Flexible and extensible intelligent energy routing system

Abstract

The invention relates to the technical field of energy management and distribution, and discloses a flexible and extensible intelligent energy routing system, and key modules of the intelligent energy routing system are in close cooperation. An intelligent interface of the energy acquisition module adapts to multi-energy characteristic efficient power conversion, a sensor array senses in real time and dynamically adjusts parameters, and an environment calibration function guarantees precision. The energy storage module deploys charging and discharging of various energy storage units through a distributed intelligent circuit, and response to high-power requirements is quick. The core control unit can update an algorithm online and quickly configure new equipment by means of a deep learning chip. The multiple ports of the energy output module accurately supply energy according to the load, and a circuit is cut off to give an alarm when a fault occurs. And the man-machine interaction interface is convenient to operate, and the redundant backup system takes over the main fault quickly, so that the operation is stable and uninterrupted. The system has the advantages that energy is efficiently integrated, utilized and sublimated, the power supply quality is extremely stable, intelligent and flexible adaptation innovation is achieved, and cost reduction and efficiency improvement are achieved through operation and maintenance management.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management and distribution, and in particular to a flexible and scalable intelligent energy routing system. Background Art

[0002] As the world accelerates towards a new era of low-carbon and intelligent development, the inherent shortcomings of the traditional energy architecture have become increasingly prominent and have become a bottleneck factor restricting sustainable development. Traditional energy supply is overly dependent on fossil fuels such as coal and oil. Their limited reserves are in danger of being depleted under continued high-intensity exploitation, not to mention the sharp increase in greenhouse gases caused by combustion emissions, which has led to catastrophic consequences such as global warming and ecological imbalance. Energy transformation is imminent.

[0003] Renewable energy sources such as solar energy, wind energy, hydropower, and thermal energy have stepped onto the historical stage and become the key to breaking the deadlock. However, their inherent intermittent, volatile, and geographical limitations cast a shadow on the efficient use of energy. Taking solar energy as an example, its energy output fluctuates greatly with the alternation of day and night and the change of weather, and the effective power generation time per day is limited; wind power generation has strict requirements on the stability of wind speed and wind direction. When the wind speed changes suddenly, the power drops sharply, making it difficult to maintain a constant power supply. Hydropower development is subject to the specific basin terrain and water resource distribution, and thermal energy utilization is closely related to the geothermal resource-rich areas or the waste heat conditions of specific industrial processes. Cross-regional allocation is almost a luxury due to energy conversion, transmission losses, and infrastructure constraints.

[0004] Looking at the current status of energy management technology, most solutions are fragmented and single. Traditional energy harvesting devices have single and fixed interfaces, and are helpless in the face of multiple energy coexistence scenarios. Different energy characteristics cannot be converted in a compatible manner, and a large amount of energy is lost at the conversion bottleneck. In the storage link, the charging and discharging strategy is simple, and complex factors such as real-time power load and electricity price fluctuations are not considered. Energy storage equipment may be idle for a long time to waste capacity, or over-charge and discharge may reduce its life. Once emerging energy storage technologies or power-consuming equipment that adapts to multiple energy sources emerge, the existing system lacks scalability, hardware adaptation requires large-scale line transformation, and software updates affect the entire system, which cannot resonate with technological innovation, giving rise to an urgent demand for building an integrated, highly flexible intelligent energy routing system. Summary of the invention

[0005] In order to solve the above-mentioned problems, the present invention proposes a flexible and scalable intelligent energy routing system.

[0006] In order to solve the above technical problems, the technical solution proposed by the present invention is: a flexible and scalable intelligent energy routing system, comprising:

[0007] Energy collection module, used to collect energy from solar energy, wind energy, hydropower and thermal energy. It is equipped with an intelligent conversion interface, which can automatically adapt to the characteristics of different energy sources and efficiently convert electrical energy. The conversion efficiency is ≥85%. The interface integrates a sensor array to sense the intensity and frequency parameters of the energy source in real time and dynamically adjust the working parameters of the conversion circuit. The collection efficiency fluctuation under different working conditions is ≤3%. It also has an environmental adaptability self-calibration function. It can automatically calibrate the collection parameter benchmark every 7 days according to seasonal and regional environmental changes to improve the collection accuracy.

[0008] The energy storage module is electrically connected to the energy collection module and includes multiple energy storage units such as lithium-ion batteries, supercapacitors, and flywheel energy storage. Each unit is connected to the management circuit through the intelligent switching of the distributed architecture and has the ability to switch quickly in milliseconds. It can flexibly adjust the charging and discharging strategies of each unit according to the real-time power demand of the system and the fluctuation of energy market prices. The cycle charging and discharging life of each unit is ≥5000 times. When encountering sudden high-power load demand, multiple energy storage units can be quickly deployed within 0.5 seconds to jointly supply power, and the system voltage fluctuation range can be controlled to not exceed ±2% of the rated voltage;

[0009] The intelligent energy routing core control unit communicates with other modules and external loads, and has a built-in deep learning intelligent algorithm chip. The chip uses deep learning algorithms to optimize the energy distribution path based on real-time energy, load and historical data, reducing energy transmission loss to less than 8% within 8 seconds. It supports online algorithm updates, which can be completed within 2 minutes with the help of wireless communication. It can also automatically identify and quickly configure new access devices, and complete the system topology and energy scheduling strategy updates within 8 minutes after the new device is connected;

[0010] The energy output module is connected to the core control unit and is equipped with multiple independently controllable energy output ports. Each port is equipped with an adaptive adjustment circuit, which can accurately adjust the output power according to the rated power, voltage and current requirements of the external load device, with a matching accuracy of 99%. This circuit has fault self-diagnosis and isolation functions. Once a short circuit, overload or leakage fault of the external load device is detected, the corresponding port circuit can be quickly cut off within microseconds and an alarm message will be sent to the core control unit;

[0011] The human-machine interaction interface is connected to the core control unit and adopts a touch screen combined with a voice interaction module. Users can intuitively view the real-time operating status of the system, such as energy flow, power of each module, and load power information. It can also conveniently set system parameters, such as energy storage unit charge and discharge thresholds and load priority settings. The interactive response delay is ≤0.3 seconds.

[0012] Redundant backup system, key components are equipped with at least one set of redundant equipment. When the main equipment fails, the redundant equipment can quickly take over the work within 3 seconds, ensuring the overall system reliability ≥ 99.95% and maintaining uninterrupted power supply.

[0013] Preferably, the sensor array of the energy harvesting module is also provided with an intelligent dustproof structure, and the air duct is designed using aerodynamic principles to regularly remove surface dust and maintain sensing accuracy, and is cleaned at least once a month.

[0014] Preferably, the intelligent switching and management circuit of the energy storage module has built-in energy storage unit health monitoring software, which analyzes the changing trends of internal resistance and temperature parameters in real time, warns of potential faults 12 hours in advance, and the fault warning accuracy rate is ≥95%.

[0015] Preferably, the intelligent algorithm chip of the intelligent energy routing core control unit uses an encrypted communication protocol to interact with each module. The encryption level meets high industry standards to prevent data leakage and tampering and ensure system communication security.

[0016] Preferably, the adaptive regulation circuit of the energy output module integrates an intelligent temperature control module, which dynamically adjusts the heat dissipation strategy according to the real-time temperature of the load, controls the load operating temperature fluctuation within ±8°C, and ensures stable operation of the equipment.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] Efficient energy integration and utilization: By intelligently converging and coordinating multiple energy sources, the energy potential can be deeply tapped. Compared with the traditional distributed energy utilization model, the system's comprehensive energy utilization rate has soared by 35%-40%, and the proportion of abandoned energy has been reduced by more than 40%, thus maximizing the value of the entire life cycle of energy and facilitating the green transformation of energy.

[0019] Extremely stable power supply quality: Relying on the high-reliability architecture with redundant backup and the millisecond-level emergency response of the energy storage unit, it completely isolates the interference of city power fluctuations and power outages caused by faults. The voltage and frequency outputs are as stable as a rock, and the fluctuation amplitude is strictly constrained to an extremely small range (voltage ±2%, frequency ±0.1Hz), laying a solid power foundation for highly sensitive power consumption scenarios such as precision manufacturing and data centers, and the risk of production interruption is almost zero.

[0020] Intelligent flexible adaptation innovation: With the power of deep learning, the system can understand the dynamic changes of load in real time, change the power consumption strategy as needed, and seamlessly adapt to the addition and deletion of power-consuming equipment and the switching of working conditions. New equipment is automatically identified and parameters are intelligently matched at the moment of access, and the whole process is seamlessly upgraded, so that you can easily embrace the future wave of energy consumption upgrades and technology iterations.

[0021] Operation and maintenance management reduces costs and increases efficiency: The simple and intuitive human-computer interaction interface greatly reduces the labor costs and technical barriers of operation and maintenance, and provides remote real-time monitoring, accurate fault prediction and one-click repair. Compared with the traditional operation and maintenance model, the manpower input is reduced by 40%-45%, the operation and maintenance cycle is shortened by 60%, and the operating cost of the system throughout its life cycle is significantly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a principle flow chart of a flexible and scalable intelligent energy routing system of the present invention. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below with reference to the accompanying drawings.

[0024] Example 1

[0025] Optimizing energy management and control in ecological farms in remote mountainous areas

[0026] In the complex energy environment of ecological farms in remote mountainous areas, this intelligent energy routing system works precisely. In the energy collection module, the solar panel array integrates a high-precision solar tracking system. Through the dual-axis linkage mechanical structure and intelligent control algorithm, the panel orientation is dynamically adjusted according to the solar azimuth and altitude angle in real time to ensure that the incident angle of light is always close to the optimal, and the photoelectric conversion efficiency is improved by 15%; the small wind turbine is equipped with an intelligent variable pitch and variable speed constant frequency control system, which dynamically adjusts the blade pitch angle and speed according to the real-time wind speed, broadens the wind energy capture range, and improves the stability of power generation by 20%. The collected energy is converted and gathered in the energy storage module. The core control unit accurately arranges the charging and discharging plan according to the working and rest rules of the farm's electrical equipment (irrigation, agricultural product processing equipment, concentrated electricity during the day, and living facilities decentralized electricity) and the charge state of the energy storage unit. During the peak of daytime electricity consumption, energy storage discharge is prioritized, and the energy output module accurately adapts electricity to various equipment. Irrigation pumps accurately supply energy according to the terrain head and flow requirements. Agricultural product processing machinery operates smoothly, and voltage fluctuations are controlled at ±1%, ensuring the consistency of product processing quality. The defective rate is reduced by 20% compared to traditional power supply. After long-term operation monitoring, the system has been running stably for more than 3 years. Due to the increase in energy self-sufficiency, the electricity cost has been reduced by 60% compared to the previous mode of dependence on municipal electricity, demonstrating excellent energy management efficiency.

[0027] Example 2

[0028] Green energy saving and reliability advancement in data centers

[0029] Under the severe energy consumption and reliability challenges of large data centers, this system is deeply embedded to achieve a gorgeous turnaround. On the energy collection side, the rooftop photovoltaic array uses high-efficiency bifacial power generation components, combined with an intelligent maximum power tracking algorithm, and backscattered light can also be efficiently converted into electrical energy, with a power generation gain of 10%-15%; the introduction of lake water cooling and computer room waste heat recovery system, through the organic Rankine cycle to achieve thermal energy cascade utilization and power conversion, broaden the energy input dimension. The core control unit dynamically allocates energy flows based on the real-time computing load, heat dissipation requirements and electricity price fluctuations of the server. During busy business hours, multiple energy sources work together to support large-scale data parallel computing, and the energy output accurately matches the power supply specifications of the cabinet server. Active power filtering technology is used to reduce the power harmonic distortion rate to less than 2%, ensuring accurate data transmission and storage; during low-load periods at night, the energy storage unit absorbs low-priced electricity and recovers waste heat for energy storage. Within a one-year period, the data center's unit computing power energy consumption was significantly reduced by 30%, and electricity bills were reduced by more than 400,000 yuan. The system intelligently sensed and optimized power distribution as soon as the new server was put on the shelves. The computing power was expanded by 15% while the system reliability remained high, ensuring the continuity of data services.

[0030] Example 3

[0031] Building a smart energy ecosystem for future campuses

[0032] This system serves as the core engine when building an energy microgrid ecosystem in a smart campus scenario. The solar panels of teaching buildings integrate translucent photovoltaic materials, taking into account both lighting and power generation, expanding the energy utilization space on the building surface; the geothermal energy collection system is deeply coupled to the campus heating and domestic hot water pipe networks, and uses thermal energy in a cascade. The smart meter feeds back the power load of dormitories and classrooms to the core control unit in real time, and accurately allocates energy according to the work and rest of teachers and students and the rules of teaching activities (power consumption in the teaching area surges during class, and in the dormitory area is low; vice versa after class). During peak teaching power consumption, energy storage is released first and energy is collected in real time to ensure that multimedia teaching equipment and laboratory precision instruments are fully powered, and the voltage recovery time under the start-up impact of power-consuming equipment is controlled within 10 milliseconds; the dormitory area customizes the power supply strategy based on the students' personalized power consumption preferences (air conditioning temperature, appliance usage time), and teachers and students can remotely control it through the mobile interactive interface. After long-term operation, the proportion of renewable energy on campus has climbed to 45%, with significant results in peak shaving and valley filling. The difference in peak-valley electricity consumption has narrowed by 40%, cultivating a green and low-carbon campus culture while injecting lasting power into the stable operation of smart campus facilities, leading a new trend in future energy consumption.

[0033] 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. A flexible and scalable intelligent energy routing system, characterized in that: include: Energy collection module, used to collect energy from solar energy, wind energy, hydropower and thermal energy. It is equipped with an intelligent conversion interface, which can automatically adapt to the characteristics of different energy sources and efficiently convert electrical energy. The conversion efficiency is ≥85%. The interface integrates a sensor array to sense the intensity and frequency parameters of the energy source in real time and dynamically adjust the working parameters of the conversion circuit. The collection efficiency fluctuation under different working conditions is ≤3%. It also has an environmental adaptability self-calibration function. It can automatically calibrate the collection parameter benchmark every 7 days according to seasonal and regional environmental changes to improve the collection accuracy. The energy storage module is electrically connected to the energy collection module and includes multiple energy storage units such as lithium-ion batteries, supercapacitors, and flywheel energy storage. Each unit is connected to the management circuit through the intelligent switching of the distributed architecture and has the ability to switch quickly in milliseconds. It can flexibly adjust the charging and discharging strategies of each unit according to the real-time power demand of the system and the fluctuation of energy market prices. The cycle charging and discharging life of each unit is ≥5000 times. When encountering sudden high-power load demand, multiple energy storage units can be quickly deployed within 0.5 seconds to jointly supply power, and the system voltage fluctuation range can be controlled to not exceed ±2% of the rated voltage; The intelligent energy routing core control unit communicates with other modules and external loads, and has a built-in deep learning intelligent algorithm chip. The chip uses deep learning algorithms to optimize the energy distribution path based on real-time energy, load and historical data, reducing energy transmission loss to less than 8% within 8 seconds. It supports online algorithm updates, which can be completed within 2 minutes with the help of wireless communication. It can also automatically identify and quickly configure new access devices, and complete the system topology and energy scheduling strategy updates within 8 minutes after the new device is connected; The energy output module is connected to the core control unit and is equipped with multiple independently controllable energy output ports. Each port is equipped with an adaptive adjustment circuit, which can accurately adjust the output power according to the rated power, voltage and current requirements of the external load device, with a matching accuracy of 99%. This circuit has fault self-diagnosis and isolation functions. Once a short circuit, overload or leakage fault of the external load device is detected, the corresponding port circuit can be quickly cut off within microseconds and an alarm message will be sent to the core control unit; The human-machine interaction interface is connected to the core control unit and adopts a touch screen combined with a voice interaction module. Users can intuitively view the real-time operating status of the system, such as energy flow, power of each module, and load power information. It can also conveniently set system parameters, such as energy storage unit charge and discharge thresholds and load priority settings. The interactive response delay is ≤0.3 seconds. Redundant backup system, key components are equipped with at least one set of redundant equipment. When the main equipment fails, the redundant equipment can quickly take over the work within 3 seconds, ensuring the overall system reliability ≥ 99.95% and maintaining uninterrupted power supply.

2. A flexible and scalable intelligent energy routing system according to claim 1, characterized in that: The sensor array of the energy harvesting module is also equipped with an intelligent dust-proof structure. The air duct is designed using aerodynamic principles to regularly remove dust from the surface to maintain sensing accuracy. It should be cleaned at least once a month.

3. A flexible and scalable intelligent energy routing system according to claim 1, characterized in that: The intelligent switching and management circuit of the energy storage module has built-in energy storage unit health monitoring software, which analyzes the changing trends of internal resistance and temperature parameters in real time, and warns of potential faults 12 hours in advance, with a fault warning accuracy rate of ≥95%.

4. A flexible and scalable intelligent energy routing system according to claim 1, characterized in that: The intelligent algorithm chip of the intelligent energy routing core control unit uses an encrypted communication protocol to interact with each module. The encryption level meets the industry's high standards to prevent data leakage and tampering and ensure system communication security.

5. A flexible and scalable intelligent energy routing system according to claim 1, characterized in that: The energy output module’s adaptive regulation circuit integrates an intelligent temperature control module, which dynamically adjusts the heat dissipation strategy based on the real-time temperature of the load, controls the load operating temperature fluctuation within ±8°C, and ensures stable operation of the equipment.

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