Abstract: Certain embodiments of the invention may include systems, methods, and apparatus for estimating demand response load change. According to an example embodiment of the invention, a method is provided for estimating energy usage change associated with a demand event. The method may include determining energy potential change during a demand event for one or more devices associated with a location; estimating energy usage patterns for the location over predefined time periods before and after the demand event; determining pre-demand event and post-demand event energy rebounds based at least in part on the estimated energy usage patterns; determining an energy change profile associated with the location based at least in part on the determined energy potential change, and the pre-demand event and post-demand event energy rebounds.

Abstract: A computing device for use with a demand response system is provided. The computing device includes a processor that is programmed to select at least one participant from a plurality of customers to participate in at least one demand response event. The processor is also programmed to schedule the demand response event. The processor is programmed to compare the selected participant with participants of previously scheduled demand response events to confirm whether the selected participant is able to participate in the demand response event. The processor is also programmed to compare the demand response event with the previously scheduled demand response events. The processor is further programmed to reschedule the demand response event and/or at least one of the previously scheduled demand response events when any conflicts are identified based on the comparison between the demand response event and the previously scheduled demand response events.

Abstract: Certain embodiments of the invention may include systems, methods, and apparatus for estimating demand response load change. According to an example embodiment of the invention, a method is provided for estimating energy usage change associated with a demand event. The method may include determining energy potential change during a demand event for one or more devices associated with a location; estimating energy usage patterns for the location over predefined time periods before and after the demand event; determining pre-demand event and post-demand event energy rebounds based at least in part on the estimated energy usage patterns; determining an energy change profile associated with the location based at least in part on the determined energy potential change, and the pre-demand event and post-demand event energy rebounds.

Abstract: A method of managing a machinery monitoring system is provided. The machinery monitoring system includes a database of at least one rule set, the rule set including at least one rule expressed as a relational expression of a real-time data output relative to a real-time data input, the relational expression being specific to a plant asset. The method includes importing data representative of a rule set into the machinery monitoring system, applying the at least one rule set to a specific plant asset wherein the at least one rule set is configured to locate the data input using at least a portion of the relative path information, determining a data output of the at least one rule set using the at least one relational expression and the data input, and transmitting the data output to at least one of the machinery monitoring system and the plant monitoring and control system.

Abstract: A computer-implemented method of managing a machinery monitoring system is provided. The method includes relating an asset output to at least one asset input, generating at least one rule based on the relation, selecting at least one of live asset data, historical asset data, user-supplied asset data, and third party supplied asset data to test the at least one rule, testing the at least one rule incrementally using the selected asset data, and monitoring the output of the at least one rule at each increment.

Abstract: Disclosed is a monitoring system implementing a network including at least one source of dynamic data, the source being in communication with a machine, a monitoring module configured for communication with the source, receiving the dynamic data, and converting the dynamic data to output data for transmittal over the network, a computing resource configured for communication with the network and receiving the output data, a rule implementer in the monitoring module, the rule implementer implementing at least one system rule that is applicable to the output data to determine optimal setpoints for at least one machine variable, and a controller configured for communication with the monitoring module and the network and receiving the output data to which the at least one system rule has been applied, the controller being configured to control the at least one machine variable according to the optimal setpoints.

Abstract: Disclosed is a monitoring system implementing a network. The system includes at least one source of dynamic data, the at least one source configured to be in signal communication with a machine, a monitoring module configured for communication with the at least one source, configured for receiving the dynamic data, and configured for converting the dynamic data to output data for transmittal over the network, a controller configured for communication with the monitoring module and the network, and configured for receiving the output data, a computing resource configured for communication with the network, and configured for receiving the output data, and a rule implementer in the monitoring module, the rule implementer configured to implement at least one system rule.