Smart Energy Decision System

Abstract

A smart energy decision-making system comprises a server that communicates with a user network device and a power device, and connects to at least one sensor that measures power device data via a communication gateway of the power device. The server executes a machine learning prediction model to make predictions based on the power device data and outputs at least one predicted data point; executes a linkage logic execution model to perform at least one corresponding logical action based on whether the at least one predicted data point conforms to at least one specific interval of preset logic; executes a large-scale language model to generate at least one corresponding generative data point based on the executed at least one logical action; and outputs application data in conjunction with the user network device's terminal application to understand the user network device's anticipated future abnormalities in the power device and to provide handling suggestions.

Claims

1. A smart energy decision-making system, comprising: An electrical device includes at least one sensor and a communication gateway; wherein the at least one sensor measures electrical device data, is electrically connected to the communication gateway, and outputs the electrical device data through the communication gateway; a user network device; a server communicatively connected to the electrical device and the user network device, and storing a linkage logic execution model, a trained machine learning prediction model, and a large language model (LLM); wherein, when the server receives electrical device data from the communication gateway of the electrical device, the server executes the machine learning prediction model to make a prediction based on the electrical device data and output at least one predicted data; wherein, the server executes the linkage logic execution model to execute at least one corresponding logical action based on whether the at least one predicted data conforms to at least one specific interval of preset logic; wherein, the server executes the large language model to generate at least one corresponding generative data based on the executed at least one logical action. The server generates application data by combining the at least one generated data with the terminal application of the user's network device, and outputs the application data to the user's network device.

2. The smart energy decision-making system as described in claim 1, wherein, The at least one sensor measuring the data of the electrical equipment includes at least one of the following: temperature data of the electrical equipment measured by a temperature sensor, voltage data of the electrical equipment measured by a voltage sensor, current data of the electrical equipment measured by a current sensor, power consumption data of the electrical equipment measured by a power consumption sensor, harmonic data of the electrical equipment measured by a harmonic detector, power / power factor (PF) of the electrical equipment measured by a power sensor, and reverse current data of the electrical equipment measured by a reverse current sensor.

3. The smart energy decision-making system as described in claim 1, wherein, The electrical equipment is a switchboard or an energy management system (EMS) device; wherein the user's network connection device is a smartphone, a computer or a tablet computer.

4. The smart energy decision-making system as described in claim 1, wherein, The at least one sensor measuring the data of the power equipment includes a temperature sensor and a current sensor; wherein, when the server executes the linkage logic execution model, the server determines whether the temperature of a transmission joint measured by the temperature sensor and the neutral current measured by the current sensor in the power equipment rise simultaneously; wherein, when the temperature of the transmission joint measured by the temperature sensor and the neutral current measured by the current sensor rise simultaneously, the server triggers a fire warning as the at least one logic action to be executed.

5. The smart energy decision-making system as described in claim 1, wherein, The at least one sensor measuring the data of the power equipment includes a temperature sensor and a harmonic detector; wherein, when the server executes the linkage logic execution model, the server determines whether the equipment temperature measured by the temperature sensor in the power equipment is higher than a equipment temperature threshold, and the server determines whether the harmonic data measured by the harmonic detector is higher than a harmonic data threshold; wherein, when the equipment temperature measured by the temperature sensor is higher than the equipment temperature threshold, and the harmonic data measured by the harmonic detector is higher than the harmonic data threshold, the server automatically reduces the remaining service life of the power equipment as the at least one logic action to be executed.

6. The smart energy decision-making system as described in claim 1, wherein, The at least one sensor measuring the data of the power equipment includes a power sensor; wherein, when the server executes the linkage logic execution model, the server determines whether the power measured by the power sensor in the power equipment is higher than a device power threshold and whether a power factor (PF) is lower than a PF threshold; wherein, when the power measured by the power sensor is higher than the device power threshold and the power factor (PF) is lower than the PF threshold, the server automatically selects non-critical loads connected to the power equipment as load reduction targets, as the at least one logic action executed by the server.

7. The smart energy decision-making system as described in claim 1, wherein, The terminal application created by the user's network device is an application (APP), a webpage, or an interactive game running on the user's network device, used to: change the operation of the power equipment, visualize the parameters of the power equipment operation, visualize the trend of big data changes in the operation of the power equipment, visualize the predicted trend of changes in the parameters of the power equipment operation, visualize early warnings of predicted abnormalities in the operation of the power equipment, or output relevant data reports of the power equipment.

8. The smart energy decision-making system as described in claim 7, wherein, The terminal application created by the user's network device uses Software as a Service (SaaS) subscription to the application data output by the server; wherein, at least one sensor periodically outputs the power equipment data to the server through the communication gateway, so that the server can periodically monitor the power equipment.

9. The smart energy decision-making system as described in claim 1, wherein, The at least one sensor of the power equipment measures energy consumption data, energy storage data and carbon emission data of ESG indicators, and the server outputs at least one prediction data corresponding to the energy consumption data, the energy storage data and the carbon emission data.

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