A light storage and charging integrated micro-grid energy management system

Abstract

The application discloses a kind of light storage and charging integrated micro-grid energy management system, it is related to micro-grid energy management technical field, for solving the problem of low energy scheduling efficiency and insufficient stability in light storage and charging system;The present application comprises power generation monitoring module, energy storage management module, charging load control module and energy coordination module;The state of photovoltaic power generation and environmental parameters are monitored in real time through a plurality of types of sensor network, to determine the operating state of photovoltaic module;Based on battery monitoring data and photovoltaic output characteristics, develop differentiated energy storage management strategy;Combined with energy state dynamic allocation of charging power, realize intelligent control of charging and discharging;Through the convergence of multi-source information, coordinate source storage and load interaction, respond to different power states;Accurate monitoring, intelligent scheduling and efficient collaboration of light storage and charging integrated micro-grid are realized, and energy utilization efficiency and operational stability are significantly improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of micro-grid energy management, in particular to a light-storage-charging integrated micro-grid energy management system. BACKGROUND

[0002] With the acceleration of global energy transformation, the light-storage-charging integrated micro-grid, as an important part of the new power system, its industry scale continues to expand; the application range extends from traditional industrial parks, commercial complexes to new energy vehicle battery swap stations, off-grid power supply in remote areas and other emerging fields. With the coordinated innovation of photovoltaic, energy storage and charging technologies, the installed capacity of the light-storage-charging integrated micro-grid has been significantly improved, making efficient energy management a key link in the development of the industry. Although the existing technology can meet the basic energy management needs of the light-storage-charging integrated micro-grid, there are still many deficiencies:

[0003] At present, the energy management scheme of the light-storage-charging integrated micro-grid is mostly based on fixed rules and models, and the photovoltaic, energy storage and charging systems operate independently, lacking a coordination mechanism, making it difficult to track real-time changes in photovoltaic output, resulting in lag in energy storage charging and discharging, power distribution and scheduling, causing energy waste or power supply shortages;

[0004] The existing technology focuses on single target optimization, only achieving optimal performance of one of the economic or stability indicators, and cannot simultaneously improve multiple targets. It is difficult to accurately control power fluctuations and voltage imbalances that occur when switching between grid-connected and off-grid modes, resulting in low energy utilization efficiency and insufficient operational stability during energy management.

[0005] In order to solve the above-mentioned defects, the present application provides a technical solution. SUMMARY

[0006] The present application aims to solve the problem of low energy scheduling efficiency and insufficient stability in the light-storage-charging system, and proposes a light-storage-charging integrated micro-grid energy management system.

[0007] The purpose of the present application can be achieved by the following technical solution:

[0008] A light-storage-charging integrated micro-grid energy management system, comprising:

[0009] A power generation monitoring module: by integrating a power sensor array and an environmental parameter sensor group, a multi-dimensional monitoring network is constructed to capture and judge the power generation state;

[0010] An energy storage management module: by monitoring the charging and discharging state of the energy storage unit, and based on real-time feedback of photovoltaic power generation output, theoretical power fluctuations and environmental parameter changes, intelligent control and capacity optimization management of the energy storage device are realized;

[0011] Charging load control module: based on power generation monitoring information and energy storage state information, calculate the optimal charging strategy, and provide intelligent power distribution services for charging equipment through multi-level regulation mode;

[0012] Energy coordination module: based on the multi-source state information provided by the power generation monitoring, energy storage management and charging load control modules, the global energy flow is regulated;

[0013] The specific operation steps of the energy storage management module include:

[0014] The battery management device monitors the parameters of the energy storage unit; the actual output power, theoretical output power, environmental irradiance and photovoltaic module operating temperature are extracted to construct a photovoltaic output prediction model; the battery state of charge, health state and power state are analyzed and matched with the pre-constructed battery performance library, and the battery charging, discharging, standby and fault states are determined by combining the stability characteristics of photovoltaic power generation and the electrochemical model;

[0015] The voltage characteristic value is obtained based on the rate of change of the battery terminal voltage with time and the characteristics of the charging and discharging stage;

[0016] The current and time product during the charging and discharging process is continuously counted and accumulated to obtain the power change amount;

[0017] The battery internal resistance change is monitored synchronously, the internal resistance values in different cycle stages are compared, and the internal resistance growth coefficient is obtained by combining the daily average fluctuation times of photovoltaic output;

[0018] The voltage characteristic value , the power change amount and the internal resistance growth coefficient are extracted, normalized and substituted into the formula to obtain the remaining available capacity of the battery, wherein, represents the real-time state of charge, represents the rated charge and discharge capacity marked at the factory of the battery, represents the error correction coefficient, are the influence weight factors of the voltage characteristic value, the power change amount and the internal resistance growth coefficient, respectively;

[0019] The specific operation steps of the energy storage management module further include:

[0020] Taking the initial internal resistance of the battery at the factory as the reference value, when the internal resistance growth exceeds 80% of the reference value, it is determined to enter the aging stage, and the internal resistance growth ratio is calculated based on the reference value and the real-time internal resistance to obtain the aging degree quantitative value ;

[0021] The real-time state of charge, the remaining available capacity of the battery and the aging degree quantitative value are normalized and then the comprehensive health index is obtained through the weighted formula;

[0022] For the battery pack with a comprehensive health index higher than a preset maximum health threshold, and when the photovoltaic output fluctuates greatly, frequent charging and discharging tasks are preferentially assigned to suppress photovoltaic power fluctuation; for the battery pack with a comprehensive health index between the preset maximum health threshold and the minimum health threshold, energy time shifting and peak shaving tasks are undertaken during a photovoltaic output peak period; for the battery pack with a comprehensive health index lower than the preset minimum health threshold, and when the photovoltaic output is weak, the depth of charging and discharging is reduced for backup and emergency power supply;

[0023] Differential management strategies are set for lithium batteries, lead-acid batteries, and vanadium flow batteries to control the depth of discharging and the discharging rate of different batteries, and the working temperature of photovoltaic modules is combined with the historical average predicted ambient temperature; when the predicted ambient temperature is out of range, start the cooling, forced air cooling or adjust the power of the electrolyte circulating pump in advance;

[0024] Real-time monitoring of single battery voltage difference, when the voltage difference is greater than 10% of the rated voltage, the battery is removed from the system and replaced; When the photovoltaic output is at a peak, during a period of low charging load, lithium batteries use active equalization to transfer energy, and lead-acid batteries use passive equalization to consume energy.

[0025] As a further improvement of the application, the specific implementation process of the power generation monitoring module is as follows:

[0026] The power sensor is installed at the output end of each photovoltaic module to collect the output power of the photovoltaic module and bind it with the rated power, and to obtain normal power generation, low efficiency and fault state in real time; based on the edge computing gateway, structured data containing component number, timestamp, power value and state identifier is generated;

[0027] The environmental parameter sensor group is deployed in a grid manner to monitor the working temperature of the module backboard and the environmental temperature of the array gap, and cross-checks with the meteorological station data, and triggers calibration when the deviation is more than 10%;

[0028] Based on the historical data of the target sensor under the same environmental conditions, a calibration compensation coefficient is generated and corrected;

[0029] Based on the basic parameters of the photovoltaic module and the calibration algorithm, a mapping relationship between the environmental parameters and the theoretical output power is established to generate a photovoltaic unit virtual network; the theoretical output power is obtained by the formula , wherein, P represents the rated power of the photovoltaic module, I represents the real-time collected irradiance, T represents the temperature coefficient, T represents the real-time collected working temperature of the photovoltaic module; based on the physical partitioning of the photovoltaic array, the modules are divided into standard power units and bound to unique numbers.

[0030] As a further improvement of the application, the specific operation steps of the charging load control module are as follows:

[0031] When the charging request is triggered, the photovoltaic power generation power, the energy storage available power and the grid adjustable power are collected and summarized in real time, a complete energy state matrix is constructed, the current allocable charging power is calculated and compared with the preset threshold;

[0032] When the allocable charging power is greater than the preset threshold, the charging device is allowed to charge at the maximum power;

[0033] The slow charging device charges based on 85% of the rated power of the device;

[0034] The fast charging device calculates the maximum charging power based on the state of charge of the battery of the device;

[0035] When the state of charge of the battery is lower than 20%, the maximum power charging is provided, and when the state of charge reaches 80%, the charging power is reduced to 30% of the maximum power to avoid overcharging of the battery;

[0036] When the allocable charging power is lower than the preset threshold but higher than the minimum running threshold, the priority coefficient is obtained based on the charging device type, the state of charge of the battery and the user reservation state combined with the weighting formula, and the power is distributed;

[0037] When the allocable charging power is lower than the minimum running threshold, the power upper limit of each charging pile is adjusted based on the analysis of historical charging mode and future energy supply prediction in a sliding time window;

[0038] When the charging demand is detected to decrease, the reserved power is released and redistributed to other charging devices; when the charging device reaches the preset state of charge or the user set target, the charging completion process is triggered, the charging power is released and the allocable charging power is updated.

[0039] As a further improvement of the application, the specific operation steps of the energy coordination module are as follows:

[0040] The actual output power, theoretical output power and component operating state information of the photovoltaic array of the power generation monitoring module are extracted; the current state of charge, remaining available capacity, comprehensive health index and current charging and discharging state of the energy storage unit are obtained; at the same time, the current total charging demand, priority distribution of various devices and charging strategy execution of the charging load control module are received, an energy state perception view is constructed, and the power balance state, total generation output power, adjustable power total and total power demand of the microgrid are calculated, forming a source storage load power flow atlas;

[0041] When the photovoltaic array component or the energy storage unit is monitored to be faulty, the power distribution weight of the faulty unit is excluded, the scheduling path of the remaining resources is optimized, and the operation and maintenance instruction is generated;

[0042] Based on the timing law of operation and the external environment change, the energy flow is dynamically predicted and the operation state of each energy unit is adjusted;

[0043] The data of various energy flow conversion, the execution record of scheduling instruction and the power distribution log are recorded; meanwhile, the data interaction with the upper control platform of micro-grid is supported, the coordinated operation among multiple micro-grids and the unified scheduling of regional energy management are realized.

[0044] As a further improvement of the application, the specific implementation process of the power balance state comprises:

[0045] Power surplus state: when the sum of the total power output and the total adjustable power is greater than the power demand of the load, the power demand of the charging load is preferentially met, the energy storage charging task is executed based on the residual available capacity and the comprehensive health index of the energy storage unit, and if the energy storage capacity has reached the upper limit, the low-priority charging task is sequentially reduced;

[0046] Power shortage state: when the sum of the total power output and the total adjustable power is lower than the minimum running threshold, the power demand of the charging equipment is reconstructed, the charging demand of the high-priority equipment is preferentially guaranteed, and the discharge depth is controlled based on the current state of charge and the comprehensive health index of the energy storage unit;

[0047] Power shortage state: when the sum of the total power output and the total adjustable power is lower than the minimum running threshold, the power demand of the charging equipment is reconstructed, the charging demand of the high-priority equipment is preferentially guaranteed, and the discharge depth is controlled based on the current state of charge and the comprehensive health index of the energy storage unit;

[0048] Compared with the prior art, the application has the following beneficial effects:

[0049] The application realizes comprehensive capture of photovoltaic power generation state, environmental parameters and energy storage unit data through the deployed power sensor array, environmental parameter sensor group and battery management equipment, standardization processing of edge computing gateway, theoretical power mapping of virtual network and construction of energy state matrix, generates a multi-dimensional energy feature vector, and significantly improves the real-time performance and accuracy of micro-grid state monitoring;

[0050] The application constructs a source-storage-load collaborative energy atlas, realizes intelligent energy flow regulation by combining a photovoltaic output prediction model and a dynamic scheduling strategy, maps photovoltaic output, energy storage state and charging demand characteristics into a globally optimal power distribution scheme through a hierarchical coordination architecture and a priority mechanism, analyzes key influencing factors when power imbalance or equipment failure occurs, generates a scheduling report containing energy fluctuation and equipment state, and significantly improves the energy utilization efficiency and operation stability of the photovoltaic-storage-charging integrated micro-grid. Attached Figure Description

[0051] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0052] Figure 1 This is the overall system block diagram of the present invention. Detailed Implementation

[0053] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] It should be understood that the terms “comprising” and “including” used in this disclosure and claims indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0055] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure. As used in this disclosure and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this disclosure and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0056] like Figure 1 As shown, an integrated photovoltaic, energy storage, and charging microgrid energy management system includes a power generation monitoring module, an energy storage management module, a charging load control module, and an energy coordination module.

[0057] The power generation monitoring module integrates a power sensor array and an environmental parameter sensor group to construct a multi-dimensional monitoring network, enabling real-time capture and judgment of the power generation status of the photovoltaic power generation unit. The specific monitoring process includes:

[0058] Multi-type sensor networks include power sensor arrays and environmental sensor groups, among which:

[0059] A power sensor is installed at the output end of each photovoltaic module. By continuously collecting the output power value and binding it to the rated power of the photovoltaic module, the current power generation status is obtained in real time. Based on the preset threshold of the power sensor, the power generation status is divided into normal power generation status, inefficient status and fault status.

[0060] The sensor acquires the real-time output power of the component at a high frequency of 10 seconds per time, generates a dynamic monitoring signal and transmits it to the edge computing gateway through the RS485 bus, and performs data standardization processing to generate structured data, which is synchronously integrated into the operation database; the structured data includes component number, timestamp, power value and state identifier;

[0061] The photovoltaic array area is grid deployed at a density of 50-100 square meters per group, each group containing 1 irradiance sensor and 2 temperature sensors, based on the component installation inclination and orientation in the photovoltaic component basic parameters, the temperature sensors are installed on the component backboard and array gap respectively to monitor the working temperature and environmental temperature; the photovoltaic component basic parameters include single component rated power, conversion efficiency, temperature coefficient, size specification, component installation inclination and orientation, array total capacity and component series and parallel connection mode;

[0062] The environmental sensor acquisition frequency is synchronized with the operation data acquisition frequency, and the environmental sensor data is transmitted to the environmental monitoring terminal through LoRa wireless transmission, and the environmental parameters collected by the weather station are cross-verified, and when the deviation exceeds 10%, the sensor calibration is triggered; lock the target sensor with excessive deviation, suspend the real-time data upload of the target sensor, at the same time, enable the standby sensor to temporarily replace the data acquisition task, and ensure the continuity of environmental parameter monitoring;

[0063] Based on the normal output value of the target sensor under the same environmental conditions in the historical data, the synchronous data of the weather station and the mean value of the surrounding same type sensors, a calibration compensation coefficient is generated to correct the current output value of the sensor; if the deviation after correction still exceeds 5%, manual calibration prompt is triggered to remind the operation and maintenance personnel to carry out on-site calibration with standard calibration equipment;

[0064] Combined with the photovoltaic component basic parameters, the mapping relationship between the environmental parameters and the theoretical output power is established through the calibration algorithm, and the photovoltaic unit virtual network is generated, taking the standard test condition as the benchmark, the theoretical output power is calculated through the formula , wherein, represents the rated power of the photovoltaic component; represents the real-time collected irradiance; represents the temperature coefficient, which is obtained based on the photovoltaic component basic parameters; represents the real-time collected photovoltaic component working temperature;

[0065] At the same time, based on the physical zoning of the photovoltaic array, the components are divided into standard power units, which are bound with unique numbers and one-to-one mapped with the digital twin model in the virtual network, realizing the accurate association from physical component number to virtual unit number to theoretical power value;

[0066] The actual output power of the photovoltaic module collected based on the power sensor is transmitted to a virtual network, and the actual output power is compared with the theoretical output power in the same time period;

[0067] If the deviation of the actual output power from the theoretical output power exceeds 30%, and the environmental parameters show that the current illumination and temperature are in the normal range, it is determined that the photovoltaic module is in a fault state or a low-efficiency state, and further distinguished in combination with historical data. If the deviation of the actual output power of the photovoltaic module from the theoretical output power is greater than 30% in n consecutive collection periods, it is determined that the photovoltaic module is faulty. If the deviation value of the actual output power of the photovoltaic module from the theoretical output power presents obvious fluctuation in different periods, and the deviation temporarily decreases or returns to the normal range in some periods, it is determined that the photovoltaic module is low-efficiency;

[0068] If the deviation of the actual output power from the theoretical output power is less than 10%, or the deviation is caused by environmental abnormalities, such as sudden decrease in irradiance or temperature exceeding the normal range, it is determined that it is normal fluctuation under the influence of the environment, and no abnormality is marked;

[0069] The energy storage management module monitors the charge and discharge state of the energy storage unit through the battery management device, and based on the real-time feedback of the photovoltaic power generation output, the theoretical power fluctuation and the environmental parameter change of the power generation monitoring module, realizes the intelligent regulation and control and capacity optimization management of the energy storage device, and the specific process is as follows:

[0070] The battery management device deployed for all-round parameter monitoring of the energy storage unit, the monitoring parameters include single battery voltage, current, temperature, internal resistance and state of charge; at the same time, through the edge computing gateway, the actual output power of photovoltaic, the theoretical output power, the environmental irradiance and the working temperature of photovoltaic module of the power generation monitoring module are received and the photovoltaic output prediction model is constructed, and transmitted to the energy storage management server for processing. By analyzing the battery state of charge, health state and power state, and matching with the pre-constructed battery performance library, combining the stability characteristics of photovoltaic power generation, including the number of daily fluctuations and the maximum fluctuation amplitude, and judging the battery state based on the electrochemical model, including the charging state, the discharging state, the standby state and the fault state;

[0071] By capturing the rate of change of the battery terminal voltage with time in real time, the voltage characteristic value related to the capacity is extracted in combination with the charging and discharging stage characteristics. The stage characteristics include the voltage sudden rise rate at the end of charging and the voltage stability degree in the middle of discharging.

[0072] The product of current and time in the charging and discharging process is continuously counted to obtain the current integral, and the cumulative calculation of the current integral obtains the power change, which is used as the basic data for capacity estimation;

[0073] Synchronous monitoring of the dynamic change of the battery internal resistance, capturing the internal resistance growth trend caused by material aging by comparing the internal resistance values at different cycle stages, calculating the internal resistance growth coefficient combined with the daily fluctuation times of photovoltaic output, and the change range of the internal resistance growth coefficient is positively correlated with the capacity attenuation;

[0074] extracting voltage characteristic values , power change , and internal resistance growth coefficient , and calculating the remaining available capacity of the battery after normalization , wherein, represents the real-time state of charge, which refers to the ratio of the actual power of the current battery to the full charge state power; represents the rated charge and discharge capacity marked when the battery is shipped; represents the error correction coefficient; are the influence weight factors of voltage characteristic values, power change, and internal resistance growth coefficient, respectively, which are dynamically adjusted based on the ratio of photovoltaic output to charging load demand;

[0075] Taking the initial internal resistance of the battery when it is shipped as the reference value, the aging degree is determined based on the change of the battery internal resistance, and the battery internal resistance increases with the increase of the cycle number. When the internal resistance growth exceeds 80% of the reference value, it is determined that the battery enters the aging stage. The internal resistance growth ratio is calculated based on the reference value and the real-time internal resistance, and the aging degree quantization value is obtained after normalization ;

[0076] The real-time state of charge, the remaining available capacity of the battery, and the aging degree quantization value obtained are normalized and substituted into the formula to calculate the comprehensive health index of the current energy storage unit, wherein, are the influence weight factors of real-time state of charge, remaining available capacity of the battery, and aging degree quantization value, respectively;

[0077] Based on the comprehensive health index of the current energy storage unit, an energy storage scheduling strategy is constructed combined with a photovoltaic output prediction model, including:

[0078] For battery groups with a comprehensive health index higher than a preset maximum health threshold, and when the photovoltaic output fluctuates greatly, frequent charge and discharge tasks are preferentially allocated to suppress photovoltaic power fluctuations. For battery groups with a comprehensive health index between the preset maximum health threshold and the minimum health threshold, they mainly undertake energy time shifting and peak shaving tasks during the peak period of photovoltaic output. For battery groups with a comprehensive health index lower than the preset minimum health threshold, and when the photovoltaic output is weak, the depth of charge and discharge is reduced, and they are mainly used for backup and emergency power supply;

[0079] Different types of batteries are set up with differentiated management strategies: lithium battery energy storage unit controls the depth of discharge not to exceed 80% of the current battery remaining available capacity, and the discharge rate not to exceed the rated capacity value, and the environmental temperature is predicted based on the real-time photovoltaic module operating temperature and the average of the photovoltaic module operating temperature in similar weather within a period of time; similar weather refers to the weather state in which the deviation of real-time solar radiation intensity, wind speed, cloud cover and air humidity from historical data in the same period is within 10% in the same time period;

[0080] If the real-time photovoltaic module operating temperature is higher than the historical average for more than 10 minutes, it is determined that the photovoltaic module operating temperature is high, indicating that the environmental temperature of the energy storage unit will rise synchronously within 15-30 minutes; when the predicted environmental temperature exceeds the range of 15-35℃, the heat dissipation is started in advance to maintain the temperature within the range of 15-35℃; the lead-acid battery energy storage unit controls the depth of discharge not to exceed 50% of the current battery remaining available capacity, and the discharge rate not to exceed 30% of the rated capacity value; when the predicted environmental temperature rises to 28-30℃, forced air cooling below the photovoltaic panel is introduced in advance to maintain the temperature within the range of 10-30℃; the vanadium flow battery energy storage unit can allow 100% depth of discharge, but the electrolyte temperature needs to be kept constant within the range of 25±5℃; when the predicted environmental temperature exceeds , the electrolyte circulating pump power is increased by 10% to stabilize the electrolyte temperature;

[0081] The adaptive equalization control technology is integrated, and when the voltage difference exceeds 50mV, the equalization charging program is started preferentially in the period of high photovoltaic output and low charging load; for lithium batteries, active equalization is adopted to transfer the energy of high-voltage monomers to low-voltage monomers; for lead-acid batteries, passive equalization is adopted to consume the energy of high-voltage monomers through shunt resistance; the equalization process continues until the voltage difference is reduced to below 20mV;

[0082] When the power generation monitoring module detects that the photovoltaic module failure causes the photovoltaic output to drop sharply, the internal resistance and voltage monitoring frequency are immediately increased, and the discharge strategy is adjusted based on the proportion of faulty components: when the proportion of faulty components is <10%, the highest health index battery group bears 60% of the energy supply demand; when the proportion of faulty components is >30% and the remaining capacity of energy storage is <30%, a power limitation request is sent to the charging load control module to preferentially guarantee the power supply of key loads; the key loads include emergency vehicle charging and micro-grid control power supply;

[0083] The charging load control module dynamically calculates the optimal charging strategy based on the power generation monitoring information and the energy storage state information, and provides intelligent power distribution services for charging equipment through multi-level regulation, and the specific process includes:

[0084] When the charging request is triggered, the available power state of the micro-grid is obtained, real-time collection and summary of photovoltaic power generation power, energy storage available power and grid adjustable power are performed, a complete energy state matrix is constructed, and the total amount of current allocable charging power and its source composition are calculated and compared with multi-dimensional preset thresholds in real time;

[0085] When the total amount of allocable charging power is greater than the preset threshold, the charging device is allowed to charge at the maximum power, the charging demand information of the charging device is received, and a charging power configuration scheme is generated based on the device type and charging demand:

[0086] For slow charging devices, a constant power charging mode is adopted, charging is performed at 85% of the rated power of the device, and a charging time window is dynamically allocated based on the user's scheduled charging time length;

[0087] For fast charging devices, the maximum charging power is calculated based on the current battery state of charge of the charging device, and the maximum charging power is calculated by the formula , wherein, represents the rated maximum power of the current charging device; represents the power coefficient function of the state of charge of the current charging device; when the battery state of charge is lower than 20%, maximum power charging is provided, and when the state of charge reaches 80%, the charging power is automatically reduced to 30% of the maximum power, to avoid overcharging of the battery;

[0088] When the total amount of allocable charging power is lower than the preset threshold but higher than the minimum running threshold, power allocation is performed based on the charging device priority strategy, and differential charging power allocation is realized by dynamically calculating the priority coefficients of each charging device; The priority coefficient is calculated by combining the charging device type, the battery state of charge and the user's reservation state with a weighting formula; The charging device type is divided into emergency vehicles, public transportation vehicles and private vehicles, the priority of emergency vehicles is the highest, and the priority of private vehicles is the lowest; The lower the battery state of charge, the higher the priority coefficient; The priority of the charging device with reservation is higher than that of the charging device without reservation;

[0089] When the total amount of allocable charging power is lower than the minimum running threshold, the charging power limiting strategy is triggered, the historical charging mode and future energy supply prediction are analyzed based on the sliding time window, and the upper limit of the power of each charging pile is dynamically adjusted;

[0090] The power demand change of the charging device is monitored in real time, when the charging demand is detected to decrease, the reserved power is released and redistributed to other charging devices; When the charging device reaches the preset state of charge or the user's set target, the charging completion process is triggered, the charging power is released and the total amount of allocable power is updated;

[0091] For the charging device of the vehicle-to-grid function, based on the grid scheduling demand and the user setting, the reverse discharge mode is started during the peak period of grid power consumption, the vehicle battery energy is fed back to the micro-grid, and the load peak shaving is supported; the depth of battery discharge is controlled not to exceed the user preset value during the reverse discharge process, and the emergency power demand of the vehicle is ensured;

[0092] A power limiter is arranged at the power output end of the charging pile, and the maximum output power of the charging pile is dynamically adjusted based on the maximum charging power calculated in real time; power distribution is realized through DC bus voltage control;

[0093] The energy coordination module coordinates and schedules the global energy flow based on the multi-source state information provided by the power generation monitoring module, the energy storage management module and the charging load control module, and the specific implementation process is as follows:

[0094] The actual output power, theoretical output power and component operating state information of the photovoltaic array from the power generation monitoring module are periodically aggregated; the current state of charge, remaining available capacity, comprehensive health index and current charging and discharging state of the energy storage unit are obtained from the energy storage management module; at the same time, the current total charging demand, priority distribution of various devices and charging strategy execution situation are received from the charging load control module, and a unified energy state perception view is constructed;

[0095] Based on the energy state perception view, the power balance state, total generation output power, total adjustable power and total load power demand of the current micro-grid are calculated in real time, and a complete source storage load power flow atlas is formed;

[0096] The power balance state is divided into the following three states, wherein:

[0097] Power surplus state: when the sum of the total generation output power and the total adjustable power is greater than the current load power demand, the power demand of the charging load is preferentially met, and the remaining available capacity of the energy storage unit is evaluated, and under the premise that the comprehensive health index meets the scheduling strategy, the energy storage charging task is executed to absorb the excess energy and prevent the occurrence of light abandonment; if the energy storage capacity has approached the upper limit, part of the low-priority charging task is sequentially reduced or the excess power is fed back to the grid;

[0098] Power shortage state: when the sum of the total generation output power and the total adjustable power is less than the current load demand but higher than the minimum running threshold, the priority scheduling mechanism is started, the power demand of the charging device is dynamically reconstructed, the charging demand of the high-priority device is preferentially guaranteed, and based on the current state of charge and the comprehensive health index of the energy storage unit, the depth of discharge is controlled to avoid excessive discharge leading to life attenuation;

[0099] Power shortage state: when the sum of the total power output and the total adjustable power is lower than the minimum running threshold, the future short-term power generation capacity is predicted based on the historical power change trend and environmental sensor data, combined with the energy storage scheduling strategy, instructing the energy storage unit to enter the power protection mode, only supplying power to the key load; at the same time, by controlling the charging pile power limiter, the power supply of ordinary load is greatly compressed, triggering the energy peak shaving response strategy; in the charging equipment with vehicle-to-grid function, the vehicle resources with reverse discharge willingness are called, and the reverse discharge process is started according to the preset strategy;

[0100] When the power generation monitoring module reports that the photovoltaic array has a faulty component or the energy storage management module detects that the energy storage unit is abnormal, the energy distribution strategy is immediately adjusted, the power distribution weight of the faulty unit is excluded, and the scheduling path of the remaining resources is re-optimized; at the same time, operation and maintenance instructions are generated to prompt the on-site maintenance personnel to carry out maintenance;

[0101] During daily operation, the energy flow is dynamically predicted based on the timing law of operation and external environmental changes; based on the prediction results, the running state of each energy unit is dynamically adjusted, the scheduling resources are prepared in advance, and feedforward control is realized;

[0102] Through the edge computing gateway and the operation database, the synchronization is maintained, the periodic recording of various energy flow data, scheduling instruction execution records and power distribution logs is carried out, the data support is provided for subsequent optimization, strategy iteration and operation and maintenance analysis; at the same time, data interaction with the upper layer control platform of the microgrid is supported, the coordinated operation of multiple microgrids and the unified scheduling of regional energy management are realized.

[0103] The preferred embodiments disclosed above are only used to help explain the present application. The preferred embodiments do not describe all the details, nor limit the application to the specific embodiments. Obviously, according to the content of the specification, many modifications and changes can be made. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and utilize the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. A photovoltaic-storage-charging integrated microgrid energy management system, characterized in that, include: Power generation monitoring module: By integrating power sensor arrays and environmental parameter sensor groups, a multi-dimensional monitoring network is constructed to capture and judge the power generation status; Energy storage management module: By monitoring the charging and discharging status of the energy storage unit and based on real-time feedback of photovoltaic power output, theoretical power fluctuations and changes in environmental parameters, it realizes intelligent control and capacity optimization management of energy storage equipment; Charging load control module: Based on power generation monitoring information and energy storage status information, calculate the optimal charging strategy and provide intelligent power distribution services to charging equipment through multi-level regulation; Energy Coordination Module: Based on the multi-source status information provided by the power generation monitoring, energy storage management, and charging load control modules, it regulates the global energy flow. The specific operation steps of the energy storage management module include: The parameters of the energy storage unit are monitored by the battery management device; the actual output power, theoretical output power, ambient irradiance and photovoltaic module operating temperature are extracted to construct a photovoltaic output prediction model; the battery state of charge, health state and power state are analyzed and matched with a pre-built battery performance library, and the battery charging, discharging, standby and fault states are judged by combining the stability characteristics of photovoltaic power generation and electrochemical model. Voltage characteristic values ​​are obtained based on the rate of change of battery terminal voltage over time and the characteristics of the charging and discharging stages; The change in charge is obtained by continuously calculating the product of current and time during the charging and discharging process and accumulating the data. Simultaneously monitor changes in battery internal resistance, compare internal resistance values ​​at different cycle stages, and obtain the internal resistance growth coefficient by combining the average daily fluctuations in photovoltaic power output. Extracting voltage characteristic values Changes in electricity and internal resistance growth coefficient After normalization, the formula is entered. The remaining usable capacity of the battery is obtained, where, Indicates the real-time state of charge. This indicates the rated charge and discharge capacity marked on the battery at the factory. This represents the error correction factor. These are the influence weighting factors for voltage characteristic value, change in electrical quantity, and internal resistance growth coefficient, respectively. The specific operation steps of the energy storage management module also include: Using the initial internal resistance of the battery at the factory as a baseline value, when the internal resistance increases by more than 80% of the baseline value, it is determined to have entered the aging stage. The internal resistance increase ratio is calculated based on the baseline value and the real-time internal resistance, and then normalized to obtain a quantitative value of the aging degree. ; The comprehensive health index is obtained by normalizing the quantified values ​​of real-time state of charge, remaining battery capacity, and degree of aging, and then using a weighted formula. For battery packs with a comprehensive health index higher than the preset maximum health threshold and large fluctuations in photovoltaic output, frequent charging and discharging tasks are prioritized to smooth out photovoltaic power fluctuations. For battery packs with a comprehensive health index between the preset maximum and minimum health thresholds, energy shifting and peak shaving tasks are undertaken during peak photovoltaic output periods. For battery packs with a comprehensive health index lower than the preset minimum health threshold and weak photovoltaic output, the depth of charging and discharging is reduced for backup and emergency power supply. Differentiated management strategies are set for lithium batteries, lead-acid batteries, and vanadium redox flow batteries to control the depth of discharge and discharge rate of different batteries. The ambient temperature is predicted by combining the operating temperature of photovoltaic modules with historical averages. When the predicted ambient temperature exceeds the range, heat dissipation, forced air cooling, or adjustment of electrolyte circulation pump power is initiated in advance. Real-time monitoring of individual cell voltage differences; when the voltage difference exceeds... Furthermore, when photovoltaic output is at its peak, during periods of low charging load, active balancing is used to transfer energy to lithium batteries, while passive balancing is used to consume energy from lead-acid batteries.

2. The integrated photovoltaic, energy storage, and charging microgrid energy management system according to claim 1, characterized in that, The specific implementation process of the power generation monitoring module is as follows: Power sensors are installed at the output end of each photovoltaic module to collect the output power of the photovoltaic module and bind it to the rated power, so as to obtain the normal power generation, inefficiency and fault status in real time; and generate structured data containing module number, timestamp, power value and status identifier based on edge computing gateway. The environmental parameter sensor group is deployed in a grid to monitor the operating temperature of the component backplane and the ambient temperature between the arrays, and cross-validates with weather station data. Calibration is triggered when the deviation exceeds 10%. The calibration compensation coefficient is generated and corrected based on historical data of the target sensor under the same environmental conditions. Based on the basic parameters of photovoltaic modules and the calibration algorithm, a mapping relationship between environmental parameters and theoretical output power is established to generate a virtual network of photovoltaic units; Through formula The theoretical output power is obtained, where, Indicates the rated power of the photovoltaic module. This indicates the real-time irradiance. Indicates the temperature coefficient. It indicates the real-time operating temperature of the photovoltaic module; based on the physical partitioning of the photovoltaic array, the module is divided into standard power units and bound with a unique number.

3. The integrated photovoltaic-storage-charging microgrid energy management system according to claim 1, characterized in that, The specific operation steps of the charging load control module are as follows: When a charging request is triggered, the photovoltaic power generation, available energy storage power, and adjustable grid power are collected and summarized in real time to construct a complete energy state matrix, and the total amount of currently allocable charging power is calculated and compared with a preset threshold. When the total available charging power exceeds a preset threshold, the charging device is allowed to charge at maximum power. Slow-charging devices charge at 85% of their rated power. Fast charging devices calculate maximum charging power based on the device's battery state of charge; Maximum power charging is provided when the battery's state of charge is below 20%, and the charging power is reduced to 30% of the maximum power when the state of charge reaches 80% to avoid overcharging the battery. When the total allocable charging power is lower than the preset threshold but higher than the minimum operating threshold, a priority coefficient is obtained based on the charging equipment type, battery state of charge and user reservation status, and power is allocated accordingly using a weighted formula. When the total available charging power is lower than the minimum operating threshold, the power limit of each charging pile is adjusted based on the analysis of historical charging patterns and future energy supply forecasts using a sliding time window. When a decrease in charging demand is detected, the reserved power is released and reallocated to other charging devices; when the charging device reaches the preset state of charge or the user-set target, the charging completion process is triggered, the charging power is released and the total amount of allocable charging power is updated.

4. The integrated photovoltaic-storage-charging microgrid energy management system according to claim 1, characterized in that, The specific operating steps of the energy coordination module are as follows: Extract the actual output power, theoretical output power, and component operating status information of the photovoltaic array from the power generation monitoring module; obtain the current state of charge, remaining available capacity, comprehensive health index, and current charging and discharging status of the energy storage unit; simultaneously receive the current total charging demand, priority distribution of various devices, and execution status of charging strategies from the charging load control module, construct an energy status perception view, and calculate the power balance status, total power output, total adjustable power, and total load power demand of the microgrid to form a source-storage-load power flow map; When a fault is detected in a photovoltaic array module or energy storage unit, the power allocation weight of the faulty unit is removed, the scheduling path of the remaining resources is optimized, and operation and maintenance instructions are generated. Based on the timing patterns of operation and changes in the external environment, the energy flow is dynamically predicted and the operating status of each energy unit is adjusted. It records various energy flow data, scheduling command execution records, and power allocation logs; it also supports data interaction with the upper-level control platform of the microgrid, enabling coordinated operation among multiple microgrids and unified scheduling of regional energy management.

5. The integrated photovoltaic-storage-charging microgrid energy management system according to claim 4, characterized in that, The specific implementation process of the power balance state includes: Power surplus state: When the sum of the total power output of the generator and the total adjustable power is greater than the load power demand, the power demand of the charging load is given priority. Based on the remaining available capacity of the energy storage unit and the comprehensive health index, the energy storage charging task is executed; if the energy storage capacity has reached its limit, the low priority charging tasks are reduced in an orderly manner. Power shortage state: When the sum of the total power output and the total adjustable power is less than the load demand but higher than the minimum operating threshold, the power demand of charging equipment is reconfigured to prioritize the charging needs of high-priority equipment; the depth of discharge is controlled based on the current state of charge and comprehensive health index of the energy storage unit. Power shortage state: When the sum of the total power output and the total adjustable power is lower than the minimum operating threshold, the power generation capacity in the short term is predicted based on historical power change trends and environmental sensor data. Combined with the energy storage scheduling strategy, the energy storage unit is instructed to enter the power supply mode and supply power only to critical loads. The power supply of ordinary loads is compressed by controlling the charging pile power limiter, triggering the energy peak shaving response.

Images