Integrated energy utilization management platform based on light storage direct flexible technology

Abstract

The invention belongs to the technical field of energy management, and particularly relates to a comprehensive energy utilization management platform based on an optical storage direct-flexible technology, which comprises an integrated photovoltaic power generation module, an energy storage allocation module, a direct-current power distribution conversion module, a flexible power utilization management module, an optical storage diagnosis analysis module and a user side, solar energy is converted into electric energy through the integrated photovoltaic power generation module by utilizing a solar photovoltaic panel, the energy storage allocation module stores redundant electric energy of photovoltaic power generation and releases the electric energy in good time, and the direct current power distribution conversion module adopts a direct current power distribution network to reduce loss in the energy conversion process. The flexible power utilization management module intelligently adjusts a power utilization strategy to realize fine management of electric energy, and the light-storage cooperation performance is analyzed through the light-storage cooperation performance analysis module, so that the subsequent supervision on the solar photovoltaic panel and the energy storage power supply is enhanced in time, and the subsequent power generation and energy storage safety is ensured.

Description

Technical Field

[0001] The present invention relates to the field of energy management technology, and in particular to an integrated energy utilization management platform based on photovoltaic storage direct-flexible technology. Background Art

[0002] With the continuous growth of global energy demand and the increasing awareness of environmental protection, the development and utilization of renewable energy and the improvement of energy efficiency have become the common goals of governments and enterprises around the world.

[0003] A Chinese invention patent, publication number CN118367539A, discloses a zero-carbon building control system and method based on solar-storage-direct-flexible systems. By collecting various feedback data, the system formulates an optimal power usage strategy to control the power consumption of subordinate subsystems. When fault information from a subordinate subsystem is detected, the system matches the historical database to summarize the current equipment fault information and reports it, protecting user power safety and improving power utilization efficiency.

[0004] However, in actual application, the above-mentioned technical solution is difficult to effectively manage building energy utilization while accurately reporting the degree of abnormal operation of solar photovoltaic panels and energy storage devices. It is also impossible to reasonably analyze and comprehensively judge the performance of photovoltaic and energy storage operation coordination and provide timely warnings. This is not conducive to ensuring the safety of power generation and energy storage, and the supervision is difficult and the level of intelligence is low.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide a comprehensive energy utilization management platform based on photovoltaic storage direct flexible technology, which solves the problems that the existing technology is difficult to effectively manage the energy utilization of buildings while accurately feedback the degree of operational abnormalities of solar photovoltaic panels and energy storage devices, and is unable to reasonably analyze and comprehensively judge the performance of photovoltaic storage operation coordination and provide timely warnings, resulting in difficult supervision and low intelligence level.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An integrated energy utilization management platform based on PV-storage-direct-flexible technology includes an integrated photovoltaic power generation module, an energy storage and dispatch module, a DC power distribution conversion module, a flexible power management module, a PV-storage coordination performance analysis module, and a user terminal.

[0009] The integrated photovoltaic power generation module uses solar photovoltaic panels to convert solar energy into electrical energy and transmits the generated electrical energy to the energy storage and dispatch module and the DC distribution conversion module;

[0010] The energy storage and dispatching module is equipped with a high-performance energy storage device to store excess electricity generated by photovoltaic power generation and release electricity when there is insufficient sunlight or peak electricity demand;

[0011] The DC power distribution conversion module integrates the DC power generated by the photovoltaic power generation module and the energy storage dispatch module, and transmits and distributes it to various loads within the building or campus. The flexible power management module monitors the power load, photovoltaic power generation, and the charge and discharge status of the energy storage device within the building or campus in real time, intelligently adjusts the power usage strategy, and sends the monitoring and adjustment information to the user end for display.

[0012] The photovoltaic and storage coordination performance analysis module analyzes the photovoltaic and storage coordination performance, and determines whether to generate a photovoltaic and storage coordination failure signal through analysis, and sends the photovoltaic and storage coordination abnormality signal to the user end. When the user end receives the photovoltaic and storage coordination failure signal, it will issue a corresponding warning.

[0013] Furthermore, the flexible power management module has the functions of load forecasting, power quality analysis, reactive power optimization and fault protection. Among them, load forecasting is the basic link of flexible power management. By using load forecasting methods to analyze historical data and real-time data, the patterns and trends of load changes are obtained and future load changes are predicted accordingly.

[0014] Power quality analysis involves real-time monitoring and analysis of power quality parameters including voltage, current, and frequency. This data is analyzed to identify power quality issues, including voltage fluctuations and harmonic pollution, and appropriate measures are taken to improve the power quality issues identified.

[0015] Reactive power optimization rationally distributes the reactive power flow of the power system to maintain the system voltage level, improve voltage stability and reduce active network losses; fault protection detects and handles potential fault risks through real-time monitoring and analysis of the power system.

[0016] Furthermore, the load forecasting methods used in load forecasting include unit consumption method, trend extrapolation method, elastic coefficient method, time series method, grey model method, Delphi method, neural network method, optimal combination forecasting method and wavelet analysis forecasting technology;

[0017] Reactive power optimization includes two aspects: optimal planning of reactive power compensation devices and voltage-reactive power optimization control. By optimizing the layout and capacity of reactive power compensation devices and adjusting the tap positions of transformers, a reasonable distribution of reactive power flow can be achieved and the operating efficiency of the power system can be improved.

[0018] Furthermore, the specific analysis process of the photovoltaic-storage coordination performance analysis module is as follows:

[0019] A monitoring period is set, and the number of times the corresponding solar photovoltaic panel is marked as an abnormal power generation object during the monitoring period is collected and defined as the abnormal power generation frequency, and the number of times the corresponding energy storage device is marked as an abnormal energy storage object during the monitoring period is collected and defined as the abnormal energy storage frequency;

[0020] The proportion of solar photovoltaic panels whose abnormal power generation frequency exceeds the preset abnormal power generation frequency during the monitoring period is marked as the power generation abnormality value, and the proportion of energy storage devices whose abnormal energy storage frequency exceeds the preset abnormal energy storage frequency threshold during the monitoring period is marked as the energy storage abnormality value. The power generation abnormality value and the energy storage abnormality value are numerically compared with the preset power generation abnormality threshold and the preset energy storage abnormality threshold respectively. If the power generation abnormality value or the energy storage abnormality value exceeds the corresponding preset threshold, a light-storage coordination unqualified signal is generated.

[0021] Furthermore, if neither the abnormal power generation value nor the abnormal energy storage value exceeds the corresponding preset threshold, the abnormal power generation frequencies of all solar photovoltaic panels are averaged to obtain the photovoltaic panel coordination value, and the abnormal energy storage frequencies of all energy storage devices are averaged to obtain the energy storage coordination value. If there is an abnormal power generation object or abnormal energy storage object within a unit time, a photovoltaic storage potential danger symbol CP-1 is assigned, and the number of times the photovoltaic storage potential danger symbol is assigned within the monitoring period is obtained and marked as the photovoltaic storage potential danger frequency.

[0022] The photovoltaic-storage coordination coefficient is obtained by numerically calculating the photovoltaic panel coordination value, energy storage coordination value and photovoltaic-storage hidden danger frequency, and the photovoltaic-storage coordination coefficient is numerically compared with the preset photovoltaic-storage coordination coefficient threshold. If the photovoltaic-storage coordination coefficient exceeds the preset photovoltaic-storage coordination coefficient threshold, a photovoltaic-storage coordination failure signal is generated.

[0023] Furthermore, the user end is connected to the photovoltaic panel detection module and the energy storage detection module. The photovoltaic panel detection module monitors and analyzes the operation of all solar photovoltaic panels, identifies abnormal power generation objects based on the information, and sends all abnormal power generation objects to the photovoltaic and energy storage coordination performance analysis module and the user end.

[0024] The energy storage detection module monitors and analyzes the operation of all energy storage devices, identifies abnormal energy storage objects based on this, and sends all abnormal energy storage objects to the photovoltaic storage coordination performance analysis module and the user end.

[0025] Furthermore, the specific analysis process of the photovoltaic panel detection module is as follows:

[0026] Several detection periods are set within a unit of time, and the average light intensity and power generation of the corresponding solar photovoltaic panels in the corresponding detection periods are collected. The ratio of the power generation of the solar photovoltaic panels to the average light intensity is marked as a power generation analysis value. The power generation analysis value is numerically compared with a preset power generation analysis value range. If the power generation analysis value is not within the preset power generation analysis value range, the corresponding detection period is marked as a power generation abnormality period.

[0027] and collecting the real-time orientation of the corresponding solar panel, marking the deviation angle of the real-time orientation compared to the current standard orientation as an orientation anomaly value, comparing the orientation anomaly value with a preset orientation anomaly threshold, and if the orientation anomaly value exceeds the preset orientation anomaly threshold, marking the corresponding orientation anomaly value as an orientation feature value;

[0028] The number of abnormal power generation periods in unit time is obtained and the ratio is calculated with the total number of detection periods to obtain the power generation period anomaly value, and the number of orientation characteristic values ​​in unit time is calculated with the number of orientation anomaly values ​​to obtain the power generation direction anomaly value; the photovoltaic panel detection value of the corresponding solar photovoltaic panel is obtained by weighted summation of the power generation period anomaly value and the power generation direction anomaly value; the photovoltaic panel detection value is numerically compared with the preset photovoltaic panel detection threshold; if the photovoltaic panel detection value exceeds the preset photovoltaic panel detection threshold, the corresponding solar photovoltaic panel is marked as an abnormal power generation object.

[0029] Furthermore, the specific analysis process of the energy storage detection module is as follows:

[0030] The actual power consumption and output of the corresponding energy storage device per unit time are collected, and the difference between the actual power consumption and the output power is calculated to obtain the power self-loss value; the internal temperature and noise data of the corresponding energy storage device are collected and marked as the energy storage internal temperature value and the energy storage noise value, respectively. The energy storage internal temperature value and the energy storage noise value are numerically compared with the preset energy storage internal temperature threshold and the preset energy storage noise threshold, respectively. If the energy storage internal temperature value or the energy storage noise value exceeds the corresponding preset threshold, it is determined that the corresponding energy storage device is in an energy storage risk state;

[0031] The total duration of the corresponding energy storage device in the energy storage risk state per unit time is obtained and marked as the energy storage risk time value, and the frequency of the single duration of the corresponding energy storage device in the energy storage risk state per unit time exceeding the corresponding preset duration threshold is marked as the energy storage risk frequency value; the energy storage detection value is obtained by numerically calculating the electric energy self-loss value, the energy storage risk time value and the energy storage risk frequency value, and the energy storage detection value is numerically compared with the preset energy storage detection threshold. If the energy storage detection value exceeds the preset energy storage detection threshold, the corresponding energy storage device is marked as an abnormal energy storage object.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The present invention integrates renewable energy generation, efficient energy storage, DC power distribution, and intelligent power regulation through PV-storage-direct-flexible technology to achieve effective energy utilization management, effectively reducing energy consumption in buildings or parks, improving energy utilization efficiency, and promoting green and low-carbon development. Furthermore, the PV-storage coordination performance analysis module analyzes the PV-storage coordination performance, allowing for timely strengthening of subsequent supervision of solar photovoltaic panels and energy storage power supplies, thereby ensuring the safety of subsequent power generation and energy storage.

[0034] 2. In the present invention, the photovoltaic panel detection module monitors and analyzes the operation of all solar photovoltaic panels to determine abnormal power generation objects, and the energy storage detection module monitors and analyzes the operation of all energy storage devices to determine abnormal energy storage objects. This not only can timely inspect the corresponding solar photovoltaic panels and energy storage devices and make corresponding control or maintenance measures to ensure the safe and stable operation of all solar photovoltaic panels and energy storage devices, but also can provide information support for the analysis process of the photovoltaic and energy storage coordination performance analysis module to ensure the accuracy of its analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0036] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0037] Figure 2 This is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0039] Example 1: Figure 1 As shown, the comprehensive energy utilization management platform based on photovoltaic, energy storage, direct current and flexible technology proposed in the present invention includes an integrated photovoltaic power generation module, an energy storage allocation module, a DC power distribution conversion module, a flexible power management module, a photovoltaic and energy storage coordination performance analysis module and a user terminal;

[0040] The integrated photovoltaic power generation module uses solar photovoltaic panels to convert solar energy into electricity and transmits the generated electricity to the energy storage and dispatch module and the DC power distribution conversion module. The energy storage and dispatch module is equipped with high-performance energy storage devices, such as lithium-ion battery packs, to store excess electricity generated by photovoltaic power generation and release electricity during periods of insufficient sunlight or peak electricity demand.

[0041] The DC power distribution conversion module uses a DC power distribution network to transmit and distribute the DC power generated by the integrated photovoltaic power generation module and energy storage and dispatch module to various loads within the building or park, reducing losses during energy conversion and improving energy transmission efficiency. The system supports flexible interconnection with the AC power grid to ensure the stability and reliability of energy supply.

[0042] The flexible power management module monitors the power load, photovoltaic power generation, and charge and discharge status of energy storage devices within a building or park in real time, intelligently adjusts power usage strategies, and sends monitoring and adjustment information to the user for display, enabling refined power management. Flexible power management includes load forecasting, power quality analysis, reactive power optimization, and fault protection.

[0043] Load forecasting is the fundamental link in flexible electricity management. By analyzing historical and real-time data using load forecasting methods such as the unit consumption method, trend extrapolation method, elasticity coefficient method, time series method, grey model method, Delphi method, neural network method, optimal combination forecasting method, and wavelet analysis forecasting technology, we can obtain the patterns and trends of load changes and predict future load changes based on them. This forecasting capability helps the power system to conduct early dispatch, effectively avoid problems such as overload or power shortage, and ensure the stable operation of the power system.

[0044] Power quality analysis aims to ensure that the power supply system provides electricity that meets standards. This involves real-time monitoring and analysis of power quality parameters (including voltage, current, and frequency). This data is analyzed to identify power quality issues, such as voltage fluctuations and harmonic pollution. Based on these issues, appropriate measures are taken to improve them. For example, to address voltage fluctuations, measures such as installing a fast-acting voltage regulator or a fast-switching series compensation device can be taken to improve voltage stability.

[0045] Reactive power optimization is a key component of flexible power management strategies. It rationally distributes reactive power flows in the power system to maintain system voltage levels, improve voltage stability, and reduce active network losses. Reactive power optimization primarily involves optimizing the planning of reactive power compensation devices and optimizing voltage and reactive power control. By optimizing the layout and capacity of reactive power compensation devices and adjusting transformer tap positions, a rational distribution of reactive power flows can be achieved, significantly improving the operating efficiency of the power system. Specifically, reactive power optimization can be achieved through the following methods:

[0046] Configuration of reactive power compensation devices: Based on the actual situation of the power system, reactive power compensation devices such as capacitors and reactors are rationally configured to provide the necessary reactive power support; Transformer tap adjustment: By adjusting the tap position of the transformer, the reactive power flow distribution of the power system can be changed, thereby optimizing the voltage level; Intelligent scheduling: Using intelligent algorithms to schedule the power system in real time, allocate reactive power in an optimal manner, and achieve stable operation and efficient utilization of the power system.

[0047] Fault protection is a safety guarantee in flexible power management strategies. It detects and addresses potential fault risks through real-time monitoring and analysis of the power system. For example, when the power system experiences faults such as overload and short circuit, the fault protection device will quickly cut off the fault circuit to prevent the fault from expanding and protect the normal operation of other equipment.

[0048] As can be seen above, the flexible power management module intelligently adjusts power usage strategies based on real-time monitored data and information. This includes adjusting the distribution of power loads, optimizing the utilization of photovoltaic power generation, and controlling the charge and discharge status of energy storage devices. By intelligently adjusting power usage strategies, refined energy management can be achieved, improving the operating efficiency and energy utilization of the power system. By integrating photovoltaic, storage, and direct-flexible technologies, the technical solution of this invention achieves efficient energy utilization and optimized allocation, providing a new energy solution for buildings or parks with significant technical advantages and practical application value.

[0049] The PV-storage coordination performance analysis module analyzes the PV-storage coordination performance and determines whether a PV-storage coordination failure signal is generated through analysis. The module then sends the PV-storage coordination failure signal to the user end. Upon receiving the PV-storage coordination failure signal, the user end issues a corresponding warning to remind the user to strengthen subsequent supervision of the solar photovoltaic panels and energy storage power supply to ensure the safety of subsequent power generation and energy storage. This helps users to reasonably formulate subsequent supervision plans and has a high level of intelligence. The specific analysis process of the PV-storage coordination performance analysis module is as follows:

[0050] A monitoring period is set, preferably, the monitoring period is twenty days; the number of times the corresponding solar photovoltaic panel is marked as an abnormal power generation object during the monitoring period is collected and defined as the abnormal power generation frequency, and the number of times the corresponding energy storage device is marked as an abnormal energy storage object during the monitoring period is collected and defined as the abnormal energy storage frequency;

[0051] The proportion of solar photovoltaic panels whose abnormal power generation frequency exceeds the preset abnormal power generation frequency during the monitoring period is marked as the power generation abnormality value, and the proportion of energy storage devices whose abnormal energy storage frequency exceeds the preset abnormal energy storage frequency threshold during the monitoring period is marked as the energy storage abnormality value. The power generation abnormality value and the energy storage abnormality value are numerically compared with the preset power generation abnormality threshold and the preset energy storage abnormality threshold respectively. If the power generation abnormality value or the energy storage abnormality value exceeds the corresponding preset threshold, it indicates that the overall operating condition of the solar photovoltaic panels or energy storage power sources involved is not good, and the photovoltaic and storage coordination performance is poor, and a photovoltaic and storage coordination unqualified signal is generated.

[0052] Furthermore, if neither the abnormal power generation value nor the abnormal energy storage value exceeds the corresponding preset threshold, the abnormal power generation frequencies of all solar photovoltaic panels are averaged to obtain the photovoltaic panel coordination value, and the abnormal energy storage frequencies of all energy storage devices are averaged to obtain the energy storage coordination value. If any abnormal power generation object or abnormal energy storage object exists within a unit time, a photovoltaic storage potential danger symbol CP-1 is assigned, and the number of times the photovoltaic storage potential danger symbol is assigned within the monitoring period is obtained and marked as the photovoltaic storage potential danger frequency.

[0053] The photovoltaic-storage coordination coefficient LP is calculated by numerically calculating the photovoltaic panel coordination value XF, the energy storage coordination value GY, and the photovoltaic-storage hidden danger frequency WL using the formula LP = a × XF + e × GY + k × WL. Here, a, e, and k are preset weight coefficients with values ​​greater than zero. Furthermore, a larger value of the photovoltaic-storage coordination coefficient LP indicates a worse photovoltaic-storage coordination performance during the monitoring period.

[0054] The photovoltaic-storage coordination coefficient LP is numerically compared with the preset photovoltaic-storage coordination coefficient threshold. If the photovoltaic-storage coordination coefficient LP exceeds the preset photovoltaic-storage coordination coefficient threshold, it indicates that the overall operating condition of the solar photovoltaic panels or energy storage power sources involved is not good, and the photovoltaic-storage coordination performance is poor, then a photovoltaic-storage coordination failure signal is generated.

[0055] Example 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the user end is communicatively connected to the photovoltaic panel detection module. The photovoltaic panel detection module monitors and analyzes the operation of all solar photovoltaic panels, identifies abnormal power generation objects based on the monitoring, and sends all abnormal power generation objects to the photovoltaic-storage coordination performance analysis module and the user end to remind the user to promptly inspect the corresponding solar photovoltaic panels and take corresponding control or maintenance measures to ensure the safe and stable operation of all solar photovoltaic panels. It can also provide information support for the analysis process of the photovoltaic-storage coordination performance analysis module to ensure the accuracy of its analysis results. The specific analysis process of the photovoltaic panel detection module is as follows:

[0056] A number of detection periods are set within a unit of time, and the average light intensity and the power generation of the corresponding solar photovoltaic panel during the corresponding detection period are collected. The ratio of the power generation of the solar photovoltaic panel to the average light intensity is marked as a power generation analysis value, wherein the power generation analysis value should be within an appropriate range; the power generation analysis value is numerically compared with a preset power generation analysis value range. If the power generation analysis value is not within the preset power generation analysis value range, it indicates that the power generation condition of the corresponding solar photovoltaic panel during the corresponding detection period is abnormal, and the corresponding detection period is marked as an abnormal power generation period;

[0057] The real-time orientation of the corresponding solar panel is collected. It should be noted that the orientation of the solar photovoltaic panel will automatically adjust according to the direction of light. The deviation angle of the real-time orientation compared to the current standard orientation is marked as an orientation anomaly value. The orientation anomaly value is numerically compared with a preset orientation anomaly threshold. If the orientation anomaly value exceeds the preset orientation anomaly threshold, it indicates that the orientation of the corresponding solar photovoltaic panel at the current moment is inaccurate, and the corresponding orientation anomaly value is marked as an orientation feature value.

[0058] The number of abnormal power generation periods per unit time is obtained and the ratio thereof is calculated with the total number of detection periods to obtain the power generation period abnormality value, and the number of direction characteristic values ​​per unit time is calculated with the ratio thereof with the number of direction abnormal values ​​to obtain the power generation direction abnormality value;

[0059] The photovoltaic panel detection value GM of the corresponding solar photovoltaic panel is calculated by weighting and summing the power generation period abnormal value SY and the power generation direction abnormal value QP using the formula GM = uy × SY + up × QP. Here, uy and up are preset weight coefficients with values ​​greater than zero. Furthermore, the larger the value of the photovoltaic panel detection value GM, the worse the power generation performance of the corresponding solar photovoltaic panel per unit time, and the greater the probability of an abnormality.

[0060] The photovoltaic panel detection value GM is numerically compared with the preset photovoltaic panel detection threshold. If the photovoltaic panel detection value GM exceeds the preset photovoltaic panel detection threshold, it indicates that the power generation performance of the corresponding solar photovoltaic panel per unit time is poor and the probability of abnormality is high, then the corresponding solar photovoltaic panel is marked as an abnormal power generation object.

[0061] Example 3: Figure 2As shown, the difference between this embodiment and the first and second embodiments is that the user end is communicatively connected to the energy storage detection module. The energy storage detection module monitors and analyzes the operation of all energy storage devices, identifies abnormal energy storage objects based on the monitoring, and sends all abnormal energy storage objects to the photovoltaic-storage coordination performance analysis module and the user end to remind the user to promptly inspect the corresponding energy storage devices and take corresponding control or maintenance measures, thereby ensuring the safe and stable operation of all energy storage devices. It can also provide information support for the analysis process of the photovoltaic-storage coordination performance analysis module, further ensuring the accuracy of its analysis results. The specific analysis process of the energy storage detection module is as follows:

[0062] The actual power consumption and output of the corresponding energy storage device per unit time are collected, and the difference between the actual power consumption and the output power is calculated to obtain the power self-loss value; the internal temperature and noise data of the corresponding energy storage device are collected and marked as the energy storage internal temperature value and the energy storage noise value, respectively. The energy storage internal temperature value and the energy storage noise value are numerically compared with the preset energy storage internal temperature threshold and the preset energy storage noise threshold, respectively. If the energy storage internal temperature value or the energy storage noise value exceeds the corresponding preset threshold, it is determined that the corresponding energy storage device is in an energy storage risk state;

[0063] The total duration of the corresponding energy storage device in the energy storage risk state per unit time is obtained and marked as the energy storage risk duration value, and the frequency of occurrences in which the corresponding energy storage device is in the energy storage risk state for a single duration exceeding the corresponding preset duration threshold per unit time is marked as the energy storage risk frequency value;

[0064] The energy storage detection value TW is calculated by numerically calculating the power self-loss value GS, the energy storage risk time value FN, and the energy storage risk frequency value PX using the formula TW = cp × GS + hy × FN + tn × PX. Here, cp, hy, and tn are preset weight coefficients greater than zero. The larger the value of the energy storage detection value TW, the worse the operating condition of the corresponding energy storage device per unit time, and the greater the probability of an abnormality.

[0065] The energy storage detection value TW is numerically compared with the preset energy storage detection threshold. If the energy storage detection value TW exceeds the preset energy storage detection threshold, it indicates that the operating condition of the corresponding energy storage device per unit time is poor and the probability of abnormality is high, and the corresponding energy storage device is marked as an abnormal energy storage object.

[0066] The working principle of the present invention is as follows: when in use, the integrated photovoltaic power generation module utilizes the solar photovoltaic panel to convert solar energy into electrical energy, the energy storage and allocation module stores the excess electrical energy generated by photovoltaic power generation, and releases the electrical energy when there is insufficient light or when electricity consumption is at peak times; the DC distribution conversion module adopts a DC distribution network to transmit and distribute the DC power generated by the integrated photovoltaic power generation module and the energy storage allocation module to various loads within the building or park, reducing losses during the energy conversion process and improving energy transmission efficiency; the flexible power management module monitors the power load, photovoltaic power generation and charging and discharging status of the energy storage device within the building or park in real time, intelligently adjusts the power consumption strategy, and realizes refined management of electric energy, and analyzes the photovoltaic and storage coordination performance through the photovoltaic and storage coordination performance analysis module, and strengthens subsequent supervision of the solar photovoltaic panels and energy storage power sources when a photovoltaic and storage coordination unqualified signal is generated to ensure the safety of subsequent power generation and energy storage, which is conducive to users to reasonably formulate subsequent supervision plans, and has a high level of intelligence.

[0067] The above formulas are all dimensionless and calculated by taking their numerical values. The formula is a formula for the latest real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made based on the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can well understand and use the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A comprehensive energy utilization management platform based on solar-storage direct-flexible technology, characterized by: It includes an integrated photovoltaic power generation module, an energy storage and dispatching module, a DC power distribution conversion module, a flexible power management module, a photovoltaic and storage coordination performance analysis module and a user end; the integrated photovoltaic power generation module uses solar photovoltaic panels to convert solar energy into electrical energy, and transmits the generated electrical energy to the energy storage and dispatching module and the DC power distribution conversion module; The energy storage and dispatching module is used to store excess electricity generated by photovoltaic power generation and release electricity when there is insufficient sunlight or when electricity consumption is at peak. The DC power distribution conversion module transmits and distributes the DC power generated by the integrated photovoltaic power generation module and the energy storage and dispatching module to various loads in the building or park. The flexible electricity management module monitors the power load, photovoltaic power generation and charging and discharging status of the energy storage device in the building or park in real time, intelligently adjusts the electricity consumption strategy, and sends the monitoring information and adjustment information to the user end for display; the photovoltaic and storage coordination performance analysis module analyzes the photovoltaic and storage coordination performance, and determines whether to generate a photovoltaic and storage coordination failure signal through analysis, and sends the photovoltaic and storage coordination abnormal signal to the user end. When the user end receives the photovoltaic and storage coordination failure signal, it will issue a corresponding warning.

2. The comprehensive energy utilization management platform based on photovoltaic storage direct flexible technology according to claim 1 is characterized in that: The flexible power management module has the functions of load forecasting, power quality analysis, reactive power optimization and fault protection. Among them, load forecasting is the basic link of flexible power management. By using the load forecasting method to analyze historical data and real-time data, the law and trend of load changes are obtained and the future load changes are predicted accordingly. Power quality analysis involves real-time monitoring and analysis of power quality parameters including voltage, current, and frequency. Power quality problems, including voltage fluctuations and harmonic pollution, are discovered through analysis of these data. Appropriate measures are taken to improve the power quality problems discovered. Reactive power optimization distributes the reactive power flow of the power system reasonably to maintain the voltage level of the system, improve voltage stability and reduce active network losses; fault protection detects and handles potential fault risks through real-time monitoring and analysis of the power system.

3. The integrated energy utilization management platform based on solar-storage-direct-flexible technology according to claim 2 is characterized in that: The load forecasting methods used in load forecasting include unit consumption method, trend extrapolation method, elastic coefficient method, time series method, grey model method, Delphi method, neural network method, optimal combination forecasting method and wavelet analysis forecasting technology; reactive power optimization includes two aspects: optimal planning of reactive power compensation devices and voltage reactive power optimization control.

4. The comprehensive energy utilization management platform based on photovoltaic storage direct flexible technology according to claim 1 is characterized in that: The specific analysis process of the photovoltaic-storage coordination performance analysis module is as follows: The percentage of solar photovoltaic panels whose abnormal power generation frequency exceeds the preset abnormal power generation frequency during the monitoring period is marked as the power generation abnormal percentage value, and the percentage of energy storage devices whose abnormal energy storage frequency exceeds the preset abnormal energy storage frequency threshold during the monitoring period is marked as the energy storage abnormal percentage value. If the power generation abnormal percentage value or the energy storage abnormal percentage value exceeds the corresponding preset threshold value, a signal of unqualified light-storage coordination is generated.

5. The comprehensive energy utilization management platform based on photovoltaic storage direct flexible technology according to claim 4 is characterized in that: If both the power generation abnormality value and the energy storage abnormality value do not exceed the corresponding preset thresholds, the photovoltaic storage coordination coefficient is obtained by numerically calculating the photovoltaic panel coordination value, the energy storage coordination value and the photovoltaic storage hidden danger frequency. If the photovoltaic storage coordination coefficient exceeds the preset photovoltaic storage coordination coefficient threshold, a photovoltaic storage coordination failure signal is generated.

6. The comprehensive energy utilization management platform based on photovoltaic storage direct flexible technology according to claim 1 is characterized in that: The user end is connected to the photovoltaic panel detection module and the energy storage detection module through communication. The photovoltaic panel detection module monitors and analyzes the operation of all solar photovoltaic panels, determines abnormal power generation objects based on the operation, and sends all abnormal power generation objects to the photovoltaic storage coordination performance analysis module and the user end. The energy storage detection module monitors and analyzes the operation of all energy storage devices, determines abnormal energy storage objects based on this, and sends all abnormal energy storage objects to the photovoltaic storage coordination performance analysis module and the user end.

7. The integrated energy utilization management platform based on photovoltaic storage direct flexible technology according to claim 6 is characterized in that: The specific analysis process of the photovoltaic panel detection module is as follows: The photovoltaic panel detection value of the corresponding solar photovoltaic panel is obtained by weighted summing up the abnormal meter value during the power generation period and the abnormal value in the power generation direction; if the photovoltaic panel detection value exceeds the preset photovoltaic panel detection threshold, the corresponding solar photovoltaic panel is marked as an abnormal power generation object.

8. The integrated energy utilization management platform based on solar-storage-direct-flexible technology according to claim 6 is characterized in that: The specific analysis process of the energy storage detection module is as follows: The energy storage detection value is obtained by numerically calculating the electric energy self-loss value, the energy storage risk time value and the energy storage risk frequency value. If the energy storage detection value exceeds the preset energy storage detection threshold, the corresponding energy storage device is marked as an abnormal energy storage object.

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