Abstract: An embodiment provides an energy management system of a community in which a plurality of buildings, each divided into a plurality of zones, are located, the energy management system including: a community agent that is a device managing energy of the community and is configured to receive a first incentive about a Demand Response (DR) or a Frequency Regulation (FR) from a demand management device, calculate a first response capacity responding to the first incentive among a community management capacity, and transmit a second incentive to a building agent; a plurality of building agents, each of which is a device managing energy of a corresponding building and is configured to calculate a second response capacity responding to the second incentive among a building management capacity, and transmit a third incentive to a zone agent; and a plurality of zone agents, each of which is a device managing energy of a corresponding zone and is configured to calculate a third response capacity responding to the third

Abstract: Disclosed is a system for managing energy of a community in which at least one building exists. The system includes a community agent for managing community energy demand prediction data including building energy demand prediction data of each building and a community demand reaction load capacity including a building demand reaction load capacity of each building and managing a community demand reaction incentive policy applied to the community; and a machine learning device for generating a building demand reaction incentive policy to be applied to each building through a community-optimized machine learning model.

Abstract: An embodiment provides an energy management system of a community in which a plurality of buildings, each divided into a plurality of zones, are located, the energy management system including: a community agent that is a device managing energy of the community and is configured to receive a first incentive about a Demand Response (DR) or a Frequency Regulation (FR) from a demand management device, calculate a first response capacity responding to the first incentive among a community management capacity, and transmit a second incentive to a building agent; a plurality of building agents, each of which is a device managing energy of a corresponding building and is configured to calculate a second response capacity responding to the second incentive among a building management capacity, and transmit a third incentive to a zone agent; and a plurality of zone agents, each of which is a device managing energy of a corresponding zone and is configured to calculate a third response capacity responding to the third

Abstract: Disclosed is a system for managing energy of a community in which at least one building exists. The system includes a community agent for managing community energy demand prediction data including building energy demand prediction data of each building and a community demand reaction load capacity including a building demand reaction load capacity of each building and managing a community demand reaction incentive policy applied to the community; and a machine learning device for generating a building demand reaction incentive policy to be applied to each building through a community-optimized machine learning model.

Abstract: Provided is a converter system including: a plurality of converter modules connected to one power source in parallel; and a controller for storing mapping information of first parameters corresponding to processing power of the converter modules and second parameters corresponding to the number of converter modules that optimally process the processing power among the converter modules, configuring a value of the first parameter according to a measurement value of power input into the converter modules or power output from the converter modules, calculating a value of the second parameter by substituting the value of the first parameter into the mapping information, selecting the number of converter modules corresponding to the value of the second parameters as active converter modules from the converter modules and processing the processing power by using the active converter modules, and controlling output power of the active converter module to gradually increase or decrease in a transient state where the