Resonance suppression method and device of energy storage converter

Abstract

The invention relates to the technical field of energy storage converters, and particularly discloses a resonance suppression method and device for an energy storage converter, and the method comprises the steps: monitoring the environment of a transformer area and the actual energy access state of the transformer area, and judging whether the actual energy access state of the transformer area is qualified or not and whether the resonance suppression needs to be carried out or not; analyzing the load condition and the electrical condition of the area with the unqualified actual energy access state, obtaining the switching frequency of the energy storage converter, and determining the resonance suppression starting level of the energy storage converter in combination with the actual energy access state evaluation value of the area, the load condition characteristic value of the area and the electrical condition characteristic value of the area. The problems that a traditional filter cannot provide flexible resonance suppression under different conditions and lacks intelligent real-time monitoring and self-adaptive adjustment capabilities are solved, the accuracy and efficiency of system decision making are improved, the starting level of resonance suppression is flexibly adjusted, excessive resonance is prevented, and the system reliability is improved. And resource waste caused by excessive inhibition can be avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage converters, and in particular to a resonance suppression method and device for energy storage converters. Background Art

[0002] As the proportion of renewable energy (such as solar energy and wind energy) in the power grid continues to increase, the role of energy storage systems is becoming increasingly important. Energy storage systems can balance the output of intermittent energy, provide power stability, and support peak load reduction. Energy storage converters are the core devices that connect energy storage devices (such as batteries) and power grids, and are responsible for realizing the conversion between DC and AC. In energy storage converters, resonance is usually caused by the interaction between the inductance and capacitance elements of the converter and the power grid or load. With the increase of converter switching frequency and the increase of power grid complexity, the resonance problem is more prominent, especially the nonlinear load and switching action of the converter, which will lead to an increase in system harmonics and then cause electrical oscillations. The development of smart grid technology has put forward higher requirements for energy storage systems, requiring them to have high dynamic response capabilities, flexible power control and good stability. Especially when distributed energy is connected in large quantities, energy storage converters, as key interfaces, need to have adaptive resonance suppression capabilities to cope with different loads and power grid fluctuations.

[0003] Nowadays, there are still some deficiencies in the research on resonance suppression of energy storage converters. Specifically, traditional passive filters are usually designed for fixed harmonic frequencies, while the conditions of the power grid and load are dynamically changing, resulting in unsatisfactory effects of traditional filters in different situations. They cannot provide flexible resonance suppression and lack intelligent real-time monitoring and adaptive adjustment capabilities, making it difficult to cope with the complex and rapidly changing operating environment in the power grid. With the large-scale access of distributed renewable energy (such as wind power and solar energy), their intermittent and instability lead to higher fluctuations in grid frequency and voltage. Traditional resonance suppression methods are difficult to effectively cope with this highly dynamic power grid environment. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a resonance suppression method and device for an energy storage converter, which can effectively solve the problems involved in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: In the first aspect, the present invention provides a resonance suppression method for an energy storage converter, comprising the following steps: monitoring the environment in which the substation is located, determining the seasonal scene of the substation and the threshold range of the energy access status of the seasonal scene in the substation; monitoring the actual energy access status of the substation, determining the evaluation value of the actual energy access status of the substation, and judging whether the actual energy access status of the substation is qualified in combination with the threshold range of the energy access status of the seasonal scene in the substation: if the actual energy access status of the substation is qualified, continue to monitor the environment in which the substation is located; if the actual energy access status of the substation is unqualified, it is necessary to suppress the resonance of the substation; analyzing the load conditions of the substation where the actual energy access status is unqualified to obtain the characteristic value of the load condition of the substation; analyzing the electrical conditions of the substation where the actual energy access status is unqualified to obtain the characteristic value of the electrical condition of the substation; obtaining the switching frequency of the energy storage converter and combining the evaluation value of the actual energy access status of the substation, the characteristic value of the load condition of the substation and the characteristic value of the electrical condition of the substation to determine the resonance suppression activation level of the energy storage converter.

[0006] As a further method, the environment in which the substation is located is monitored to determine the seasonal scenes in the substation and the threshold range of energy access status for the seasonal scenes in the substation. The specific analysis process is as follows: obtaining a data set of the environment in which the substation is located, the data set of the environment in which the substation is located specifically includes the ambient temperature, humidity, wind speed, and precipitation in the environment in which the substation is located; based on the obtained data set of the environment in which the substation is located, a comprehensive analysis is performed to obtain characteristic values ​​of the environment in which the substation is located, and the characteristic values ​​of the environment in which the substation is located are used as an analysis basis for determining the seasonal scenes in the substation; the characteristic values ​​of the environment in which the substation is located are stored as designated tags, and the designated tags are compared with the seasonal scenes in the substation corresponding to the designated tags stored in the database to obtain the seasonal scenes in the substation corresponding to the designated tags; the seasonal scenes in the substation are stored as designated codes, and the designated codes are compared with the threshold ranges of energy access status for the seasonal scenes in the substation corresponding to the designated codes stored in the database to obtain the threshold ranges of energy access status for the seasonal scenes in the substation corresponding to the designated codes.

[0007] As a further method, it is determined whether the actual energy access status of the substation is qualified. The specific analysis process is as follows: obtaining the actual energy access status data set of the substation, the actual energy access status data set of the substation specifically includes the deviation of the new energy access proportion of the substation, the deviation of the solar power generation proportion of the substation, and the deviation of the wind power generation of the substation; based on the obtained actual energy access status data set of the substation, a comprehensive analysis is performed to obtain an evaluation value of the actual energy access status of the substation, and the evaluation value of the actual energy access status of the substation is used as an analysis basis for determining whether the actual energy access status of the substation is qualified; comparing the evaluation value of the actual energy access status of the substation with the threshold range of the seasonal scenario energy access status of the substation; if the evaluation value of the actual energy access status of the substation falls within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the evaluation value of the actual energy access status of the substation is qualified, and the environment of the substation continues to be monitored; if the evaluation value of the actual energy access status of the substation does not fall within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the evaluation value of the actual energy access status of the substation is unqualified, and resonance suppression of the substation is required.

[0008] As a further method, the load conditions of the substations with unqualified actual energy access status are analyzed. The specific analysis process is: obtaining the substation load condition data set, and based on the obtained substation load condition data set, a comprehensive analysis is performed to obtain the substation load condition characteristic value, and the substation load condition characteristic value is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter.

[0009] As a further method, the substation load condition data set specifically includes the ratio of the average load to the peak load of the substation, the total load deviation of the main transmission lines in the substation, and the total load deviation of the distribution lines in the substation.

[0010] As a further method, the electrical conditions of the substations with unqualified actual energy access status are analyzed. The specific analysis process is: obtaining the substation electrical condition data set, based on the obtained substation electrical condition data set, comprehensive analysis to obtain the substation electrical condition characteristic value, the substation electrical condition characteristic value is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter.

[0011] As a further method, the electrical condition data set of the substation specifically includes the voltage fluctuation frequency of the substation, the power factor of the substation, and the total harmonic distortion of the substation.

[0012] As a further method, the resonance suppression activation level of the energy storage converter is determined, and the specific analysis process is: obtaining the switching frequency of the energy storage converter and determining the switching frequency deviation of the energy storage converter; importing the switching frequency deviation of the energy storage converter, the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation into the resonance suppression matching model, and comprehensively analyzing to obtain the resonance suppression matching characteristic value, and the resonance suppression matching characteristic value is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter; if the resonance suppression matching characteristic value is not lower than the first resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level three; if the resonance suppression matching characteristic value is lower than the first resonance suppression matching threshold value stored in the database, but not lower than the second resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level two; if the resonance suppression matching characteristic value is lower than the second resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level one.

[0013] As a further method, the resonance suppression matching model, the specific analysis process is:

[0014]

[0015] Where ω is the resonance suppression matching characteristic value, δ is the switching frequency deviation of the energy storage converter, γ is the actual energy access status evaluation value of the substation, α is the load condition characteristic value of the substation, and β is the electrical condition characteristic value of the substation.

[0016] The second aspect of the present invention provides a resonance suppression device for an energy storage converter, including a seasonal scene determination module for a substation, an actual energy access status qualification judgment module, a load condition characteristic value acquisition module, an electrical condition characteristic value acquisition module, and a resonance suppression activation level determination module, wherein: the seasonal scene determination module for the substation is used to monitor the environment in which the substation is located, determine the seasonal scene of the substation and the threshold range of the seasonal scene energy access status of the substation; the actual energy access status qualification judgment module is used to monitor the actual energy access status of the substation, determine the evaluation value of the actual energy access status of the substation, and judge whether the actual energy access status of the substation is qualified in combination with the threshold range of the seasonal scene energy access status of the substation: if the substation If the actual energy access status is qualified, the environment of the substation will continue to be monitored; if the actual energy access status of the substation is unqualified, the substation needs to be resonantly suppressed; the load condition characteristic value acquisition module is used to analyze the load conditions of the substation where the actual energy access status is unqualified, and obtain the load condition characteristic value of the substation; the electrical condition characteristic value acquisition module is used to analyze the electrical conditions of the substation where the actual energy access status is unqualified, and obtain the electrical condition characteristic value of the substation; the resonance suppression activation level determination module is used to obtain the switching frequency of the energy storage converter and determine the resonance suppression activation level of the energy storage converter in combination with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation.

[0017] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0018] (1) The present invention provides a resonance suppression method and device for an energy storage converter, monitors the actual energy access status of the substation and compares it with the seasonal scenario threshold, can detect potential abnormal conditions before the problem becomes serious, and perform preventive maintenance and adjustments in advance to prevent more serious resonance phenomena or system instability. By comprehensively analyzing the actual energy access status, load conditions and electrical conditions of the substation, blind resonance suppression is avoided, and the accuracy and efficiency of system decision-making are improved. By obtaining the switching frequency of the energy storage converter and combining multiple evaluation parameters, the activation level of resonance suppression can be flexibly adjusted. According to different resonance degrees, the system can select different levels of suppression measures, which can prevent excessive resonance and avoid waste of resources caused by excessive suppression.

[0019] (2) The present invention monitors the environment in which the substation is located to determine the seasonal scenario of the substation and the threshold range of the energy access status of the seasonal scenario in the substation. Different seasons have a significant impact on the power demand of the substation. By monitoring the seasonal scenario, the energy distribution is adjusted to ensure that the load distribution of the power grid is more balanced. In the case of large seasonal load changes, a reasonable energy access status threshold can ensure that the voltage and frequency of the power grid remain within a stable range, reduce voltage fluctuations and frequency deviations, and adapt to reasonable load distribution in seasonal scenarios. It can reduce the generation of harmonics, improve the harmonic distortion problem in the power grid, and improve the overall power quality. By continuously monitoring the environment and seasonal scenarios of the substation, the power system can dynamically adjust the energy distribution and control strategy according to the actual situation to achieve intelligent energy management, which can not only improve the flexibility of power grid operation, but also respond to unexpected load fluctuations and environmental changes in a timely manner.

[0020] (3) The present invention determines the resonance suppression activation level of the energy storage converter by obtaining the switching frequency of the energy storage converter and combining it with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation. By combining the switching frequency of the energy storage converter and multiple parameters such as load and electrical conditions, it can more accurately determine whether there is a resonance risk and avoid blind or excessive suppression. It can adaptively adjust according to different operating conditions and environmental conditions to ensure that the suppression measures are effective but not excessive. The load conditions, electrical parameters and switching frequency of the energy storage converter in the power grid may fluctuate with time, environment, season, etc. Acquiring and combining these parameters for analysis can ensure that the resonance suppression measures can respond quickly to dynamic changes and maintain the flexibility and adaptability of the power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0022] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0023] Figure 2 It is a schematic diagram of the connection of the device modules of the present invention.

[0024] Figure 3 This is a flow chart of the present invention for determining whether the actual energy access status of the substation is qualified. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0026] Reference Figure 1 As shown, the first aspect of the present invention provides a resonance suppression method for an energy storage converter, including: monitoring the environment in the substation area, determining the seasonal scene of the substation area and the threshold range of the energy access state of the seasonal scene of the substation area.

[0027] The specific analysis process is as follows: obtaining the data set of the environment in which the substation is located, which specifically includes the ambient temperature, humidity, wind speed and precipitation of the substation; based on the obtained data set of the environment in which the substation is located, a comprehensive analysis is performed to obtain the characteristic values ​​of the environment in which the substation is located, and the characteristic values ​​of the environment in which the substation is located are used as the analysis basis for determining the seasonal scenes in the substation; the characteristic values ​​of the environment in which the substation is located are stored as designated tags, and the designated tags are compared with the seasonal scenes in the substation corresponding to the designated tags stored in the database to obtain the seasonal scenes in the substation corresponding to the designated tags; the seasonal scenes in the substation are stored as designated codes, and the designated codes are compared with the energy access status threshold ranges of the seasonal scenes in the substation corresponding to the designated codes stored in the database to obtain the energy access status threshold ranges of the seasonal scenes in the substation corresponding to the designated codes.

[0028] In a specific embodiment, the ambient temperature refers to the air temperature of the area where the station is located, usually expressed in degrees Celsius (°C). Temperature sensors (such as electronic thermometers, infrared temperature sensors, etc.) are usually used to obtain ambient temperature data and can be installed at key locations in the station to monitor the air temperature in real time. The ambient humidity of the station refers to the moisture content in the air in the area where the station is located, usually expressed in relative humidity (RH), and the unit is percentage (%). Humidity sensors (such as relative humidity sensors, dew point sensors) are used to detect air humidity. The ambient wind speed of the station refers to the air flow speed in the area where the station is located, usually in meters per second (m / s). Wind speed sensors (such as ultrasonic anemometers, mechanical anemometers) are used to monitor ambient wind speed. The ambient precipitation of the station refers to the amount of rainfall in the area where the station is located within one day, usually expressed in millimeters (mm). Rainfall sensors (such as tipping bucket rain gauges, photoelectric rain gauges) are used to measure precipitation.

[0029] It needs to be explained that the above-mentioned high temperature may aggravate the impedance change of power equipment, especially the impedance characteristics of power capacitors and inductors will change at high temperature, which may cause the resonance phenomenon of the system to be more prominent. If the temperature is too high and the energy access state is not matched with the actual environmental scenario, the system may need to start the resonance suppression mechanism to avoid frequency fluctuations or power instability. The increase in humidity may cause the insulation material performance of equipment such as cables and transformers in the power system to decline, thereby affecting the electrical parameters, changing the system impedance characteristics, and increasing the possibility of resonance. When the wind speed is high, the output power volatility of wind power generation equipment may increase, resulting in voltage or frequency fluctuations in the power system. The wind speed adjusts the distribution of temperature and humidity, plays a key role in cooling and heat dissipation, and also affects the distribution of precipitation. Precipitation may cause the insulation performance of cables and equipment to decline, thereby causing impedance changes in the power system, and then causing resonance.

[0030] It should be explained that the seasonal scenario labels generated by the environmental data (temperature, humidity, wind speed, precipitation) can more accurately predict the energy demand and distribution of the substation. Under different seasons or climatic conditions, the energy consumption pattern of the substation may change significantly. The compared threshold range helps to optimize the energy supply. The comparison of the seasonal scenarios of the substation and its energy access status threshold range can ensure that the system always maintains the best energy access state under different seasonal environments, thereby improving the overall efficiency of energy access and ensuring energy reliability and stability. Adjusting the energy access state according to changes in seasonal scenarios can avoid overloading of equipment under unsuitable conditions, extend equipment life, reduce the frequency of maintenance and replacement, improve the reliability and economic operation of the overall system, and help determine whether the energy access state is qualified and whether resonance suppression of the substation is required.

[0031] It needs to be explained that the specific analysis process of the environmental characteristic values ​​of the above-mentioned substation area is as follows:

[0032]

[0033] In the formula, λ is the characteristic value of the environment in which the substation is located, wd is the ambient temperature in the substation, sd is the ambient humidity in the substation, fs is the ambient wind speed in the substation, js is the ambient precipitation in the substation, μ1 is the compensation factor of the set wd, μ2 is the compensation factor of the set sd, μ3 is the compensation factor of the set fs, μ4 is the compensation factor of the set js, and e is a natural constant.

[0034] It needs to be explained that the above-mentioned environmental characteristic values ​​of the substation are calculated through the ambient temperature, humidity, wind speed and precipitation of the substation. Normalization of wd, sd, fs and js can fully reflect the current environmental conditions of the substation. Calculation of environmental characteristic values ​​can accurately assess the impact of external climate on the operation of the power system and equipment. For example, high temperature may cause equipment overheating and humidity may affect the insulation performance of equipment. Based on environmental characteristic values, the system can automatically adjust operating parameters according to real-time environmental changes. For example, under extreme weather conditions, energy storage converters or other power equipment can adjust their working modes in time according to environmental characteristic values ​​to ensure safe operation and optimize performance. Dynamic optimization helps to improve the adaptability and reliability of the power system. The calculation of environmental characteristic values ​​provides an important basis for system decision-making, especially for the dispatch and operation management of energy storage systems, power generation equipment or distribution systems.

[0035] It needs to be explained that the compensation factors of wd, sd, fs, and js set above are obtained from the database. According to the historical data, a mapping set of the historically measured ambient temperature, ambient humidity, ambient wind speed, ambient precipitation and the compensation factors of wd, sd, fs, and js is established to obtain the compensation factors of wd, sd, fs, and js corresponding to the current wd, sd, fs, and js.

[0036] It should be noted that ε1, ε2, ε3, σ1, σ2, σ3, τ1, τ2, and τ3 mentioned below are also obtained through a mapping set of historical data and compensation factors established in a database, that is, the corresponding compensation factors are obtained based on the current data.

[0037] like Figure 3 As shown, the actual energy access status of the substation is monitored, the actual energy access status evaluation value of the substation is determined, and combined with the threshold range of the energy access status of the seasonal scenario in the substation, it is judged whether the actual energy access status of the substation is qualified: if the actual energy access status of the substation is qualified, the environment of the substation will continue to be monitored; if the actual energy access status of the substation is unqualified, the substation needs to be resonantly suppressed.

[0038] The specific analysis process is as follows: obtain the actual energy access status data set of the substation, which specifically includes the new energy access ratio deviation of the substation (the absolute value of the difference between the actual new energy access ratio of the substation and the reference new energy access ratio), the solar power generation ratio deviation of the substation (the absolute value of the difference between the actual solar power generation ratio of the substation and the reference solar power generation ratio), and the wind power generation deviation of the substation (the absolute value of the difference between the actual wind power generation of the substation and the reference wind power generation); based on the obtained actual energy access status data set of the substation, a comprehensive analysis is performed to obtain the actual energy access status evaluation value of the substation, and the actual energy access status evaluation value of the substation is used as The analytical basis for judging whether the actual energy access status of the substation is qualified; comparing the actual energy access status evaluation value of the substation with the threshold range of the seasonal scenario energy access status of the substation; if the actual energy access status evaluation value of the substation falls within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the actual energy access status evaluation value of the substation is qualified, and the environment of the substation continues to be monitored; if the actual energy access status evaluation value of the substation does not fall within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the actual energy access status evaluation value of the substation is unqualified, and the substation needs to be resonantly suppressed.

[0039] It needs to be explained that the above-mentioned deviation in the proportion of new energy access in the substation indicates the difference between the actual proportion of new energy access and the reference value, whether it is a positive or negative difference, which measures the degree of deviation between the actual amount of new energy accessed and the set reference value. The absolute value is used to focus on the size of the deviation, regardless of the direction of the deviation. Smart meters can record the input of new energy and traditional energy. The deviation in the proportion of solar power generation in the substation indicates the deviation between the actual solar energy access proportion in the substation and the reference proportion, which measures whether the solar energy access situation meets expectations and is used to determine whether the current solar energy access is within a reasonable range. Based on photovoltaic inverter monitoring, the deviation in wind power generation in the substation indicates the deviation between the actual wind power generation and the reference value, which is used to evaluate whether the current wind power generation meets expectations. The smaller the deviation, the closer the power generation is to the ideal state. Based on the energy management system (EMS), the actual power generation data from each wind farm or wind turbine is summarized, and the actual wind power access amount is calculated and compared with the reference value.

[0040] It should be explained that the absolute value of the above-mentioned difference in the proportion of new energy access is an overall measurement standard, while the absolute value of the difference in the proportion of solar power generation and the absolute value of the difference in wind power generation respectively evaluate the power generation and access deviations of different types of new energy. The larger the difference of each single item, the more serious the deviation between the actual access and the target of this type of new energy, which will affect the difference in the total access proportion of new energy, and can more comprehensively judge the overall new energy access status of the substation. When the difference between the actual new energy access proportion and the reference proportion is large, especially when the solar or wind energy access deviates significantly from expectations, it may cause power imbalance in the power system. This unbalanced state may cause grid voltage fluctuations, frequency changes or other resonance phenomena. Frequent power generation fluctuations can easily excite the resonance problem of the system, resulting in a decline in power quality or equipment abnormalities. After discovering that the new energy access status is unqualified and taking resonance suppression measures, environmental monitoring of the substation is still very important. Continuous monitoring of these external conditions will help further adjust the energy access strategy and prevent the recurrence of resonance.

[0041] It needs to be explained that the above-mentioned difference between the actual renewable energy access ratio and the reference value can more accurately manage the renewable energy access in different seasons or environments. If the access ratio is too high or too low, it may cause imbalance in the power system and affect the overall stability. Real-time monitoring and evaluation can help to accurately adjust the access volume and ensure that the system is in a qualified state. The changes in solar and wind power generation are greatly affected by environmental factors. Therefore, by comparing the difference between the actual power generation ratio and the reference ratio, it is possible to timely understand whether the contribution of solar and wind energy to the energy of the substation is in line with expectations. Dynamic adjustment can help to better allocate energy resources, avoid over-reliance on a certain type of energy, and prevent energy shortages or overloads. The actual energy access status assessment value of the substation is not within the energy access status threshold range of the seasonal scenario, indicating that the current energy access status may have shown signs of instability, which helps to prevent resonance in the power system, reduce voltage fluctuations and frequency anomalies, and ensure the stability of the power system. A qualified access status can prevent system overload or equipment damage, and ensure a safe and reliable energy supply.

[0042] It should be explained that the specific analysis process of the above-mentioned actual energy access status assessment value is as follows:

[0043]

[0044] In the formula, γ is the actual energy access status assessment value of the substation, bl is the new energy access ratio deviation of the substation, fd is the solar power generation ratio deviation of the substation, dl is the wind power generation deviation of the substation, ε1 is the compensation factor of the set bl, ε2 is the compensation factor of the set fd, and ε3 is the compensation factor of the set dl.

[0045] It should be explained that the above-mentioned actual energy access status assessment value of the substation is calculated through the deviation of the new energy access ratio of the substation, the deviation of the solar power generation ratio of the substation, and the deviation of the wind power generation of the substation. BL, FD, and DL are normalized, and the difference between the actual access ratio of solar energy and wind energy and the reference value is calculated respectively. This can more comprehensively assess the deviation of the new energy access of the substation, help understand the difference between the actual contribution and expectation of different types of new energy (such as solar energy and wind energy) in the power system, so as to identify problems in the access process and accurately assess the deviation of new energy access. The system can better balance the load and power supply to prevent oversupply or undersupply. The actual access status assessment value helps the system to predict possible power supply fluctuations in advance and flexibly adjust the energy scheduling strategy to ensure the stability and efficiency of the system operation. When there is a large difference between the actual value of the new energy access ratio and the reference value, power fluctuations may occur in the power system, which will affect the power quality. By timely evaluating these differences, the system can take measures to smooth power fluctuations to ensure the stability of the accessed power, thereby improving the power quality and reducing the impact of voltage fluctuations or frequency anomalies on equipment.

[0046] The load conditions of the substations where the actual energy access status is unqualified are analyzed to obtain the characteristic values ​​of the load conditions of the substations.

[0047] The specific analysis process is: obtaining a data set of load conditions in the substation, and based on the obtained data set of load conditions in the substation, obtaining a characteristic value of the load conditions in the substation through comprehensive analysis. The characteristic value of the load conditions in the substation is used as an analysis basis for determining the resonance suppression activation level of the energy storage converter.

[0048] It should be explained that the above analysis of the substation load condition data can extract the load condition characteristic value, which can reflect the operating conditions of the substation load and its potential impact on the energy storage converter, thereby helping to determine under what load conditions resonance suppression is more needed. According to the load condition characteristic value, the system can accurately determine whether resonance suppression needs to be enabled and determine the level of enablement to avoid excessive or insufficient suppression measures and ensure the efficiency and accuracy of the suppression strategy. Determining the enablement level of resonance suppression based on the load condition characteristic value can optimize the operating efficiency of the energy storage system. Only enabling higher-level resonance suppression measures when necessary can avoid energy waste and maximize the output efficiency of the energy storage system. When the energy storage converter excessively enables resonance suppression under non-essential conditions, it may increase the operating load of the equipment and cause premature wear of the equipment. Enabling the appropriate level of resonance suppression through the load condition characteristic value can reduce the operating pressure of the energy storage converter and reduce the equipment wear rate. Automatically determining the resonance suppression enablement level of the energy storage converter based on the load condition characteristic value can achieve highly automated management and reduce the risk of manual intervention and misoperation.

[0049] Furthermore, the substation load condition data set specifically includes the ratio of the substation average load to the peak load, the total load deviation of the substation main transmission lines (the absolute value of the difference between the total load of the substation main transmission lines and the total load of the reference main transmission lines), and the total load deviation of the substation distribution lines (the absolute value of the difference between the total load of the substation distribution lines and the total load of the reference distribution lines).

[0050] It should be explained that the ratio of the above-mentioned average load to peak load reflects the volatility of the substation load, and the data is obtained by using smart meters and load monitoring systems. The total load deviation of the main transmission lines in the substation measures the difference between the actual load and the ideal load of the main transmission lines, and is obtained through line load monitoring equipment and smart grid systems. The total load deviation of the distribution lines in the substation evaluates the deviation between the actual load and the target load of the distribution lines, and is obtained through distribution line monitoring equipment and power dispatching systems.

[0051] It needs to be explained that the load volatility of the above-mentioned substations is reflected through the peak-to-average load ratio, which directly affects the load pressure of the transmission lines and distribution lines. The greater the load fluctuation, the greater the load difference between the transmission lines and distribution lines, and the more difficult it is to ensure the stability of the system. If the difference between the actual load of the transmission lines and distribution lines and the reference load is small, it means that the system load distribution is relatively balanced and the power network operation is more stable and efficient. When the difference is large, it may lead to unbalanced power transmission and distribution, and the operating efficiency and safety of the system will be affected.

[0052] It should be explained that the specific analysis process of the above-mentioned load condition characteristic value is as follows:

[0053]

[0054] Wherein, α is the characteristic value of the load condition in the substation, bi is the ratio of the average load to the peak load in the substation, zx is the total load deviation of the main transmission lines in the substation, px is the total load deviation of the distribution lines in the substation, σ1 is the compensation factor of the set bi, σ2 is the compensation factor of the set zx, and σ3 is the compensation factor of the set px.

[0055] It should be explained that the above-mentioned substation load condition characteristic values ​​are calculated through the ratio of the substation average load to the peak load, the total load deviation of the main transmission lines in the substation, and the total load deviation of the distribution lines in the substation. Bi, zx, and px are normalized to calculate the ratio of the average load to the peak load in the substation. The system can quantify the volatility of the substation load and identify the difference between the peak and average demand in load operation. The larger the ratio, the more stable the load, and the smaller the ratio, the greater the load volatility, which provides an important reference for the system's load stability. Assessing load volatility helps identify unbalanced or violently fluctuating areas in the system, thereby optimizing load management and avoiding frequent load changes that affect system stability and equipment life. Through the calculation of these differences, it is possible to promptly discover uneven load distribution, identify potential risks in the transmission and distribution networks, and prevent damage to the system caused by excessive or insufficient load, thereby improving system safety.

[0056] The electrical conditions of the substations where the actual energy access status is unqualified are analyzed to obtain the characteristic values ​​of the electrical conditions of the substations.

[0057] The specific analysis process is: obtaining the substation electrical condition data set, based on the obtained substation electrical condition data set, comprehensive analysis to obtain the substation electrical condition characteristic value, the substation electrical condition characteristic value is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter.

[0058] It should be explained that the above-mentioned electrical condition characteristic values ​​reflect the electrical operating environment of the substation. The analysis of these characteristic values ​​can determine whether the current power grid state is prone to cause resonance, thereby accurately determining whether resonance suppression needs to be enabled and the specific level of activation. The electrical conditions of the substation (such as voltage fluctuations, frequency anomalies, etc.) may cause instability in the power grid, which in turn leads to resonance. If the electrical condition characteristic values ​​exceed the safe range, the system can promptly enable the appropriate level of resonance suppression to avoid system oscillation and instability due to abnormal electrical conditions. By comprehensively analyzing the electrical conditions of the substation, the operating mode of the energy storage converter can be dynamically adjusted according to actual needs. If the electrical conditions indicate that the system is in a relatively stable state, the energy storage converter can operate in low power consumption mode to reduce unnecessary energy consumption.

[0059] Furthermore, the electrical condition data set of the substation includes the voltage fluctuation frequency of the substation, the power factor of the substation, and the total harmonic distortion of the substation.

[0060] It needs to be explained that the above-mentioned voltage fluctuation frequency refers to the frequency of voltage change over time in the substation power grid. Voltage fluctuations are usually caused by load changes, switching of power factor compensation equipment, etc. Frequent voltage fluctuations will affect the stable operation of the equipment and even cause power system failures. It is obtained based on the power quality monitor. The power factor is the ratio of active power to apparent power in the power grid, which indicates the proportion of actually effectively utilized power in the total input power. The power factor value ranges from 0 to 1. When it is close to 1, it means that the power grid is more efficient and less energy is wasted. A power factor that is too low means that there is a large amount of reactive power in the system, which may lead to a decrease in power transmission efficiency. It is obtained based on the power factor meter. The total harmonic distortion refers to the size of the harmonic content in the power grid, which is the ratio of the sum of all harmonics to the fundamental component, usually expressed as a percentage, and is obtained based on a harmonic analyzer.

[0061] It needs to be explained that the high harmonic content mentioned above will lead to a decrease in power factor, and low power factor will aggravate the current waveform distortion of the system and further increase the harmonic content. The presence of harmonics will also cause voltage fluctuations, making the system operation more unstable. The increase in voltage fluctuation frequency will affect the control of power factor and may amplify the impact of harmonics in the system, thereby further deteriorating the power quality of the system. When the voltage fluctuation frequency increases, the reactive power demand in the system changes greatly, and the power factor is difficult to maintain at an ideal level. The impact of harmonics becomes more significant. Low power factor and high harmonic content will lead to more frequent voltage fluctuations, forming a vicious circle, further reducing the stability of the system and power quality.

[0062] It should be explained that the specific analysis process of the above-mentioned characteristic values ​​of the electrical conditions of the substation is as follows:

[0063]

[0064] In the formula, β is the characteristic value of the electrical condition of the substation, bdp is the voltage fluctuation frequency of the substation, ys is the power factor of the substation, jb is the total harmonic distortion of the substation, τ1 is the compensation factor of the set bdp, τ2 is the compensation factor of the set ys, and τ3 is the compensation factor of the set jb.

[0065] It needs to be explained that the above-mentioned characteristic values ​​of electrical conditions in the substation are calculated through the voltage fluctuation frequency, power factor and total harmonic distortion of the substation. BDP, YS and JB are normalized, and the voltage fluctuation frequency, power factor and total harmonic distortion are analyzed, which can more comprehensively reflect the operating status of the power system in the substation, covering multiple aspects such as voltage stability, system energy efficiency and power quality, and help to understand the overall health of the power system. The voltage fluctuation frequency reflects the stability of the voltage. Frequent voltage fluctuations may affect the operating efficiency and life of power equipment. By calculating the voltage fluctuation frequency, the system can adopt more effective voltage regulation strategies to maintain voltage stability and ensure safe and reliable operation of equipment. Total harmonic distortion and power factor changes may cause resonance in the system, affecting the stability of the power system. Through the characteristic values ​​of electrical conditions, the system can predict the risk of resonance in advance and take corresponding suppression measures to avoid grid failures or equipment damage caused by resonance.

[0066] The switching frequency of the energy storage converter is obtained and combined with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation to determine the resonance suppression activation level of the energy storage converter.

[0067] The specific analysis process is as follows: obtaining the switching frequency of the energy storage converter, determining the switching frequency deviation of the energy storage converter (the absolute value of the difference between the switching frequency of the energy storage converter and the reference switching frequency); importing the switching frequency deviation of the energy storage converter, the actual energy access status assessment value of the substation, the characteristic value of the load condition of the substation and the characteristic value of the electrical condition of the substation into the resonance suppression matching model, and comprehensively analyzing to obtain the resonance suppression matching characteristic value, which is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter; if the resonance suppression matching characteristic value is not lower than the first resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level three; if the resonance suppression matching characteristic value is lower than the first resonance suppression matching threshold value stored in the database, but not lower than the second resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level two; if the resonance suppression matching characteristic value is lower than the second resonance suppression matching threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level one.

[0068] It should be explained that the resonance suppression matching characteristic value obtained by comprehensive analysis of the difference between the switching frequency and the reference frequency of the energy storage converter, the actual operating conditions and load of the substation, and the electrical characteristics can better reflect the current operating status and resonance risk of the system. The dynamic matching model can adjust the resonance suppression activation level according to the real-time situation, so that the system can adapt to different load changes and power grid environments, and can effectively deal with the resonance phenomenon in the system to avoid excessive or insufficient suppression operations. The resonance suppression matching characteristic value is used as the basis for determining the resonance suppression activation level of the energy storage converter, and different suppression levels can be accurately set according to the actual needs of the system. Based on hierarchical management, the system can enable resonance suppression measures of different intensities under different operating conditions to ensure stronger suppression when the resonance risk is high and reduce energy consumption when the risk is low. The resonance phenomenon will affect the power quality of the system and reduce the efficiency and stability of the power system. By acquiring the switching frequency of the energy storage converter, the energy access status of the substation and other data in real time, and importing the resonance suppression matching model, the system can accurately predict and suppress the resonance phenomenon to prevent voltage fluctuations, frequency anomalies and other problems in the power grid. Intelligent resonance suppression management improves the automation level of the system, reduces manual intervention, and improves the response speed and flexibility of the system.

[0069] Furthermore, the resonance suppression matching model, the specific analysis process is:

[0070]

[0071] Where ω is the resonance suppression matching characteristic value, δ is the switching frequency deviation of the energy storage converter, γ is the actual energy access status evaluation value of the substation, α is the load condition characteristic value of the substation, and β is the electrical condition characteristic value of the substation.

[0072] It should be explained that the above-mentioned resonance suppression matching characteristic value is calculated through the switching frequency deviation of the energy storage converter, the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation. Through the comprehensive analysis of the switching frequency, energy access status, load condition and electrical condition of the energy storage converter, the resonance risk can be identified more accurately, and the comprehensive resonance suppression matching characteristic value helps to accurately judge whether resonance suppression needs to be enabled, and determine the appropriate suppression level (primary, secondary or tertiary). The resonance suppression matching characteristic value is dynamically adjusted according to the real-time data changes of the energy storage converter, load, energy access and electrical conditions to ensure that the appropriate suppression strategy can be selected under different system conditions (such as load fluctuations, changes in power quality), so that the system can be dynamically adjusted according to the actual situation to ensure the efficiency and flexibility of the resonance suppression measures. The resonance suppression matching characteristic value provides the basis for the system's automatic decision-making, and can be intelligently adjusted according to real-time conditions without human intervention. This intelligent resonance suppression management reduces the error of human judgment and improves the system's adaptability.

[0073] In a specific embodiment, the ambient temperature of the substation is 30°C, the ambient humidity of the substation is 70%, the ambient wind speed of the substation is 5m / s, the ambient precipitation of the substation is 10mm, μ1=0.005.μ2=0.02, μ3=0.1, μ4=0.01, e=2.718, and the calculated environmental characteristic value of the substation is 3.3006. The seasonal scene of the substation is spring with a small amount of precipitation, and the energy access status threshold range is [-10, 10].

[0074] It is monitored that the difference between the actual wind power generation in the substation and the reference value is 50kW, the difference between the actual solar power generation ratio and the reference value is 6%, and the difference between the actual new energy access ratio and the reference value is 10%. ε1=0.5, ε2=0.3, ε3=0.4, and the calculated energy access status evaluation value is -19.249, which does not fall within the substation's seasonal scenario energy access status threshold range. The actual energy access status of the substation corresponding to the actual energy access status evaluation value of the substation is unqualified, and resonance suppression of the substation is required.

[0075] The ratio of the average load to the peak load in the substation is 0.6, the absolute value of the difference between the total load of the main transmission lines in the substation and the reference value is 200kW, the absolute value of the difference between the total load of the distribution lines in the substation and the reference value is 150kW, σ1=0.1, σ2=0.05, σ3=0.07, and the calculated load condition characteristic value is 0.06238.

[0076] The voltage fluctuation frequency of the substation is 0.05Hz, the power factor of the substation is 0.92, the total harmonic distortion of the substation is 3%, τ1=0.1, τ2=0.02, τ3=0.05, and the calculated electrical condition characteristic value is 0.15005.

[0077] The calculated resonance suppression matching characteristic value is 0.0452, the first resonance suppression matching threshold is 0.3, and the second resonance suppression matching threshold is 0.03. Since 0.0452 is greater than 0.03 but less than 0.3, the resonance suppression activation level of the energy storage converter is level 2, which avoids excessive activation of resonance suppression when it is not necessary, reduces equipment wear, and extends service life.

[0078] Reference Figure 2 As shown, the second aspect of the present invention provides a resonance suppression device for an energy storage converter, a station seasonal scenario determination module, an actual energy access status qualification judgment module, a load condition characteristic value acquisition module, an electrical condition characteristic value acquisition module and a resonance suppression activation level determination module.

[0079] The seasonal scene determination module of the substation area is used to monitor the environment of the substation area, determine the seasonal scene of the substation area and the threshold range of the energy access status of the seasonal scene of the substation area.

[0080] The actual energy access status qualification judgment module is used to monitor the actual energy access status of the substation, determine the actual energy access status evaluation value of the substation, and judge whether the actual energy access status of the substation is qualified in combination with the threshold range of the seasonal scene energy access status of the substation: if the actual energy access status of the substation is qualified, continue to monitor the environment in which the substation is located; if the actual energy access status of the substation is unqualified, resonance suppression of the substation is required.

[0081] The load condition characteristic value acquisition module is used to analyze the load conditions of the substation where the actual energy access status is unqualified, and obtain the load condition characteristic value of the substation.

[0082] The electrical condition characteristic value acquisition module is used to analyze the electrical conditions of the substation where the actual energy access status is unqualified, and obtain the electrical condition characteristic value of the substation.

[0083] The resonance suppression activation level determination module is used to obtain the switching frequency of the energy storage converter and determine the resonance suppression activation level of the energy storage converter in combination with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation.

[0084] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A resonance suppression method for an energy storage converter, characterized in that: The following steps are involved: Monitor the environment of the substation area, determine the seasonal scene of the substation area and the threshold range of the energy access status of the seasonal scene of the substation area; Monitor the actual energy access status of the substation, determine the evaluation value of the actual energy access status of the substation, and judge whether the actual energy access status of the substation is qualified based on the threshold range of the energy access status in seasonal scenarios of the substation: If the actual energy access status of the substation is qualified, continue to monitor the environment of the substation; If the actual energy access status of the substation is not up to standard, the substation needs to be resonantly suppressed; Analyze the load conditions of the substations where the actual energy access status is unqualified, and obtain the characteristic values ​​of the load conditions of the substations; Analyze the electrical conditions of the substations where the actual energy access status is unqualified, and obtain the characteristic values ​​of the electrical conditions of the substations; The switching frequency of the energy storage converter is obtained and combined with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation to determine the resonance suppression activation level of the energy storage converter.

2. The resonance suppression method of the energy storage converter according to claim 1, characterized in that: The monitoring of the environment of the substation area determines the seasonal scene of the substation area and the threshold range of the energy access state of the seasonal scene of the substation area. The specific analysis process is as follows: Obtaining a data set of the environment in which the substation is located, the data set of the environment in which the substation is located specifically includes the environment temperature in which the substation is located, the environment humidity in which the substation is located, the environment wind speed in which the substation is located, and the environment precipitation in which the substation is located; Based on the acquired data set of the environment in which the substation is located, a comprehensive analysis is performed to obtain the characteristic values ​​of the environment in which the substation is located. The characteristic values ​​of the environment in which the substation is located serve as the analysis basis for determining the seasonal scenes in the substation. The characteristic value of the environment in which the substation is located is stored as a designated tag, and the designated tag is compared with the seasonal scene of the substation corresponding to each designated tag stored in the database to obtain the seasonal scene of the substation corresponding to the designated tag; The seasonal scene of the substation is stored as a designated code, and the designated code is compared with the seasonal scene energy access status threshold range of the substation corresponding to each designated code stored in the database to obtain the seasonal scene energy access status threshold range of the substation corresponding to the designated code.

3. The resonance suppression method of the energy storage converter according to claim 1, characterized in that: The specific analysis process of judging whether the actual energy access status of the substation is qualified is as follows: Obtaining a data set of actual energy access status in the substation area, the data set of actual energy access status in the substation area specifically includes a deviation of the proportion of new energy access in the substation area, a deviation of the proportion of solar power generation in the substation area, and a deviation of the amount of wind power generation in the substation area; Based on the acquired actual energy access status data set of the substation, a comprehensive analysis is performed to obtain an actual energy access status evaluation value of the substation, which is used as an analysis basis for judging whether the actual energy access status of the substation is qualified; Compare the actual energy access status assessment value of the substation area with the energy access status threshold range of the substation area in seasonal scenarios; If the actual energy access status assessment value of the substation falls within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the actual energy access status assessment value of the substation is qualified, and the environment of the substation continues to be monitored; If the actual energy access status evaluation value of the substation does not fall within the threshold range of the seasonal scenario energy access status of the substation, the actual energy access status of the substation corresponding to the actual energy access status evaluation value of the substation is unqualified, and resonance suppression of the substation is required.

4. The resonance suppression method of the energy storage converter according to claim 1, characterized in that: The load conditions of the substations where the actual energy access status is unqualified are analyzed, and the specific analysis process is as follows: A substation load condition data set is obtained, and based on the obtained substation load condition data set, a substation load condition characteristic value is obtained through comprehensive analysis, and the substation load condition characteristic value is used as an analysis basis for determining the resonance suppression activation level of the energy storage converter.

5. The resonance suppression method of the energy storage converter according to claim 4, characterized in that: The substation load condition data set specifically includes the ratio of the substation average load to the peak load, the total load deviation of the substation main transmission lines, and the total load deviation of the substation distribution lines.

6. The resonance suppression method of the energy storage converter according to claim 1, characterized in that: The electrical conditions of the substations where the actual energy access status is unqualified are analyzed, and the specific analysis process is as follows: A data set of electrical conditions of the substation is obtained, and based on the obtained data set of electrical conditions of the substation, a comprehensive analysis is performed to obtain a characteristic value of the electrical conditions of the substation, which is used as an analysis basis for determining the resonance suppression activation level of the energy storage converter.

7. The resonance suppression method of the energy storage converter according to claim 6, characterized in that: The substation electrical condition data set specifically includes the substation voltage fluctuation frequency, the substation power factor, and the substation total harmonic distortion.

8. The resonance suppression method of the energy storage converter according to claim 1, characterized in that: The specific analysis process of determining the resonance suppression activation level of the energy storage converter is as follows: Obtaining the switching frequency of the energy storage converter and determining the switching frequency deviation of the energy storage converter; The switching frequency deviation of the energy storage converter, the actual energy access status evaluation value of the substation, the characteristic value of the load condition of the substation and the characteristic value of the electrical condition of the substation are introduced into the resonance suppression matching model, and the resonance suppression matching characteristic value is obtained through comprehensive analysis. The resonance suppression matching characteristic value is used as the analysis basis for determining the resonance suppression activation level of the energy storage converter. If the resonance suppression matching characteristic value is not lower than the resonance suppression matching first threshold value stored in the database, the resonance suppression activation level of the energy storage converter is level three; If the resonance suppression matching characteristic value is lower than the first resonance suppression matching threshold value stored in the database, but not lower than the second resonance suppression matching threshold value stored in the database, the resonance suppression enabling level of the energy storage converter is level 2; If the resonance suppression matching characteristic value is lower than the resonance suppression matching second threshold value stored in the database, the resonance suppression enabling level of the energy storage converter is level one.

9. The resonance suppression method of the energy storage converter according to claim 8, characterized in that: The specific analysis process of the resonance suppression matching model is as follows: Where ω is the resonance suppression matching characteristic value, δ is the switching frequency deviation of the energy storage converter, γ is the actual energy access status evaluation value of the substation, α is the load condition characteristic value of the substation, and β is the electrical condition characteristic value of the substation.

10. A resonance suppression device for an energy storage converter, applied to a resonance suppression method for an energy storage converter as claimed in any one of claims 1 to 9, characterized in that: It includes a seasonal scenario determination module for the substation area, a qualified judgment module for the actual energy access status, a load condition characteristic value acquisition module, an electrical condition characteristic value acquisition module and a resonance suppression activation level determination module, wherein: The seasonal scene determination module of the substation area is used to monitor the environment of the substation area, determine the seasonal scene of the substation area and the threshold range of the energy access state of the seasonal scene of the substation area; The actual energy access status qualification judgment module is used to monitor the actual energy access status of the substation, determine the actual energy access status evaluation value of the substation, and judge whether the actual energy access status of the substation is qualified in combination with the threshold range of the seasonal scene energy access status of the substation: If the actual energy access status of the substation is qualified, continue to monitor the environment of the substation; If the actual energy access status of the substation is not up to standard, the substation needs to be resonantly suppressed; The load condition characteristic value acquisition module is used to analyze the load condition of the substation where the actual energy access status is unqualified to obtain the load condition characteristic value of the substation; The electrical condition characteristic value acquisition module is used to analyze the electrical conditions of the substation area where the actual energy access status is unqualified, and obtain the electrical condition characteristic value of the substation area; The resonance suppression activation level determination module is used to obtain the switching frequency of the energy storage converter and determine the resonance suppression activation level of the energy storage converter in combination with the actual energy access status evaluation value of the substation, the load condition characteristic value of the substation and the electrical condition characteristic value of the substation.

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