Multi-energy complementary intelligent energy routing method

Abstract

The invention relates to the technical field of energy management and intelligent control, and discloses a multi-energy complementary intelligent energy routing method, which comprises the following steps: energy data acquisition: deploying a plurality of sensors, and accurately acquiring the generation amount, storage amount, usage amount, quality parameters and equipment state information of energy; and information integration and analysis: transmitting the data to a central processing unit through a communication network, and cleaning and sorting. And strategy generation: based on the analysis result and the optimization target, adopting an intelligent optimization algorithm to generate a flexible and adaptive multi-energy complementary strategy. And conversion and distribution: the central processing unit controls the energy conversion equipment to convert energy according to a strategy, and directs the intelligent energy routing device to dynamically distribute energy according to terminal requirements, price fluctuation, power grid loads and the like. System performance monitoring and feedback: system performance is monitored in an omnibearing manner, and a central processing unit adjusts strategies and schemes to guarantee stable operation. The system has the advantages that intelligent management and cooperative operation of multiple kinds of energy are achieved, and the overall performance and reliability of the energy system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management and intelligent control, and in particular to an intelligent energy routing method for multi-energy complementarity. Background Art

[0002] With the continuous growth of global energy demand and the increasing attention to environmental protection, the traditional single energy supply model can no longer meet the requirements of sustainable development. As an emerging energy solution, the multi-energy complementary system can integrate multiple energy sources such as solar energy, wind energy, electricity, thermal energy, and gas energy, and achieve efficient energy utilization and supply and demand balance by optimizing energy production, storage, conversion, and distribution. However, the existing multi-energy complementary system still has many shortcomings in energy management and control, such as inaccurate energy data collection, lack of flexibility in the generation of multi-energy complementary strategies, low efficiency in energy conversion and distribution, and untimely system performance monitoring and feedback, which limits the widespread application and promotion of the multi-energy complementary system. Summary of the invention

[0003] In order to solve the above-mentioned problems, the present invention proposes a multi-energy complementary intelligent energy routing method for realizing intelligent management and coordinated operation of multiple energy sources and improving the overall performance and reliability of the energy system.

[0004] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0005] Energy data collection steps: deploy a variety of specially designed sensors to accurately collect various key data of various energy sources such as solar energy, wind energy, electrical energy, thermal energy, and gas energy. These sensors can monitor the amount of energy generated in real time, such as the power generated by solar panels and the output power of wind turbines; accurately obtain energy storage information, such as the remaining power of batteries and the gas reserves of gas tanks; record energy usage in detail, including energy consumption data of various electrical and thermal equipment; at the same time, they can also accurately measure energy quality parameters, such as voltage stability and frequency deviation of electrical energy, as well as operating status information of energy equipment, such as the start and stop status of equipment, fault codes, etc. These data will provide a comprehensive and reliable basis for subsequent energy management and control.

[0006] Energy information integration and analysis steps: The rich and diverse energy data collected are transmitted to the central processing unit in real time through a high-speed and stable communication network. The central processing unit has a built-in advanced data integration and analysis software module, which first cleans and organizes the data to remove invalid and redundant data information. Then, complex mathematical models and algorithms are used to deeply explore the laws and relationships behind the data and build a real-time operation model of the multi-energy system. This model can not only clearly present the interdependence and conversion relationship between different energy sources, such as the charging and discharging relationship between solar power generation and battery energy storage, the conversion ratio of thermal energy and electrical energy in energy conversion equipment, etc., but also accurately reflect the working characteristics of energy equipment, such as the power curves of different types of wind turbines, the energy consumption characteristics of various gas equipment, etc., as well as the dynamic trend of energy supply and demand, including the fluctuation of energy demand in different time periods, the stability analysis of energy supply, etc., thereby providing a solid theoretical basis for the generation of multi-energy complementary strategies.

[0007] Steps for generating multi-energy complementary strategies: Based on the comprehensive and in-depth results obtained from the integration and analysis of energy information, combined with the preset multi-energy complementary optimization goals, the strategy generation work is carried out. These optimization goals cover multiple key aspects such as the lowest energy cost, the highest energy utilization rate, and the lowest carbon emissions. In order to achieve these goals, the central processing unit adopts intelligent optimization algorithms, including but not limited to genetic algorithms, particle swarm optimization algorithms, simulated annealing algorithms, etc. These algorithms quickly search for the optimal solution in a huge solution space by simulating the evolution process of natural organisms or the annealing process of physical systems. For example, the genetic algorithm regards the multi-energy complementary strategy as a chromosome, and continuously iterates and optimizes through genetic operations such as selection, crossover, and mutation to find the best energy combination and allocation scheme that meets the optimization goal; the particle swarm optimization algorithm represents each particle as a possible strategy, and gradually approaches the optimal strategy through information sharing and position update between particles. The generated control strategy has a high degree of flexibility and adaptability, and can achieve fast and accurate dynamic switching and coordinated complementarity between different energy forms according to the real-time status of the energy system, effectively meet the energy needs of the system under different working conditions, and ensure that the entire energy system always operates in an efficient and stable state.

[0008] Energy conversion and distribution steps: Strictly based on the generated multi-energy complementary strategy, the central processing unit sends precise control instructions to the energy conversion equipment, driving the energy conversion equipment to efficiently convert one form of energy into other required forms of energy. For example, when there is sufficient solar energy and low electricity demand, the inverter is controlled to convert excess solar power into DC power that can be stored in the battery; or when the demand for heat energy is large and the gas supply is sufficient, the gas turbine is started to convert the gas energy into heat energy, and the heat energy is distributed to each heat-using terminal through the heat exchange system. At the same time, the central processing unit also directs the intelligent energy routing device to accurately distribute a variety of converted or unconverted energy to different energy consumption terminals according to the optimized distribution plan. During the distribution process, the intelligent energy routing device monitors various information of the energy consumption terminal in real time, including changes in its real-time demand, fluctuations in energy prices, and the real-time status of the grid load. For example, when it is monitored that the demand for electricity of a certain industrial electrical equipment increases sharply during the peak production period, and the grid load permits, the intelligent energy routing device will give priority to allocating electricity from the energy storage device or other high-efficiency power generation equipment; and when the energy price fluctuates, such as the low electricity price at night, it will appropriately increase the storage capacity of electricity and reduce the use of high-priced energy, thereby achieving efficient energy utilization and supply and demand balance by dynamically adjusting the energy allocation ratio, minimizing energy costs and improving the reliability of the energy system.

[0009] System performance monitoring and feedback steps: Establish a comprehensive, multi-level system performance monitoring system to monitor the overall performance of the multi-energy complementary intelligent energy routing system in real time and accurately. The monitoring indicators cover the stability of energy supply, such as monitoring whether there are interruptions in energy supply, excessive fluctuations, etc.; the accuracy of energy conversion and distribution, including whether the output of energy conversion equipment meets expectations and whether energy distribution reaches the target terminal accurately; the operational reliability of energy equipment, such as whether the equipment has potential faults such as overheating and abnormal vibration. At the same time, the quality of energy is also monitored to ensure that the energy distributed to the terminal meets the relevant quality standards. When the system performance monitoring module detects that the system performance deviates from the preset standard, such as the energy conversion efficiency is lower than the set threshold, the energy supply interruption time exceeds the allowable range, etc., detailed feedback information will be generated immediately and transmitted to the central processing unit. Based on the feedback information, the central processing unit quickly starts the strategy adjustment mechanism, re-evaluates the state of the energy system, optimizes the multi-energy complementary strategy, and adjusts the energy conversion and distribution plan to maintain the stable and efficient operation of the system, ensuring that the energy system can always provide users with reliable and high-quality energy services.

[0010] Compared with the prior art, the present invention has the following advantages:

[0011] Improve energy efficiency: Integrate multiple energy sources such as solar energy, wind energy, electricity, thermal energy and gas energy, and intelligently switch and coordinate and complement each other according to different energy characteristics and real-time working conditions. For example, according to changes in light and wind power, dynamically adjust the proportion of wind and solar power generation, avoid the limitation of a single energy source, reduce energy waste, and significantly improve comprehensive utilization efficiency.

[0012] Reduce energy costs: Analyze energy price fluctuations, store or purchase energy during low-price periods, and reduce usage during high-price periods to reduce procurement costs. Multi-energy complementarity reduces repeated equipment investment and operation and maintenance costs, such as avoiding the independent construction and maintenance of multiple facilities for a single energy system, extending equipment life, reducing fault repairs, and cutting costs in many ways.

[0013] Enhanced energy supply stability: Energy storage modules store multiple energy sources and serve as backup in case of supply fluctuations or interruptions. At the same time, intelligent fault monitoring and switching mechanisms can quickly enable redundant equipment or switch energy paths to ensure supply continuity. For example, when solar energy is unstable, the battery will supply power in time, and automatically resume optimized operation after troubleshooting to ensure stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a principle flow chart of a multi-energy complementary intelligent energy routing method of the present invention. DETAILED DESCRIPTION

[0015] The present invention is further described in detail below with reference to the accompanying drawings.

[0016] Example 1

[0017] Small distributed energy systems

[0018] System configuration: Build a distributed energy system in a small community or commercial building. The energy collection module includes a solar panel array installed on the roof to collect solar energy; a small wind turbine to collect wind energy; and an electric energy transformer connected to the mains grid to obtain mains electricity. The energy storage module is equipped with a lithium-ion battery pack to store excess electricity. The energy conversion module contains an inverter to convert the DC power generated by the solar panels and wind turbines into AC power for use by local loads or to be incorporated into the grid; and a rectifier to convert AC power into DC power for storage when needed. The energy distribution module uses an intelligent energy routing device composed of smart meters and smart switches to distribute electricity according to user needs and energy supply conditions. The central control unit is a high-performance industrial computer that runs specially developed energy management software.

[0019] Operation process: In the energy data collection step, the sensors on the solar panels monitor the solar radiation intensity and power generation in real time, the sensors on the wind turbines monitor the wind speed and output power, the power transformers monitor the voltage, current and power of the mains, and the sensors on the battery packs monitor the battery power, charge and discharge current and voltage, and transmit these data to the central control unit. In the energy information integration and analysis step, the central control unit organizes and analyzes the data to build an operation model of the small distributed energy system, such as analyzing the complementarity of solar energy and wind energy and determining the energy supply capacity under different weather conditions. Based on this, in the multi-energy complementary strategy generation step, when the sun is abundant and the wind is weak, the central control unit generates a strategy to give priority to solar power generation and store excess power in the battery; at night or on rainy days, it decides whether to take power from the battery or purchase power from the mains grid according to the battery power and the mains price. In the energy conversion and distribution step, the intelligent energy routing device distributes power to loads such as residential power equipment, commercial power equipment and public lighting in the community according to the strategy. In the system performance monitoring and feedback step, the central control unit monitors the system's energy supply stability, power quality and other indicators in real time. If it finds that the power generation efficiency of the solar panel has suddenly dropped, it may be caused by dust accumulation through analysis. The system will issue a cleaning reminder to maintain the efficient operation of the system.

[0020] Example 2

[0021] Industrial Park Integrated Energy Management System

[0022] System configuration: In an industrial park, the energy collection module is large in scale, with solar panel arrays distributed in the open space and factory roofs of the park; multiple large wind turbines; connected to the industrial waste heat recovery system in the park to collect heat energy; and gas meters connected to gas pipelines to obtain gas energy. The energy storage module includes a large-capacity battery pack, heat storage tank and gas storage tank. The energy conversion module is equipped with efficient inverters, rectifiers, heat pumps (for conversion between heat and electricity), gas turbines and other equipment. The energy distribution module is a complex intelligent energy routing network that can distribute electricity, heat and gas energy to energy consumption terminals in different areas such as factory workshops, office buildings, dormitories, etc. in the park. The central control unit adopts a distributed computing architecture, consisting of multiple servers, running complex energy management and optimization algorithms.

[0023] Operation process: In the energy data collection step, numerous sensors are distributed on various energy collection devices and energy conversion devices to collect massive amounts of energy data, such as the temperature, light intensity, and power generation efficiency of solar panels, the wind speed, wind direction, and output power of wind turbines, the heat flow and temperature of waste heat recovery systems, and the flow and pressure of gas meters, and transmit them to the central control unit. In the energy information integration and analysis step, the central control unit builds a detailed operation model of the energy system of the entire industrial park, analyzes the energy demand patterns of different factories, the synergy between different energy sources, and the relationship between the operating status of energy equipment and energy output. For example, it is analyzed that some factories have a large demand for electricity during the peak production period during the day, and a large demand for heat energy at night for equipment insulation. Based on this, in the multi-energy complementary strategy generation step, the central control unit formulates a strategy to give priority to the use of solar energy, wind energy, and city electricity during the day, and use the heat energy generated by the waste heat recovery system to store it in the heat storage tank; at night, according to the gas price and the energy storage situation of the heat storage tank and battery, the gas energy, heat energy, and electricity are reasonably allocated. In the energy conversion and distribution step, the intelligent energy routing network accurately distributes various energy sources to various areas and equipment according to the strategy, such as distributing electrical energy to production equipment, thermal energy to heating systems and heat demand links in production processes, and gas energy to gas equipment or converting it into electrical energy through gas turbines to supplement the power grid. In the system performance monitoring and feedback step, the central control unit continuously monitors the system performance. If a wind turbine fails, it immediately starts the backup unit and arranges maintenance personnel to overhaul it. At the same time, it adjusts the energy distribution strategy to ensure that the energy supply of the park is not affected.

[0024] Example 3

[0025] Smart Building Energy Management System

[0026] System configuration: For a modern intelligent building, the energy collection module includes solar panels installed on the building facade and roof to collect solar energy; a ground source heat pump system to collect underground heat energy; and an electrical energy interface connected to the city power grid. The energy storage module has a small battery pack for storing solar power, and a heat storage device for storing excess heat energy generated by the ground source heat pump. The energy conversion module includes an inverter and a ground source heat pump unit (which can realize two-way conversion of electrical energy and thermal energy). The energy distribution module realizes energy distribution through the intelligent building energy management system (BEMS), which integrates equipment such as smart electricity meters, smart heat meters and smart valves, and can distribute electrical energy and thermal energy to energy consumption terminals such as air conditioning systems, lighting systems, elevator systems, and office equipment in the building. The central control unit is a core functional module in the building automation system (BAS), running algorithms specifically for energy management of intelligent buildings.

[0027] Operation process: In the energy data collection step, the sensors of the solar panels collect data such as light intensity and power generation, the sensors of the ground source heat pump system monitor underground temperature, heat exchange volume and other information, the power interface monitors the relevant parameters of the city power, and the sensors of the battery group and the heat storage device monitor the energy storage status and transmit the data to the central control unit. In the energy information integration and analysis step, the central control unit builds an operation model of the intelligent building energy system, analyzes the energy demand characteristics of different areas and different equipment in the building, and the synergistic relationship between solar energy, geothermal energy and electric energy. For example, it is analyzed that the air conditioning system has a large demand for cooling (provided by the ground source heat pump) in summer, and a large demand for heat in winter, and the office area has a high demand for electricity during the day on weekdays. Based on this, in the multi-energy complementary strategy generation step, the central control unit formulates a strategy to give priority to the use of solar power generation for lighting and office equipment during the day in summer, and the ground source heat pump provides air conditioning cooling and stores excess heat; in winter, according to the situation of solar energy and batteries, the electric energy and the heat generated by the ground source heat pump are reasonably allocated. In the energy conversion and distribution step, the smart building energy management system controls smart meters, smart heat meters and smart valves according to the strategy to distribute electricity and heat to various devices and areas. In the system performance monitoring and feedback step, the central control unit monitors the stability of energy supply, the operating status of energy equipment, etc. If the energy efficiency of the ground source heat pump is found to be reduced, it may be due to the blockage of the underground heat exchange pipeline through analysis. The system will issue an alarm and recommend pipeline cleaning and maintenance to ensure the efficient operation of the building energy system.

[0028] 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 multi-energy complementary intelligent energy routing method, characterized in that: The following steps are involved: Step 1: Energy data collection: Use a variety of sensors to collect real-time data on solar energy, wind energy, electricity, thermal energy, and gas energy, including energy generation, storage, usage, energy quality parameters, and energy equipment operating status information; Step 2: Energy information integration and analysis: The collected energy data are transmitted to the central processing unit, where the data are integrated and analyzed to build a real-time operation model of the multi-energy system. The model can reflect the relationship between different energy sources, the working characteristics of energy equipment, and the dynamic changes of energy supply and demand; Step 3: Generation of multi-energy complementarity strategy: Based on the results of energy information integration and analysis, and according to the preset multi-energy complementarity optimization goals, such as lowest energy cost, highest energy utilization rate, and lowest carbon emissions, a multi-energy complementarity control strategy is generated using an intelligent optimization algorithm. The intelligent optimization algorithm includes but is not limited to a genetic algorithm, a particle swarm optimization algorithm, and a simulated annealing algorithm. The generated control strategy can achieve dynamic switching and coordinated complementarity between different energy forms to meet the energy needs of the system. Step 4: Energy conversion and distribution: Based on the generated multi-energy complementary strategy, control the energy conversion equipment to convert one energy form into other required energy forms, and distribute multiple energy sources to different energy consumption terminals through intelligent energy routing devices. During the distribution process, dynamically adjust the energy distribution ratio according to the real-time demand of the energy consumption terminal, energy price fluctuations, and grid load conditions to ensure efficient use of energy and balance between supply and demand; Step 5: System performance monitoring and feedback: Real-time monitoring of the overall performance of the multi-energy complementary intelligent energy routing system, including the stability of energy supply, the accuracy of energy conversion and distribution, and the operational reliability of energy equipment. When the system performance deviates from the preset standards, timely feedback information is generated and the control strategy is adjusted to maintain the stable and efficient operation of the system.

2. The multi-energy complementary intelligent energy routing method according to claim 1, characterized in that: In step one, the multiple sensors also include environmental sensors for collecting environmental parameters such as ambient temperature, humidity, light intensity, and wind speed. The collected environmental parameters are used to assist in analyzing the operating efficiency of energy generation equipment and predicting energy demand.

3. The multi-energy complementary intelligent energy routing method according to claim 1, characterized in that: In step three, the preset multi-energy complementary optimization target can also be customized according to the user's personalized needs. The user can set the energy cost upper limit, energy quality requirements, and carbon emission quota personalized parameters through the human-computer interaction interface. The system adjusts the optimization target weight according to the personalized parameters set by the user to generate a multi-energy complementary strategy that meets the user's needs.

4. The multi-energy complementary intelligent energy routing method according to claim 1, characterized in that: In step 4, the intelligent energy routing device has an energy caching function, which can cache a certain amount of energy to cope with instantaneous fluctuations in energy supply, and the charging and discharging efficiency of the cached energy is at a reasonable level.

5. The multi-energy complementary intelligent energy routing method according to claim 1, characterized in that: In step five, the system performance monitoring also includes fault monitoring of energy conversion equipment and intelligent energy routing devices. When equipment failure is detected, redundant equipment can be automatically started or emergency measures can be taken to ensure the continuity of energy supply.

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