Abstract: The present disclosure relates to a method and system for indicating energy savings for a distributed site. The energy savings is indicated by an energy management system, which receives energy consumption data of the distributed site for a first observation period. Further one or more service windows are defined for the distributed site and an energy saving strategy is applied to at least one service window. Further, the energy consumption data for the second observation period is received and a compared of one or more service windows of the first observation period with the corresponding service windows of the second observation period is done. The energy management system further determines adjustment factors in the energy profiles based on parameters affecting the energy profiles which were not considered during the first observation period and hence indicate the energy savings for the distributed site based on the first saving and adjustment factor.

Abstract: The present disclosure relates to a method and system for indicating energy savings for a distributed site. The energy savings is indicated by an energy management system, which receives energy consumption data of the distributed site for a first observation period. Further one or more service windows are defined for the distributed site and an energy saving strategy is applied to at least one service window. Further, the energy consumption data for the second observation period is received and a compared of one or more service windows of the first observation period with the corresponding service windows of the second observation period is done. The energy management system further determines adjustment factors in the energy profiles based on parameters affecting the energy profiles which were not considered during the first observation period and hence indicate the energy savings for the distributed site based on the first saving and adjustment factor.

Abstract: The present disclosure relates to a method for managing performance of at least one instrumentation device deployed across one or more sites. The method comprises receiving instrument data from the at least one instrumentation device. The instrument data comprises data pertaining to performance of the at least one instrumentation device. The method further comprises validating the instrument data based on at least one of predefined range parameters, predefined error parameters, predefined policy parameters, and historical analysis parameters. The method further comprises determining at least one of calibration issues, maintenance issues, reliability of at least one of the instrumentation device, and quality of the instrument data based on validation of the instrument data and generating performance report based on the validation and the determination for managing the performance of the one or more instrumentation devices.

Abstract: A method, non-transitory computer readable medium, and energy optimization device that optimizes energy consumption includes generating an energy model for each of a plurality of sites in an enterprise network. A plurality of service windows is determined for each of the sites. An energy consumption forecast is generated for each of the sites based on the generated energy models and the determined service windows. Current energy consumption information is obtained for one of the sites. Optimization recommendation(s) are determined for the one site based on a deviation of the obtained current energy consumption information for the one site from the generated energy consumption forecast for the one site in an active one of the determined service windows for the one site, and the optimization recommendation(s) are output.

Abstract: A method, non-transitory computer readable medium, and energy optimization device that optimizes energy consumption includes generating an energy model for each of a plurality of sites in an enterprise network. A plurality of service windows is determined for each of the sites. An energy consumption forecast is generated for each of the sites based on the generated energy models and the determined service windows. Current energy consumption information is obtained for one of the sites. Optimization recommendation(s) are determined for the one site based on a deviation of the obtained current energy consumption information for the one site from the generated energy consumption forecast for the one site in an active one of the determined service windows for the one site, and the optimization recommendation(s) are output.