one of a demand response, load management, energy pricing, or weather conditions.
5. The computer-implemented method of claim 1 , wherein the generated energy of the one or more computational devices is thermal energy.
6. The computer-implemented method of claim 1 , wherein the generated energy of the one or more computational devices is used for electric vehicle charging.
7. The computer-implemented method of claim 1 , comprising initiating a transaction between two parties of one or more tokens in exchange for the generated energy of the one or more computational devices.
8. The computer-implemented method of claim 1 , wherein the transaction is completed before the computational workload is transmitted from the controller to the one or more computational devices.
9. The computer-implemented method of claim 7 , comprising recording data of the transaction on a blockchain ledger.
10. The computer-implemented method of claim 1 , wherein the computational workload is continuously redetermined to adapt to changing energy demand and available energy conditions.
11. The computer-implemented method of claim 1 , wherein the one or more computational devices are configured to execute climate models or machine learning models.
12. The computer-implemented method of claim 1 , wherein the controller is configured to optimize the computational workload based on energy demand and available energy conditions.
13. The computer-implemented method of claim 1 , wherein the one or more computational devices are at least two computational devices distributed within a distributed computing network.
14. The computer-implemented method of claim 1 , wherein the computational workload is cryptographically secure.
15. A computer-implemented method comprising:
receiving, at a controller, first data indicative of renewable energy generated at one or more sites, and second data indicative of a utility grid condition of a utility grid servicing energy to the one or more sites, and wherein each site of the one or more sites comprise one or more building end use systems configured to consume energy;
predictively determining, by the controller, an energy demand of the one or more building end use systems;
determining, by the controller, a computational workload based on the first data, the second data, and the predictively determined energy demand; and
generating energy, by executing the computational workload, to at least partially satisfy a predicted energy shortfall between (i) available energy from the utility grid and the renewable energy generated at the one or more sites and (ii) the predictively determined energy demand of the one or more building end use systems.
16. The computer-implemented method of claim 15 , wherein the first data indicative of the utility grid condition comprises data of at least one of a demand response, load management, energy pricing, or weather conditions.
17. The computer-implemented method of claim 15 , wherein one or more computational devices execute the computational workload to generate thermal energy to at least partially satisfy the predicted energy shortfall, the generated thermal energy being storable in one or more thermal reservoirs at the one or more sites, each thermal reservoir having one or more temperature layers.
18. The computer-implemented method of claim 15 , comprising:
initiating a transaction between two parties of one or more tokens in exchange for the generated energy of the one or more computational devices; and
recording data of the transaction on a blockchain ledger.
19. The computer-implemented method of claim 15 , wherein the computational workload is continuously redetermined to adapt to changing energy demand and available energy conditions.
20. The computer-implemented method of claim 15 , wherein the computational workload is cryptographically secure, and one or more computational devices execute the computational workload to generate the energy to at least partially satisfy the predicted energy shortfall.