Patent ID: 11953870
Assignee: NANOOMENERGY CO., LTD.
Field: Electrical machinery, apparatus, energy (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 3:
4. The machine-learning-based photovoltaic power generation control system according to claim 1, wherein the machine learning server comprises:
an interface unit configured to allow the machine learning server to perform real-time data transmission and reception therethrough;
a monitoring unit configured to monitor photovoltaic power generation data transmitted from a photovoltaic power generation construction device comprising the photovoltaic modules, the node controllers, the gateway unit, and the real-time control module through integrated processing comprising analysis, sorting, comparison, and conversion based on characteristics thereof;
a determination unit configured to determine whether machine learning is to be performed based on profile information of the integrated-processed data transmitted from the monitoring unit;
a learning module configured to perform new learning for data necessary to be newly learned according to determination of the determination unit;
a modeling unit configured to extract data using a result of learning and to perform modeling;
a learning database configured to store the result of learning and a result of modeling;
a controller configured to retrieve modeling data from the learning database in order to control photovoltaic power generation and to transmit the modeling data to a service unit configured to control photovoltaic power generation together with data determined not to be learned by the determination unit;
a service unit configured to select one of reference models transmitted from the controller, to define photovoltaic power generation control service data, and to transmit the data to the real-time control module through the interface unit; and
a service management module configured to delete, add, update, and manage a modeling data list transmitted to the service unit.