Cognitive platform and method for energy management for enterprises

At least one non-transitory computer readable storage medium encoded with processing instructions performed by at least one processor, said at least one computer readable storage medium and at least one processor comprising an information processing system for resource management, said system comprises:

• (a) a module for receiving data related to at least one resource from plurality of data sources;
• (b) a module for performing at least one learning operation, via a cognitive decision maker, to improve resource optimization using cognition or machine learning;
• (c) a module for providing processed information or at least one command to any one of an equipment, external application or storage of any type.

The computer readable storage medium of 15, wherein said at least one learning operation uses multi-criteria decision making to approach a target or goal.

A method for processing of information for resource management, the method comprising the steps of:

• (a) generating forecasts of at least one parameter representing at least one piece of equipment for a future period of time using data related to said equipment and to control scenarios;
• (b) determining at least one value of the predictions and control scenarios using a cost function, the cost function comprising weighted factors related to an error between a setpoint and the parameter predicted, a length of runtime for the equipment based on the control scenarios, and
• (c) selecting at least one control scenario to apply to control the equipment.

At least one non-transitory computer readable storage medium encoded with processing instructions to be performed by at least one processor, wherein said at least one computer readable storage medium and at least one processor comprise an information processing system for resource management, said system comprises:

• (a) a module for generating forecasts of at least one parameter of at least one piece of equipment for a future period of time using data related to equipment and control scenarios;
• (b) a processor to determine one or more forecast values and control scenarios using a cost function, said cost function comprising weighted factors related to an error between a setpoint and the parameter forecast, a length of runtime for the equipment based on the control scenarios, and for selecting the control scenario with the highest value to apply to control the equipment.