Method and system for determining energy savings target for distributed sites of an entity

An energy savings prediction device, comprising:

• one or more processors;
• and
• a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution by the processors, cause the processors to:
• identify one or more energy profiles at each of one or more distributed sites by defining a service window and one or more energy control measures associated with the service window;
• determine one or more values of each of one or more operational parameters for a baseline period against a target reporting period in each of the one or more energy profiles;
• compute one or more energy coefficients by performing one or more energy optimization techniques on the values of each of the one or more operational parameters;
• predict energy consumption in the service window by performing a modular transformation of the one or more energy coefficients;
• compute current energy savings at each of the one or more distributed sites based on the energy consumption thus predicted and one or more adjustment factors;
• and
• determine the energy savings target for each of the one or more distributed sites by performing the modular transformation of the one or more energy coefficients when compared with the current energy savings.

A non-transitory computer-readable medium comprising instructions for determining an energy savings target for distributed sites of an entity, which, when executed by one or more processors, cause the processors to perform operations comprising:

• identifying one or more energy profiles at each of one or more distributed sites by defining a service window and one or more energy control measures associated with the service window;
• determining one or more values of each of one or more operational parameters for a baseline period against a target reporting period in each of the one or more energy profiles;
• computing one or more energy coefficients by performing one or more energy optimization techniques on the values of each of the one or more operational parameters;
• predicting energy consumption in the service window by performing a modular transformation of the one or more energy coefficients;
• computing current energy savings at each of the one or more distributed sites based on the energy consumption thus predicted and one or more adjustment factors;
• and
• determining the energy savings target for each of the one or more distributed sites by performing the modular transformation of the one or more energy coefficients when compared with the current energy savings.