Optical storage charging and discharging integrated controller method and system

Abstract

The invention discloses an optical storage charging and discharging integrated controller method and system, and the method comprises the steps: obtaining the operation parameters and instructions of a micro-grid, constructing a factor coupling model according to the operation parameters and instructions of the micro-grid, and generating an optimization control strategy based on the operation targets of the micro-grid in a plurality of scenes; constructing a micro-grid autonomous operation energy balance model based on the optimization control strategy, and constructing a micro-grid source grid load storage scheduling energy balance strategy by using a droop control method; designing an intelligent algorithm lightweight technology and a local control strategy according to the energy balance model and the energy balance strategy, wherein the local control strategy comprises voltage out-of-limit control and over-capacitance control; and designing an optical storage charging and discharging integrated controller based on an internal bus according to an intelligent algorithm lightweight technology and a local control strategy, performing energy monitoring, formulating an energy balance strategy, and realizing source network load storage energy monitoring and balance autonomy.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control instruments, and in particular to a photovoltaic storage charging and discharging integrated controller method and system. Background Art

[0002] In the context of the new power grid, it is of great significance to study the integrated controller of photovoltaic storage charging and discharging. With the transformation of the global energy structure and the rapid development of renewable energy, the power grid system is facing unprecedented challenges and opportunities. As a key technology connecting solar power generation, energy storage system and electric vehicle charging station, the integrated controller of photovoltaic storage charging and discharging has a far-reaching impact on promoting the efficient use of energy, improving the stability and reliability of the power grid, promoting the popularization of electric vehicles and achieving sustainable development of energy.

[0003] However, there are still some technical problems in the existing photovoltaic storage charging and discharging technology. The construction of the photovoltaic storage charging and discharging integrated controller requires the integration of photovoltaic power generation, energy storage system and charging facilities, which leads to high initial investment costs. According to relevant research, the investment payback period of a 6-parking charging station is about 5 to 6 years. In some cases, the simple charging and discharging mode of low-cost charging and high-cost discharging cannot quickly respond to the changing load power, resulting in insufficient energy storage utilization. Although the energy storage control strategy based on the particle swarm algorithm can solve the load tracking problem and obtain the local optimal solution, it cannot achieve the maximum utilization of energy storage. At the same time, the safety of energy storage batteries is an issue that the photovoltaic storage charging and discharging integrated controller needs to focus on. In addition, the coordinated scheduling of charging, discharging and energy storage lacks rationality: in reality, it is not easy to adjust the energy structure of the power grid, and the relationship and law between the distribution of photovoltaic energy and the charging station area are not easy to control. With the increasing scale of automobile charging stations, the energy storage load continues to increase. Due to the obvious differences in photovoltaic power generation characteristics in different regions, the capacity configuration of photovoltaic charging stations and other aspects need to be optimized and scheduled. There are also optimization problems in charging and discharging strategies: In order to improve the economic benefits of photovoltaic storage charging stations and reduce carbon dioxide emissions, effective charging and discharging strategies need to be proposed. This involves real-time scheduling and optimization of photovoltaic power generation, energy storage systems and charging needs to achieve the goals of minimizing carbon emissions and minimizing operating costs. Finally, the technical maturity and reliability need to be improved. As an emerging technology, the technical maturity and reliability of the photovoltaic storage charging and discharging integrated controller need to be further improved. Continuous technological innovation and practical application are needed to solve the current problems and improve the overall performance and stability of the system. The photovoltaic storage charging and discharging integrated controller still faces many challenges in technological development. It is necessary to promote its widespread application and healthy development in the context of the new power grid through technological innovation, cost reduction, safety improvement and optimized scheduling. Summary of the invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a photovoltaic storage charging and discharging integrated controller method and system to solve the problem that the simple low-price charging and high-price discharging charging and discharging mode cannot quickly respond to changing load power, resulting in insufficient energy storage utilization, the existing technology cannot achieve the maximum utilization of energy storage, and the coordinated scheduling of charging, discharging and energy storage lacks rationality.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a photovoltaic storage charging and discharging integrated controller method, comprising:

[0008] Acquire microgrid operating parameters and instructions, construct a factor coupling model according to the microgrid operating parameters and instructions, and generate an optimization control strategy based on the microgrid operating objectives in various scenarios;

[0009] Based on the optimization control strategy, an energy balance model for autonomous operation of a microgrid is constructed, and a droop control method is used to construct an energy balance strategy for source-grid-load-storage scheduling of a microgrid;

[0010] Design intelligent algorithm lightweight technology and local control strategy based on energy balance model and energy balance strategy, the local control strategy includes voltage over-limit control and over-capacity control;

[0011] According to the intelligent algorithm lightweight technology and local control strategy, an integrated photovoltaic storage charging and discharging controller based on the internal bus is designed to carry out energy monitoring.

[0012] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method described in the present invention, the factor coupling model is constructed according to the microgrid operating parameters and instructions, including:

[0013] The uncertainty mathematical programming theory is introduced to describe and simulate the main uncertain factors with corresponding random variables, and a coupling model of factors affecting the stability of the microgrid is constructed.

[0014] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method described in the present invention, the optimization control strategy includes:

[0015] Based on the droop control strategy, the droop relationship between active power and frequency and the droop relationship between reactive power and frequency are controlled to control the power of distributed generation in the microgrid and adjust the voltage and frequency;

[0016] Information is exchanged between adjacent distributed generation through the microgrid control module, and the frequency and voltage compensation of the module is obtained based on the finite time consistency algorithm to eliminate frequency and voltage deviations. The droop coefficient of each distributed generation is adjusted according to the operating objectives under different working scenarios and transmitted to the direct control layer.

[0017] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method described in the present invention, the voltage over-limit control includes:

[0018] Obtaining a detection voltage of the integrated photovoltaic storage charging and discharging controller, and making a first judgment on the detection voltage;

[0019] When the detection voltage is less than the first threshold, it is in the continuous monitoring interval;

[0020] When the detected voltage is greater than or equal to the first threshold and less than the second threshold, and the duration exceeds the limit and is in the flexible control interval, the voltage limit time is reported, the photovoltaic inverter is flexibly controlled, and a flexible control event is reported;

[0021] If the detected voltage is greater than or equal to the first threshold and the number of regulation times is less than or equal to the set number of times, the photovoltaic inverter continues to be flexibly regulated, otherwise a second judgment is performed.

[0022] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method of the present invention, the second judgment includes:

[0023] When the detection voltage is less than the first threshold and the number of adjustments is less than the set number, a third judgment is performed;

[0024] Otherwise, the control lockout time is reported, and if the lockout duration reaches the first set duration, the lockout is released and the first judgment is performed again;

[0025] The third judgment includes detecting that the voltage is less than the first threshold and the duration reaches a second set time, restoring the maximum output of the photovoltaic inverter or controlling the closing of the switch, and reporting the control event to the acquisition master station.

[0026] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method of the present invention, it also includes:

[0027] When the detected voltage is greater than the second threshold and the over-limit duration is greater than or equal to the fourth duration, the voltage over-limit time is reported, the circuit breaker is controlled to trip, a rigid control event is reported, a third judgment is made, and the control event is reported to the acquisition master station.

[0028] As a preferred solution of the photovoltaic storage charging and discharging integrated controller method described in the present invention, the overcapacity control includes:

[0029] When the photovoltaic grid-connected power is greater than the over-capacity control threshold and the duration is greater than or equal to the third set time, the photovoltaic inverter output is adjusted to make the photovoltaic grid-connected power lower than the reported capacity, and the photovoltaic storage charging and discharging integrated controller reports a flexible control event.

[0030] In a second aspect, the present invention provides a photovoltaic storage charging and discharging integrated controller system, comprising:

[0031] A model building module, used to obtain microgrid operating parameters and instructions, build a factor coupling model according to the microgrid operating parameters and instructions, and generate an optimization control strategy based on the microgrid operating goals in various scenarios;

[0032] A strategy building module is used to build a microgrid autonomous operation energy balance model based on the optimization control strategy, and to build a microgrid source-grid-load-storage scheduling energy balance strategy using a droop control method;

[0033] A technology design module, for designing intelligent algorithm lightweight technology and local control strategy according to an energy balance model and energy balance strategy, wherein the local control strategy includes voltage over-limit control and over-capacity control;

[0034] The controller module is used to design an integrated photovoltaic storage and charging and discharging controller based on an internal bus according to the intelligent algorithm lightweight technology and local control strategy to perform energy monitoring.

[0035] In a third aspect, the present invention provides a computing device, comprising:

[0036] Memory and processor;

[0037] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the photovoltaic storage charging and discharging integrated controller method are implemented.

[0038] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the photovoltaic storage charging and discharging integrated controller method.

[0039] Compared with the prior art, the present invention has the following beneficial effects: the present invention configures grid-type energy storage, studies its effectiveness in improving the grid-connected stability of new energy microgrids, realizes voltage compensation and inertia support under load fluctuations and power oscillations of microgrids, constructs a coupling model of uncertainty factors affecting the stability of microgrids, studies the operation objectives and control models of microgrids in various scenarios, generates optimized control strategies to maintain the source-load balance and power stability of microgrids, designs lightweight intelligent algorithm technology, and the terminal can have built-in local control strategies to achieve optimal energy management, improve the response speed and operation efficiency of the system, and adopts internal real-time bus broadband technology to achieve high-bandwidth, deterministic, strong real-time, and highly reliable data transmission of the terminal, thereby improving the data transmission performance of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0041] Figure 1 The figure is a schematic diagram of the overall process logic of a photovoltaic storage charging and discharging integrated controller method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0043] Example 1

[0044] Reference Figure 1 , is an embodiment of the present invention, and provides a photovoltaic storage charging and discharging integrated controller method, comprising:

[0045] S100: Acquire microgrid operation parameters and instructions, build a factor coupling model according to the microgrid operation parameters and instructions, and generate an optimization control strategy based on the microgrid operation goals in various scenarios;

[0046] S200: constructing a microgrid autonomous operation energy balance model based on the optimization control strategy, and constructing a microgrid source-grid-load-storage scheduling energy balance strategy using the droop control method;

[0047] Specifically, based on factors such as real-time power balance, mutual sharing, and rotating reserve capacity of microgrids, and considering the natural properties of strong fluctuations in new energy output and the uncertainty of load access, the energy balance constraint of microgrids is:

[0048] The electrical busbar balance equation is expressed as:

[0049]

[0050] The flue gas busbar balance equation is expressed as:

[0051]

[0052] The thermal busbar balance equation is expressed as:

[0053]

[0054] The cold busbar balance equation is expressed as:

[0055]

[0056] Among them, PV is photovoltaic, WT is wind power, ES is electric energy storage, CS is cold storage device, EC is electric refrigeration, AC is absorption chiller, GB is gas boiler, PGU is gas unit, HR is waste heat, HS is heat storage device, F is gas calorific value, P is electric power, Q is cold and hot power, CL and HL are cold and hot loads respectively.

[0057] Specifically, an energy balance model for autonomous operation of microgrids is constructed. Based on the day-ahead and intraday cross-time dispatch cycle of microgrid sources, grids, loads and storages, the economic cost, carbon emissions and dispatch flexibility of autonomous operation of microgrids are considered, and a droop control method is adopted to construct an energy balance strategy for microgrid sources, grids, loads and storages dispatch under differentiated demand response strategies.

[0058] Adjustable loads are heterogeneous in terms of load type, physical parameters, load response, etc. The system after the aggregation of these heterogeneous loads presents mixed characteristics such as nonlinearity, randomness, and time-varying. The parameter identification method of heterogeneous load clusters in microgrids is studied. Taking heterogeneous clusters as the identification objects, the heterogeneous clusters are identified according to the physical parameters of the clusters using deep learning methods such as neural networks. Based on the existing homogeneous aggregation model, a control-oriented aggregation model for heterogeneous clusters is constructed to ensure the stability and controllability of heterogeneous clusters.

[0059] Based on historical energy consumption data, an energy demand forecasting and evaluation method and an energy balancing strategy are constructed which take into account the energy consumption period, energy quality and energy consumption frequency of the microgrid. The entropy weight method is used to evaluate the energy consumption strategy considering factors such as the energy consumption environment. According to the evaluation results, the output of wind and solar power sources is changed preferentially to maintain the power balance of the system, and the energy storage and controllable load are assisted to adjust the energy consumption strategy.

[0060] It should be noted that, by comprehensively considering the different operation scenarios of the microgrid, the uncertainty mathematical programming theory is introduced to construct the coupling model of uncertainty factors of the microgrid, and the influence of uncertainty factors is quantitatively analyzed, so as to comprehensively and detailedly analyze the control objectives in different scenarios of the microgrid.

[0061] S300: Design intelligent algorithm lightweight technology and local control strategy based on energy balance model and energy balance strategy. Local control strategy includes voltage over-limit control and over-capacity control.

[0062] S400: Based on the intelligent algorithm lightweight technology and local control strategy, an integrated photovoltaic storage charging and discharging controller based on the internal bus is designed for energy monitoring.

[0063] Specifically, the functional requirements of new energy microgrids for integrated photovoltaic, storage, charging and discharging controllers and the technical characteristics of the ATUBUS bus are studied, and an integrated photovoltaic, storage, charging and discharging controller based on the ATUBUS bus is designed. The stability control strategy library of new energy microgrids under scenarios such as system flexibility adjustment and distributed energy consumption is studied, and the integrated photovoltaic, storage, charging and discharging controller based on the ATUBUS bus is studied. Local stability control and energy management control strategies are formulated according to business needs.

[0064] The internal bus is a high-speed field bus using two-wire non-bridge media, with a bus data bandwidth of 100Mbps, a maximum transmission distance of 500 meters, a minimum cycle period of 8 microseconds, a maximum number of nodes of 256, and a synchronization accuracy of no less than 10ns. At the same time, the internal bus combines the advantages of Profibus, CAN, Ethernet IP, Profinet and other buses, and uses twisted pair polarity-free transmission. It has the characteristics of high bandwidth, strong real-time capability, long transmission distance, simple wiring and installation, etc. It is used in the integrated controller of optical storage and charging and discharging, and can realize high-speed and high-reliability data collection.

[0065] It should be noted that the photovoltaic storage charging and discharging integrated controller communicates with the microgrid energy management system upstream and with various energy measurement and control terminals (or systems) downstream, and is used for the collection, conversion, and upload of various energy consumption data, as well as the reception and issuance of control strategies. After receiving the upper-level load control command, according to the user's industry classification and load composition type, considering the power balance and operation safety of the power grid, facing the scenarios of system flexibility adjustment, distributed energy consumption, and the monitoring and control principles of user load access in rounds, through artificial intelligence algorithms and energy balance research results, a local stable control strategy library and flexible control strategy are formulated to reasonably control and adjust the power load, respond to the upper-level load adjustment command in real time and accurately, and realize flexible interactive adjustment with user participation.

[0066] In the embodiment of the present application, the above step S100 includes the following sub-step A1:

[0067] In A1: introduce uncertainty mathematical programming theory, describe and simulate the main uncertain factors with corresponding random variables, and build a coupling model of factors affecting the stability of microgrid;

[0068] Specifically, first, we investigated the typical equipment architecture of new energy microgrids, and based on the EEMD-LSTM empirical mode decomposition long short-term memory network method, we built an ultra-short-term power prediction model for new energy power generation systems to address the volatility and intermittency of new energy in microgrids.

[0069] Secondly, the typical problems of low rotational inertia, easy frequency mutation, and weak load inertia frequency support capacity of microgrids with the participation of high-energy devices are classified and aggregated, and the feasibility of grid-type energy storage systems to smooth load fluctuations and maintain the frequency and voltage stability of microgrids is analyzed;

[0070] Next, the circuit commutation analysis of the grid-type energy storage PCS is carried out and its topological characteristics are analyzed. The mathematical model of the grid-type energy storage PCS is established, and the effectiveness of configuring the grid-type energy storage to improve the grid-connected stability of the new energy microgrid is analyzed.

[0071] Finally, the mainstream grid-connected energy storage PCS control technologies such as droop control, voltage-type VSG, and matching control are studied, and the grid-connected energy storage PCS control technology considering renewable energy power generation is studied to achieve voltage compensation and inertia support under microgrid load fluctuations and power oscillations.

[0072] In the embodiment of the present application, after completing step A1, the above step S100 may further include the following sub-steps A2-A3;

[0073] In A2: based on the droop control strategy, the droop relationship between active power and frequency and the droop relationship between reactive power and frequency are controlled to control the power of distributed generation in the microgrid and adjust the voltage and frequency;

[0074] In A3: Information is exchanged between adjacent distributed generation through the microgrid control module, and the frequency and voltage compensation of the module is obtained based on the finite time consistency algorithm to eliminate the frequency and voltage deviations. The droop coefficient of each distributed generation is adjusted according to the operating objectives under different working scenarios and transmitted to the direct control layer.

[0075] Specifically, first, establish the energy interaction architecture between the microgrid and the local load and the external power grid, study data processing and storage technologies such as MySQL cluster, OSS object storage, and API open interface, deploy a microgrid control system architecture based on device layer-terminal layer-network layer-data layer-decision layer, obtain and transmit microgrid operating parameters and instructions, and realize data collection and real-time communication of various departments of the microgrid;

[0076] Next, the uncertainty mathematical programming theory is introduced to describe and simulate the main uncertain factors with corresponding random variables, build a coupling model of factors affecting the stability of the microgrid, and analyze the operation objectives of the microgrid under different working scenarios;

[0077] Finally, based on the droop control strategy, P, f and Q, V are controlled to achieve power control and voltage and frequency regulation of the microgrid DG. The microgrid control system exchanges information with adjacent DGs, obtains the frequency and voltage compensation of the system based on the finite time consistency algorithm, eliminates frequency and voltage deviations, and adjusts the droop coefficient of each DG according to the operating objectives in different working scenarios, and transmits it to the direct control layer.

[0078] It should be noted that a coupling model of uncertain factors that affect the stability of the microgrid is constructed, and the operation objectives and control models of the microgrid under scenarios such as new energy fluctuations, system flexibility regulation, and distributed energy consumption are studied; power distribution and voltage and frequency adjustment are carried out among distributed power sources in the microgrid through droop control, and based on the operation objectives of the microgrid system in different scenarios, an optimized control strategy is further generated to maintain the source-load balance and power stability of the microgrid, and to ensure that the power supply quality of the microgrid system meets the power standard requirements.

[0079] In the embodiment of the present application, the voltage over-limit control in the above step S300 includes the following sub-steps B1-B4;

[0080] In B1: obtaining the detection voltage of the photovoltaic storage charging and discharging integrated controller, and performing a first judgment on the detection voltage;

[0081] In B2: when the detection voltage is less than the first threshold, it is in the continuous monitoring interval;

[0082] In B3: when the detected voltage is greater than or equal to the first threshold and less than the second threshold, and the duration exceeds the limit and is in the flexible control interval, the voltage limit time is reported, the photovoltaic inverter is flexibly controlled, and the flexible control event is reported;

[0083] In B4: if the detection voltage is greater than or equal to the first threshold and the number of regulation times is less than or equal to the set number of times, the photovoltaic inverter continues to be flexibly regulated, otherwise the second judgment is performed.

[0084] In the embodiment of the present application, after completing steps B1-B4, the above step S300 may further include the following sub-steps B5-B7:

[0085] In B5: when the detection voltage is less than the first threshold and the number of regulation times is less than the set number of times, a third judgment is performed;

[0086] In B6: Otherwise, the control lockout time is reported, and if the lockout time reaches the first set time, the lockout is released and the first judgment is performed again;

[0087] In B7: the third judgment includes detecting that the voltage is less than the first threshold and the duration reaches a second set time, restoring the maximum output of the photovoltaic inverter or controlling the switch to close, and reporting the control event to the data collection master station.

[0088] In the embodiment of the present application, after completing steps B5-B7, the above step S300 may further include the following sub-step B8;

[0089] In B8: When the detected voltage is greater than the second threshold and the over-limit duration is greater than or equal to the fourth duration, the voltage over-limit time is reported, the circuit breaker is controlled to trip, and a rigid control event is reported. A third judgment is performed and the control event is reported to the acquisition master station.

[0090] Specifically, the integrated photovoltaic storage charging and discharging controller receives the 4 groups of control parameters from the first threshold to the fourth threshold, the first duration to the fourth duration issued by the acquisition master station, the setting number can be 5, the first setting duration is 30 minutes, the second setting duration is 1 minute, and the parameters can be set;

[0091] Judgment condition 1 is that the first threshold is 255V and the first duration is 60min;

[0092] Judgment condition 2 is that the second threshold is 265V and the second duration is 30min;

[0093] Judgment condition 3 is that the third threshold is 275V and the third duration is 30s;

[0094] Judgment condition 4 is that the fourth threshold is 285V and the fourth duration is 2s.

[0095] When the photovoltaic storage charging and discharging integrated controller monitors that the property boundary voltage meets judgment condition 1, judgment condition 2 or judgment condition 3, it collects the electric energy meter data of the photovoltaic grid-connected point and regulates the photovoltaic inverter of the branch with the highest voltage. The photovoltaic storage charging and discharging integrated controller adjusts the output of the photovoltaic inverter by issuing active power and reactive power control instructions to make the property boundary voltage less than the first threshold, and reports the control event to the collection master station. The control method should adopt limit control and proportional control.

[0096] When the photovoltaic storage charging and discharging integrated controller detects that the voltage at the property boundary point meets judgment condition 4, it controls the photovoltaic dedicated circuit breaker at the photovoltaic grid-connected point to trip and reports the control event to the data collection master station;

[0097] Each time a control is performed, the voltage value of the property rights demarcation point is monitored, and if the voltage is greater than or equal to the first threshold, the control is continued;

[0098] When the integrated photovoltaic storage charging and discharging controller detects that the voltage at the property boundary point is less than the first threshold and lasts for 60 minutes, it will issue active power and reactive power control instructions to restore the maximum output of the photovoltaic inverter and report the control event to the collection master station.

[0099] It should be noted that by setting specific voltage thresholds and durations, the controller can respond to voltage changes in a timely manner, take corresponding regulatory measures, and effectively maintain the stability of the grid voltage. Through real-time monitoring and control of voltage, it can prevent damage or accidents to grid equipment caused by excessive voltage, and improve the safety of the grid. By adjusting the output of the photovoltaic inverter, the controller can optimize the operation of the photovoltaic power generation system, improve power generation efficiency, and reduce energy waste.

[0100] In the embodiment of the present application, the over-capacity control in the above step S300 includes the following sub-steps C1-C4:

[0101] In C1: when the photovoltaic grid-connected power is greater than the over-capacity control threshold and the duration is greater than or equal to the third set duration, the photovoltaic inverter output is adjusted to make the photovoltaic grid-connected power lower than the reported capacity, and the photovoltaic storage charging and discharging integrated controller reports a flexible control event.

[0102] Specifically, the overcapacity control threshold is the installed capacity of energy storage of local users in the regional power grid, i.e., preventing storage overcapacity;

[0103] The integrated photovoltaic storage charging and discharging controller receives the user's reported capacity parameters sent by the collection master station as the over-capacity control threshold (the default duration is 1 minute). The threshold and time parameters can be set. When the integrated photovoltaic storage charging and discharging controller detects that the photovoltaic grid-connected power has reached the over-capacity control threshold, it reports the over-capacity grid-connected event to the collection master station; the integrated photovoltaic storage charging and discharging controller sends active power and reactive power control instructions to adjust the photovoltaic inverter output so that the photovoltaic grid-connected power is lower than the reported capacity, and reports the control event to the collection master station. The control method should adopt limit control.

[0104] When it is monitored that the power quality of the microgrid system does not meet the grid connection requirements or when the large grid fails, the microgrid system and the grid are switched on and off. Energy optimization operation and control strategy of new energy microgrids The new energy microgrid system has two operation modes: island operation and grid-connected operation. Island operation is a mode in which the microgrid is separated from the large grid and operates independently when the power quality does not meet the requirements or the grid fails. The independent island operation capability can improve the power supply reliability of the microgrid. Grid-connected operation is that the microgrid is connected to the large grid as a single controlled source. The large grid can supplement the insufficient power generation of the microgrid or the microgrid can send the surplus power to the large grid. In addition, the control strategy can be used to seamlessly switch between the two operation modes. The integrated photovoltaic storage charging and discharging controller has the ability to monitor the power quality of the microgrid system. In the grid-connected operation state, when it is monitored that the power quality of the microgrid system does not meet the grid connection requirements, it will issue a grid-connected command to the system; at the same time, when the large grid fails, it will also issue a grid-connected command.

[0105] It should be noted that when the microgrid is in normal operation, the integrated photovoltaic storage charging and discharging controller takes maximizing user benefits as the principle, and formulates different coordinated control strategies according to the energy requirements of different application scenarios such as photovoltaic / wind power output, energy storage equipment characteristics, charging piles, AC / DC microgrids, and energy consumption of equipment within the microgrid. By collecting and analyzing historical data, the energy use and storage rules are mastered, and intelligent control is realized by combining machine learning, artificial intelligence and other technologies to perform intelligent switching between different energy storage devices, realize intelligent energy scheduling and optimal configuration, and achieve efficient, stable and reliable energy supply and use.

[0106] The above is a schematic scheme of a method for integrated photoelectric storage charging and discharging controller of this embodiment. It should be noted that the technical scheme of the system of the integrated photoelectric storage charging and discharging controller and the technical scheme of the integrated photoelectric storage charging and discharging controller method described above belong to the same concept. For details not described in detail in the technical scheme of the integrated photoelectric storage charging and discharging controller system of this embodiment, please refer to the description of the technical scheme of the integrated photoelectric storage charging and discharging controller method described above.

[0107] The photovoltaic storage charging and discharging integrated controller system in this embodiment includes:

[0108] A model building module, used to obtain microgrid operating parameters and instructions, build a factor coupling model according to the microgrid operating parameters and instructions, and generate an optimization control strategy based on the microgrid operating goals in various scenarios;

[0109] A strategy building module is used to build a microgrid autonomous operation energy balance model based on the optimization control strategy, and to build a microgrid source-grid-load-storage scheduling energy balance strategy using a droop control method;

[0110] A technology design module, for designing intelligent algorithm lightweight technology and local control strategy according to an energy balance model and energy balance strategy, wherein the local control strategy includes voltage over-limit control and over-capacity control;

[0111] The controller module is used to design an integrated photovoltaic storage and charging and discharging controller based on an internal bus according to the intelligent algorithm lightweight technology and local control strategy to perform energy monitoring.

[0112] This embodiment further provides a computing device, which is applicable to the case of a photovoltaic storage charging and discharging integrated controller, including:

[0113] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the method for realizing the integrated controller of photovoltaic storage charging and discharging as proposed in the above embodiment.

[0114] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for realizing an integrated photovoltaic storage charging and discharging controller as proposed in the above embodiment is implemented.

[0115] The storage medium proposed in this embodiment and the method for realizing an integrated photo-storage charging and discharging controller proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0116] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0117] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A photovoltaic storage charging and discharging integrated controller method, characterized in that: include: Acquire microgrid operating parameters and instructions, construct a factor coupling model according to the microgrid operating parameters and instructions, and generate an optimization control strategy based on the microgrid operating objectives in various scenarios; Based on the optimization control strategy, an energy balance model for autonomous operation of a microgrid is constructed, and a droop control method is used to construct an energy balance strategy for source-grid-load-storage scheduling of a microgrid; Design intelligent algorithm lightweight technology and local control strategy based on energy balance model and energy balance strategy, the local control strategy includes voltage over-limit control and over-capacity control; According to the intelligent algorithm lightweight technology and local control strategy, an integrated photovoltaic storage charging and discharging controller based on the internal bus is designed to carry out energy monitoring.

2. The photovoltaic storage charging and discharging integrated controller method according to claim 1, characterized in that: The factor coupling model constructed according to the microgrid operation parameters and instructions includes: The uncertainty mathematical programming theory is introduced to describe and simulate the main uncertain factors with corresponding random variables, and a coupling model of factors affecting the stability of the microgrid is constructed.

3. The photovoltaic storage charging and discharging integrated controller method according to claim 2, characterized in that: The optimized control strategies include: Based on the droop control strategy, the droop relationship between active power and frequency and the droop relationship between reactive power and frequency are controlled to control the power of distributed generation in the microgrid and adjust the voltage and frequency; Information is exchanged between adjacent distributed generation through the microgrid control module, and the frequency and voltage compensation of the module is obtained based on the finite time consistency algorithm to eliminate frequency and voltage deviations. The droop coefficient of each distributed generation is adjusted according to the operating objectives under different working scenarios and transmitted to the direct control layer.

4. The integrated photovoltaic storage charging and discharging controller method according to claim 3, characterized in that: Voltage over-limit control includes: Obtaining a detection voltage of the integrated photovoltaic storage charging and discharging controller, and making a first judgment on the detection voltage; When the detection voltage is less than the first threshold, it is in the continuous monitoring interval; When the detected voltage is greater than or equal to the first threshold and less than the second threshold, and the duration exceeds the limit and is in the flexible control interval, the voltage limit time is reported, the photovoltaic inverter is flexibly controlled, and a flexible control event is reported; If the detected voltage is greater than or equal to the first threshold and the number of regulation times is less than or equal to the set number of times, the photovoltaic inverter continues to be flexibly regulated, otherwise a second judgment is performed.

5. The photovoltaic storage charging and discharging integrated controller method as claimed in claim 4, characterized in that: The second judgment includes: When the detection voltage is less than the first threshold and the number of adjustments is less than the set number, a third judgment is performed; Otherwise, the control lockout time is reported, and if the lockout duration reaches the first set duration, the lockout is released and the first judgment is performed again; The third judgment includes detecting that the voltage is less than the first threshold and the duration reaches a second set time, restoring the maximum output of the photovoltaic inverter or controlling the closing of the switch, and reporting the control event to the acquisition master station.

6. The photovoltaic storage charging and discharging integrated controller method according to claim 5, characterized in that: Also includes: When the detected voltage is greater than the second threshold and the over-limit duration is greater than or equal to the fourth duration, the voltage over-limit time is reported, the circuit breaker is controlled to trip, a rigid control event is reported, a third judgment is made, and the control event is reported to the acquisition master station.

7. The photovoltaic storage charging and discharging integrated controller method according to claim 5 or 6, characterized in that: Over capacity control includes: When the photovoltaic grid-connected power is greater than the over-capacity control threshold and the duration is greater than or equal to the third set time, the photovoltaic inverter output is adjusted to make the photovoltaic grid-connected power lower than the reported capacity, and the photovoltaic storage charging and discharging integrated controller reports a flexible control event.

8. A system using the photovoltaic storage charging and discharging integrated controller method as described in any one of claims 1 to 7, characterized in that: include: A model building module, used to obtain microgrid operating parameters and instructions, build a factor coupling model according to the microgrid operating parameters and instructions, and generate an optimization control strategy based on the microgrid operating goals in various scenarios; A strategy building module is used to build a microgrid autonomous operation energy balance model based on the optimization control strategy, and to build a microgrid source-grid-load-storage scheduling energy balance strategy using a droop control method; A technology design module, for designing intelligent algorithm lightweight technology and local control strategy according to an energy balance model and energy balance strategy, wherein the local control strategy includes voltage over-limit control and over-capacity control; The controller module is used to design an integrated photovoltaic storage and charging and discharging controller based on an internal bus according to the intelligent algorithm lightweight technology and local control strategy to perform energy monitoring.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the photovoltaic storage charging and discharging integrated controller method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the photovoltaic storage charging and discharging integrated controller method as described in any one of claims 1 to 7.

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