Light storage and charging integrated smart energy management system

Abstract

The invention relates to the technical field of energy management, and particularly discloses a light storage and charging integrated smart energy management system, which comprises a data acquisition and monitoring module. An automatic power generation control module; a communication module; a network security monitoring module; an optical power prediction transmission module; an electric energy meter data transmission module; through cooperation of a data acquisition and monitoring module, an automatic power generation control module, a communication module, a network security monitoring module, an optical power prediction transmission module and an electric energy meter data transmission module, multi-dimensional power decomposition can be carried out by adopting an intelligent distribution strategy according to a real-time adjustment instruction or a scheduling power generation plan curve of a scheduling master station; a progressive processing algorithm is adopted for staged adjustment, it is ensured that power control is not interrupted, the grid-connected power requirement of a dispatching end for a wind power occasion or a photovoltaic electric field is met, precise control over the power of a new energy field station is achieved, the requirements of a power grid for the power change rate and the adjustment precision are met, and the equipment operation mode is optimized.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of energy management, and particularly relates to a light storage and charging integrated intelligent energy management system. BACKGROUND

[0002] In a solar power generation system, an intelligent energy management system is usually used to efficiently utilize and manage the energy of a new energy power station. The current intelligent energy management system (SEMS) usually adopts a distributed collaborative management mode.

[0003] The distributed collaborative management mode is to distribute management tasks to subsystems such as a photovoltaic inverter cluster, an energy storage unit and a fan, to collaboratively make decisions through a regional controller, to generate an error signal by comparing real-time collected output power, voltage, current and the like with target values, and to adjust device parameters (such as inverter switching frequency and fan pitch angle) by using a control algorithm (such as PID and model predictive control) to form a closed-loop regulation. The distributed collaborative management mode has fast response speed and high fault tolerance, but requires efficient communication between subsystems and high complexity of coordination algorithms.

[0004] However, the current control algorithm has poor adaptability to nonlinear systems, so that the maximum power and power variation of the new energy power station may exceed the given value, which cannot guarantee the regulation accuracy and the optimal operation mode of the photovoltaic inverter or the fan. For example, the PID control relies on a linearized model, and in the nonlinear working condition (such as the high wind speed area and the inverter saturation area) of the new energy device (such as the photovoltaic inverter and the variable pitch fan), the regulation accuracy significantly decreases, and oscillation or steady-state error easily occurs. For another example, the model predictive control requires an accurate system model, but the model parameters (such as the equivalent circuit parameters of the photovoltaic array and the aerodynamic model of the fan) change in real time due to the influence of the environment (such as the randomness of the light intensity, the temperature and the wind speed), which leads to the accumulation of prediction errors and the attenuation of the regulation accuracy over time.

[0005] To solve the above problems, a light storage and charging integrated intelligent energy management system is proposed, which can accurately control the power of the new energy power station, meet the requirements of the power grid for the power variation rate and the regulation accuracy, optimize the device operation mode, and improve the system stability and power generation efficiency. SUMMARY

[0006] The purpose of the present application is to provide a light storage and charging integrated intelligent energy management system, which adopts an intelligent distribution strategy and uses a progressive processing algorithm to ensure that the maximum power and power variation of the new energy power station do not exceed the given value, meet the grid-connected power requirements of the dispatching end for the wind power station or the photovoltaic power station, accurately control the power of the new energy power station, meet the requirements of the power grid for the power variation rate and the regulation accuracy, optimize the device operation mode, and improve the system stability and power generation efficiency, thereby solving the problems proposed in the background.

[0007] To achieve the above object, the application adopts the following technical scheme:

[0008] A light storage and charging integrated intelligent energy management system, comprising: a data acquisition and monitoring module for acquiring and processing power plant, booster station and reactive power compensation device operation data;

[0009] An automatic generation control module, according to the real-time instructions of the dispatching master station or the generation plan curve, through intelligent distribution strategy for multi-dimensional power decomposition, using progressive processing algorithm for phased adjustment, and switching mode according to communication state, and receiving data transmitted by the data acquisition module;

[0010] A communication module for safe transmission of data to vertical boundary security protection;

[0011] A network security monitoring module for collecting security events and state data of servers, network devices and security devices in the station and uploading to the dispatching master station;

[0012] A light power prediction transmission module for obtaining distributed photovoltaic power prediction data, ground cloud image and weather data, and transmitting to the dispatching master station through the dispatching data network or wireless private network;

[0013] An electric energy meter data transmission module for reading the metering data of the electric energy meter on the power plant or booster station side through RS485 serial port and uploading to the dispatching master station;

[0014] The automatic generation control module is electrically connected with the light power prediction transmission module and the electric energy meter data transmission module, and the communication module is electrically connected with the data acquisition and monitoring module, the light power prediction transmission module, the electric energy meter data transmission module and the network security monitoring module.

[0015] Preferably, the data acquisition and monitoring module comprises a data acquisition unit for acquiring the operation data of the power plant, booster station and reactive power compensation device, a data processing unit for processing the acquired data, and a control and adjustment unit for ensuring the safety and reliability of the control operation, and the data acquisition unit, data processing unit and control and adjustment unit are connected in sequence.

[0016] Preferably, the data processing unit uses a multi-core microprocessor to check the effectiveness of the acquired data, and performs multi-source fusion processing through a multi-source data fusion algorithm, including data filtering, zero drift processing, limit value checking and dead zone setting.

[0017] Preferably, the control and regulation unit comprises circuit breaker opening / closing, regulation transformer tap, set value control, active regulation control, reactive compensation device switching and regulation, control instructions are generated based on processed data, such as inverter power regulation, reactive compensation switching, and safety check is performed before execution of the instructions.

[0018] Preferably, the data acquisition module further comprises a data management unit for event sequence recording, accident and alarm, historical data management, data calculation and system time.

[0019] Preferably, the intelligent distribution strategy comprises equal power factor distribution, similar adjustment margin distribution and power equal proportion distribution, wherein the equal power factor distribution is to distribute active power regulation targets in proportion according to the rated capacity and current power factor of each inverter, so as to ensure that the power factor of the whole station is stable in a reasonable range.

[0020] The similar adjustment margin distribution is to preferentially regulate the inverters with large current power margins, so as to avoid overloading of part of the devices.

[0021] The power equal proportion distribution is to distribute the total regulation amount in proportion to the rated power of the inverters, so as to ensure power balance of the whole station.

[0022] Preferably, the communication module comprises an RJ45 Ethernet interface, an RS485 communication interface and a redundancy device, the RJ45 Ethernet interface and the RS485 communication interface are connected with the redundancy device, and the redundancy device adopts a double CPU module.

[0023] Preferably, the network security monitoring module performs the following process for security event and state data acquisition:

[0024] A1, obtain device state information through a simple network management protocol, receive log data using a Syslog protocol, and collect security events through an API interface to an security system;

[0025] A2, pre-process the obtained security events and state data;

[0026] A3, transmit the processed data to a dispatching master station through an encrypted wireless private network.

[0027] Preferably, the dispatching data network comprises short-term power prediction data collection and ground-based cloud image and weather data acquisition, the short-term power prediction data collection collects historical power generation data accumulated for a long time by the distributed photovoltaic power station, the historical power generation data covers power generation information under different seasons and different weather conditions, and a relatively accurate short-term power prediction data is obtained through comprehensive analysis using a weather model combined with real-time weather data.

[0028] The ground cloud chart and meteorological data are acquired by a ground cloud chart photovoltaic resource monitoring device which captures the distribution and change of the cloud in the sky in real time, and meanwhile, various meteorological sensors continuously collect real-time meteorological data of radiation intensity, temperature and wind speed, which are not only used for real-time monitoring of the current power generation environment, but also used as important correction factors for optimizing and adjusting the power prediction model.

[0029] Preferably, the system further comprises a human-computer interaction module for displaying the system running state, device parameters, accident alarm picture and trend curve in real time, and the human-computer interaction module is interacted with the data acquisition and monitoring module, the automatic power generation control module, the communication module, the network security monitoring module, the light power prediction transmission module and the electric energy meter data transmission module.

[0030] Compared with the prior art, the intelligent energy management system has the following advantages:

[0031] 1、The data acquisition and monitoring module, the automatic power generation control module, the communication module, the network security monitoring module, the light power prediction transmission module, the electric energy meter data transmission module and the human-computer interaction module are cooperated, the real-time adjustment instruction of the dispatching master station or the dispatching power generation plan curve is adopted, the intelligent distribution strategy is used for multi-dimensional power decomposition, the gradual processing algorithm is used for stage adjustment, the power control is ensured not to be interrupted, the requirements of the dispatching end to the grid-connected power of the wind power station or the photovoltaic power station are met, the precise control of the power of the new energy station is realized, the requirements of the power grid to the power change rate and the adjustment accuracy are met, the equipment operation mode is optimized, and the system stability and the power generation efficiency are improved. BRIEF DESCRIPTION OF DRAWINGS

[0032] Fig. 1 The figure shows the block diagram of the intelligent energy management system according to the embodiment of the application;

[0033] Fig. 2 The figure shows the block diagram of the data acquisition and monitoring module according to the embodiment of the application;

[0034] Fig. 3 The figure shows the flow block diagram of the network security monitoring module for collecting security events and state data according to the embodiment of the application. DETAILED DESCRIPTION

[0035] The technical solutions in the embodiments of the present application will be described clearly and completely below with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. The specific embodiments described herein are only used to explain the present application, and are not used to limit the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present application.

[0036] The present application provides a kind of optical storage and charging integrated wisdom energy management system as shown in Figs. 1-3 Data collected by data acquisition and monitoring module need to be transmitted to automatic generation control module for processing, the automatic generation control module is electrically connected with optical power prediction transmission module and electric energy meter data transmission module respectively, the communication module is electrically connected with data acquisition and monitoring module, optical power prediction transmission module, electric energy meter data transmission module and network security monitoring module respectively, man-machine interaction module is respectively interacted with data acquisition and monitoring module, automatic generation control module, communication module, network security monitoring module, optical power prediction transmission module and electric energy meter data transmission module, display data and receive operation instruction;

[0037] Data acquisition and monitoring module collects and processes power generation field, booster station and reactive power compensation device operation data;The data acquisition and monitoring module includes a data acquisition unit for collecting power generation field, booster station and reactive power compensation device operation data, a data processing unit for processing collected data, a control and regulation unit for ensuring safe and reliable control operation, the data acquisition unit, the data processing unit and the control and regulation unit are connected in sequence;

[0038] The data acquisition unit is connected with the inverter of the power generation field, the booster station measurement and control device and the reactive power compensation device through the RS485 interface, for collecting the analog data of current, voltage and power of the inverter, the booster station measurement and control device and the reactive power compensation device;

[0039] The data processing unit adopts a multi-core microprocessor to check the effectiveness of the collected data, and performs multi-source fusion processing through a multi-source data fusion algorithm, fuses electric energy metering data and light power prediction data, so as to improve the data reliability. The multi-source fusion processing includes data filtering, zero drift processing, limit value checking and dead zone setting. The data filtering is used to eliminate abnormal values, the zero drift processing is used to correct the errors caused by the zero position offset of the sensor, the limit value checking is used to compare whether the data exceeds the safety threshold, such as the upper limit of voltage, and the dead zone setting is used to ignore the slight fluctuations less than the safety threshold and reduce invalid data processing. Through the state variable displacement and effectiveness checking processing, the power generation plan, voltage control curve and other plan values issued by the dispatching master station are automatically received and imported into the real-time operation system, so as to provide accurate data source for the automatic power generation control module.

[0040] The multi-source data fusion algorithm formula is as follows:

[0041] ,

[0042] Among them, is the kth state estimation value, is the kth measurement value, is the Kalman gain, is the measurement matrix, is the k-1th state estimation value.

[0043] The control and regulation unit includes circuit breaker opening / closing, regulation transformer tap setting, set value control, active regulation control, reactive compensation device switching and regulation. Based on the processed data, control instructions such as inverter power regulation and reactive compensation switching are generated. Before executing the instructions, safety verification such as authority verification and operation process legality check is performed to ensure the safety and reliability of the control operation and meet the time response requirements of stable and reliable operation of the power grid.

[0044] The data acquisition module further includes a data management unit, which is used for event sequence recording, accident and alarm, historical data management, data calculation and system time synchronization. The event sequence recording is automatically sorted by time and has functions of display, query, printing and uploading to the master station. The accident and alarm include the following aspects:

[0045] 1) When an accident occurs, the accident picture is automatically pushed out, the picture flashes and changes color, and a signal is sent on the display screen;

[0046] 2) The abnormal state can be displayed through the indicator light during the fault;

[0047] 3) The events and alarms appear in the form of time sequence table. The data acquisition and monitoring module records the action sequence, event occurrence time (year, month, day, hour, minute, second, millisecond), event name and event nature of each important event, and generates alarms and reports according to the specifications.

[0048] Historical data management primarily uses comprehensive data processing measures such as timed storage and statistics to process real-time data collected on-site for easy retrieval and use. Historical data content is retained for at least one year. Data calculation supports various conventional operations, derivative calculations, and automatic calculations, with high computing speed. System synchronization receives precise clock signals from the clock synchronization system signal source through the synchronization interface, and combines with the synchronization software function module to achieve unified time synchronization for the entire system.

[0049] The automatic power generation control module uses an intelligent allocation strategy to perform multi-dimensional power decomposition based on the real-time adjustment instructions or the scheduling power generation plan curve of the scheduling master station, adopts a progressive processing algorithm to perform staged adjustment, monitors the communication status, and switches modes according to the monitoring status to ensure uninterrupted power control and meet the scheduling end's grid-connected power requirements for wind power or photovoltaic power fields;

[0050] The dispatching master station includes a power prediction system, a network security management platform, an automatic power generation control module, a metering and data management system, and a dispatching data network and communication system.

[0051] Intelligent allocation strategies include equal power factor allocation, similar adjustment margin allocation, and proportional power allocation. Equal power factor allocation proportionally allocates active power regulation targets based on the rated capacity and current power factor of each inverter, ensuring that the power factor of the entire station remains stable within a reasonable range and reducing reactive power losses.

[0052] The calculation formula for active power regulation target ratio distribution is:

[0053] ,

[0054] in, For the The inverters distribute power. is the rated capacity of the inverter, is the dynamic correction coefficient, is the scheduling target power;

[0055] Similar adjustment margin allocation is to prioritize the adjustment of inverters with large current power margins to avoid overloading of some equipment. For example, when the dispatcher requires an increase in active power, the automatic power generation control module calculates the adjustable upper limit of each inverter and preferentially issues adjustment instructions to equipment with large margins.

[0056] Power proportional distribution distributes the total regulation amount according to the rated power ratio of the inverter to ensure power balance of the entire station;

[0057] The formula of the asymptotic processing algorithm is:

[0058] ,

[0059] ,

[0060] wherein, is the maximum allowed power variation, is the maximum ramp rate, i.e. the upper limit of the power variation per unit of time, is the regulation period, i.e. the time interval between two regulations, is the regulated power setpoint, is the dispatch target power, is the current actual power;

[0061] The mode switching is performed for switching between the local control mode and the remote control mode, wherein the local control mode is autonomously completed by the field device for fault judgment and operation without intervention of the master station, completely independently operates, does not need communication operation, and is only triggered by local voltage or current; the remote control mode is centrally decided by the remote master station or the central control system, sends instructions to the field device through the communication network, highly depends on the stable communication network, needs real-time transmission of device state data, can be based on global topology analysis to realize accurate positioning of faults, network reconstruction and load transfer; when the dispatch communication fails or the control instruction from the dispatch end is not received within a timeout, the local control mode is automatically switched to ensure uninterrupted power control;

[0062] The communication module realizes safe transmission of data from a remote place by using technical measures of authentication, encryption and access control to achieve security protection of the vertical boundary, and meets the overall scheme requirements of security protection of the power monitoring system;

[0063] The communication module includes an RJ45 Ethernet interface, an RS485 communication interface and a redundancy device, the RJ45 Ethernet interface and the RS485 communication interface are connected with the redundancy device, the redundancy device uses a double-CPU module, one main CPU and one standby CPU, when the main CPU fails, the standby CPU quickly takes over the control logic, the redundancy device increases backup components or designs a redundancy structure to ensure that when the main component or the communication channel fails, the system can be seamlessly switched to the standby component or channel, thereby maintaining the continuity and stability of the communication;

[0064] The communication module monitors the operation of the inverter and the dynamic reactive power compensation device in a communication mode, exchanges data with the measurement and control device of the booster station using the protocol DL / T634.5104, can also communicate with the power prediction system, the electric meter and the micro weather device, and can interact information with the superior dispatch master station using the protocol DL / T634.5104, so that the system supports double-plane access to the dispatch automation system, follows the principles of direct direct sampling and direct sampling direct sending, and realizes safe transmission of data and safe protection of the vertical boundary by using authentication, encryption and access control technical measures; the authentication control uses digital certificate or password verification to confirm the identity of the communication parties, the encryption uses the AES algorithm to encrypt the transmission data to prevent tampering or theft in the middle, and the access control uses firewall rules to implement the access control policy and restricts the access of unauthorized devices to the network;

[0065] The network security monitoring module is used for collecting security events and state data of servers, network devices and security devices in the station, and uploading the security events and state data to the network security management platform in the dispatch master station;

[0066] The network security management platform is a system for centralized monitoring, management and analysis of network security states of each new energy station in the power system, and the new energy station includes photovoltaic power generation and wind power generation; the network security management platform collects security events and running state data of servers, network devices and security devices in the station in real time, and performs correlation analysis and risk assessment on the collected data, identifies potential security threats such as virus intrusion, abnormal access and device failure, generates security alarms and pushes them to operation and maintenance personnel, traces the source of security events and responds to emergencies, follows the standard of the overall security protection scheme of the power monitoring system, and realizes unified management and protection of the network security of the power system; wherein, the correlation analysis is to correlate multiple source logs through Snort rules or self-defined strategies to identify composite attacks such as login failure + port scanning + data transmission, which may indicate brute force cracking attack;

[0067] The risk score is calculated according to the severity of the event, the influence range and the occurrence frequency, and a security situation map is generated; high-risk events are pushed to the operation and maintenance personnel in real time, and event details are attached;

[0068] The process of the network security monitoring module for collecting security events and state data is as follows:

[0069] A1, obtain device state information through a simple network management protocol (SNMP), receive log data using a Syslog protocol, and collect security events through an API interface connected to a security system;

[0070] A2, pre-process the obtained security events and state data;

[0071] During preprocessing, repeated logs are filtered, invalid data is removed, the time stamps of the logs of each device are synchronized, the log formats of different devices are converted into a unified data model, subsequent analysis is facilitated, and finally the original logs and the preprocessed data are stored in a local server, and backups are retained for at least 6 months;

[0072] A3, the processed data is transmitted to the dispatch master station through an encrypted wireless private network, and is transmitted to the network security management platform in the dispatch master station;

[0073] The network security management platform in the dispatch master station realizes the whole life cycle monitoring of the network security of the new energy station, and ensures that the power system network meets the national and industry standards.

[0074] The power prediction transmission module is used to obtain power prediction data of distributed photovoltaics, ground-based cloud images and weather data, and transmit the prediction data to the power prediction system in the dispatch master station through the dispatch data network or the wireless private network;

[0075] The power prediction system in the dispatch master station aims to integrate various data related to photovoltaic power generation, predict the power generation of distributed photovoltaic power stations through complex and accurate algorithm models, and provide an important basis for power dispatching decisions. Through deep mining and analysis of a large amount of historical data, real-time operation data and weather data, the power prediction system can predict the power generation trend of distributed photovoltaic power stations at different times in advance, help dispatch personnel reasonably arrange power grid operation mode, optimize power resource allocation, and improve the overall operation efficiency and reliability of the power system;

[0076] The dispatch data network includes short-term power prediction data collection and ground-based cloud image and weather data acquisition. The short-term power prediction data collection collects historical power generation data accumulated by the distributed photovoltaic power station for a long time. This historical power generation data covers power generation information under different seasons and different weather conditions. At the same time, a weather model is used to analyze the real-time weather data to obtain relatively accurate short-term power prediction data. The time span of short-term power prediction is several hours to several days in the future, which can provide a relatively recent power generation estimate for power dispatching, helping dispatch personnel to plan power distribution in advance.

[0077] The ground cloud chart and meteorological data are acquired by the ground cloud chart photovoltaic resource monitoring device to capture the cloud distribution and change in the sky in real time, and meanwhile, various meteorological sensors continuously collect real-time meteorological data of radiation intensity, temperature and wind speed. The real-time meteorological data are not only used for real-time monitoring of the current power generation environment, but also used as an important correction factor to optimize and adjust the power prediction model, so as to improve the prediction accuracy. The ground cloud chart photovoltaic resource monitoring device is a professional equipment integrating advanced optical, image processing and artificial intelligence technologies, which is mainly used for real-time monitoring of the change of sky cloud conditions, resource evaluation and power prediction in combination with photovoltaic power generation characteristics;

[0078] When the wireless private network is transmitted, the dispatching master station communicates with the plant side acquisition control device through the safe access area server, and the data acquisition of the prediction data, the ground cloud chart and the meteorological data is completed through the transparent transmission mode, and the data is transmitted to the power prediction data acquisition server in the dispatching master station area through the forward and reverse isolation device.

[0079] The electric energy meter data transmission module reads the metering data of the electric energy meter on the power plant or booster station side through the RS485 serial port, and uploads the calculation data to the dispatching master station;

[0080] The electric energy meter data transmission module connects the electric energy meter on the power plant or booster station side through the RS485 serial port, reads the data such as electric energy and power factor according to the protocol, and then verifies and calculates the read data, and transmits the data to the dispatching master station through the wireless private network;

[0081] When the data is verified and calculated, the data verification algorithm is used to verify the correctness of the electric energy meter data transmission, and the formula expression of the data verification algorithm is:

[0082] CRC=CRC16(data_bytes,polynomial), wherein CRC is an algorithm for detecting errors in data transmission or storage, CRC16 represents a type of CRC verification, the generated verification code is 16 bits, data_bytes is a data byte sequence to be verified, polynomial is used to define the verification rule, and is usually represented by a binary number or a hexadecimal number, for example, the binary number corresponding to the polynomial 0x1021 is 1000000000100001, and the mathematical expression is .

[0083] The man-machine interaction module displays the system running state, device parameters, accident alarm picture and trend curve in real time;

[0084] The man-machine interaction module includes a liquid crystal display screen with a man-machine interaction interface, and the man-machine interaction interface has the functions of running information display, parameter configuration, function switching, function debugging and user management;

[0085] The man-machine interactive interface can display the running state of the electric field main system, the dynamic operation process of the main equipment, accidents and failures, relevant parameters and running monitoring figures, operation wiring diagrams and the like on the screen in real time, as well as trend curves, various lists, measurement point indexes and the like; the device conditions and running data on the screen are refreshed at a fixed time, and the screen of the accident alarm has the highest priority and can cover other screens being displayed, the screen is automatically pushed out during the accident, and the screen can be called by the running personnel;

[0086] The man-machine interactive interface supports control operations such as opening / closing of the circuit breaker on the interface, active regulation control, switching of the reactive power compensation device and regulation and the like;

[0087] The man-machine interactive interface has system user adding and management functions, supports user level and permission setting, including user permissions of different levels such as the system administrator, the running operation personnel and the browsing user. A plurality of groups of operation permissions of different security levels are provided for the operators with different responsibilities, and a plurality of users with respective passwords can be identified under the operation permissions of different levels. Before entering, the authorized running personnel must register the "user name" and the "password", and the password operation enables each user to independently enter and exit. Different man-machine interfaces are displayed according to the logged-in user group;

[0088] The man-machine interactive interface supports function switching operation, can integrally switch in / out the AGC and AVC functions, can individually switch in / out any inverter, and the SVC / SVG, capacitor / inductor participation and withdrawal of the AGC / AVC regulation; in the case of fault recovery, the operation interface supports the reset operation function.

[0089] Through the cooperation of the data acquisition and monitoring module, the automatic power generation control module, the communication module, the network security monitoring module, the optical power prediction transmission module, the electric energy meter data transmission module and the man-machine interaction module, multi-dimensional power decomposition can be carried out by using intelligent distribution strategies according to the real-time regulation instructions of the dispatching master station or the dispatching power generation plan curve, and phased regulation can be carried out by using a gradual processing algorithm, so as to ensure uninterrupted power control, meet the grid-connected power requirements of the dispatching end to the wind power plant or the photovoltaic power plant, realize accurate control of the power of the new energy plant, meet the requirements of the power grid on the power change rate and the regulation accuracy, optimize the equipment operation mode, and improve the system stability and power generation efficiency.

[0090] In the integrated management of light storage, the data processing unit integrates photovoltaic real-time power generation data, energy storage state data (implicit in reactive power compensation device), charging load data, and constructs a dynamic model of power generation, energy storage and load integration, such as real-time calculation of photovoltaic available power, energy storage remaining capacity and charging load demand through multi-source data fusion algorithm, to provide decision basis for automatic generation control module. The automatic generation control module uses a gradual processing algorithm to adjust the power in stages, including a prediction stage and a real-time adjustment stage. The prediction stage is based on light power prediction data to plan energy storage charging and discharging strategies in advance, such as energy storage discharging before photovoltaic peak and charging at photovoltaic peak. The real-time adjustment stage dynamically adjusts the inverter power according to real-time data through intelligent distribution strategy, while coordinating the energy flow of energy storage and charging load, such as when photovoltaic power suddenly decreases, the automatic generation control module first instructs the energy storage to discharge quickly to compensate for the power gap, and then gradually adjusts the inverter output to avoid voltage fluctuations.

[0091] The integrated management is realized through a closed-loop process of data collection, prediction analysis, power distribution, control execution and data feedback. The data collection and monitoring module monitors the power generation, energy storage and load state in real time and feeds back to the automatic generation control module. The automatic generation control module generates control instructions combined with prediction data to adjust the power generation and energy storage equipment and affect the charging load distribution. The control results are fed back through the data collection and monitoring module to form a dynamic optimization cycle, realize dynamic optimization and collaborative scheduling of energy flow, and ultimately achieve the goal of improving energy utilization and ensuring power supply stability.

[0092] Finally, it should be noted that the above-described only for the preferred embodiments of the present application, and not for the purpose of limiting the present application, although the foregoing detailed description of the present application is made with reference to the foregoing embodiments, for those skilled in the art, it still can be modified to the technical solutions recorded in the foregoing embodiments, or equivalent replacement of some technical features, any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application, should be included in the scope of protection of the present application.

Claims

1. A solar-storage-charging integrated smart energy management system, characterized by: include: Data acquisition and monitoring module, used to collect and process operating data of power plants, booster stations and reactive power compensation devices; The automatic power generation control module performs multi-dimensional power decomposition through intelligent allocation strategies based on real-time instructions or power generation plan curves from the dispatching master station, adopts a progressive processing algorithm for phased adjustment, switches modes based on communication status, and receives data transmitted by the data acquisition module. Communication module, used for remote secure data transmission and vertical boundary security protection; The network security monitoring module collects security events and status data of servers, network devices and security equipment within the station and uploads it to the dispatching master station; The optical power prediction and transmission module obtains distributed photovoltaic power prediction data, ground cloud maps and meteorological data, and transmits them to the dispatching master station via the dispatching data network or wireless private network; The electric energy meter data transmission module reads the metering data of the electric energy meter at the power plant or booster station through the RS485 serial port and uploads it to the dispatching master station; The automatic power generation control module is electrically connected to the optical power prediction and transmission module and the electric energy meter data transmission module respectively, and the communication module is electrically connected to the data acquisition and monitoring module, the optical power prediction and transmission module, the electric energy meter data transmission module and the network security monitoring module respectively.

2. The integrated solar-storage-charging smart energy management system according to claim 1, characterized in that: The data acquisition and monitoring module includes a data acquisition unit for the operating data of the power plant, booster station and reactive compensation device, a data processing unit for processing the collected data, and a control and adjustment unit for ensuring safe and reliable control operations. The data acquisition unit, data processing unit and control and adjustment unit are connected in sequence.

3. The integrated solar-storage-charging smart energy management system according to claim 2 is characterized by: The data processing unit uses a multi-core microprocessor to check the validity of the collected data, and performs multi-source fusion processing through a multi-source data fusion algorithm to fuse the electricity meter measurement data and optical power prediction data. The multi-source fusion processing includes data filtering, zero drift processing, limit checking and dead zone setting.

4. The integrated solar-storage-charging smart energy management system according to claim 2 is characterized by: The control and adjustment unit includes circuit breaker opening / closing, transformer tap adjustment, set value control, active power adjustment control, reactive power compensation device switching and adjustment, generates control instructions based on processed data, such as inverter power adjustment and reactive power compensation switching, and performs safety checks before executing the instructions.

5. The integrated solar-storage-charging smart energy management system according to claim 4 is characterized by: The data acquisition module also includes a data management unit, which is used for event sequence recording, accidents and alarms, historical data management, data calculation and system time synchronization.

6. The integrated solar-storage-charging smart energy management system according to claim 5 is characterized by: Intelligent allocation strategies include equal power factor allocation, similar adjustment margin allocation, and proportional power allocation. Equal power factor allocation proportionally allocates active power regulation targets based on the rated capacity and current power factor of each inverter, ensuring that the power factor of the entire station remains stable within a reasonable range. Similar adjustment margin allocation is to prioritize the adjustment of inverters with large current power margin to avoid overloading of some equipment; The power proportional distribution distributes the total regulation amount according to the rated power ratio of the inverter to ensure the power balance of the entire station.

7. The integrated solar-storage-charging smart energy management system according to claim 6 is characterized by: The communication module includes an RJ45 Ethernet interface, an RS485 communication interface and a redundant device. The RJ45 Ethernet interface and the RS485 communication interface are both connected to the redundant device, and the redundant device adopts a dual CPU module.

8. The integrated solar-storage-charging smart energy management system according to claim 7, characterized in that: The process of collecting security events and status data by the network security monitoring module is as follows: A1. Obtain device status information through the Simple Network Management Protocol, receive log data using the Syslog protocol, and connect to the security system through the API interface to collect security events; A2. Pre-process the acquired security events and status data; A3. Transmit the processed data to the dispatching master station via an encrypted wireless private network.

9. The integrated solar-storage-charging smart energy management system according to claim 8, characterized in that: The dispatching data network includes the collection of short-term power forecast data and the acquisition of ground-based cloud maps and meteorological data. Short-term power forecast data collection relies on the long-term accumulation of historical power generation data collected by distributed photovoltaic power stations. This historical power generation data covers power generation information in different seasons and weather conditions. At the same time, meteorological models are used in combination with real-time meteorological data for comprehensive analysis to obtain relatively accurate short-term power forecast data. Ground-based cloud maps and meteorological data are obtained by capturing the distribution and changes of clouds in the sky in real time through ground-based cloud map photovoltaic resource monitoring devices. At the same time, various meteorological sensors continuously collect real-time meteorological data of radiation illumination, temperature, and wind speed. Real-time meteorological data is not only used to monitor the current power generation environment in real time, but also serves as an important correction factor for optimizing and adjusting the power prediction model.

10. The photovoltaic, storage and charging integrated smart energy management system according to any one of claims 1 to 9, characterized in that: It also includes a human-computer interaction module for displaying the system operation status, equipment parameters, accident alarm screen and trend curve in real time. The human-computer interaction module interacts with the data acquisition and monitoring module, automatic power generation control module, communication module, network security monitoring module, optical power prediction and transmission module and electricity meter data transmission module respectively.

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