Dispatch engine for optimizing demand-response thermostat events
A thermostat management server may include one or more processors and one or more memory devices comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising receiving information that characterizes energy usage associated with the plurality of thermostats, receiving parameters characterizing proposed future demand-response events, selecting a combination of thermostats from the plurality of thermostats for which the energy usage can be reduced, simulating a demand response event based on the parameters and using different weather conditions for the combination of the plurality of thermostats, generating statistical probabilities of meeting a plurality of capacity reduction levels based on the different weather conditions, selecting a capacity reduction level from the plurality of capacity reduction levels based on the statistical probabilities, and sending the capacity reduction level to the utility provider computer system.
1. A thermostat management server comprising:
one or more processors; and
one or more memory devices comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
receiving, from a plurality of thermostats, information that characterizes energy usage associated with the plurality of thermostats;
receiving, from a utility provider computer system, parameters characterizing proposed future demand-response events;
selecting a combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
simulating a demand response event based on the parameters and using different weather conditions for the combination of the plurality of thermostats;
generating statistical probabilities of meeting a plurality of capacity reduction levels based on the different weather conditions;
selecting a capacity reduction level from the plurality of capacity reduction levels based on the statistical probabilities; and
sending the capacity reduction level to the utility provider computer system.
2. The thermostat management server of claim 1 , wherein the parameters characterizing the proposed future demand-response events comprise a capacity reduction requirement.
3. The thermostat management server of claim 1 , wherein the parameters characterizing the proposed future demand-response events comprise payout ratio vs. delivered-capacity ratio.
4. The thermostat management server of claim 1 , wherein simulating the demand response event comprises using a plurality of Monte-Carlo simulations.
5. The thermostat management server of claim 1 , wherein the one or more memory devices further comprise additional instructions that, when executed by the one or more processors, cause the one or more processors to perform additional operations comprising:
loading a dispatch engine to select the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced.
6. The thermostat management server of claim 5 , wherein the dispatch engine is configured to:
select the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
determine whether an actual energy usage of the combination of thermostats meets the capacity reduction level; and
add or subtract thermostats from the combination of thermostats during successive time intervals to meet the capacity reduction level.
7. The thermostat management server of claim 1 , wherein the information that characterizes the energy usage associated with the plurality of thermostats comprises HVAC capacities and thermal characteristics of associated buildings.
8. The thermostat management server of claim 1 , wherein simulating the demand response event comprises compensating for simulation noise.
9. The thermostat management server of claim 1 , wherein the statistical probabilities of meeting a plurality of capacity reduction levels comprises a plurality of probability curves, wherein the plurality of probability curves comprises an expected value curve, a 10 th percentile curve, and the 90 th percentile curve.
10. A method for responding to requests to fulfill future power capacity reductions, the method comprising:
receiving, from a plurality of thermostats, information that characterizes energy usage associated with the plurality of thermostats;
receiving, from a utility provider computer system, parameters characterizing proposed future demand-response events;
selecting, by a thermostat management server, a combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
simulating, by the thermostat management server, a demand response event based on the parameters and using different weather conditions for the combination of the plurality of thermostats;
generating, by the thermostat management server, statistical probabilities of meeting a plurality of capacity reduction levels based on the different weather conditions;
selecting, by the thermostat management server, a capacity reduction level from the plurality of capacity reduction levels based on the statistical probabilities; and
sending, by the thermostat management server, the capacity reduction level to the utility provider computer system.
11. The method of claim 10 , wherein the parameters characterizing the proposed future demand-response events comprise payout ratio vs. delivered-capacity ratio.
12. The method of claim 10 , wherein simulating the demand response event comprises using a plurality of Monte-Carlo simulations.
13. The method of claim 10 , further comprising:
loading a dispatch engine to select the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced.
selecting the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
determining whether an actual energy usage of the combination of thermostats meets the capacity reduction level; and
adding or subtracting thermostats from the combination of thermostats during successive time intervals to meet the capacity reduction level.
14. The method of claim 10 , wherein simulating the demand response event comprises compensating for simulation noise.
15. The method of claim 10 , wherein the statistical probabilities of meeting a plurality of capacity reduction levels comprises a plurality of probability curves, wherein the plurality of probability curves comprises an expected value curve, a 10 th percentile curve, and the 90 th percentile curve.
16. A non-transitory, computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
receiving, from a plurality of thermostats, information that characterizes energy usage associated with the plurality of thermostats;
receiving, from a utility provider computer system, parameters characterizing proposed future demand-response events;
selecting a combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
simulating a demand response event based on the parameters and using different weather conditions for the combination of the plurality of thermostats;
generating statistical probabilities of meeting a plurality of capacity reduction levels based on the different weather conditions;
selecting a capacity reduction level from the plurality of capacity reduction levels based on the statistical probabilities; and
sending the capacity reduction level to the utility provider computer system.
17. The non-transitory, computer-readable medium of claim 16 , wherein simulating the demand response event comprises using a plurality of Monte-Carlo simulations.
18. The non-transitory, computer-readable medium of claim 16 , comprising additional instructions that cause the one or more processors to perform additional operations comprising:
loading a dispatch engine to select the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced.
selecting the combination of thermostats from the plurality of thermostats for which the energy usage can be reduced;
determining whether an actual energy usage of the combination of thermostats meets the capacity reduction level; and
adding or subtracting thermostats from the combination of thermostats during successive time intervals to meet the capacity reduction level.
19. The non-transitory, computer-readable medium of claim 16 , wherein simulating the demand response event comprises compensating for simulation noise.
20. The non-transitory, computer-readable medium of claim 16 , wherein the statistical probabilities of meeting a plurality of capacity reduction levels comprises a plurality of probability curves, wherein the plurality of probability curves comprises an expected value curve, a 10 th percentile curve, and the 90 th percentile curve.