General Electric Company

Amirhossein Hajimiragha

Mohammad Reza Dadash Zadeh

Michael Joseph Krok

Iulian Raducanu

In a first embodiment, a system for controlling a microgrid includes a processor-based control system. The control system is configured to receive information via a communications pathway from at least one microgrid asset within a microgrid system and identify one or more errors associated with an operation of the microgrid system. In addition, the control system is configured to respond to the one or more identified errors with one or more actions. Each identified error from the one or more identified errors is associated with at least one action from the one or more actions. Further, control system is configured to generate an optimal dispatch schedule having one or more control signals configured to control the microgrid operation to reduce cost and to improve an operational efficiency of the microgrid. The optimal dispatch schedule is based at least in part on the response to the one or more identified errors.

Systems and methods for error monitoring and handling in control systems

A microgrid including a renewable power source is optimized by treating the renewable source as operating in an isochronous mode, and by decomposing the optimization process. A renewable capability is defined for the renewable source to enable treatment of the renewable source as operating in an isochronous mode. The renewable capability may be based on a power rating of the renewable source. An objective function of the microgrid optimization problem may then be optimized while treating the renewable source as operating in an isochronous mode. A penalty factor may be applied to avoid power shortage.

Power generation optimization in microgrid including renewable power source

A power generation system including an electrolyzer may be optimized taking non-linear operational constraints into account with lower processing requirements than current solutions in real time. A pre-processing module assesses non-linear operational constraints in a low-overhead manner and passes results to an optimization module. The optimization module determines an operating power value constrained in accordance with results from the pre-processing module. A post-processing module uses results from the pre-processing and optimization modules to assemble instructions to control the electrolyzer. As a result, optimization may be performed in real time.

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Richmond Hill, Canada

Amirhossein Hajimiragha