Micro-grid energy interaction system and method based on distributed energy storage equipment

Abstract

The invention discloses a micro-grid energy interaction system and method based on distributed energy storage equipment, and relates to the technical field of micro-grid energy interaction.The micro-grid energy interaction system comprises a processor and a loss monitoring module, the loss monitoring module is used for monitoring energy loss generated in the power generation, storage, transportation and use processes of energy, and the energy loss monitoring module is used for monitoring the energy loss; the loss detection module is used for receiving energy loss information and transmitting the information to the processor through baseband transmission and Bluetooth transmission, the processor constructs an energy loss model according to the energy loss information, and the loss detection module comprises a power generation monitoring assembly, a storage monitoring assembly, a transmission monitoring assembly and a use monitoring assembly. By designing the lossy monitoring module, the function of acquiring the energy loss condition in real time is achieved, the problems that the energy loss monitoring precision is insufficient and energy loss information of all links cannot be coupled are solved, energy loss coupling analysis of all links can be subjected to cross-module coordinated regulation and control, the energy utilization efficiency is improved, and the energy utilization rate is increased. And the system operation safety and stability are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of microgrid energy control technology, and in particular to a microgrid energy interaction system and method based on distributed energy storage equipment. Background Art

[0002] The large-scale integration of distributed renewable energy sources such as wind power and photovoltaics has led to increased power fluctuations in the grid. The randomness and intermittency of these fluctuations pose challenges to grid stability. Distributed energy storage systems mitigate these fluctuations through real-time charging and discharging, improving the grid's ability to absorb high-penetration renewable energy. The spatial separation of my country's energy centers and load centers makes long-distance power transmission costly and poses safety risks. Developing a localized "distributed renewable energy + energy storage" microgrid model can reduce transmission losses and enable local energy production and consumption.

[0003] The existing microgrid energy interaction system has insufficient accuracy in monitoring energy loss and poor dynamic adaptability. The statistical deviation of the total system loss is amplified due to the superposition of multi-node errors, and the energy loss of each link cannot be coupled and analyzed after being collected.

[0004] Patent CN110112775B discloses a micro-energy grid system with distributed energy storage. The above patent realizes the smooth access and stable use of new energy, as well as the efficient and economical use of new energy.

[0005] The above patent has high flexibility in scheduling of the micro-energy grid system containing distributed energy storage. When scheduling energy, multiple factors such as demand-side load and energy devices can be considered at the same time. Therefore, it can effectively improve the comprehensive utilization efficiency of energy in the entire micro-energy grid system containing distributed energy storage, as well as the supply and demand matching degree of the distributed micro-energy grid system composed of distributed energy storage. There is room for optimization in the monitoring of energy loss during energy collection, storage, transportation and utilization.

[0006] To this end, the present application proposes a microgrid energy interaction system and method based on distributed energy storage devices for real-time acquisition of energy loss conditions. Summary of the Invention

[0007] The purpose of the present invention is to provide a microgrid energy interaction system and method based on distributed energy storage devices to solve the technical problems raised in the above background technology of collecting, analyzing and utilizing energy loss information in various links during system operation.

[0008] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: a microgrid energy interaction system based on distributed energy storage equipment, comprising a processor and a loss monitoring module, wherein the loss monitoring component is used to monitor energy loss generated during the generation, storage, transmission and use of energy, and transmit the information to the processor via baseband transmission and Bluetooth transmission, and the processor constructs an energy loss model based on the energy loss information, and the loss detection module comprises: a power generation monitoring component, a storage monitoring component, a transmission monitoring component and a usage monitoring component, wherein the power generation detection component is used to monitor the power generation module, the storage monitoring component is used to monitor the energy storage module, the transmission monitoring component is used to monitor the transmission module, and the usage monitoring component is used to monitor the usage module;

[0009] The power generation monitoring component includes: a Hall effect sensor for collecting output DC current and voltage values, a smart meter for monitoring the AC output power of the inverter, and an environmental monitoring unit for quantifying power generation efficiency deviations caused by environmental factors;

[0010] The storage monitoring component includes: a voltage sensor and a current sensor for monitoring ohmic loss and polarization loss during charging and discharging, a temperature sensor for detecting the temperature difference inside the battery cluster, and a bidirectional converter efficiency analyzer for measuring the charging and discharging conversion efficiency of the energy storage AC;

[0011] The transmission detection assembly includes a bus monitoring unit for capturing line loss and contact loss, a power analyzer for analyzing the difference between the input and output power of the connected converter, and a switch status recorder for recording the instantaneous energy loss from grid-connected to islanded power.

[0012] The usage monitoring component includes a smart meter cluster for monitoring the actual energy consumption of DC loads and AC loads and a non-intrusive load identification unit for analyzing load types by current waveform.

[0013] Preferably, the environmental monitoring unit includes: an irradiance sensor, a wind speed sensor and a temperature sensor. The irradiance sensor and the wind speed sensor are used to quantify the power generation efficiency deviation caused by environmental factors, and the temperature sensor is used to monitor the power generation attenuation caused by the temperature rise of the photovoltaic panel.

[0014] Preferably, the power generation monitoring component is connected to the power generation module via Bluetooth transmission, and the power generation module includes: a photovoltaic power generation unit, a wind power generation unit, a micro gas turbine and a fuel cell;

[0015] The photovoltaic power generation unit includes: silicon-based thin-film cells, MPPT controller and inverter, which uses the photovoltaic effect to directly convert solar energy into electrical energy, and then converts it into AC power through the inverter;

[0016] The wind power generation unit includes blades, a gearbox, a permanent magnet synchronous generator, and a converter. The blades capture wind energy to drive the rotor, which is then increased in speed by the gearbox to drive the generator to output AC power.

[0017] The micro gas generator set includes a centrifugal compressor, a regenerator, a combustion chamber, and a centripetal turbine. The gas explodes in the combustion chamber to drive the turbine to rotate and drive the generator to generate electricity.

[0018] A fuel cell consists of a motor, an electrolyte membrane, a bipolar plate, and a hydrogen supply unit. It uses the electrochemical reaction of hydrogen and oxygen through a proton exchange membrane to convert chemical energy into direct current.

[0019] Preferably, the storage monitoring component is connected to the energy storage module via baseband transmission, and the energy storage module includes: an energy storage component, a battery management unit and a thermal management unit;

[0020] Energy storage components include: lithium-ion batteries, flow batteries, lead-acid batteries, supercapacitors and flywheel energy storage units, which are used to store the electrical energy converted by the power generation module;

[0021] The battery management unit is used to monitor the voltage, temperature and state of charge of single cells in real time;

[0022] The thermal management unit is used to maintain the operating temperature of the energy storage module.

[0023] Preferably, the output end of the power generation module is connected to the input end of the energy storage module through a switching module, and the switching module includes: an energy router and a power unit;

[0024] The energy router includes a multi-port power converter and an FPGA high-speed switch array, which is used to monitor the output power of the power generation module and the state of charge of the battery of the energy storage module in real time, and dynamically switch the power generation-energy storage connection path through a solid-state relay matrix;

[0025] The power unit obtains load demand by connecting with the delivery module and the usage module and automatically distributes power flow according to the load demand.

[0026] Preferably, the output end of the energy storage module is connected to a transmission module via a switching module, and the transmission module includes: a power distribution network, a power electronic conversion unit, a grid connection and protection unit and a local controller;

[0027] The power distribution network includes AC bus, DC bus and AC / DC hybrid bus system, which constitute the backbone channel for power transmission;

[0028] The power electronic conversion unit includes a converter and inverter that converts DC power output from photovoltaic and energy storage into AC power, a rectifier that converts AC power into DC power, and a bidirectional converter that supports the bidirectional flow of electric energy between the AC bus and the DC bus.

[0029] The grid connection and protection unit includes: an automatic transfer switch for switching between microgrid grid connection operation and island operation, and a circuit breaker and protection relay for providing electrical protection;

[0030] The local controller is used to execute real-time scheduling instructions.

[0031] Preferably, the energy storage module is connected to the use module via a transmission line, and the use module is a user-end load.

[0032] Preferably, the power generation module and the energy storage module are connected via an energy router.

[0033] Preferably, the microgrid energy interaction method is:

[0034] S1: Electricity is generated by photovoltaic power generation units, wind power generation units, micro gas generators and fuel cells and stored in energy storage modules;

[0035] S2: The electric energy stored in the energy storage module is transmitted to the use module through the transmission line to operate the user-side load;

[0036] S3: The loss monitoring module collects energy loss information during power generation, storage, transmission, and use, and transmits the loss information to the processor. The processor builds an energy loss model based on the received energy loss information and generates an adjustment plan based on the energy loss information.

[0037] S4: The processor adjusts the power generation module, energy storage module, transmission module, and usage module according to the generated adjustment plan to compensate for energy consumption and maintain the stability of the microgrid energy interaction system;

[0038] S5: During the energy regulation process, the loss monitoring module collects energy loss information for a second time and builds a regulation loss model;

[0039] S6: The processor optimizes the energy consumption model by adjusting the consumption model.

[0040] Preferably, the S3 is specifically:

[0041] S31: collecting energy loss in power generation, storage, transmission, and interaction through the energy loss module, and transmitting the collected energy loss information to the processor;

[0042] S32: After receiving the energy loss information, the processor aligns the time axis of the energy loss data using dynamic time warping and identifies outliers using the isolation forest algorithm. If missing data is found after outliers are removed, the processor uses linear interpolation to fill in the missing data. The processor then decomposes the seasonal cycle of the line loss data by inputting the SARIMA algorithm.

[0043] S33: Random forest feature importance analysis is used to quantify the contribution of each factor. The processor uses the voltage, current, temperature, and historical battery aging coefficient of the energy storage module during system operation as input, and processes the nonlinear time series characteristics of battery polarization loss through an LSTM network. Bayesian optimization is used to automatically adjust network hyperparameters and a Shapley value-based alliance algorithm is used to allocate multi-node coupling losses, completing the construction of the energy loss model.

[0044] S34: After the processor inputs the irradiance trend and component aging rate, it can predict the photovoltaic attenuation rate in the next 1 hour through the LSTM network. The processor calculates the power deviation and dynamically adjusts the MPPT operating point through the PID controller. The SARIMA model decomposes the load cycle pattern and pre-generates the transformer tap adjustment plan. The processor obtains electricity price signals, battery life loss and carbon emission intensity as features, quantifies the decision weights through the random forest algorithm, and generates an economical power dispatch plan.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. This invention, through the design of a loss monitoring module, realizes the function of obtaining energy loss information in real time, solving the problems of insufficient energy loss monitoring accuracy and the inability to couple energy loss information in various links. It can couple energy loss analysis in various links and conduct cross-module coordinated regulation, thereby improving energy utilization efficiency, enhancing the safety and stability of system operation, and optimizing economic operation benefits.

[0047] 2. The present invention realizes the function of multi-energy coordinated scheduling by designing a power generation module, solving the problems of single energy dependence, low energy utilization and low system reliability. It can switch the energy supply mode according to different load demands, reduce the operating cost of the system, and improve the environmental performance and operational stability of the system.

[0048] 3. This invention incorporates a switching module to dynamically adjust energy transmission paths, addressing issues such as grid instability, prolonged energy supply interruptions, and insufficient system resilience caused by energy fluctuations. It also prevents equipment damage caused by power fluctuations, improves system operational stability, and optimizes user experience.

[0049] 4. The present invention realizes the function of optimizing the energy supply of user-end loads by designing a transmission monitoring component, a transmission module, a usage monitoring component and a usage module, solves the problems of low energy transmission efficiency, mismatch between intermittent power supply and load, and poor adaptability to complex scenarios, can dynamically compensate for the loss occurring during energy transmission, improves the response speed of switching energy transmission modes, reduces energy transmission losses, improves the renewable energy absorption rate, and reduces equipment failure rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic diagram of the microgrid energy interaction system of the present invention;

[0051] Figure 2 This is a schematic diagram of the power generation module of the present invention;

[0052] Figure 3 This is a schematic diagram of the energy storage module of the present invention;

[0053] Figure 4 It is a schematic diagram of the conveying module of the present invention;

[0054] Figure 5 It is a schematic diagram of the composition of the switching module of the present invention;

[0055] Figure 6 This is a schematic diagram of the composition of the loss monitoring module of the present invention;

[0056] Figure 7 This is a schematic diagram of the system information flow of the present invention;

[0057] Figure 8 A schematic diagram of a process for constructing an energy loss model of the present invention. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] Example 1: Please refer to Figure 1 、 Figure 6 and Figure 8 A microgrid energy interaction system based on distributed energy storage equipment includes a processor and a loss monitoring module. The loss monitoring component is used to monitor energy loss generated during the generation, storage, transmission and use of energy, and transmits the information to the processor via baseband transmission and Bluetooth transmission. The processor constructs an energy loss model based on the energy loss information. The loss detection module includes: a power generation monitoring component, a storage monitoring component, a transmission monitoring component and a usage monitoring component. The power generation detection component is used to monitor the power generation module, the storage monitoring component is used to monitor the energy storage module, the transmission monitoring component is used to monitor the transmission module, and the usage monitoring component is used to monitor the usage module.

[0060] The power generation monitoring component includes: a Hall effect sensor for collecting output DC current and voltage values, a smart meter for monitoring the AC output power of the inverter, and an environmental monitoring unit for quantifying power generation efficiency deviations caused by environmental factors;

[0061] The storage monitoring component includes: a voltage sensor and a current sensor for monitoring ohmic loss and polarization loss during charging and discharging, a temperature sensor for detecting the temperature difference inside the battery cluster, and a bidirectional converter efficiency analyzer for measuring the charging and discharging conversion efficiency of the energy storage AC;

[0062] The transmission detection assembly includes a bus monitoring unit for capturing line loss and contact loss, a power analyzer for analyzing the difference between the input and output power of the connected converter, and a switch status recorder for recording the instantaneous energy loss from grid-connected to islanded power.

[0063] The usage monitoring component includes a smart meter cluster for monitoring the actual energy consumption of DC loads and AC loads and a non-intrusive load identification unit for analyzing load types through current waveforms;

[0064] The environmental monitoring unit includes: an irradiance sensor, a wind speed sensor, and a temperature sensor. The irradiance sensor and wind speed sensor are used to quantify the power generation efficiency deviation caused by environmental factors, and the temperature sensor is used to monitor the power generation attenuation caused by the temperature rise of the photovoltaic panel;

[0065] Furthermore, during the operation of the microgrid energy interaction system, the power generation module generates electricity and stores it in the energy storage module, and the transmission module transmits the electricity to the use module for load operation. In this process, the loss monitoring module collects energy loss information during the power generation conversion, storage, transmission and use consumption, and transmits the energy loss information to the processor. The processor receives the energy loss information in the four links of power generation, storage, transmission and use, aligns the time axis of the energy loss data through dynamic time warping, and identifies outliers through the isolation forest algorithm. When missing data occurs after the outliers are removed, the processor uses linear interpolation to fill the missing data, and then inputs the SARIMA algorithm to decompose the seasonal cycle of the line loss data, and quantifies the contribution of each factor through random forest feature importance analysis. The processor inputs the voltage, current, temperature and historical battery aging coefficient of the energy storage module during the system operation through the LSTM network to process the nonlinear time of battery polarization loss. Sequential features, by running Bayesian optimization to automatically adjust network hyperparameters and the alliance algorithm based on Shapley values ​​to allocate multi-node coupling losses, the energy loss model is constructed. After the processor inputs the irradiance trend and component aging rate, it can predict the photovoltaic attenuation rate in the next 1 hour through the LSTM network. The processor calculates the power deviation and dynamically adjusts the MPPT working point through the PID controller. The SARIMA model decomposes the load cycle law and pre-generates the transformer tap adjustment plan. The processor obtains electricity price signals, battery life loss and carbon emission intensity as features, quantifies the decision weights through the random forest algorithm, and generates the most economical power dispatch plan, realizing the function of real-time acquisition of energy loss conditions, solving the problems of insufficient energy loss monitoring accuracy and the inability to couple energy loss information in various links, and can conduct cross-module collaborative regulation of energy loss coupling analysis in various links, thereby improving energy utilization efficiency, enhancing the safety and stability of system operation, and optimizing economic operation benefits.

[0066] Example 2: Please refer to Figure 1 and Figure 2 , a microgrid energy interaction system based on distributed energy storage equipment, wherein the power generation monitoring component is connected to the power generation module via Bluetooth transmission, and the power generation module includes: a photovoltaic power generation unit, a wind power generation unit, a micro gas turbine and a fuel cell;

[0067] The photovoltaic power generation unit includes: silicon-based thin-film cells, MPPT controller and inverter, which uses the photovoltaic effect to directly convert solar energy into electrical energy, and then converts it into AC power through the inverter;

[0068] The wind power generation unit includes blades, a gearbox, a permanent magnet synchronous generator, and a converter. The blades capture wind energy to drive the rotor, which is then increased in speed by the gearbox to drive the generator to output AC power.

[0069] The micro gas generator set includes a centrifugal compressor, a regenerator, a combustion chamber, and a centripetal turbine. The gas explodes in the combustion chamber to drive the turbine to rotate and drive the generator to generate electricity.

[0070] A fuel cell consists of a motor, an electrolyte membrane, a bipolar plate, and a hydrogen supply unit. It uses hydrogen and oxygen to undergo an electrochemical reaction through a proton exchange membrane, converting chemical energy into direct current.

[0071] Furthermore, in the microgrid energy interaction system, a variety of power generation measures are adopted. Silicon-based thin-film batteries are used to convert solar radiation into DC power through the photovoltaic effect. The generated DC power is optimized for maximum power point tracking through the MPPT controller to improve energy capture efficiency, and the DC power is converted into AC power that meets the system standards through the inverter. The wind energy is captured by the blades and drives the rotor to rotate. The mechanical energy is increased by the gearbox. The high-speed rotation is converted into AC power by the synchronous motor. The voltage and frequency are further adjusted by the converter to ensure stable output of AC power. The air is compressed by the centrifugal compressor and then transported to the combustion chamber. The fuel is mixed with the air in the combustion chamber and exploded to generate high-temperature and high-pressure gas to drive the centripetal turbine to rotate and drive the generator to generate electricity. The regenerator recovers the waste heat It can improve the overall power generation efficiency and output AC power. The fuel cell provides hydrogen fuel through the hydrogen supply unit, and undergoes an electrochemical reaction with oxygen through the electrolyte membrane. The bipolar plate collects the DC current generated by the reaction, and the output DC power is converted into AC power. Due to the intermittent nature of the photovoltaic power generation unit and the wind power generation unit, when the power generation of the photovoltaic power generation unit and the wind power generation unit drops sharply, the processor can generate electricity through the micro gas unit and the fuel cell to maintain the stable operation of the system, realize the function of multi-energy coordinated scheduling, solve the problems of single energy dependence, low energy utilization and low system reliability, and can switch the energy supply mode according to different load requirements, reducing the operating cost of the system and improving the environmental protection performance and operating stability of the system.

[0072] Example 3: Please refer to Figure 1 、 Figure 2 、 Figure 3 and Figure 5 , a microgrid energy interaction system based on distributed energy storage equipment, wherein the power generation monitoring component is connected to the power generation module via Bluetooth transmission, and the power generation module includes: a photovoltaic power generation unit, a wind power generation unit, a micro gas turbine and a fuel cell;

[0073] The photovoltaic power generation unit includes: silicon-based thin-film cells, MPPT controller and inverter, which uses the photovoltaic effect to directly convert solar energy into electrical energy, and then converts it into AC power through the inverter;

[0074] The wind power generation unit includes blades, a gearbox, a permanent magnet synchronous generator, and a converter. The blades capture wind energy to drive the rotor, which is then increased in speed by the gearbox to drive the generator to output AC power.

[0075] The micro gas generator set includes a centrifugal compressor, a regenerator, a combustion chamber, and a centripetal turbine. The gas explodes in the combustion chamber to drive the turbine to rotate and drive the generator to generate electricity.

[0076] A fuel cell consists of a motor, an electrolyte membrane, a bipolar plate, and a hydrogen supply unit. It uses hydrogen and oxygen to undergo an electrochemical reaction through a proton exchange membrane, converting chemical energy into direct current.

[0077] The storage monitoring component is connected to the energy storage module via baseband transmission, and the energy storage module includes: an energy storage component, a battery management unit and a thermal management unit;

[0078] Energy storage components include: lithium-ion batteries, flow batteries, lead-acid batteries, supercapacitors and flywheel energy storage units, which are used to store the electrical energy converted by the power generation module;

[0079] The battery management unit is used to monitor the voltage, temperature and state of charge of single cells in real time;

[0080] The thermal management unit is used to maintain the operating temperature of the energy storage module;

[0081] The power generation module and the energy storage module are connected via a switching module, which includes: an energy router and a power unit;

[0082] The energy router includes a multi-port power converter and an FPGA high-speed switch array, which is used to monitor the output power of the power generation module and the state of charge of the battery of the energy storage module in real time, and dynamically switch the power generation-energy storage connection path through a solid-state relay matrix;

[0083] The power unit obtains the load demand by connecting with the delivery module and the use module and automatically allocates the power flow according to the load demand;

[0084] The power generation module and the energy storage module are connected via an energy router;

[0085] Furthermore, during the operation of the power generation module, the power generation monitoring component obtains real-time data such as photovoltaic inverter power and wind turbine speed through Bluetooth transmission, and the storage monitoring component synchronously collects the battery charge state, temperature and health status of each component in the storage component. Different connections between the power generation structure in the power generation module and the structure in the storage component have different effects. The photovoltaic power generation unit is directly connected to the DC bus to buffer instantaneous fluctuations and is connected to the supercapacitor without conversion. The response time is short and the conversion loss can be reduced. The wind power generation unit can process the converted wind power fluctuations through the supercapacitor and the flywheel energy storage unit. The micro gas unit can be connected to lithium-ion batteries, lead-acid batteries and flow batteries. The fuel cell DC output is compatible with DC interface energy storage. The power generation monitoring component captures the photovoltaic power generation unit and wind power generation in real time. The energy storage monitoring component monitors the battery charge status in real time to detect the fluctuation of the unit. When loss occurs, the processor switches the connection mode between the power generation module and the energy storage module through the energy router to reduce energy loss. After receiving the switching instruction, the FPGA high-speed switch array reconstructs the power flow topology. The solid-state relay matrix replaces the mechanical contact to achieve zero arc on and off. The bidirectional converter converts the AC bus power into DC storage and energy storage module when there is surplus photovoltaic power. When the load demand surges, the DC power stored in the energy storage module is converted into AC output, realizing the function of dynamically adjusting the energy transmission path, solving the problems of grid instability caused by energy fluctuations, long-term energy supply interruption and insufficient system resilience, avoiding equipment damage caused by power fluctuations, improving system operation stability and optimizing user experience.

[0086] Example 4: Please refer to Figure 1 、 Figure 4 、 Figure 5 and Figure 7 , a microgrid energy interaction system based on distributed energy storage equipment, wherein the output end of the power generation module is connected to the input end of the energy storage module through a switching module, and the switching module includes: an energy router and a power unit;

[0087] The energy router includes a multi-port power converter and an FPGA high-speed switch array, which is used to monitor the output power of the power generation module and the state of charge of the battery of the energy storage module in real time, and dynamically switch the power generation-energy storage connection path through a solid-state relay matrix;

[0088] The power unit obtains the load demand by connecting with the delivery module and the use module and automatically allocates the power flow according to the load demand;

[0089] The output end of the energy storage module is connected to the transmission module through the switching module. The transmission module includes: a power distribution network, a power electronic conversion unit, a grid connection and protection unit and a local controller;

[0090] The power distribution network includes AC bus, DC bus and AC / DC hybrid bus system, which constitute the backbone channel for power transmission;

[0091] The power electronic conversion unit includes a converter and inverter that converts DC power output from photovoltaic and energy storage into AC power, a rectifier that converts AC power into DC power, and a bidirectional converter that supports the bidirectional flow of electric energy between the AC bus and the DC bus.

[0092] The grid connection and protection unit includes: an automatic transfer switch for switching between microgrid grid connection operation and island operation, and a circuit breaker and protection relay for providing electrical protection;

[0093] The local controller is used to execute real-time scheduling instructions;

[0094] The energy storage module is connected to the use module via a transmission line, and the use module is a user-end load;

[0095] Furthermore, when the transmission module transmits electric energy from the energy storage module to the use module for user-side load operation, the transmission monitoring component can capture line loss, contact loss and converter conversion efficiency loss in real time. After receiving the energy loss information, the processor can dynamically adjust the power conversion method through the power electronic conversion unit to reduce the energy loss in the energy transmission link. When switching between grid connection and island connection, the switch status recorder can capture the instantaneous energy loss when switching from grid connection to island connection, and trigger the automatic switching action to ensure uninterrupted power supply to critical loads. When the user-side load uses electricity, the monitoring component uses the non-invasive load identification unit to identify the load type, and obtains the actual energy consumption data through the smart meter cluster, and transmits the information After transmission to the processor, the processor can build an energy consumption profile of the user end, and can prioritize the use of electric energy stored in the energy storage module for power supply through the energy router during peak electricity price periods, thereby reducing electricity costs. When the transmission monitoring component detects abnormal temperature rise at the contact point, the processor can link the circuit breaker through the local controller to isolate the risk section in advance to avoid equipment damage, thereby realizing the function of optimizing the energy supply of the user-end load, solving the problems of low energy transmission efficiency, mismatch between intermittent power supply and load, and poor adaptability to complex scenarios, and can dynamically compensate for the losses incurred during energy transmission, thereby improving the response speed of switching energy transmission modes, reducing energy transmission losses, increasing the renewable energy absorption rate, and reducing equipment failure rates.

[0096] Example 5: Please refer to Figure 1 、 Figure 7 and Figure 8A microgrid energy interaction system based on distributed energy storage equipment includes a processor and a loss monitoring module. The loss monitoring component is used to monitor energy loss generated during the generation, storage, transmission and use of energy, and transmits the information to the processor via baseband transmission and Bluetooth transmission. The processor constructs an energy loss model based on the energy loss information. The loss detection module includes: a power generation monitoring component, a storage monitoring component, a transmission monitoring component and a usage monitoring component. The power generation detection component is used to monitor the power generation module, the storage monitoring component is used to monitor the energy storage module, the transmission monitoring component is used to monitor the transmission module, and the usage monitoring component is used to monitor the usage module.

[0097] The power generation monitoring component includes: a Hall effect sensor for collecting output DC current and voltage values, a smart meter for monitoring the AC output power of the inverter, and an environmental monitoring unit for quantifying power generation efficiency deviations caused by environmental factors;

[0098] The storage monitoring component includes: a voltage sensor and a current sensor for monitoring ohmic loss and polarization loss during charging and discharging, a temperature sensor for detecting the temperature difference inside the battery cluster, and a bidirectional converter efficiency analyzer for measuring the charging and discharging conversion efficiency of the energy storage AC;

[0099] The transmission detection assembly includes a bus monitoring unit for capturing line loss and contact loss, a power analyzer for analyzing the difference between the input and output power of the connected converter, and a switch status recorder for recording the instantaneous energy loss from grid-connected to islanded power.

[0100] The usage monitoring component includes a smart meter cluster for monitoring the actual energy consumption of DC loads and AC loads and a non-intrusive load identification unit for analyzing load types through current waveforms;

[0101] The environmental monitoring unit includes: an irradiance sensor, a wind speed sensor, and a temperature sensor. The irradiance sensor and wind speed sensor are used to quantify the power generation efficiency deviation caused by environmental factors, and the temperature sensor is used to monitor the power generation attenuation caused by the temperature rise of the photovoltaic panel;

[0102] Furthermore, after the energy loss model component is completed, the processor inputs corresponding data according to the specific situation of the system operation to predict the energy loss that may exist in the subsequent energy conversion, storage, transmission and use process, and adjusts the power generation module, energy storage module, transmission module and use module. During the adjustment process, the power fluctuations, system equipment status changes and control signal timing in the adjustment process are recorded in real time through the power generation monitoring unit, storage monitoring unit, transmission monitoring unit and use monitoring unit, and dynamic parameters such as transient loss indicators and adjustment execution delay loss are extracted. The second-level response loss, minute-level adjustment loss and hour-level adjustment loss are hierarchically modeled, and the steady-state parameters and adjustment loss variables of the energy loss model are associated through the state transition equation. The initial energy loss model is integrated with the adjustment loss model, and the transient loss caused by battery cycle aging and adjustment is dynamically coupled. It can extend the service life of the energy storage module while reducing the system operating cost. The energy loss model after integrating the adjustment loss model can add the adjustment loss as a parameter to the model to optimize the original adjustment scheme, thereby further reducing energy loss.

[0103] Working principle: In the microgrid energy interaction system, a variety of power generation measures are adopted. Silicon-based thin-film batteries use the photovoltaic effect to convert solar radiation into DC power. The generated DC power is optimized through the MPPT controller for maximum power point tracking to improve energy capture efficiency, and the DC power is converted into AC power that meets the system standards through the inverter. The blades capture wind energy and drive the rotor to rotate. The mechanical energy is increased by the gearbox. The high-speed rotation is converted into AC power by the synchronous motor. The voltage and frequency are further adjusted by the converter to ensure stable output of AC power. The air is compressed by the centrifugal compressor and then transported to the combustion chamber for combustion. The material mixes with air in the combustion chamber and explodes, generating high-temperature and high-pressure gas that drives the centripetal turbine to rotate and drive the generator to generate electricity. The regenerator recovers waste heat energy to improve the overall power generation efficiency and output AC power. The fuel cell provides hydrogen fuel through the hydrogen supply unit, which reacts electrochemically with oxygen through the electrolyte membrane. The bipolar plate collects the DC current generated by the reaction, and the output DC power is converted into AC power. Due to the intermittent nature of the photovoltaic power generation unit and the wind power generation unit, when the power generation of the photovoltaic power generation unit and the wind power generation unit drops sharply, the processor can generate electricity through the micro gas unit and the fuel cell to maintain stable operation of the system.

[0104] During the operation of the power generation module, the power generation monitoring component obtains real-time data such as photovoltaic inverter power and wind turbine speed through Bluetooth transmission. The storage monitoring component synchronously collects the battery charge status, temperature and health status of each component in the storage component. Different connections between the power generation structure in the power generation module and the structure in the storage component have different effects. The photovoltaic power generation unit is directly connected to the DC bus to buffer instantaneous fluctuations and is connected to the supercapacitor without conversion. The response time is short and the conversion loss can be reduced. The wind power generation unit can process the converted wind power fluctuations through supercapacitors and flywheel energy storage units. The micro gas unit can be connected with lithium-ion batteries, lead-acid batteries and liquid flow batteries. The DC output of the fuel cell is compatible with the DC interface energy storage. The power generation monitoring component captures the fluctuations of the photovoltaic power generation unit and the wind power generation unit in real time. The energy storage monitoring component monitors the battery charge status in real time. When loss occurs, the processor switches the connection mode between the power generation module and the energy storage module through the energy router to reduce energy loss. After receiving the switching instruction, the FPGA high-speed switch array reconstructs the power flow topology. The solid-state relay matrix replaces the mechanical contact to achieve zero arc switching. The bidirectional converter converts the AC bus power into DC storage and energy storage module when there is surplus photovoltaic power. When the load demand surges, the DC power stored in the energy storage module is converted into AC output.

[0105] When the transmission module transmits electricity from the energy storage module to the usage module for user-side load operation, the transmission monitoring component can capture line loss, contact loss, and converter conversion efficiency loss in real time. After receiving energy loss information, the processor can dynamically adjust the energy conversion method through the power electronic conversion unit to reduce energy loss in the energy transmission link. When switching between grid connection and island connection, the switch status recorder can capture the instantaneous energy loss when switching from grid connection to island connection and trigger automatic switching action to ensure uninterrupted power supply to critical loads. When the user-side load uses electricity, the monitoring component uses the non-intrusive load identification unit to identify the load type, obtain actual energy consumption data through the smart meter cluster, and transmit this information to the processor. The processor can then build an energy usage profile for the user. During peak electricity price periods, the energy router can prioritize the use of energy stored in the energy storage module for power supply, thereby reducing electricity costs. When the transmission monitoring component detects an abnormal temperature rise at the contact point, the processor can use the local controller to trigger the circuit breaker to isolate the risk section in advance to avoid equipment damage.

[0106] During the operation of the microgrid energy interaction system, the power generation module generates electricity and stores it in the energy storage module, and the transmission module transmits the electricity to the use module for load operation. In this process, the loss monitoring module collects the energy loss in the process of power generation conversion, storage, transmission and consumption, and transmits the energy loss information to the processor. The processor receives the energy loss in the four links of power generation, storage, transmission and use, aligns the time axis of the energy loss data through dynamic time warping, and identifies outliers through the isolation forest algorithm. After the outliers are removed, the missing data processor uses linear interpolation to fill the missing data and then inputs the SARIMA algorithm decomposition line The seasonal cycle of loss data is analyzed, and the contribution of each factor is quantified through random forest feature importance analysis. The processor processes the nonlinear time series characteristics of battery polarization loss through the LSTM network by inputting the voltage, current, temperature and historical battery aging coefficient of the energy storage module during system operation. By running Bayesian optimization to automatically adjust the network hyperparameters and the alliance algorithm based on Shapley value to allocate multi-node coupling loss, the energy loss model is constructed. After the processor inputs the irradiance trend and component aging rate, it can predict the photovoltaic attenuation rate in the next 1 hour through the LSTM network. The processor calculates the power deviation and dynamically adjusts the MPPT operating point through the PID controller. SARIMA The model decomposes the load cycle law and pre-generates the transformer tap adjustment plan. The processor obtains electricity price signals, battery life loss and carbon emission intensity as features, quantifies decision weights through the random forest algorithm, and generates an economically optimal power dispatch plan. After the energy loss model component is completed, the processor inputs the corresponding data according to the specific situation of the system operation to predict the possible energy loss in the subsequent energy conversion, storage, transmission and use process, and adjusts the power generation module, energy storage module, transmission module and use module. During the adjustment process, the power generation monitoring unit, storage monitoring unit, transmission monitoring unit and use monitoring unit are used to record the power in real time during the adjustment process. Fluctuations, system equipment state changes and control signal timing, extract dynamic parameters such as transient loss indicators and adjustment execution delay losses, hierarchically model the second-level response loss, minute-level adjustment loss and hour-level adjustment loss, associate the steady-state parameters and adjustment loss variables of the energy loss model through the state transfer equation, merge the initial energy loss model with the adjustment loss model, dynamically couple the transient loss caused by battery cycle aging and adjustment, and extend the service life of the energy storage module while reducing the system operating cost. In the energy loss model after integrating the adjustment loss model, the adjustment loss can be added as a parameter to the model to optimize the original adjustment scheme, thereby further reducing energy loss.

[0107] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A microgrid energy interaction system based on distributed energy storage equipment, characterized by: It includes a processor and a loss monitoring module. The loss monitoring component is used to monitor the energy loss generated during the power generation, storage, transmission and use of energy, and transmits the information to the processor via baseband transmission and Bluetooth transmission. The processor builds an energy loss model based on the energy loss information. The loss detection module includes: a power generation monitoring component, a storage monitoring component, a transmission monitoring component and a usage monitoring component. The power generation detection component is used to monitor the power generation module, the storage monitoring component is used to monitor the energy storage module, the transmission monitoring component is used to monitor the transmission module, and the usage monitoring component is used to monitor the usage module. The power generation monitoring component includes: a Hall effect sensor for collecting output DC current and voltage values, a smart meter for monitoring the AC output power of the inverter, and an environmental monitoring unit for quantifying power generation efficiency deviations caused by environmental factors; The storage monitoring component includes: a voltage sensor and a current sensor for monitoring ohmic loss and polarization loss during charging and discharging, a temperature sensor for detecting the temperature difference inside the battery cluster, and a bidirectional converter efficiency analyzer for measuring the charging and discharging conversion efficiency of the energy storage AC; The transmission detection assembly includes a bus monitoring unit for capturing line loss and contact loss, a power analyzer for analyzing the difference between the input and output power of the connected converter, and a switch status recorder for recording the instantaneous energy loss from grid-connected to islanded power. The usage monitoring component includes a smart meter cluster for monitoring the actual energy consumption of DC loads and AC loads and a non-intrusive load identification unit for analyzing load types by current waveform.

2. A microgrid energy interaction system based on distributed energy storage equipment according to claim 1, characterized in that: The environmental monitoring unit includes: an irradiance sensor, a wind speed sensor and a temperature sensor. The irradiance sensor and the wind speed sensor are used to quantify the power generation efficiency deviation caused by environmental factors, and the temperature sensor is used to monitor the power generation attenuation caused by the temperature rise of the photovoltaic panel.

3. The microgrid energy interaction system based on distributed energy storage equipment according to claim 1, characterized in that: The power generation monitoring component is connected to the power generation module via Bluetooth transmission, and the power generation module includes: a photovoltaic power generation unit, a wind power generation unit, a micro gas turbine and a fuel cell; The photovoltaic power generation unit includes: silicon-based thin-film cells, MPPT controller and inverter, which uses the photovoltaic effect to directly convert solar energy into electrical energy, and then converts it into AC power through the inverter; The wind power generation unit includes blades, a gearbox, a permanent magnet synchronous generator, and a converter. The blades capture wind energy to drive the rotor, which is then increased in speed by the gearbox to drive the generator to output AC power. The micro gas generator set includes a centrifugal compressor, a regenerator, a combustion chamber, and a centripetal turbine. The gas explodes in the combustion chamber to drive the turbine to rotate and drive the generator to generate electricity. A fuel cell consists of a motor, an electrolyte membrane, a bipolar plate, and a hydrogen supply unit. It uses the electrochemical reaction of hydrogen and oxygen through a proton exchange membrane to convert chemical energy into direct current.

4. The microgrid energy interaction system based on distributed energy storage equipment according to claim 1, characterized in that: The storage monitoring component is connected to the energy storage module via baseband transmission, and the energy storage module includes: an energy storage component, a battery management unit and a thermal management unit; Energy storage components include: lithium-ion batteries, flow batteries, lead-acid batteries, supercapacitors and flywheel energy storage units, which are used to store the electrical energy converted by the power generation module; The battery management unit is used to monitor the voltage, temperature and state of charge of single cells in real time; The thermal management unit is used to maintain the operating temperature of the energy storage module.

5. The microgrid energy interaction system based on distributed energy storage equipment according to claim 3, characterized in that: The output end of the power generation module is connected to the input end of the energy storage module through a switching module, and the switching module includes: an energy router and a power unit; The energy router includes a multi-port power converter and an FPGA high-speed switch array, which is used to monitor the output power of the power generation module and the state of charge of the battery of the energy storage module in real time, and dynamically switch the power generation-energy storage connection path through a solid-state relay matrix; The power unit obtains load demand by connecting with the delivery module and the usage module and automatically distributes power flow according to the load demand.

6. The microgrid energy interaction system based on distributed energy storage equipment according to claim 4, characterized in that: The output end of the energy storage module is connected to the transmission module through the switching module. The transmission module includes: a power distribution network, a power electronic conversion unit, a grid connection and protection unit and a local controller; The power distribution network includes AC bus, DC bus and AC / DC hybrid bus system, which constitute the backbone channel for power transmission; The power electronic conversion unit includes a converter and inverter that converts DC power output from photovoltaic and energy storage into AC power, a rectifier that converts AC power into DC power, and a bidirectional converter that supports the bidirectional flow of electric energy between the AC bus and the DC bus. The grid connection and protection unit includes: an automatic transfer switch for switching between microgrid grid connection operation and island operation, and a circuit breaker and protection relay for providing electrical protection; The local controller is used to execute real-time scheduling instructions.

7. The microgrid energy interaction system based on distributed energy storage equipment according to claim 4, characterized in that: The energy storage module is connected to the use module via a transmission line, and the use module is a user-end load.

8. The microgrid energy interaction system based on distributed energy storage equipment according to claim 3, characterized in that: The power generation module and the energy storage module are connected via an energy router.

9. A microgrid energy interaction method based on a distributed energy storage device, applicable to a microgrid energy interaction system based on a distributed energy storage device according to any one of claims 1 to 8, characterized in that: The microgrid energy interaction method is: S1: Electricity is generated by photovoltaic power generation units, wind power generation units, micro gas generators and fuel cells and stored in energy storage modules; S2: The electric energy stored in the energy storage module is transmitted to the use module through the transmission line to operate the user-side load; S3: The loss monitoring module collects energy loss information during power generation, storage, transmission, and use, and transmits the loss information to the processor. The processor builds an energy loss model based on the received energy loss information and generates an adjustment plan based on the energy loss information. S4: The processor adjusts the power generation module, energy storage module, transmission module, and usage module according to the generated adjustment plan to compensate for energy consumption and maintain the stability of the microgrid energy interaction system; S5: During the energy regulation process, the loss monitoring module collects energy loss information for a second time and builds a regulation loss model; S6: The processor optimizes the energy consumption model by adjusting the consumption model.

10. A microgrid energy interaction method based on distributed energy storage equipment according to claim 9, characterized in that: The S3 is specifically: S31: collecting energy loss in power generation, storage, transmission, and interaction through the energy loss module, and transmitting the collected energy loss information to the processor; S32: After receiving the energy loss information, the processor aligns the time axis of the energy loss data using dynamic time warping and identifies outliers using the isolation forest algorithm. If missing data is found after outliers are removed, the processor uses linear interpolation to fill in the missing data. The processor then decomposes the seasonal cycle of the line loss data by inputting the SARIMA algorithm. S33: Random forest feature importance analysis is used to quantify the contribution of each factor. The processor uses the voltage, current, temperature, and historical battery aging coefficient of the energy storage module during system operation as input, and processes the nonlinear time series characteristics of battery polarization loss through an LSTM network. Bayesian optimization is used to automatically adjust network hyperparameters and a Shapley value-based alliance algorithm is used to allocate multi-node coupling losses, completing the construction of the energy loss model. S34: After the processor inputs the irradiance trend and component aging rate, it can predict the photovoltaic attenuation rate in the next 1 hour through the LSTM network. The processor calculates the power deviation and dynamically adjusts the MPPT operating point through the PID controller. The SARIMA model decomposes the load cycle pattern and pre-generates the transformer tap adjustment plan. The processor obtains electricity price signals, battery life loss and carbon emission intensity as features, quantifies the decision weights through the random forest algorithm, and generates an economical power dispatch plan.

Images