Energy routing system with intelligent regulation and control function
By designing an energy routing system with intelligent adaptation circuits and deep learning algorithms, the problem that traditional energy management systems cannot integrate and regulate multiple energy sources is solved, and efficient energy utilization and stable energy supply are achieved.
Patent Information
- Application Number
- CN202411983571.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-31
- Publication Date
- 2025-05-13
AI Technical Summary
Traditional energy management systems cannot effectively integrate and intelligently regulate various energy forms, resulting in low energy utilization efficiency and inability to meet the efficient and stable operation requirements in modern complex energy demand scenarios.
An energy routing system with intelligent regulation functions was designed. Through intelligent adaptation circuits and deep learning algorithms, multiple energy forms (electrical energy, thermal energy, mechanical energy) can be automatically identified and converted, and through real-time monitoring and data analysis, the energy flow direction and distribution ratio can be dynamically planned.
It has achieved efficient integration and intelligent regulation of a variety of energy sources, improved energy utilization efficiency, met the efficient and stable operation requirements in complex energy demand scenarios, and has redundancy and switching mechanisms to ensure the reliability of energy supply.
Smart Images
Figure CN119991006A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of energy management and distribution, and in particular to an energy routing system with intelligent control function. Background Art
[0002] With the continuous development of energy technology, various forms of energy have been widely used in different scenarios. For example, in industrial production, there are both electrically driven equipment and processes that utilize thermal energy. At the same time, there may also be mechanical energy recovery and reuse. Traditional energy management systems can often only process a single type of energy and lack the ability to comprehensively and intelligently regulate multiple energy sources, resulting in low energy utilization efficiency and unable to meet the requirements of efficient and stable operation in modern complex energy demand scenarios. Therefore, it is of great significance to develop an energy routing system that can integrate multiple energy sources and perform intelligent regulation. Summary of the invention
[0003] In order to solve the above-mentioned problems, the present invention proposes an energy routing system with intelligent control function.
[0004] In order to solve the above technical problems, the technical solution proposed by the present invention is: an energy routing system with intelligent control function, comprising:
[0005] Energy input unit: equipped with a variety of energy access ports, compatible with common energy forms such as electrical energy, thermal energy, and mechanical energy. For example, the electrical energy input port can be connected to the mains power grid, distributed power generation equipment (such as solar photovoltaic panels, wind turbines, etc.); the thermal energy input port can receive thermal energy resources such as industrial waste heat and geothermal energy; the mechanical energy input port can be connected to equipment with mechanical energy output (such as mechanical vibration devices, hydraulic systems, etc.).
[0006] The intelligent adapter circuit is the core part of the energy input unit. When electrical energy is input, it can automatically identify the voltage and current type (such as AC or DC, different voltage levels, etc.) and convert it into a unified standard electrical energy signal within the system (such as DC of a specific voltage). During the conversion process, by real-time monitoring of circuit parameters such as power factor and conversion efficiency, the parameters of electronic components in the circuit (such as transformer turns ratio, rectifier conduction angle, etc.) are automatically adjusted to ensure efficient conversion under different electrical energy input conditions. For thermal energy input, the intelligent adapter circuit converts thermal energy into electrical energy signals or other storable and transmittable energy forms using heat exchangers, thermoelectric conversion devices, etc. according to parameters such as temperature and flow of thermal energy, and can dynamically adjust the heat exchange efficiency according to the temperature difference between the hot end and the cold end. When mechanical energy is input, it is connected to the energy conversion device (such as a generator) through a mechanical transmission device. The intelligent adaptation circuit optimizes the excitation current, load resistance and other parameters of the generator according to the speed, torque and other characteristics of the mechanical energy, so that the mechanical energy can be efficiently converted into electrical energy signals. The conversion efficiency monitoring function can detect the conversion efficiency of mechanical energy to electrical energy in real time, so as to timely detect the wear or failure of mechanical transmission components.
[0007] Intelligent processing unit:
[0008] The energy parameter monitoring module is connected to the energy input unit and other system components through a sensor network. For electrical energy, it can accurately measure parameters such as voltage, current, power, and power factor; for thermal energy, it can monitor temperature, flow, thermal enthalpy, etc.; for mechanical energy, it can detect physical quantities such as speed, torque, and displacement. These parameters are collected in real time and transmitted to the data analysis module.
[0009] The data analysis module uses deep learning algorithms to build an energy management model. It first learns a large amount of historical operation data, which includes time series data of different energy inputs, corresponding load demand data, and system operation status data. Through deep learning algorithms, the model can dig out the potential relationship and rules between energy input and load demand. For example, it can learn the changing rules of the demand ratio of electrical energy, thermal energy and mechanical energy in a specific time period (such as different process stages of industrial production), as well as the impact of changes in solar photovoltaic power generation under different weather conditions on overall energy demand. In the real-time operation process, based on the currently collected energy parameter data and combined with the learned rules, the analysis module can quickly plan the optimal energy flow and distribution ratio. For example, when it is detected that the solar photovoltaic power generation suddenly increases and the current power load demand is low, the analysis module will instruct to allocate excess power to the energy storage unit for storage, or adjust the energy output unit to convert part of the power into thermal energy for industrial heating process.
[0010] The instruction generation module generates precise control instructions based on the decision results of the data analysis module. These instructions include parameter adjustment instructions for controlling the intelligent adaptation circuit in the energy input unit (such as changing the transformer ratio, adjusting the working point of the thermoelectric conversion device, etc.), charging and discharging instructions for controlling the energy storage unit (such as determining the charging current of the battery pack, the charging and discharging time of the supercapacitor, etc.), and energy conversion and output parameter adjustment instructions for the energy output unit (such as setting the voltage and frequency of the electrical energy output, and controlling the temperature and flow of the thermal energy output, etc.).
[0011] The communication module supports multiple communication protocols such as Wi-Fi, Bluetooth and 4G. On the one hand, it is connected to local intelligent terminals (such as industrial control computers, smart phones, etc.) to enable local operators to monitor the system and input operation instructions. For example, operators can view the real-time energy status and historical operation data of the system through a mobile phone APP, and manually adjust certain parameters of the system (such as manually controlling the priority of energy output in an emergency). On the other hand, the communication module exchanges information with the remote monitoring center or other distributed energy systems. In a distributed energy network, this energy routing system can send its own energy surplus or shortage information to other systems, and at the same time receive collaborative work instructions or energy sharing information from other systems to achieve optimal energy scheduling and distributed collaborative management.
[0012] Energy storage unit:
[0013] It includes a variety of energy storage components, such as lithium-ion battery packs, supercapacitors, and energy storage devices made of new energy storage materials. Lithium-ion battery packs have a high energy density and are suitable for long-term, large-capacity energy storage, such as storing excess electricity generated by solar photovoltaic power generation at night for use during peak power consumption during the day. Supercapacitors have fast charging and discharging characteristics and can be used to cope with instantaneous fluctuations in energy demand, such as providing instantaneous high current support when industrial equipment is started.
[0014] Each energy storage element is equipped with an independent management module. For battery packs, the management module can accurately monitor the voltage, temperature, internal resistance and other parameters of each battery cell to prevent overcharging, over-discharging, overheating and other situations. By controlling the charging current and voltage, the battery can switch between different charging modes such as constant current charging and constant voltage charging to extend the battery life. During the discharge process, the discharge current is adjusted according to the remaining capacity of the battery and the load requirements to ensure that the battery operates safely and stably. The supercapacitor management module focuses on parameters such as the capacitor's voltage, charge and discharge current, and equivalent series resistance. It uses its fast response characteristics to quickly absorb or release energy when the system's energy demand suddenly changes, and uses a voltage equalization circuit to ensure voltage balance when multiple supercapacitors are connected in series.
[0015] The management module can also realize flexible combination and switching between energy storage components according to the overall energy scheduling needs of the system. For example, when the system requires long-term stable energy output and relatively stable energy input, the battery pack is used for energy supply first; when facing instantaneous high power demand or energy regulation that requires fast response, it switches to the working mode of supercapacitor or battery pack and supercapacitor in parallel, giving full play to the advantages of different energy storage components and improving the reliability and flexibility of the system's energy supply.
[0016] Energy output unit:
[0017] It has powerful energy conversion capabilities and can convert the standard energy signal inside the system into an energy form that is suitable for various external loads. For power output, it can convert DC power into AC power of different voltages, frequencies, and phases to meet the needs of different types of loads such as industrial motors and household appliances. For example, for industrial three-phase asynchronous motors, the energy output unit can provide a stable three-phase AC power supply, and dynamically adjust the output voltage and frequency according to the load changes of the motor to achieve efficient and energy-saving operation of the motor. For electronic equipment that requires DC power, such as computer servers, communication base stations, etc., the energy output unit can provide precise and stable DC voltage output.
[0018] The energy quality detection and correction module is a key part to ensure that the output energy meets the load requirements. For electrical energy output, it monitors the quality indicators of electrical energy such as harmonic content, voltage fluctuation, and frequency deviation in real time. When it is detected that the harmonic content exceeds the standard, the harmonics are filtered out by devices such as active power filters; when the voltage fluctuates greatly, the voltage output is stabilized by devices such as dynamic voltage restorers. For thermal energy output, the uniformity of temperature, the stability of flow and other indicators are detected, and the heat exchange area of the heat exchanger and the flow of the pump are adjusted to ensure that the thermal energy output meets the quality requirements of industrial heating processes or building heating.
[0019] Compared with the prior art, the present invention has the following advantages:
[0020] Multi-energy access and conversion: It can receive multiple energy forms such as electrical energy, thermal energy, and mechanical energy, and accurately convert them into a unified energy transmission form through intelligent adaptation circuits, avoiding the utilization limitations of different energy forms due to differences in characteristics, and greatly improving the comprehensive utilization rate of energy. For example, in industrial scenarios, low-quality thermal energy such as waste heat can be converted and utilized to reduce energy waste.
[0021] Intelligent allocation strategy: The intelligent processing unit based on deep learning algorithm can dynamically plan the energy flow and allocation ratio according to real-time monitoring data and historical operation rules. In the distributed energy microgrid scenario, it can be reasonably allocated according to the energy supply and demand of each user, so that energy can flow efficiently between different loads and energy storage units, reducing transmission and distribution losses.
[0022] Redundancy and switching mechanism: The intelligent adaptation circuit of the energy input unit has self-diagnosis and backup circuit switching functions, which can automatically switch in case of circuit failure to ensure the stability of energy input. The energy storage unit's various energy storage elements and flexible combination switching strategies can ensure reliable energy supply under different working conditions, such as supercapacitors to cope with instantaneous high power demands, and battery packs to ensure long-term stable output.
[0023] Adaptation to a wide range of application scenarios: Whether it is industrial production, smart buildings or distributed energy microgrids and other different scenarios, it can adapt to its specific energy structure and load requirements by adjusting the configuration of energy input and output units and the strategy of intelligent processing units, and realize customized energy management and regulation. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] Figure 1 It is a principle flow chart of an energy routing system with intelligent control function of the present invention. DETAILED DESCRIPTION
[0025] The present invention is further described in detail below with reference to the accompanying drawings.
[0026] Example 1
[0027] Industrial production scene
[0028] In a comprehensive industrial production workshop, there are multiple energy devices and different types of loads. In terms of electrical energy, there is the mains power supply and the solar photovoltaic power generation system on the roof of the workshop; in terms of thermal energy, there is the waste heat recovery system in the industrial production process; in terms of mechanical energy, there is the vibration mechanical energy generated by some large mechanical equipment during operation.
[0029] The power access port of the unit is connected to the mains and solar photovoltaic panels, the heat access port is connected to the waste heat recovery pipeline, and the mechanical energy access port is connected to the vibration energy collection device of the mechanical equipment. The intelligent adapter circuit converts the power generated by solar photovoltaic power generation into a standard DC power signal, converts the heat energy recovered from waste heat into power or other storable energy forms, and converts mechanical energy into power and performs efficiency monitoring.
[0030] The unit collects the parameters of each energy input and the energy demand information of various loads in the workshop (such as motors, heating equipment, lighting equipment, etc.) through the energy parameter monitoring module. The data analysis module determines the energy management strategy based on the deep learning algorithm. When the solar energy is sufficient and the industrial electricity load is low during the day, it instructs the excess solar energy to be stored in the battery pack in the energy storage unit; when a certain process in the industrial production process requires a large amount of heat energy and the waste heat recovery is insufficient, the stored electric energy is retrieved from the energy storage unit and converted into heat energy through the energy output unit for supplement. At the same time, the communication module sends the energy usage in the workshop to the factory's energy management center for overall energy scheduling and optimization management.
[0031] Example 2
[0032] Smart building scene
[0033] In a modern intelligent building, there are mains electricity supply, rooftop solar panels and geothermal energy utilization systems. The loads in the building include lighting systems, air conditioning systems, elevators and other electrical equipment, as well as some heating equipment that requires thermal energy supply.
[0034] The unit converts the mains electricity, solar power and geothermal energy into a unified energy signal. When the intelligent processing unit detects that there is sufficient solar energy during the day in summer and the air conditioning power demand is high, it will give priority to allocating solar power to the air conditioning system and store the excess power in the supercapacitor to cope with the instantaneous high power demand of equipment such as elevators. When the mains electricity price is low at night, appropriate power is obtained from the mains for storage or directly supplied to the building load. In winter, geothermal energy is supplied to heating equipment after energy conversion. The intelligent processing unit adjusts the output flow and temperature of geothermal energy according to the feedback information from the indoor temperature sensor to ensure comfortable indoor temperature and efficient energy utilization. The communication module is connected to the building's property management system. Property management personnel can remotely monitor the building's energy usage through mobile phones or computers, and perform some basic parameter settings and adjustments.
[0035] Example 3
[0036] Distributed energy microgrid scenario
[0037] In a distributed energy microgrid consisting of multiple household users and small commercial users, each user is equipped with solar panels, small wind turbines, energy storage batteries and other equipment.
[0038] The unit converts the solar energy, wind energy and other energy of each user and connects them to the microgrid. The intelligent processing unit performs unified scheduling according to the energy production and consumption of all users in the microgrid. For example, when the solar power generation of a user exceeds its own demand and the power of nearby users is insufficient, the intelligent processing unit instructs the energy output unit to transmit the excess power to the demanding user. When the energy reserve of the entire microgrid is low and the external mains price is high, the intelligent processing unit will send charging restriction instructions to the energy storage batteries of each user to give priority to the power supply of key loads (such as medical equipment, communication equipment, etc.). The communication module connects the energy routing system of each user to the microgrid control center to realize the sharing and collaborative control of energy information. The microgrid control center can formulate electricity price strategies based on the overall energy supply and demand situation, encourage users to reasonably adjust energy production and consumption behaviors, and improve the economy and reliability of the entire distributed energy microgrid.
[0039] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.
Claims
1. An energy routing system with intelligent control function, characterized in that: include: The energy input unit is equipped with multiple energy access ports, which can receive electrical energy, thermal energy, and mechanical energy, and convert different energies into standard energy signals through intelligent adaptation circuits. This circuit can automatically adjust conversion parameters according to energy characteristics and monitor conversion efficiency; The intelligent processing unit is connected to the energy input unit and includes an energy parameter monitoring module, which can obtain real-time data of energy power, voltage and current. The data analysis module analyzes the data according to the preset optimization strategy to plan the energy flow direction and distribution ratio. The instruction generation module generates control instructions according to the analysis results. The energy storage unit interacts with the intelligent processing unit and has a variety of energy storage components, such as battery packs and supercapacitors. Each component has an independent management module, which can realize charge and discharge control, status monitoring and fault warning, and store and release energy according to instructions, and can also switch energy storage combinations according to needs; The energy output unit is connected to the intelligent processing unit and can convert the standard energy signal into an energy form that is suitable for the external load. It can dynamically adjust the output energy parameters, such as the voltage and frequency of the electric energy, and has an energy quality detection and correction module to ensure the output quality.
2. The energy routing system with intelligent control function according to claim 1, characterized in that: The intelligent processing unit also includes a communication module that supports Wi-Fi, Bluetooth and 4G protocols to achieve information interaction with external devices or other systems, including transmitting energy data, receiving remote commands, and working with distributed energy.
3. The energy routing system with intelligent control function according to claim 1, characterized in that: The intelligent adapter circuit of the energy input unit has a self-diagnosis function, which can detect circuit faults and automatically switch to the backup circuit, while sending fault information to the intelligent processing unit.
4. The energy routing system with intelligent control function according to claim 1, characterized in that: The management module of the energy storage unit can estimate the remaining life of the energy storage element and adjust the charging and discharging strategy according to usage and environmental parameters to extend the service life of the energy storage element and ensure stable operation of the system.
5. The energy routing system with intelligent control function according to claim 1, characterized in that: The quality detection and correction module of the energy output unit can perform real-time analysis on the harmonic content and voltage fluctuation of the output energy, and correct the circuit parameters through feedback control so that the output energy meets the load's requirements for power quality.
6. The energy routing system with intelligent control function according to claim 1, characterized in that: It also includes an intelligent early warning and protection module, which can judge abnormal conditions based on the operating data of each unit in the system, issue early warning information and take corresponding protection measures, such as limiting energy input and cutting off the connection of faulty energy storage components.
7. The energy routing system with intelligent control function according to claim 1, characterized in that: The data analysis module in the intelligent processing unit adopts a deep learning algorithm. Through learning and training of a large amount of historical operation data, it can automatically adapt to the changing patterns of energy demand in different application scenarios, dynamically optimize the energy allocation strategy, and improve the overall energy efficiency of the system.
8. The energy routing system with intelligent control function according to claim 1, characterized in that: The various energy access ports of the energy input unit are designed with electromagnetic compatibility, which can effectively suppress the impact of external electromagnetic interference on the energy conversion process, while shielding and limiting the electromagnetic radiation generated by itself.
9. The energy routing system with intelligent control function according to claim 1, characterized in that: When the energy output unit supplies power to multiple different types of loads at the same time, it has the function of intelligent load identification and group management. It can automatically prioritize and reasonably allocate output energy according to the power requirements, voltage and current characteristics and operating status of each load.