System and method for intelligent optimized bidding in a battery energy storage system

A non-transitory computer-readable medium, comprising an intelligent optimized bidding (IOB) module, wherein execution of the IOB module by one or more processors configures one or more computing devices to:

• obtain previous energy bidding information including at least one of a unit price and a total power amount purchased in a last energy bidding;
• acquire state data of components of an energy storage system including a plurality of energy storage nodes and at least one inverter, wherein each energy storage node includes a plurality of battery modules, wherein the state data of at least the plurality of battery modules and the at least one inverter is measured and stored in a memory coupled to the at least one processor;
• analyze the acquired state data to determine whether a value of the acquired state data exceeds a predicted limit provided in an algorithm of the previous energy bidding information, wherein:
• when the value of the acquired state data does not exceed the predicted limit, report a result of the determination, and
• when the value of the acquired state data exceeds the predicted limit, apply a cost function model for at least the plurality of battery modules, the at least one inverter, and an operating efficiency of the energy storage system to provide a respective cost degradation value for the plurality of battery modules, the inverter, and the operating efficiency of the energy storage system, and
• adjust an optimized gain value for a next energy bidding based upon the acquired state data and the cost degradation value for the plurality of battery modules, the at least one inverter, and the operating efficiency of the energy storage system.

A method for intelligent optimized bidding, comprising:

• obtaining previous energy bidding information including at least one of a unit price and a total power amount purchased in a last energy bidding;
• acquiring state data of components of an energy storage system, the energy storage system including a plurality of energy storage nodes and at least one inverter, wherein each energy storage node includes a plurality of battery modules, wherein the state data of at least the plurality of battery modules and the at least one inverter of the plurality of energy storage nodes is measured and stored in a memory coupled to the energy storage nodes;
• analyzing the acquired state data to determine whether a value of the acquired state data exceeds a predicted limit in an algorithm of the previous energy bidding information, wherein:
• when the value of the acquired state data does not exceed the predicted limit, reporting a result of the determination, and
• when the value of the acquired state data exceeds the predicted, applying a cost function model for at least the plurality of battery modules, the at least one inverter, and an operating efficiency of the energy storage system to provide a respective cost degradation value for the battery modules, the inverter, and the operating efficiency of the battery storage system, and
• adjusting an optimized gain value for a next energy bidding based upon the acquired state data and the cost degradation value for the plurality of battery modules, the at least one inverter, and the operating efficiency of the energy storage system.