Intelligent energy management system based on Internet of Things and artificial intelligence

Abstract

According to the intelligent energy management system based on the Internet of Things and artificial intelligence, an Internet of Things access module collects real-time energy data of water equipment and electric equipment; the big data analysis module is used for processing and analyzing the energy data acquired by the Internet of Things access module by utilizing a big data technology, mining an energy use rule, identifying an energy waste link and providing decision support for energy management; the artificial intelligence optimization module is used for realizing self-adaptive control and optimal scheduling of the energy system by applying advanced algorithms such as deep learning and reinforcement learning based on an analysis result of the big data analysis module; the energy storage module can generate power and store energy at the same time; the storage module is connected with electric equipment and is used for storing redundant electric energy or other forms of energy; and the user interaction module is used for providing services such as energy use reports, energy-saving suggestions, expense settlement, fault repair and the like through various forms such as a graphical user interface, a mobile application, a voice assistant and the like based on the analysis result of the big data analysis module.

Description

Technical Field

[0001] The present invention relates to a digital energy system, specifically to an intelligent energy management system that combines Internet of Things (IoT) technology with artificial intelligence (AI), aiming to achieve efficient utilization and management of energy. Background Art

[0002] Traditional energy management systems have many shortcomings, such as inaccurate energy monitoring and control, low energy utilization efficiency, serious energy waste, and lack of intelligent scheduling and optimization capabilities. With the rapid development of the Internet of Things and artificial intelligence technologies, digital energy has gradually become an important way to solve the above problems. However, existing digital energy management systems still have limitations in technology application, system integration, and energy data analysis and processing, which affects the intelligence and refinement of energy management.

[0003] Therefore, it is necessary to provide an intelligent energy management system based on the Internet of Things and artificial intelligence to achieve the above objectives. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent energy management system based on the Internet of Things and artificial intelligence.

[0005] The present invention achieves the above object through the following technical solutions:

[0006] An intelligent energy management system based on the Internet of Things and artificial intelligence, comprising:

[0007] Internet of Things access module, collecting real-time energy data of water-consuming equipment and electricity-consuming equipment;

[0008] The big data analysis module uses big data technology to process and analyze the energy data collected by the IoT access module, explore the patterns of energy use, identify energy waste links, and provide decision support for energy management;

[0009] The artificial intelligence optimization module uses advanced algorithms such as deep learning and reinforcement learning based on the results of the big data analysis module to achieve adaptive control and optimal scheduling of the energy system;

[0010] Energy storage modules can generate electricity and store energy at the same time; they are connected to electrical equipment to store excess electricity or other forms of energy;

[0011] The user interaction module, based on the analysis results of the big data analysis module, provides energy usage reports, energy-saving suggestions, fee settlement, fault repair and other services through various forms such as graphical user interface (GUI), mobile applications, and voice assistants.

[0012] Furthermore, the IoT access module can realize monitoring and data collection of the entire chain of energy production, transmission, distribution and consumption through sensor networks, wireless communication technology and standardized interface protocols.

[0013] Furthermore, the big data analysis module receives the massive data transmitted by the IoT access module, and uses cloud computing and distributed processing technologies to efficiently store, clean, integrate and analyze the data.

[0014] Furthermore, the AI ​​optimization module can predict changes in energy supply and demand, automatically adjust energy production strategies, optimize the charging and discharging plans of energy storage equipment, and perform fault warnings and intelligent maintenance.

[0015] Furthermore, the energy storage module can achieve the effect of using relatively cheap electricity by utilizing wind or solar power for normal times, or storing energy during electricity price valley periods, and can release it when demand peaks or energy supply is insufficient, so as to balance supply and demand and improve energy utilization.

[0016] Compared with the prior art, the modules of the present invention cooperate with each other to form an efficient, intelligent and sustainable energy management system, providing strong technical support for building a green and low-carbon future society. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0018] See also Figure 1 , this embodiment shows an intelligent energy management system based on the Internet of Things and artificial intelligence, including:

[0019] IoT access module 1: Through IoT technology, traditional water and electricity meters are replaced with smart meters, which are seamlessly connected to the system to realize real-time collection and transmission of energy data. The IoT access module is the perception layer of the smart energy system, responsible for collecting real-time data from various energy devices (such as smart grids, solar panels, wind turbines, smart home devices, etc.). Through sensor networks, wireless communication technology and standardized interface protocols, this module can realize monitoring and data collection of the entire chain of energy production, transmission, distribution and consumption. Its specific technology adopts RFID (radio frequency identification), low-power wide area network communications such as Zigbee / LoRa / NB-IoT, IoT communication protocols such as MQTT / CoAP, data encryption and secure transmission. Its role is to ensure the comprehensive, accurate and timely collection of data, and provide a basis for subsequent analysis and decision-making.

[0020] Big data analysis module 2: Use big data technology to process and analyze the collected energy data, explore the patterns of energy use, identify energy waste links, and provide decision support for energy management. The big data processing and analysis module receives the massive data transmitted by the IoT access module, and uses cloud computing and distributed processing technology for efficient storage, cleaning, integration and analysis. By mining historical data and quickly responding to real-time data, the module can identify energy usage patterns, predict energy demand trends, and discover potential energy-saving opportunities. Its specific technology uses big data processing frameworks such as Hadoop / Spark, machine learning algorithms (such as cluster analysis, regression analysis), and data visualization tools (such as Tableau, Power BI). Its role is to provide deep insights, support energy management decisions, and optimize resource allocation.

[0021] Artificial intelligence optimization module 3: Relying on artificial intelligence technology, an energy optimization model is constructed to intelligently dispatch and optimize energy to achieve efficient energy utilization and cost savings. The artificial intelligence module is the decision-making layer of the intelligent energy system. Based on the results of big data analysis, it uses advanced algorithms such as deep learning and reinforcement learning to achieve adaptive control and optimal scheduling of the energy system. This module can predict changes in energy supply and demand, automatically adjust energy production strategies, optimize the charging and discharging plans of energy storage equipment, and perform fault warnings and intelligent maintenance. Its specific technology uses deep learning frameworks (such as TensorFlow, PyTorch), reinforcement learning algorithms, and natural language processing (NLP) to understand user needs and feedback. Its role is to improve the level of system automation and achieve intelligent and efficient energy use.

[0022] Energy storage module 4: can generate electricity and store energy at the same time. Usually, using wind or solar power to generate electricity, or storing energy during the electricity price valley period, can achieve the effect of using relatively cheap electricity. The energy storage module is a key component of the smart energy system. It is used to store excess electricity or other forms of energy, and release it when demand peaks or energy supply is insufficient to balance supply and demand and improve energy utilization. Energy storage modules include battery energy storage systems, pumped storage power stations, compressed air energy storage and other forms. Its specific technology uses high-performance battery technology (such as lithium-ion batteries, sodium-sulfur batteries), energy management systems (EMS), and smart grid integration technology. Its role is to enhance the flexibility and reliability of the energy system and promote the effective use of renewable energy.

[0023] User Interaction Module 5: Provides a friendly user interaction interface, enabling users to monitor energy usage in real time, receive energy management suggestions, and make personalized settings for energy usage. The user interaction module is a bridge between the smart energy system and users. It provides services such as energy usage reports, energy-saving suggestions, fee settlement, and fault repair through a variety of forms such as a graphical user interface (GUI), mobile applications, and voice assistants. This module also allows users to adjust energy usage strategies according to their own needs, enhancing user participation and satisfaction.

[0024] Its specific technologies include responsive design, mobile application development frameworks (such as React Native and Flutter), and artificial intelligence chatbots. Its role is to enhance user experience, promote user participation in energy management, and form a new culture of energy consumption.

[0025] The present invention is an intelligent energy management system based on the Internet of Things and artificial intelligence. The modules cooperate with each other to form an efficient, intelligent and sustainable energy management system, providing strong technical support for building a green and low-carbon future society.

[0026] The above are only some embodiments of the present invention. For those skilled in the art, several modifications and improvements can be made without departing from the creative concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. An intelligent energy management system based on the Internet of Things and artificial intelligence, characterized in that: include: An Internet of Things access module (1) collects real-time energy data of water-consuming equipment and electricity-consuming equipment; A big data analysis module (2) uses big data technology to process and analyze the energy data collected by the Internet of Things access module (1), explore energy use patterns, identify energy waste links, and provide decision support for energy management; The artificial intelligence optimization module (3) uses advanced algorithms such as deep learning and reinforcement learning based on the analysis results of the big data analysis module (2) to achieve adaptive control and optimal scheduling of the energy system; The energy storage module (4) can generate electricity and store energy at the same time; it is connected to the electrical equipment to store excess electrical energy or other forms of energy; The user interaction module (5) provides services such as energy usage reports, energy-saving suggestions, fee settlement, fault repair, etc. based on the analysis results of the big data analysis module (2) through various forms such as a graphical user interface (GUI), a mobile application, and a voice assistant.

2. According to claim 1, the intelligent energy management system based on the Internet of Things and artificial intelligence is characterized by: The Internet of Things access module (1) can monitor and collect data on the entire chain of energy production, transmission, distribution and consumption through sensor networks, wireless communication technology and standardized interface protocols.

3. According to claim 1, the intelligent energy management system based on the Internet of Things and artificial intelligence is characterized by: The big data analysis module (2) receives the massive data transmitted by the Internet of Things access module and uses cloud computing and distributed processing technology to efficiently store, clean, integrate and analyze the data.

4. According to claim 1, the intelligent energy management system based on the Internet of Things and artificial intelligence is characterized by: The artificial intelligence optimization module (3) can predict changes in energy supply and demand, automatically adjust energy production strategies, optimize the charging and discharging plans of energy storage equipment, and perform fault warnings and intelligent maintenance.

5. According to claim 1, the intelligent energy management system based on the Internet of Things and artificial intelligence is characterized by: The energy storage module (4) generates electricity by using wind or solar energy in normal times, or stores energy during the electricity price valley period, so as to achieve the effect of using relatively cheap electricity, and releases it when demand peaks or energy supply is insufficient, so as to balance supply and demand and improve energy utilization.

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