Load reduction optimization

A system comprising:

• one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
• maintaining data a) for executing a load reduction event b) that comprises (i) a first set of load reduction parameters associated with the load reduction event, (ii) energy consumptions models from multiple systems participating in the load reduction event, and (iii) a load reduction curve for the load reduction event;
• maintaining, for each system of the multiple systems, data that comprises (i) an indicator of a system, (ii) a likelihood that each system is not likely to participate in the load reduction event, and (iii) an estimated time at which each system of the multiple system is likely to stop participating in the load reduction event;
• maintaining timing data comprising (i) a current time of the load reduction event and (ii) a start time of the load reduction event;
• comparing, for each system of the multiple systems, the maintained timing data to the estimated time at which the system is likely to stop participating in the load reduction event;
• identifying a subset of the multiple systems using a result of the comparison;
• optimizing, against the load reduction curve, the load reduction event by performing simulations with the energy consumption models of the identified subset of systems to generate an optimal load reduction event that comprises a second set of load reduction parameters;
• and
• providing the second set of load reduction parameters to one or more systems of the multiple systems to execute the optimal load reduction event.

A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

• maintaining data a) for executing a load reduction event b) that comprises (i) a first set of load reduction parameters associated with the load reduction event, (ii) energy consumptions models from multiple systems participating in the load reduction event, and (iii) a load reduction curve for the load reduction event;
• maintaining, for each system of the multiple systems, data that comprises (i) an indicator of a system, (ii) a likelihood that each system is not likely to participate in the load reduction event, and (iii) an estimated time at which each system of the multiple system is likely to stop participating in the load reduction event;
• maintaining timing data comprising (i) a current time of the load reduction event and (ii) a start time of the load reduction event;
• comparing, for each system of the multiple systems, the maintained timing data to the estimated time at which the system is likely to stop participating in the load reduction event;
• identifying a subset of the multiple systems using a result of the comparison;
• optimizing, against the load reduction curve, the load reduction event by performing simulations with the energy consumption models of the identified subset of systems to generate an optimal load reduction event that comprises a second set of load reduction parameters;
• and
• providing the second set of load reduction parameters to one or more systems of the multiple systems to execute the optimal load reduction event.