A power quality optimization control system applied to a distributed photovoltaic system

Abstract

The application provides a power quality optimization control system applied to a distributed photovoltaic system, and the system comprises photovoltaic power generation and energy storage units, each of which is composed of a power generation module, an inverter module, an energy storage module, an electric energy evaluation module and a control module. The power generation module converts solar energy into direct current, the inverter module converts the direct current into alternating current, and the energy storage module is used for storing excess electric energy. The electric energy evaluation module collects electric energy quality related data through alpha collection submodules and beta collection submodules, performs electric energy quality analysis, and cross- verifies the electric energy quality results of each unit through a decentralized electric energy quality evaluation network. The electric energy quality evaluation network adopts a distributed consensus mechanism to ensure the accuracy of the electric energy evaluation results and further control the access authority of the photovoltaic power generation and energy storage units to the public power grid. In addition, the system has a double evaluation process, which ensures the consistency and reliability of the evaluation results.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of digital information technology, and specifically relates to an electric energy quality optimization control system applied to a distributed photovoltaic system. BACKGROUND

[0002] In recent years, distributed photovoltaic systems have been widely used worldwide due to their high flexibility, easy installation and other advantages. Photovoltaic power generation, as a clean and renewable energy source, plays an important role in alleviating energy crisis and reducing environmental pollution. However, during the grid-connected operation of distributed photovoltaic systems, electric energy quality problems have gradually become a key challenge that needs to be addressed. The output electric energy of photovoltaic power generation systems may have voltage fluctuations, frequency deviations, harmonic pollution and low power factors, and these substandard electric energies not only affect the power generation efficiency of the system, but also may pose potential risks to grid equipment and load facilities.

[0003] Traditional electric energy quality monitoring methods mainly rely on centralized monitoring, which cannot meet the needs of real-time detection and optimization control of electric energy quality in distributed photovoltaic systems. In addition, centralized monitoring systems often face problems such as monitoring blind spots and data transmission delays, which cannot effectively guarantee the stability of photovoltaic systems and the safety of power grids. Therefore, there is an urgent need for an efficient and real-time response electric energy quality monitoring and optimization control system that can improve the electric energy quality management level of distributed photovoltaic systems, ensure that they do not have negative effects when connected to the grid, and at the same time guarantee the safety and stability of power grid operation.

[0004] After consulting relevant public technologies, the technical solution with publication number CN103199557A monitors and controls multiple control parameters of photovoltaic power generation components by using high-integration chips to achieve optimization management of independent photovoltaic power generation components during operation. The technical solution with publication number WO2012059061A1 proposes a high-voltage electric energy quality detection method, which detects high-voltage electric energy quality by using low-voltage current components to detect high-voltage electricity. The technical solution with publication number WO2014089900A1 proposes an electric energy quality disturbance type identification method based on a PQView data source, which uses the PQView data source as the source of the evaluation algorithm to improve the identification efficiency of electric energy disturbance types.

[0005] The above technical solutions all propose several methods for evaluating electric energy quality and related control systems, but for distributed photovoltaic power generation systems, since there are many points to be detected and the points are scattered, more effective optimization control methods need to be further proposed.

[0006] The foregoing discussion of the background art is intended only to facilitate an understanding of the present application. The discussion is not an acknowledgment or admission that any of the material referred to is part of the common general knowledge of those working in the field. SUMMARY

[0007] The purpose of the present application is to provide a power quality optimization control system applied to a distributed photovoltaic system, which comprises photovoltaic power generation and energy storage units, each of which is composed of a power generation module, an inverter module, an energy storage module, an electric energy evaluation module and a control module. The power generation module converts solar energy into direct current, the inverter module converts direct current into alternating current, and the energy storage module is used to store excess electric energy. The electric energy evaluation module collects electric energy quality related data through the alpha collection submodule and the beta collection submodule, performs electric energy quality analysis, and cross- validates the electric energy quality results of each unit through a decentralized electric energy quality evaluation network. The electric energy quality evaluation network adopts a distributed consensus mechanism to ensure the accuracy of the electric energy evaluation results and further control the access rights of the photovoltaic power generation and energy storage units to the public power grid. In addition, the system has a double evaluation process to ensure the consistency and reliability of the evaluation results.

[0008] The present application adopts the following technical solution: a power quality optimization control system applied to a distributed photovoltaic system, which comprises at least one photovoltaic power generation and energy storage unit; the photovoltaic power generation and energy storage unit comprises:

[0009] a power generation module for converting solar energy into direct current;

[0010] an inverter module for converting direct current generated by the power generation module into alternating current;

[0011] an energy storage module for storing excess electric energy;

[0012] an electric energy evaluation module, which collects and analyzes electric energy quality related indicators in the photovoltaic power generation and energy storage unit through an alpha collection submodule and a beta collection submodule;

[0013] The electric energy evaluation module is in communication connection with the electric energy evaluation modules of other photovoltaic power generation and energy storage units and forms a decentralized electric energy quality evaluation network; the electric energy quality evaluation network adopts a distributed consensus mechanism to cross-validate the electric energy quality evaluation results to ensure that the electric energy evaluation results of the electric energy evaluation modules of each photovoltaic power generation and energy storage unit are correct and available, and further control the access rights of the photovoltaic power generation and energy storage units to the public power grid.

[0014] Illustratively, the alpha collection submodule is arranged at the input end of the inverter module and is specially used to collect electric parameter data of direct current generated by the photovoltaic power generation module; the beta collection submodule is arranged at the output end of the inverter module and is specially used to collect electric parameter data of alternating current output by the inverter module.

[0015] Illustratively, the electric energy evaluation module comprises:

[0016] an evaluation unit configured to periodically calculate the power quality state of the system using a preset power quality evaluation algorithm and evaluate whether it meets the set threshold requirement;

[0017] a storage unit for storing historical power parameter data collected by the alpha collection submodule and the beta collection submodule, and evaluation data made by the evaluation unit on the historical power parameter data;

[0018] a communication unit configured to establish a decentralized data communication network with power evaluation modules of other photovoltaic power generation and energy storage units.

[0019] Exemplarily, a branch selector is further arranged between the inverter module and the energy storage module; the branch selector is used to control the flow direction of the inverter module output power and realize dynamic switching between the energy storage module, the grid line or the power load.

[0020] Exemplarily, the optimization control system includes a double evaluation process during operation; the double evaluation process includes the following steps:

[0021] The power evaluation module serves as a main detection module, periodically performs preliminary evaluation on the power quality of the photovoltaic power generation and energy storage unit based on a main evaluation period T1, and generates an alpha evaluation result by taking the collected sample data as alpha collection samples;

[0022] The main detection module periodically sends the alpha collection samples to at least two randomly selected power evaluation modules as supervision detection modules through a power quality evaluation network based on a secondary evaluation period T2; the selected power evaluation modules evaluate the power quality of the alpha collection samples and generate beta evaluation samples;

[0023] The main detection module sends the alpha evaluation result to at least one management node through the power quality evaluation network;

[0024] The at least two supervision detection modules send the beta evaluation samples to at least one management node selected by the main detection module;

[0025] The at least one management node responds to the alpha evaluation result and the beta evaluation result, calculates the deviation degree between the alpha evaluation result and the beta evaluation result, and performs consistency verification;

[0026] The management node feeds back the deviation degree to the main detection module; if the deviation exceeds a threshold value, the main detection module triggers the power transmission path control of the photovoltaic power generation and energy storage unit.

[0027] Exemplarily, the secondary evaluation period T2 is greater than the main evaluation period T1.

[0028] Exemplarily, the inverter module is a bidirectional inverter, and the output end of the energy storage module outputs electric energy to the inverter module according to the electric energy demand, and provides electric energy to the power grid or the load through the branch selector.

[0029] The present application has the following beneficial effects:

[0030] 1. The technical solution establishes a decentralized power quality evaluation network, distributes the power quality monitoring function of multiple photovoltaic power generation and energy storage units to each unit, and cross- verifies through a distributed consensus mechanism. This structure avoids the single point failure problem of traditional centralized monitoring systems, improves the reliability and fault tolerance of the system, and ensures the accuracy of the power quality evaluation results of each unit.

[0031] 2. The technical solution realizes self-checking and rechecking of power quality data through the double evaluation process of the main detection module and the supervision detection module, ensures the consistency and accuracy of the evaluation results, and if deviation is detected, the system will automatically trigger a consistency checking mechanism to further improve the accuracy of power quality monitoring and ensure that any abnormalities in system operation can be discovered and corrected in time.

[0032] 3. The technical solution realizes real-time collection and evaluation of power quality, and can quickly respond and dynamically adjust when the power quality of the photovoltaic power generation and energy storage unit is abnormal. For example, the system can automatically control the electric energy transmission path or adjust the working state of the inverter according to the evaluation results, so as to ensure that unqualified electric energy is not directly input into the power grid or load, thereby ensuring the stable operation of the power grid and the safety of the load equipment.

[0033] 4. The hardware and software parts of the optimization control system of the technical solution are designed in a modular manner, and the working modules, components of the hardware part, and instructions, parameters, algorithms of the software part can be conveniently replaced and / or upgraded in the later stage, thereby reducing the construction cost and maintenance cost of the system. BRIEF DESCRIPTION OF DRAWINGS

[0034] The present application can be further understood from the following description in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but the emphasis is placed on showing the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0035] BRIEF DESCRIPTION OF DRAWINGS: 1-photovoltaic power generation and energy storage unit; 10-power generation module; 20-electricity evaluation module; 22-α collection sub-module; 24-β collection sub-module; 30-inverter module; 40-energy storage module; 42-energy storage module management system; 44-energy storage unit; 50-electric load; 60-grid line; 70-branch selector; 80-control module; 200-main detection module; 210-supervision detection module; 220-management node; 500-computing architecture; 502-bus; 504-processor; 506-main memory; 508-read only memory; 510-storage device; 512-display; 514-input device; 516-cursor control device; 518-network device;

[0036] Figure 1 Architectural diagram of the optimization system described in the embodiments of the present application;

[0037] Figure 2 Architectural diagram of the power quality evaluation network described in the embodiments of the present application;

[0038] Figure 3 Flowchart of the double evaluation process described in the embodiments of the present application;

[0039] Figure 4 Detailed step diagram of the double evaluation process described in the embodiments of the present application;

[0040] Figure 5 Architectural diagram of the computer system used in the embodiments of the present application. DETAILED DESCRIPTION

[0041] In order to make the technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the embodiments thereof. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Other systems, methods and / or features of the embodiments will become apparent to those skilled in the art upon review of the following detailed description. It is intended that all such additional systems, methods, features and advantages be included within this specification. They are included within the scope of the present application and are protected by the accompanying claims. Additional features of the disclosed embodiments are described in the following detailed description and will be apparent to one of ordinary skill in the art upon review of the following detailed description.

[0042] The same or similar reference numerals in the drawings of the embodiments of the present application correspond to the same or similar components; in the description of the present application, it is understood that if the orientations or positional relationships indicated by the terms "upper", "lower", "left", "right" and the like are based on the orientations or positional relationships shown in the drawings, they are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or components referred to must have a particular orientation. The orientation and operation are constructed in a particular orientation, so the positional relationship described in the drawings is only used for exemplary illustration, and cannot be understood as a limitation on the present patent. For those skilled in the art, the specific meanings of the above terms can be understood according to the specific circumstances.

[0043] Embodiment one: an exemplary power quality optimization control system applied to a distributed photovoltaic system is proposed, the optimization control system comprises at least one photovoltaic power generation and energy storage unit; the photovoltaic power generation and energy storage unit comprises:

[0044] a power generation module for converting solar energy into direct current power;

[0045] an inverter module for converting direct current generated by the power generation module into alternating current;

[0046] an energy storage module for storing excess power;

[0047] an electric energy evaluation module, the electric energy evaluation module collects and analyzes the electric energy quality related indicators in the photovoltaic power generation and energy storage unit through the alpha collection submodule and the beta collection submodule;

[0048] The electric energy evaluation module is in communication connection with the electric energy evaluation modules of other photovoltaic power generation and energy storage units, and forms a decentralized electric energy quality evaluation network; the electric energy quality evaluation network adopts a distributed consensus mechanism to cross-verify the electric energy quality evaluation results, to ensure that the electric energy evaluation results of the electric energy evaluation modules of each photovoltaic power generation and energy storage unit are correct and available, and further control the permission of the photovoltaic power generation and energy storage unit to access the public power grid.

[0049] Exemplarily, the alpha collection submodule is arranged at the input end of the inverter module and is specially used for collecting the electric parameter data of the direct current generated by the photovoltaic power generation module; the beta collection submodule is arranged at the output end of the inverter module and is specially used for collecting the electric parameter data of the alternating current output by the inverter module.

[0050] Exemplarily, the electric energy evaluation module comprises:

[0051] an evaluation unit configured to periodically calculate the electric energy quality state of the system using a preset electric energy quality evaluation algorithm, and evaluate whether it meets the set threshold requirement;

[0052] a storage unit configured to store historical electric energy parameter data collected by the first collection sub-module and the second collection sub-module, and evaluation data made by the evaluation unit on the historical electric energy parameter data;

[0053] a communication unit configured to establish a decentralized data communication network with electric energy evaluation modules of other photovoltaic power generation and energy storage units.

[0054] Exemplarily, a branch selector is further arranged between the inverter module and the energy storage module; the branch selector is configured to control the flow direction of the output electric energy of the inverter module, and to realize dynamic switching among the energy storage module, the power grid line or the power load.

[0055] Exemplarily, the optimization control system comprises a double evaluation process during operation; the double evaluation process comprises the following steps:

[0056] The electric energy evaluation module as a main detection module periodically evaluates the electric energy quality of the photovoltaic power generation and energy storage unit based on a main evaluation period T1, using the collected sample data as the first collection sample, and generates a first evaluation result;

[0057] The main detection module periodically sends the first collection sample to at least two randomly selected electric energy evaluation modules through an electric energy quality evaluation network based on a secondary evaluation period T2; the selected electric energy evaluation modules as supervisory detection modules evaluate the electric energy quality of the first collection sample, and generate a second evaluation sample;

[0058] The main detection module sends the first evaluation result to at least one management node through the electric energy quality evaluation network;

[0059] The at least two supervisory detection modules send the second evaluation sample to the at least one management node selected by the main detection module;

[0060] The at least one management node calculates the deviation between the first evaluation result and the second evaluation result in response to the first evaluation result and the second evaluation result, and performs consistency verification;

[0061] The management node feeds back the deviation to the main detection module; if the deviation exceeds a threshold value, the main detection module triggers the electric energy transmission path control of the photovoltaic power generation and energy storage unit.

[0062] Exemplarily, the secondary evaluation period T2 is greater than the main evaluation period T1.

[0063] Exemplarily, the inverter module is a bidirectional inverter, and the output end of the energy storage module outputs electric energy to the inverter module according to the electric energy demand, and provides electric energy to the power grid or the load through the branch selector.

[0064] As shown in FIG. 1, the photovoltaic power generation and energy storage unit comprises an inverter module 1, an energy storage module 2, an optimization control system 3, and a communication unit 4. Figure 1The illustrated example embodiment of the optimization control system is shown.

[0065] In an example embodiment, a plurality of photovoltaic power generation and energy storage units 1 are included in a distributed photovoltaic system. Each photovoltaic power generation and energy storage unit can be independently arranged geographically or physically spaced apart from other photovoltaic power generation and energy storage units. For example, a photovoltaic power generation and energy storage unit 1 can refer to a total assembly of photovoltaic power generation equipment arranged at a household, or a small micro photovoltaic power station arranged outdoors. The scale of a photovoltaic power generation and energy storage unit is generally less than 10 kV in grid access capability, or less than 6 MW in power generation capacity.

[0066] In a preferred embodiment, each photovoltaic power generation and energy storage unit 1 includes at least a power generation module 10, an electrical energy evaluation module 20, an inverter module 30, and an energy storage module 40.

[0067] In a preferred embodiment, the power generation module 10 includes at least one photovoltaic assembly and a corresponding electrical connection circuit, for converting solar energy into direct current electrical energy. The photovoltaic assembly can be a single-crystal silicon, polycrystalline silicon, or thin-film solar cell panel, and can be selected according to the specific application scenario to improve the utilization of light energy, with fixed, adjustable, or automatic tracking installation structures. The power generation module 10 preferably also includes a direct current busbar device for converging the power of multiple photovoltaic assemblies, and ensuring the safety and stability of power transmission through appropriate anti-reverse diodes, fuses, and other protection elements.

[0068] In a preferred embodiment, the inverter module 30 is configured to convert the direct current generated by the power generation module 10 into alternating current that can be integrated into the power grid or used by a load. Preferably, the inverter module 30 can include a power conversion circuit, a maximum power point tracking (MPPT) control unit, a power factor correction unit, and a filter circuit.

[0069] Preferably, the inverter module 30 adjusts the voltage, current, power factor, and other input electrical energy in real time, and provides functions such as harmonic suppression, overvoltage protection, and undervoltage protection, to control the output parameters of the alternating current output by the inverter module 30, and ensure that the power quality of the output alternating current meets predetermined standards.

[0070] In a preferred embodiment, each energy storage module 40 comprises an energy storage module management system 42, a plurality of energy storage units 44, and a circuit electrically connecting the plurality of energy storage units 44 and the energy storage module management system 42; the energy storage module 40 can be optimally designed by the manufacturer and internally comprise a minimum single structure system assembled by connecting two or more energy storage units 44 in series / parallel; the energy storage unit 44 can refer to a single battery or other independent individual with energy storage function, such as a super capacitor; the energy storage module 40 can be monitored and controlled by the energy storage module management system 42; each energy storage module 40 can comprise a plurality of energy storage units 44 and corresponding protection units or any other protection devices.

[0071] Preferably, the energy storage module management system 42 is configured to monitor the working state of each energy storage unit 44 and the energy storage module 40.

[0072] Preferably, the energy storage unit 44 is a battery pack or a super capacitor, each of which is independently packaged and electrically connected by a circuit; the battery pack can use lithium ion batteries, lithium iron phosphate batteries, lead-acid batteries, or other energy storage technologies suitable for application scenarios.

[0073] Preferably, the energy storage module management system 42 monitors the real-time parameters such as voltage, current, and temperature of the energy storage module 40, and implements equalization management, overcharge / overdischarge protection, and health status evaluation.

[0074] In a preferred embodiment, the input end of the inverter module 30 is electrically connected to the power generation module 10. The output end of the inverter module 30 is connected to a branch selector 70. The branch selector 70 comprises a first branch, a second branch, and a third branch. The first branch is connected to the energy storage module 40, the second branch is connected to the grid line 60, and the third branch is connected to the electrical load 50.

[0075] Specifically, the branch selector 70 is used to control the flow direction of the output power of the photovoltaic power generation and energy storage unit 1 to realize on-demand distribution of photovoltaic power. The branch selector 70 can comprise a plurality of power switches, relays, or semiconductor switch circuits, which can dynamically switch between the photovoltaic system, the energy storage module, the grid, and the electrical load.

[0076] The first branch is an energy storage path; the first branch is connected to the energy storage module 40, and when the photovoltaic system has sufficient power generation capacity and the grid demand is low, the branch selector 70 can conduct the first branch to store excess power to the energy storage module 40. When the charging state of the energy storage module 40 is completed or the battery charging level reaches a preset threshold, the branch selector 70 can cut off the first branch to prevent overcharging.

[0077] The second branch is a grid-connected path; the second branch is connected to the grid line 60, and when the power generation capacity of the photovoltaic system meets the power supply demand of the grid, the branch selector 70 can conduct the second branch to deliver the electrical energy generated by the photovoltaic system to the grid. When the grid line fails or the power quality does not meet the standard, the branch selector 70 can automatically disconnect the second branch to prevent affecting the safe operation of the grid.

[0078] The third branch is a load path; the third branch is connected to the electrical load 50, and when the electrical energy generated by the photovoltaic system can directly meet the user load demand, the branch selector 70 can conduct the third branch to make the photovoltaic power generation preferentially supply the local load. When the load power demand is low or the energy storage module 40 needs to be preferentially charged, the branch selector 70 can adjust the load power supply mode according to the system demand.

[0079] In other embodiments, the inverter module 30 is a bidirectional inverter. The output end of the energy storage module 40 outputs current to the inverter module 30 to provide electrical energy during the peak demand for electricity, and provides electrical energy to the grid or the load through the branch selector 70.

[0080] In some embodiments, the user can manually select the electrical energy switching direction of the branch selector 70 through an operation interface such as a switch, a touch screen, or a mobile terminal application, etc., to meet specific application scenarios, such as user self-scheduling electrical energy use strategy.

[0081] Further, in the preferred embodiment, the electrical energy evaluation module 20 cooperates with the alpha acquisition submodule 22 and the beta acquisition submodule 24 to evaluate the electrical energy quality of each circuit section in the photovoltaic power generation and energy storage unit 1. The alpha acquisition submodule 22 and the beta acquisition submodule 24 are respectively used to collect electrical energy parameters on the photovoltaic direct current side and the alternating current side, and the electrical energy evaluation module 20 is used to analyze and evaluate the collected data to ensure the stability of the system and the compliance of the electrical energy output. The alpha acquisition submodule 22 and the beta acquisition submodule 24 are both configured with multiple sensors to continuously measure the electrical energy characteristics of the configured sampling points.

[0082] Specifically, the input end of the inverter module 30 is provided with a sampling port, and the electrical energy data is sampled by the alpha acquisition submodule 22, and the sampling data comes from the direct current generated by the photovoltaic assembly. The collected electrical parameter data includes but is not limited to direct current voltage, current, power, power factor, ripple voltage, short / long time voltage fluctuation, direct current harmonic component, temperature, environmental illumination, etc. Preferably, the alpha acquisition submodule 22 collects the output electrical energy state of the power generation module 10 in real time, and sends the collected data to the electrical energy evaluation module 20 for subsequent electrical energy quality analysis.

[0083] On the other hand, a sampling port is arranged at the output end of the inverter module 30, and the electric energy data is sampled by the B acquisition submodule 24, and the output end of the inverter module 30 is connected with the branch selector 70. The B acquisition submodule 24 acquires the AC electric energy related parameters output by the inverter. Preferably, the electric parameter data acquired by the B acquisition submodule 24 includes but is not limited to AC voltage, current, power, power factor, total harmonic distortion (THD), voltage distortion rate, current distortion rate, frequency deviation, three-phase voltage unbalance degree, transient voltage, instantaneous voltage drop, transient rise, flicker, overvoltage, undervoltage and the like. The B acquisition submodule 24 monitors the output electric energy quality of the inverter module 30 in real time, and sends the acquired data to the electric energy evaluation module 20, so as to comprehensively analyze the output quality of the inverter.

[0084] Preferably, the electric energy evaluation module 20 is a core evaluation unit, which receives the electric parameter data from the A acquisition submodule 22 and the B acquisition submodule 24, and performs data analysis according to the preset electric energy quality evaluation algorithm. The evaluation content of the electric energy evaluation module 20 includes but is not limited to comparison and analysis of the electric energy quality on the DC side and the AC side, electric energy quality qualification judgment, data anomaly detection, load characteristic analysis, energy storage strategy optimization and the like. According to the evaluation result, the electric energy evaluation module 20 provides adjustment suggestions or protection measures to the control module 80, so as to ensure the stability and safety of each circuit part of the photovoltaic power generation and energy storage unit. When detecting the electric energy quality anomaly, the electric energy evaluation module 20 triggers the early warning mechanism, and instructs the branch selector 70 to perform adaptive adjustment, for example, guiding the electric energy to the energy storage module 40, so as to avoid that the unqualified electric energy is directly delivered to the power grid line 60 or the electric load 50.

[0085] Preferably, the electric energy evaluation module 20 includes evaluation of the total harmonic distortion of the AC electric output by the inverter module 30, so as to ensure that the harmonic content is within the specified range, and avoid interference to the power grid or the load equipment. The harmonic analysis is performed by Fourier transform (FFT) on the voltage or current waveform provided by the B acquisition submodule 24, the amplitude of each harmonic is calculated, and the THD value is determined according to the following calculation formula:

[0086]

[0087] wherein, V n represents the effective value of the nth harmonic voltage; V1 represents the effective value of the fundamental wave voltage. The FFT calculation module is arranged in the data processing unit of the electric energy evaluation module 20, which can calculate the THD in real time, and compare the result with the preset threshold value. If the THD exceeds the set range, the electric energy evaluation module 20 will issue an instruction to the control module 80 to adjust the output waveform of the inverter, or instruct the branch selector 70 to switch to the energy storage mode, so as to prevent the unqualified electric energy from being input into the power grid.

[0088] Preferably, the power evaluation module 20 includes evaluation of whether the output voltage of the photovoltaic power generation system meets the rated value, preventing voltage deviation from affecting the normal operation of the equipment. The calculation of voltage deviation is based on the voltage data collected by the voltage acquisition submodule 24. The power evaluation module 20 will calculate the voltage deviation in the short term (for example, 1 second period) and long term (for example, 15 minute period) respectively, and compare with the national standard to determine whether adjustment measures need to be taken. If the voltage deviation exceeds the allowed range, for example, ±3%, send adjustment instructions to the control module 80 to optimize the output parameters of the inverter, or trigger the energy storage unit to provide power compensation to maintain voltage stability.

[0089] Preferably, the power evaluation module 20 uses the voltage and current data provided by the voltage acquisition submodule 22 and the voltage acquisition submodule 24 to calculate the power factor of the system to ensure the efficiency of power utilization. The power factor is a measure of the ratio of active power to total power provided by the photovoltaic power generation system. The power evaluation module 20 will periodically evaluate the power factor and compare it with the specified minimum power factor threshold (for example, 0.9 or 0.95). If the power factor is lower than the set threshold, the power evaluation module 20 will trigger the inverter to adjust the reactive power output, or start the energy storage module 40 to provide reactive compensation, in order to improve the power factor of the system, reduce power loss and meet the grid-connected requirements.

[0090] The above-mentioned evaluation indicators are not presented as restrictive options. In the specific embodiments of the present technical solution, more evaluation indicators can be calculated as needed.

[0091] Embodiment two: This embodiment should be understood as including all the features of any one of the preceding embodiments, and further improving on the basis thereof;

[0092] Further, in the preferred embodiment, the power evaluation modules 20 of a plurality of photovoltaic power generation and energy storage units 1 in the distributed photovoltaic system are connected by a communication network to form a decentralized power quality evaluation network, which improves the overall power quality monitoring capability of the distributed photovoltaic system, and ensures the operation stability of each photovoltaic power generation and energy storage unit and the safety of the power grid through a decentralized collaboration mechanism.

[0093] Specifically, each power evaluation module 20 is configured with a communication submodule. Through the communication submodule, the power evaluation module 20 is allowed to communicate data with other power evaluation modules 20, and the power evaluation module 20 becomes a network node of the power quality evaluation network. In the decentralized network, each power evaluation module 20 forms a distributed topology. The power quality evaluation network does not rely on a single central server, but cross- verifies the power quality evaluation results through a distributed consensus mechanism.

[0094] In preferred embodiments, the power evaluation module 20 comprises the following working units:

[0095] Evaluation unit: the evaluation unit periodically calculates the power quality state of the system using preset power quality evaluation algorithms, such as root mean square error analysis, voltage deviation calculation, FFT harmonic analysis, etc., and evaluates whether it meets the set threshold requirements.

[0096] Storage unit: for storing historical power parameter data collected by the alpha collection submodule 22 and the beta collection submodule 24, as well as evaluation data made by the evaluation unit on historical power parameter data, in order to conduct trend analysis, predictive maintenance and compliance audit. The storage unit preferably uses a ring buffer storage mechanism to store recent data and periodically upload to the cloud or local management node.

[0097] Communication unit: the communication unit establishes a decentralized data sharing network with other power evaluation modules 20 of photovoltaic power storage units through wired communication methods such as RS485, CAN, Ethernet, etc., or wireless communication methods such as LoRa, Wi-Fi, 5G, etc.

[0098] In some embodiments, the photovoltaic power storage unit 1 performs a double evaluation process. The double evaluation process is first performed by the power evaluation module 20 configured by the photovoltaic power storage unit 1 itself as the main detection module 200, which performs self-evaluation of power quality based on a main evaluation period T1. At the same time, each main detection module 200 selects at least two power evaluation modules 20 other than itself in the power quality evaluation network as the supervisory detection module 210 in a randomly selected manner based on a secondary evaluation period T2, to perform secondary evaluation.

[0099] And the secondary evaluation period T2 is greater than the main evaluation period T1. In preferred embodiments, T2 can be calculated from T1 by a review multiple p, i.e. T2 = p·T1. Wherein, the optional value of p can be 100 or more, such as 120, 150, 180 or other values.

[0100] More specifically, the double evaluation process includes the following steps:

[0101] S100: The main detection module 200 prepares the power parameter data collected by the photovoltaic power storage unit 1 in the last main evaluation period T1, referred to as alpha collection samples here; at the same time, the power quality evaluation results of the alpha collection samples, referred to as alpha evaluation results here, are prepared.

[0102] S200: sending the evaluation result of the main detection module 200 to at least one management node 220 in the power quality evaluation network; further, sending the collected sample and the identification information of the selected management node 220 to at least two supervision detection modules 210.

[0103] S300: the two power evaluation modules 20 selected as the supervision detection modules 210 re-calculate the power quality represented by the collected sample according to the same evaluation algorithm in response to the received collected sample, and generate the evaluation result of B.

[0104] S400: the at least two supervision detection modules 210 send the evaluation result of B to the management node 220 selected in step S200.

[0105] S500: the management node 220 calculates the deviation degree of the evaluation result of A and the evaluation result of B in response to the received evaluation result of A and the evaluation result of B.

[0106] S600: the management node 220 reflects the calculation result of the deviation degree of the collected sample to the main detection module 200.

[0107] In the preferred embodiment, when the deviation between the evaluation result of A and the evaluation result of B exceeds the preset threshold, the system will trigger a consistency checking mechanism. Under this mechanism, the period length of the main evaluation period T1 can be shortened by the main detection module 200 again to increase the frequency of performing the double evaluation process; or the main detection module 200 is required to perform the double evaluation process again immediately, and at least two supervision detection modules 210 are requested to perform the double evaluation process again to ensure the accuracy and consistency of the evaluation result. The management node 220 is responsible for coordinating these evaluation processes and finally confirming the validity of the result. Once it is confirmed that there is an abnormality in a certain photovoltaic power storage unit, the power evaluation module 20 thereof will trigger the corresponding protection mechanism, for example, notifying the control module 80 to take necessary adjustment measures such as limiting grid-connected output, switching to energy storage mode or shutdown self-checking, to prevent unqualified power from affecting the stable operation of the entire photovoltaic system.

[0108] In the preferred embodiment, the deviation degree σ of the evaluation result of A and the evaluation result of B is calculated by the following formula 甲 :

[0109]

[0110] In the above formula, N is the total number of indicators of the power quality indicators, m is the number of selected supervision detection modules 210; Xi is the value of the i-th indicator in the evaluation result of A; Xj is the value of the j-th indicator in the evaluation result of B; and σ is the deviation degree of the evaluation result of A and the evaluation result of B. 甲,i 乙,m,i ​The value of the i-th index in the j-th evaluation result of the m-th supervision detection module 210.

[0111] Preferably, when three or more supervision detection modules 210 are selected, the deviation value σ 甲 Before that, first calculate whether there is an abnormal deviation in the m evaluation results, that is, first exclude whether there is an abnormal supervision detection module 210. The following calculation formula can be used to calculate the deviation degree σ 乙 :

[0112]

[0113] σ 乙,j The deviation degree of the j-th evaluation result is represented by X 乙,j,i The value of the i-th index in the j-th evaluation result of the supervision detection module is represented by μ 乙，i The mean value of the i-th index in the m evaluation results is represented by μ

[0114] Further, the threshold values of σ 甲 and σ 乙 are set by relevant technical personnel.

[0115] In the preferred embodiment, if the deviation degree of an evaluation result is also significantly higher than the evaluation result of the supervision detection module 210 and at least two evaluation results, the management node 220 sends the main detection module 200 to re-execute steps S100-S600, and reselect at least two power evaluation modules 20 different from the previous supervision detection module 210 as the supervision detection module 210 to perform the double evaluation process.

[0116] The advantage of the decentralized network is that it has high reliability, fault tolerance and data consistency guarantee. Since the evaluation process is distributed on multiple independent units, even if some units fail, the overall system can still operate normally. In addition, the network can be dynamically expanded, and when a new photovoltaic power storage unit is added, only its power evaluation module 20 needs to be added to the existing network architecture, without the need for large-scale modification of the overall system.

[0117] Embodiment three: this embodiment should be understood as at least containing all the features of any one of the preceding embodiments, and further improving on the basis thereof;

[0118] Exemplarily, as shown in the accompanying Figure 5 The computer system 500 adopted by the optimization control system, such as the power evaluation module 20 or the control module 80, or other working modules, is shown in the embodiment; the computer system 500 can be applied to the data storage, operation and result output process of each working module in the identification and judgment system.

[0119] By way of example, the computer system 500 includes a bus 502 or other communication mechanism for communicating information, and a processor 504 coupled with bus 502 for processing information. The processor 504 can be, for example, a general purpose microprocessor;

[0120] The computer system 500 also includes a main memory 506, such as a random access memory (RAM), cache and / or other dynamic storage devices, coupled to bus 502 for storing information and instructions to be executed by processor 504. Main memory 506 also can be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 504. Such instructions can be stored or executed in order to implement the operations described herein with regard to the management system;

[0121] The computer system 500 further can include a read only memory (ROM) 508 or other static storage device coupled to bus 502 for storing static information and instructions for processor 504. A storage device 510, such as a magnetic disk, optical disk, or USB drive (flash drive), etc., can be coupled to bus 502 for storing information and instructions;

[0122] Further, a display 512, such as a cathode ray tube (CRT), plasma, or liquid crystal display (LCD) or touch screen, can be coupled to bus 502 for displaying information in various forms to users of computer system 500;

[0123] One preferred manner of interacting with the management system can be through a cursor control device 516, such as a computer mouse, or similar pointing / control / navigating mechanism;

[0124] Further, the computer system 500 can also include a network interface device 518 coupled to bus 502; where the network interface device 518 can include, for example, a wired network card, a wireless network card, a switch chip, a router, a switch, etc.;

[0125] Generally, the terms "engine," "component," "system," "database," and the like, as used herein, can refer to logic embodied in hardware or firmware, or to a collection of software instructions, possibly having entry and exit points, written in a programming language, such as, for example, Java, C or C++; a software component can be compiled and linked into an executable program, installed in a dynamic link library, or can be written in an interpreted programming language such as, for example, BASIC, Perl, or Python; it will be appreciated that software components can be callable from other components or be callable into them and / or can be invoked in response to detected events or interrupts;

[0126] Software components configured to execute on a computing device can be provided on a computer- readable medium, such as an optical disc, a digital video disc, a flash drive, a magnetic disc or any other tangible medium, or as a digital download (and can initially be stored) in a compressed or installable format, requiring installation, decompression or decryption, before execution); such software code can be stored, in whole or in part, on a memory device of the executing computing device, for execution by the computing device; software instructions can be embedded in firmware, such as an EPROM; it will also be appreciated that hardware components can be comprised of connected logic units, such as gates and flip-flops, and / or can be comprised of programmable units, such as programmable gate arrays or processors;

[0127] The computer system 500 includes a custom hard-wired logic, one or more ASICs or FPGAs, firmware and / or program logic which in combination with the computer system causes or programs computer system 500 to be a special purpose machine;

[0128] In accordance with one or more embodiments, the techniques herein are performed by computer system 500 in response to processor 504 executing one or more sequences of one or more instructions contained in main memory 506; such instructions can be read into main memory 506 from another storage medium, such as storage device 510; execution of the sequences of instructions contained in main memory 506 causes processor 504 to perform the process steps described herein; in alternative embodiments, hard-wired circuitry can be used in place of or in combination with software instructions;

[0129] The term "non-transitory medium" and similar terms as used herein refers to any medium that stores the data and / or instructions that cause a machine to operate in a specific manner; such a non-transitory medium can include non-volatile media and / or volatile media; non-volatile media includes, for example, optical or magnetic disks, such as storage device 510; volatile media includes dynamic memory, such as main memory 506;

[0130] Common forms of non-transitory media include, for example, a floppy disk, a flexible disk, a hard disk, a solid-state drive, a magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge, and a networked version of any of the above;

[0131] A non-transitory medium is distinct from a transmission medium, but can be used in combination with a transmission medium; a transmission medium participates in communicating information between non-transitory media; for example, a transmission medium includes a coaxial cable, a copper wire, and a fiber optic cable, including the wires that make up bus 502; a transmission medium can also take the form of acoustic or light waves, such as radio or infrared transmissions.

[0132] While the application has been described with reference to various embodiments, it will be understood that many changes can be made and equivalents can be substituted for elements thereof without departing from the scope of the application. Many of the details of the application, as discussed above, are provided for the purpose of illustration. Therefore, it is to be understood that the foregoing description of the application is intended to be illustrative only, and not limiting of the scope of the application. As port of the disclosure, there is shown and described a number of embodiments of the application as currently an envisioned. It is understood that the use of these embodiments for illustrating the application does not impose a limitation on the scope of the application. Input / output or program components and processes depicted as separate from each other and / or remote from each other can or can not be so configured. For example, these components and processes can be physically integrated into one or more common processing and / or memory devices and / or can exist as virtual programs in one or more locations of one or more processing and / or memory devices. In addition, those skilled in the art will appreciate that the mechanisms of the present application allow for a variety of possible configurations, and that the application described and claimed should not be construed as limited to the understand configurations.

[0133] In the description specific details are set forth in order to provide a thorough understanding of the exemplary configurations including implementations. However, configurations can be practiced without these specific details. For example, well known circuits, processes, algorithms, structures, and techniques have not been described in detail because such details are already well known in the art. The description provides example configurations only, and is not intended to limit the scope, applicability or configuration of the claims. Rather, the preceding description of the configurations will provide those skilled in the art with an enabling description for implementing described techniques. Various changes can be made to the function and arrangement of elements without departing from the spirit of the disclosure, the scope of which is defined by the appended claims.

[0134] In view of the above, it will be seen that the details set forth in the preceding description are to be interpreted as illustrative and not in a limiting sense. The preceding description is intended to cover all alternatives, modifications and equivalents of the application falling within the scope of the claims.

Claims

1. A power quality optimization control system applied to a distributed photovoltaic system, characterized in that, The optimization control system comprises at least one photovoltaic power generation and energy storage unit, wherein the photovoltaic power generation and energy storage unit comprises: a power generation module for converting solar energy into direct current power; an inverter module for converting the direct current power generated by the power generation module into alternating current power; an energy storage module for storing excess power; an electric energy evaluation module for collecting and analyzing electric energy quality related indexes in the photovoltaic power generation and energy storage unit through an alpha collection sub-module and a beta collection sub-module; wherein the electric energy evaluation module is in communication connection with electric energy evaluation modules of other photovoltaic power generation and energy storage units and forms a decentralized electric energy quality evaluation network; the electric energy quality evaluation network adopts a distributed consensus mechanism to cross-verify the electric energy quality evaluation results to ensure that the electric energy evaluation results of the electric energy evaluation modules of the photovoltaic power generation and energy storage units are correct and available, and further control the access rights of the photovoltaic power generation and energy storage units to the public power grid; the alpha collection sub-module is arranged at the input end of the inverter module and is specially used for collecting electric parameter data of the direct current power generated by the photovoltaic power generation module; the beta collection sub-module is arranged at the output end of the inverter module and is specially used for collecting electric parameter data of the alternating current power output by the inverter module; the electric energy evaluation module comprises: an evaluation unit configured to periodically calculate the electric energy quality state of the system by using a preset electric energy quality evaluation algorithm and evaluate whether the electric energy quality state meets the set threshold requirement; a storage unit for storing historical electric energy parameter data collected by the alpha collection sub-module and the beta collection sub-module and evaluation data made by the evaluation unit on the historical electric energy parameter data; a communication unit configured to establish a decentralized data communication network with electric energy evaluation modules of other photovoltaic power generation and energy storage units; a branch selector is further arranged between the inverter module and the energy storage module; the branch selector is used for controlling the flow direction of the power output by the inverter module and realizing dynamic switching between the energy storage module, the power grid line or the power load; the optimization control system comprises a double evaluation process in the running process; the double evaluation process comprises the following steps: the electric energy evaluation module as a main detection module periodically preliminarily evaluates the electric energy quality of the photovoltaic power generation and energy storage unit based on a main evaluation period T1 and generates alpha evaluation results by taking the collected sample data as alpha collection samples; the main detection module periodically sends the alpha collection samples to at least two randomly selected electric energy evaluation modules through the electric energy quality evaluation network based on a secondary evaluation period T2; the selected electric energy evaluation modules as supervisory detection modules evaluate the electric energy quality of the alpha collection samples and generate beta evaluation samples; the main detection module sends the alpha evaluation results to at least one management node through the electric energy quality evaluation network; the at least two supervisory detection modules send the beta evaluation samples to the at least one management node selected by the main detection module; at least one management node calculates the deviation degree between the alpha evaluation results and the beta evaluation results in response to the alpha evaluation results and the beta evaluation results and performs consistency verification; ​ ​ The management node feeds the deviation degree to a main detection module; if the deviation exceeds a threshold, the main detection module triggers control of an electric energy transmission path of the photovoltaic power generation and energy storage unit; The inverter module is a bidirectional inverter, and an output end of the energy storage module outputs electric energy to the inverter module according to electric energy demand, and provides electric energy to a power grid or a load through a branch selector. The secondary evaluation period T2 is greater than the primary evaluation period T1.

2. The optimal control system of claim 1, wherein, ​

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