An electronic device, comprising: a communicator comprising communication circuitry; a processor electronically connected to the communicator and configured to control the communicator; and a memory electrically connected to the processor, wherein the memory is configured to store instructions to control the processor to transmit control information, which is acquired by applying target information of an air conditioning system to a learning network model, to a plurality of air conditioning devices included in the air conditioning system via the communicator, characterized in that the learning network model is configured to, based on identifying that an error is present in an estimation result of energy consumption through linear regression analysis based on learning data, generate virtual data and be retrained based on the generated virtual data, wherein the learning network model is further configured to generate the virtual data corresponding to a first condition based on learning data of a second condition where the error is not present in the estimation result of energy consumption, and wherein the first condition is a condition where the error is present in the estimation result of energy consumption, wherein the learning network is further configured to: cluster the estimation result of energy consumption into two groups according to a relationship between a processed heat quantity and an energy consumption of the electronic device, the two groups comprising a first group in which the processed heat quantity is in proportion to energy consumption, and a second group in which a processed heat quantity is not in proportion to energy consumption and the second group is a group in which the energy consumption remains unchanged or decreases even when the processed heat quantity is increased, and generate the virtual data based on learning data included in the first group. a communicator comprising communication circuitry; a processor electronically connected to the communicator and configured to control the communicator; and a memory electrically connected to the processor, wherein the memory is configured to store instructions to control the processor to transmit control information, which is acquired by applying target information of an air conditioning system to a learning network model, to a plurality of air conditioning devices included in the air conditioning system via the communicator, characterized in that the learning network model is configured to, based on identifying that an error is present in an estimation result of energy consumption through linear regression analysis based on learning data, generate virtual data and be retrained based on the generated virtual data, wherein the learning network model is further configured to generate the virtual data corresponding to a first condition based on learning data of a second condition where the error is not present in the estimation result of energy consumption, and wherein the first condition is a condition where the error is present in the estimation result of energy consumption, wherein the learning network is further configured to: cluster the estimation result of energy consumption into two groups according to a relationship between a processed heat quantity and an energy consumption of the electronic device, the two groups comprising a first group in which the processed heat quantity is in proportion to energy consumption, and a second group in which a processed heat quantity is not in proportion to energy consumption and the second group is a group in which the energy consumption remains unchanged or decreases even when the processed heat quantity is increased, and generate the virtual data based on learning data included in the first group. cluster the estimation result of energy consumption into two groups according to a relationship between a processed heat quantity and an energy consumption of the electronic device, the two groups comprising a first group in which the processed heat quantity is in proportion to energy consumption, and a second group in which a processed heat quantity is not in proportion to energy consumption and the second group is a group in which the energy consumption remains unchanged or decreases even when the processed heat quantity is increased, and generate the virtual data based on learning data included in the first group.