A coal mine power grid operation optimization method and system based on energy storage composite control

Abstract

The application discloses a coal mine power grid operation optimization method and system based on energy storage composite control, belongs to the technical field of coal mine power grid operation optimization, and comprises the following steps: S10, collecting operation parameters of a coal mine power grid, wherein the operation parameters comprise operation parameters of key components of the coal mine power grid, the key components comprise a power supply, a power transmission line and power transformation and distribution equipment, and an electrical model is constructed based on the operation parameters of the key components; the operation parameters comprise power, load, current and voltage; S20, performing characteristic analysis on the operation parameters, and configuring an energy storage system for the coal mine power grid according to the analyzed characteristics. The application can predict the operation state of the coal mine power grid in advance, take optimization measures in time and enhance the power supply reliability of the coal mine power grid by analyzing the change law of the operation parameters in different production periods and optimizing energy storage control based on the law.

Description

Technical Field

[0001] This invention relates to the field of coal mine power grid operation optimization technology, and in particular to a coal mine power grid operation optimization method and system based on energy storage composite control. Background Technology

[0002] As a crucial infrastructure for coal mine production, the stable and efficient operation of coal mine power grids is essential for ensuring safe production. Under the dual pressures of environmental pollution and the fossil fuel crisis, distributed power generation technologies such as wind and solar power have developed rapidly, and their role in power supply and low-carbon living is becoming increasingly apparent. However, coal mine power grids still face challenges such as large load fluctuations, high requirements for power supply reliability, and difficulties in guaranteeing power quality.

[0003] Regarding this research, application CN201910696249.3 provides a control method for a combined cooling, heating, and power (CCHP) system incorporating an electrothermal energy storage device. This technical solution includes steps such as acquiring load data, limiting the charging power of the energy storage system, limiting the total amount of surplus energy stored, charging the grid during low-electricity-price periods, discharging the energy storage system, storing heat in the thermal storage system, and releasing heat from the thermal storage system. This technical solution combines the power and capacity limitations of the energy storage and thermal storage devices to optimize the energy distribution of the system, thereby improving unit operating efficiency and energy utilization efficiency, and reducing system operating costs.

[0004] Another application, CN201610914762.1, provides an energy management optimization method based on composite energy storage. The composite energy storage system consists of a supercapacitor and a battery. This technical solution distributes the total power of the composite energy storage through a low-pass filter, allowing the supercapacitor and battery to respectively handle the high-frequency and low-frequency components of the fluctuating power. Through constant power control of the bidirectional DC / DC1 converter of the battery and constant bus voltage control of the bidirectional DC / DC2 converter of the supercapacitor, as well as the control strategy of the bidirectional DC / AC converter, the network loss of the distribution network is reduced, the utilization efficiency of new energy sources is improved, the power fluctuations during microgrid grid connection are effectively smoothed, and the power quality of the regional power grid is improved.

[0005] However, energy storage composite control strategies are often quite complex, requiring consideration of various factors and constraints, such as grid power balance, power quality, and energy storage system status. In actual coal mine power grid operation, facing complex operating conditions and variable load demands, the control strategies of the above-mentioned technical solutions struggle to make quick and accurate decisions and adjustments, lacking adaptability and resulting in unsatisfactory optimization effects. Summary of the Invention

[0006] In view of the problems existing in the field of coal mine power grid operation optimization technology, the present invention is proposed.

[0007] Therefore, one of the objectives of this invention is to provide a method and system for optimizing the operation of a coal mine power grid based on energy storage composite control. By monitoring the power flow of the coal mine power grid and monitoring and adjusting voltage sags and harmonics, the power quality of the coal mine power grid is effectively improved. Furthermore, by analyzing the variation patterns of operating parameters during different production periods and optimizing energy storage control based on these patterns, the operating status of the coal mine power grid can be predicted in advance, and optimization measures can be taken in a timely manner, thereby enhancing the reliability of power supply to the coal mine power grid.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0009] On the one hand, this invention provides a method for optimizing the operation of a coal mine power grid based on energy storage composite control, comprising the following steps:

[0010] S10: Collect operating parameters of the coal mine power grid, including operating parameters of key components of the coal mine power grid, including power sources, transmission lines and power distribution equipment, and construct an electrical model based on the operating parameters of the key components; the operating parameters include power, load, current and voltage;

[0011] S20: Perform feature analysis on the operating parameters, and configure the energy storage system for the coal mine power grid based on the analyzed features;

[0012] S30: Based on the characteristic analysis of the operating parameters, obtain the regular changes of the operating parameters, and optimize the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control.

[0013] S40: Differentiate the aforementioned regular changes, including regular changes during shift handover periods, regular changes during peak production periods, regular changes during equipment maintenance periods, and regular changes during nighttime off-peak periods, and analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid;

[0014] S50: Generate datasets on different regular changes based on the correlation effects, collect operating parameters corresponding to the regular changes in each dataset, and obtain a set of operating parameters that appear most frequently from the operating parameters; mark the operating parameters as reference operating parameters, wherein the number of reference operating parameters is at least 10;

[0015] S60: Obtain the regular changes corresponding to the reference operating parameters, and preset a strategy for optimizing the energy storage control of the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in a future time period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular changes.

[0016] In a preferred embodiment of the present invention, in step S20, the operating parameters are subjected to feature analysis, and the analysis method includes time domain analysis, which includes time domain waveform analysis, statistical analysis and trend analysis.

[0017] The time-domain waveform analysis is used to obtain the time-domain waveforms of the operating parameters of the coal mine power grid, and to obtain the sudden changes, fluctuations and transient processes of the operating parameters based on the time-domain waveforms.

[0018] The statistical analysis involves calculating statistics for the operating parameters, including the mean and variance, and obtaining the distribution characteristics of the operating parameters based on the statistics.

[0019] The trend analysis is used to analyze the changing trend of operating parameters over time and predict the changing trend of the operating parameters in future periods.

[0020] In a preferred embodiment of the present invention, the operating parameters are subjected to feature analysis, and the analysis method further includes multivariate analysis, which includes correlation analysis, multiple regression analysis and multivariate statistical analysis.

[0021] The correlation analysis is to calculate the correlation coefficient between the operating parameters and obtain the correlation between the operating parameters.

[0022] The multiple regression analysis is used to establish a multiple regression model between the operating parameters and to obtain the quantitative relationship between the operating parameters.

[0023] The multivariate statistical analysis is to analyze the multivariate characteristics of the operating parameters using multivariate statistical methods; the multivariate statistical methods include multivariate analysis of variance and discriminant analysis.

[0024] In a preferred embodiment of the present invention, in step S30, the power balance optimization control is to monitor the power flow of the coal mine power grid. When a power imbalance occurs in the power flow, the charging and discharging power of the energy storage system is adjusted to achieve dynamic power balance of the coal mine power grid.

[0025] The power quality optimization control monitors voltage dips and harmonics in the coal mine power grid. For voltage dips, it adjusts the discharge rate of the energy storage system, including accelerating the discharge rate of the energy storage system, to provide reactive power support to the coal mine power grid.

[0026] For the harmonics of the voltage, the harmonic current in the coal mine power grid is filtered by the energy storage system.

[0027] In a preferred embodiment of the present invention, the statistical measures of the operating parameters are calculated in the statistical analysis according to the following formula:

[0028] Where ρ represents the mean;

[0029] In the formula, x i This represents the i-th running parameter, and n represents the total number of running parameters;

[0030]

[0031] In the formula, θ represents the variance, and x i Let represent the i-th running parameter, n represent the total number of running parameters, and ρ represent the mean.

[0032] In a preferred embodiment of the present invention, in step S40, historical operating parameters for peak production periods and nighttime off-peak periods are obtained based on the analyzed correlation effects. Operating parameters corresponding to the initial periods of the peak production periods and nighttime off-peak periods are then obtained from these historical operating parameters. These initial periods are divided into an early initial period, a mid-term initial period, and a late initial period. The 10-15 most frequently occurring operating parameters in each period are collected. A database is generated based on these operating parameters. When the coal mine power grid is in a peak production period or a nighttime off-peak period in the future, the operating parameters of the coal mine power grid in the early initial period are collected. If the operating parameters are the same as those in the database, the operating state of the coal mine power grid is determined to be stable. If the operating parameters are different from those in the database, the operating state of the coal mine power grid is obtained, and energy storage control optimization is performed on the coal mine power grid based on the obtained operating state.

[0033] In a preferred embodiment of the present invention, if the operating parameters are different from the operating parameters in the database, the variation pattern of the operating parameters collected in the initial period of the early stage is calculated based on the operating parameters of the intermediate initial period, and the result is calculated according to the method of calculating the absolute change, as shown below:

[0034] Δx=x 中期 -x 前期 ;

[0035] In the formula, Δx represents the absolute change, x 中期 Indicates the operating parameters for the initial period of the intermediate phase, x 前期 Indicates the operating parameters during the initial period of the medium term;

[0036] It also includes calculations based on the correlation coefficient, as shown below:

[0037]

[0038] In the formula, δ represents the correlation coefficient of the operating parameters in the initial period of the early stage, w represents the correlation coefficient of the operating parameters in the initial period of the middle stage, and Cov(x) 前期 x中期 σ represents the covariance of the operating parameters in the initial period of the early stage and the initial period of the middle stage. 前期 and σ 中期 This represents the standard deviation of the operating parameters during the initial period and the initial period during the middle period.

[0039] In a preferred embodiment of the present invention, if the operating parameters collected in the initial period change towards the operating parameters in the intermediate initial period, it is determined that the coal mine power grid is developing towards a stable operating state. Otherwise, a calculation period is preset in the initial period based on the changes in the collected operating parameters. This includes calculating the confidence level of the changes in the operating parameters in the initial period towards the intermediate initial period every 10 seconds. If the calculated confidence level exceeds 50%, it is determined that the operating parameters of the coal mine power grid will change towards the intermediate initial period. Otherwise, the energy storage control optimization of the coal mine power grid is initiated.

[0040] On the other hand, the present invention provides a system for applying the above-described coal mine power grid operation optimization method based on energy storage composite control, comprising:

[0041] The data acquisition module is used to collect operating parameters of the coal mine power grid. These operating parameters include those of key components of the coal mine power grid, such as power sources, transmission lines, and power distribution equipment. An electrical model is constructed based on the operating parameters of these key components. The operating parameters include power, load, current, and voltage.

[0042] A feature extraction module, which responds to the data acquisition module, is used to perform feature analysis on the operating parameters and configure the energy storage system of the coal mine power grid based on the analyzed features.

[0043] The data analysis module obtains the regular changes of the operating parameters based on the feature analysis of the operating parameters, and optimizes the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control.

[0044] A data fusion processing module, comprising a differentiation unit, a processing unit, and a determination unit;

[0045] The differentiation unit is used to differentiate the regular changes, including the regular changes during shift handover periods, the regular changes during peak production periods, the regular changes during equipment maintenance periods, and the regular changes during off-peak night periods, and to analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid.

[0046] The processing unit is used to generate datasets about different regular changes based on the correlation influence, collect operating parameters corresponding to the regular changes in each dataset, obtain a set of operating parameters that appear most frequently from the operating parameters, and mark the operating parameters as reference operating parameters, wherein the number of reference operating parameters is at least 10.

[0047] The determination unit is used to acquire the regular changes corresponding to the reference operating parameters, and to preset a strategy for optimizing the energy storage control of the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in a future time period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular change.

[0048] Beneficial effects:

[0049] 1. By monitoring the power flow of the coal mine power grid and adjusting the charging and discharging power of the energy storage system, the load fluctuations of the coal mine power grid can be effectively addressed, the dynamic balance of the power grid can be maintained, and the stability of the power grid can be improved. In particular, under the circumstances of sudden increase or decrease in load, it can quickly respond and stabilize the operation of the coal mine power grid.

[0050] 2. By monitoring and regulating voltage sags and harmonic issues, and utilizing energy storage systems to provide reactive power support and filter harmonic currents, the power quality of the coal mine power grid is effectively improved. This is of great significance for reducing equipment failures and production losses caused by power quality problems, and can extend equipment lifespan and reduce maintenance costs.

[0051] 3. By analyzing the variation patterns of operating parameters during different production periods (such as shift handover, production peak, equipment maintenance, and nighttime off-peak), and optimizing energy storage control based on these patterns, this method can predict the operating status of the power grid in advance and take timely optimization measures, thereby enhancing the power supply reliability of the coal mine power grid and reducing the occurrence of accidents.

[0052] 4. By collecting and analyzing the operating parameters of the coal mine power grid at different initial periods (early, middle, and late stages), a database is established. Statistical analysis and multivariate analysis methods are then used to more accurately predict the power grid's operating status in future periods. This helps to formulate optimization strategies in advance and improve the predictability and controllability of power grid operation.

[0053] 5. By establishing a database of operating parameters and a multiple regression model, potential problems in the operation of coal mine power grids can be identified and diagnosed more accurately, and timely measures can be taken to adjust and optimize them, thereby enhancing the fault diagnosis capability of coal mine power grids. Attached Figure Description

[0054] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0055] Figure 1 This is a schematic diagram of the modular structure of a coal mine power grid operation optimization system based on energy storage composite control, according to an embodiment of the present invention.

[0056] Figure 2 This is a schematic diagram of the method flow according to an embodiment of the present invention;

[0057] The numbers in the diagram are: 110 - Data acquisition module; 120 - Feature extraction module; 130 - Data analysis module; 140 - Data fusion processing module; 1401 - Differentiation unit; 1402 - Processing unit; 1403 - Decision unit. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0059] Because existing technologies are not adaptable enough to make quick and accurate decisions and adjustments when faced with complex operating conditions and changing load requirements, the optimization effect is not ideal.

[0060] Based on this, the present invention proposes a coal mine power grid operation optimization method and system based on energy storage composite control. By monitoring the power flow of the coal mine power grid and monitoring and adjusting voltage sags and harmonics, it effectively improves the power quality of the coal mine power grid. Furthermore, by analyzing the variation patterns of operating parameters during different production periods and optimizing energy storage control based on these patterns, the operating status of the coal mine power grid can be predicted in advance, and optimization measures can be taken in a timely manner, thereby enhancing the power supply reliability of the coal mine power grid.

[0061] The present solution will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0062] Reference Figures 1 to 2 This is one embodiment of the present invention, which provides a method for optimizing the operation of a coal mine power grid based on energy storage composite control, comprising the following steps:

[0063] S10: Collect operating parameters of the coal mine power grid, including the operating parameters of key components of the coal mine power grid, such as power sources, transmission lines, and power distribution equipment, and construct an electrical model based on the operating parameters of the key components; the operating parameters include power, load, current, and voltage.

[0064] S20: Perform characteristic analysis on the operating parameters and configure the energy storage system for the coal mine power grid based on the analyzed characteristics;

[0065] In this embodiment, the energy storage system includes a lithium-ion battery, a supercapacitor, and a flywheel energy storage system;

[0066] By performing time-domain analysis (time-domain waveform analysis, statistical analysis, and trend analysis) on operating parameters, we can gain a comprehensive understanding of the characteristics of these parameters, including sudden changes, fluctuations, transient processes, distribution characteristics, and trends. Based on these analysis results, we can rationally configure the energy storage system.

[0067] S30: Based on the characteristic analysis of operating parameters, obtain the regular changes of operating parameters, and optimize the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control.

[0068] In this embodiment, dynamic balance of the coal mine power grid and improvement of power quality are achieved, reducing equipment failures and production losses caused by load fluctuations and power quality problems.

[0069] S40: Differentiate the regular changes, including the regular changes during shift handover periods, the regular changes during peak production periods, the regular changes during equipment maintenance periods, and the regular changes during nighttime off-peak periods, and analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid.

[0070] In this embodiment, the regular changes are divided into shift handover periods, peak production periods, equipment maintenance periods, and nighttime off-peak periods, and the correlation between these periods and changes in operating parameters is analyzed, which can provide a more detailed understanding of the power grid operation patterns; at the same time, it provides targeted strategies for the optimized control of different production periods, improving the adaptability and effectiveness of optimization measures.

[0071] To further illustrate this embodiment, during shift handover, coal mines typically operate on a multi-shift system. During shift handover, the previous shift's workers will gradually stop operating some equipment, while the next shift's workers will restart the equipment according to the production plan. For example, in the mining face, after the previous shift's coal mining machine, tunneling machine, and other equipment stop, the next shift may need to readjust the equipment positions and start them up, which can cause a significant fluctuation in the power grid load in a short period of time.

[0072] At this time, the active power, reactive power, current and other parameters of the power grid will change abruptly. If the equipment is started and stopped in a concentrated manner, it may also cause a temporary drop or rise in the power grid voltage, which will affect the power quality of the power grid.

[0073] During peak production periods, such as normal daytime production hours, almost all mining, transportation, and ventilation equipment are in operation, and the power grid load reaches a high level. At this time, if the production task is urgent or the equipment suddenly fails, it may further increase the operating pressure on the power grid.

[0074] At this time, the power factor of the power grid may decrease, voltage stability may be challenged, and frequency may fluctuate to some extent. In addition, due to the full load operation of equipment, the harmonic content in the power grid may increase, affecting power quality.

[0075] During equipment maintenance periods, coal mine equipment needs to be regularly inspected and maintained to ensure normal operation and safe production. During equipment maintenance, some equipment will stop operating, causing changes in the power grid load. If the maintenance involves critical equipment, such as the main ventilation fan or the main hoist, it may also have a significant impact on the operation of the entire coal mine power grid.

[0076] At this time, the load level of the power grid decreases, the power factor may improve, but the voltage may increase to some extent. Meanwhile, due to equipment shutdown, the short-circuit capacity of the power grid may change, affecting the protection settings and operational stability of the power grid.

[0077] During off-peak hours at night, coal mine production activities decrease, some non-critical equipment may stop operating, and the grid load is at a low level. At this time, if there are renewable energy power generation devices in the grid (such as small wind power, solar power, etc.), their power generation may be relatively stable, but the matching degree with the grid load will be reduced.

[0078] At this time, the voltage of the power grid may increase and the power factor may be better, but the stability and reliability of the power grid still need to be monitored. In addition, the backup capacity of the power grid is relatively large at night. If a fault occurs, it may cause large voltage fluctuations in the power grid, affecting the safe operation of equipment.

[0079] In addition, the operation of coal mine power grids is also affected by weather changes. For example, during thunderstorms, the power grid may be disturbed by natural factors such as lightning strikes, leading to power grid failures or voltage fluctuations; during hot weather, heat dissipation problems of equipment may cause equipment to operate under overload, increasing the burden on the power grid.

[0080] At this time, during thunderstorms, the power grid may experience short-term voltage dips, spikes, or flicker, which may even lead to power outages. In hot weather, the load on the power grid may increase, and the temperature rise of equipment may lead to an increase in equipment failure rate, affecting the stable operation of the power grid.

[0081] S50: Generate datasets about different regular changes based on correlation effects, collect the operating parameters corresponding to the regular changes in each dataset, and obtain a set of operating parameters that appear most frequently from the operating parameters; mark the operating parameters as reference operating parameters, wherein the number of reference operating parameters is at least 10;

[0082] In this embodiment, a data-driven approach is used to ensure that the optimization strategy can be adjusted based on actual operating data, thereby improving the scientific nature and accuracy of the optimization strategy.

[0083] S60: Obtain the regular changes corresponding to the reference operating parameters, and pre-set the energy storage control optimization strategy for the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in the future period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular change.

[0084] In this embodiment, the preset energy storage composite control strategy for the coal mine power grid includes power balance optimization control and power quality optimization control.

[0085] Based on the preset optimization strategy according to the reference operating parameters, and in real time, it can determine whether the power grid is in the corresponding regular change state, so as to realize the real-time monitoring and optimized control of the power grid operating status.

[0086] In S20, the operating parameters are characterized. The analysis methods include time domain analysis, which includes time domain waveform analysis, statistical analysis, and trend analysis.

[0087] Time-domain waveform analysis is used to obtain the time-domain waveforms of the operating parameters of the coal mine power grid, and to obtain the sudden changes, fluctuations and transient processes of the operating parameters based on the time-domain waveforms.

[0088] In this embodiment, the time-domain waveforms of the operating parameters of the coal mine power grid are obtained. For example, phenomena such as voltage dips, voltage swells, and short-term interruptions are manifested as obvious waveform changes in the time-domain waveform.

[0089] Statistical analysis involves calculating statistics for operating parameters, including the mean and variance, and obtaining the distribution characteristics of the operating parameters based on these statistics.

[0090] In this embodiment, the statistics of operating parameters are calculated. For example, by calculating the mean and standard deviation of the voltage, it can be determined whether the grid voltage is stable.

[0091] Trend analysis is used to analyze the changing trends of operating parameters over time and to predict the changing trends of operating parameters in future periods.

[0092] In this embodiment, the changing trend of operating parameters over time is analyzed. For example, the changing trend of voltage or current is fitted by methods such as linear regression to detect potential anomalies in advance.

[0093] It should be noted in this embodiment that the characteristic analysis of the operating parameters is performed, and the analysis method also includes multivariate analysis, which includes correlation analysis, multiple regression analysis and multivariate statistical analysis.

[0094] Correlation analysis is used to calculate the correlation coefficient between operating parameters and obtain the correlation between them.

[0095] In this embodiment, the correlation coefficient between operating parameters is calculated. For example, by calculating the correlation coefficient between voltage and current, the load characteristics of the power grid can be determined.

[0096] Multiple regression analysis is used to establish a multiple regression model between operating parameters and to obtain the quantitative relationship between the operating parameters.

[0097] In this embodiment, a multiple regression model is established between operating parameters. For example, a relationship model between voltage and load can be established through multiple regression analysis to predict voltage changes.

[0098] Multivariate statistical analysis is used to analyze the multivariate characteristics of operating parameters through multivariate statistical methods; multivariate statistical methods include multivariate analysis of variance and discriminant analysis.

[0099] In this embodiment, the multivariate characteristics of the operating parameters are analyzed using multivariate statistical methods. For example, discriminant analysis can be used to classify and identify parameters under different operating conditions.

[0100] In S30, power balance optimization control monitors the power flow of the coal mine power grid. When a power imbalance occurs, the charging and discharging power of the energy storage system is adjusted to achieve dynamic power balance in the coal mine power grid.

[0101] Power quality optimization control involves monitoring voltage dips and harmonics in the coal mine power grid. For voltage dips, the discharge rate of the energy storage system is adjusted, including accelerating the discharge rate of the energy storage system, to provide reactive power support to the coal mine power grid.

[0102] For voltage harmonics, the harmonic current in the coal mine power grid is filtered out through the energy storage system;

[0103] In this embodiment, collaborative optimization control is also included, which combines the power balance optimization control and power quality optimization control to achieve comprehensive control of the energy storage system. By establishing a collaborative control model, the target factors such as power balance and power quality optimization are comprehensively considered, and the optimal optimization control is solved using intelligent optimization algorithms (such as genetic algorithms, particle swarm optimization algorithms, etc.). The collaborative control strategy can give full play to the multiple advantages of the energy storage system and achieve comprehensive optimization of the coal mine power grid operation.

[0104] Based on the above, the statistics of the operating parameters are calculated in the statistical analysis, and are obtained according to the following formula:

[0105] Where ρ represents the mean;

[0106] In the formula, x i This represents the i-th running parameter, and n represents the total number of running parameters;

[0107]

[0108] In the formula, θ represents the variance, and x i Let represent the i-th running parameter, n represent the total number of running parameters, and ρ represent the mean.

[0109] In step S40, historical operating parameters for peak production periods and nighttime off-peak periods are obtained based on the analyzed correlation effects. From these historical parameters, the operating parameters corresponding to the initial periods of these peak and off-peak periods are extracted. The initial periods are divided into early, middle, and late initial periods, and the 10-15 most frequently occurring operating parameters in each period are collected. A database is generated based on these operating parameters. When the coal mine power grid is in a peak production period or a nighttime off-peak period in the future, the operating parameters of the coal mine power grid in the early initial period are collected. If the operating parameters are the same as those in the database, the coal mine power grid is considered to be in a stable operating state. If the operating parameters are different from those in the database, the operating state of the coal mine power grid is obtained, and energy storage control optimization is performed on the coal mine power grid based on the obtained operating state.

[0110] Furthermore, if the operating parameters differ from those in the database, the variation pattern of the operating parameters collected in the initial period of the early stage is calculated based on the operating parameters of the initial period of the mid-term. The calculation is performed according to the method for calculating absolute changes, as shown below:

[0111] Δx=x 中期 -x 前期 ;

[0112] In the formula, Δx represents the absolute change, x 中期 Indicates the operating parameters for the initial period of the intermediate phase, x 前期Indicates the operating parameters during the initial period of the medium term;

[0113] In this embodiment, the absolute change is the difference between the operating parameters in the initial period of the early stage and the operating parameters in the initial period of the middle stage, which can reflect the degree of absolute change of the operating parameters;

[0114] It also includes calculations based on the correlation coefficient, as shown below:

[0115]

[0116] In the formula, δ represents the correlation coefficient of the operating parameters in the initial period of the early stage, w represents the correlation coefficient of the operating parameters in the initial period of the middle stage, and Cov(x) 前期 x 中期 σ represents the covariance of the operating parameters in the initial period of the early stage and the initial period of the middle stage. 前期 and σ 中期 This represents the standard deviation of the operating parameters during the initial period and the initial period during the middle period;

[0117] In this embodiment, the correlation coefficient is the correlation coefficient between the operating parameters in the initial period of the early stage and the operating parameters in the initial period of the middle stage, which can reflect the degree of linear correlation between the operating parameters in the two periods.

[0118] By calculating the absolute changes and correlation coefficients of the operating parameters in the initial period of the early stage and the initial period of the middle stage, the changing patterns of the operating parameters can be quantified, providing a quantitative basis for judging the changing trends of the operating parameters and improving the prediction accuracy of changes in operating status.

[0119] Based on the calculation results, if the operating parameters collected in the initial period change towards the operating parameters in the middle initial period, it is determined that the coal mine power grid is developing towards a stable operating state. Otherwise, a calculation period is preset based on the changes in the collected operating parameters in the initial period. This includes calculating the confidence level of the changes in the operating parameters in the initial period towards the middle initial period every 10 seconds. If the calculated confidence level exceeds 50%, it is determined that the operating parameters of the coal mine power grid will change towards the middle initial period. Otherwise, the energy storage control optimization of the coal mine power grid is initiated.

[0120] In this embodiment, based on the calculation results, it is determined whether the operating parameters of the initial period in the early stage change towards the initial period in the middle stage, and optimization decisions are made based on this. By calculating the confidence level, the scientific nature and accuracy of the decision are further improved.

[0121] As can be seen from the above, by analyzing the variation patterns of operating parameters during different production periods and optimizing energy storage control based on these patterns, the operating status of the coal mine power grid can be predicted in advance, and optimization measures can be taken in a timely manner, thereby enhancing the power supply reliability of the coal mine power grid.

[0122] This embodiment, in conjunction with the above-mentioned coal mine power grid operation optimization method based on energy storage composite control, also proposes a system applied to this method, as follows:

[0123] The data acquisition module 110 is used to collect the operating parameters of the coal mine power grid. The operating parameters include the operating parameters of the key components of the coal mine power grid, including power sources, transmission lines and power distribution equipment. An electrical model is constructed based on the operating parameters of the key components. The operating parameters include power, load, current and voltage.

[0124] Feature extraction module 120, which responds to data acquisition module, is used to perform feature analysis on operating parameters and configure energy storage system for coal mine power grid based on the analyzed features.

[0125] The data analysis module 130 obtains the regular changes of operating parameters based on the feature analysis of operating parameters, and optimizes the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control.

[0126] The data fusion processing module 140 includes a differentiation unit 1401, a processing unit 1402, and a determination unit 1403.

[0127] The differentiation unit 1401 is used to differentiate the regular changes, including the regular changes during shift handover periods, the regular changes during peak production periods, the regular changes during equipment maintenance periods, and the regular changes during nighttime off-peak periods, and to analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid.

[0128] The processing unit 1402 is used to generate datasets about different regular changes based on the correlation influence, collect the running parameters corresponding to the regular changes in each dataset, obtain a set of running parameters that appear most frequently from the running parameters, and mark the running parameters as reference running parameters, wherein the number of reference running parameters is at least 10;

[0129] The determination unit 1403 is used to acquire the regular changes corresponding to the reference operating parameters, and to preset the energy storage control optimization strategy for the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in the future period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular change.

[0130] In summary, this invention effectively improves the power quality of coal mine power grids by monitoring power flow and addressing voltage sags and harmonics. Furthermore, by analyzing the variation patterns of operating parameters during different production periods and optimizing energy storage control based on these patterns, the operating status of coal mine power grids can be predicted in advance, allowing for timely optimization measures and enhancing the reliability of power supply to coal mine power grids.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing the operation of a coal mine power grid based on energy storage composite control, characterized in that, Includes the following steps: S10: Collect operating parameters of the coal mine power grid, including operating parameters of key components of the coal mine power grid, including power sources, transmission lines and power distribution equipment, and construct an electrical model based on the operating parameters of the key components; the operating parameters include power, load, current and voltage; S20: Perform feature analysis on the operating parameters, and configure the energy storage system for the coal mine power grid based on the analyzed features; S30: Based on the characteristic analysis of the operating parameters, obtain the regular changes of the operating parameters, and optimize the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control. S40: Differentiate the aforementioned regular changes, including regular changes during shift handover periods, regular changes during peak production periods, regular changes during equipment maintenance periods, and regular changes during nighttime off-peak periods, and analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid; Based on the analyzed correlations, historical operating parameters for peak production periods and nighttime off-peak periods are obtained. From these historical parameters, operating parameters corresponding to the initial periods of peak production periods and nighttime off-peak periods are extracted. These initial periods are divided into early initial periods, mid-term initial periods, and late initial periods. The 10-15 most frequently occurring operating parameters in each period are collected. A database is generated based on these operating parameters. When the coal mine power grid is in a peak production period or a nighttime off-peak period in the future, the operating parameters of the coal mine power grid in the early initial period are collected. If these operating parameters are the same as those in the database, the operating state of the coal mine power grid is determined to be stable. If the operating parameters are different from those in the database, the operating state of the coal mine power grid is obtained, and energy storage control optimization is performed on the coal mine power grid based on the obtained operating state. S50: Generate datasets on different regular changes based on the correlation effects, collect operating parameters corresponding to the regular changes in each dataset, and obtain a set of operating parameters that appear most frequently from the operating parameters; mark the operating parameters as reference operating parameters, wherein the number of reference operating parameters is at least 10; S60: Obtain the regular changes corresponding to the reference operating parameters, and preset a strategy for optimizing the energy storage control of the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in a future time period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular changes.

2. The coal mine power grid operation optimization method based on energy storage composite control as described in claim 1, characterized in that, In step S20, feature analysis is performed on the operating parameters. The analysis methods include time-domain analysis, which includes time-domain waveform analysis, statistical analysis, and trend analysis. The time-domain waveform analysis is used to obtain the time-domain waveforms of the operating parameters of the coal mine power grid, and to obtain the sudden changes, fluctuations and transient processes of the operating parameters based on the time-domain waveforms. The statistical analysis involves calculating statistics for the operating parameters, including the mean and variance, and obtaining the distribution characteristics of the operating parameters based on the statistics. The trend analysis is used to analyze the changing trend of operating parameters over time and predict the changing trend of the operating parameters in future periods.

3. The coal mine power grid operation optimization method based on energy storage composite control as described in claim 2, characterized in that, The operating parameters are subjected to feature analysis, and the analysis methods also include multivariate analysis, which includes correlation analysis, multiple regression analysis and multivariate statistical analysis. The correlation analysis is to calculate the correlation coefficient between the operating parameters and obtain the correlation between the operating parameters. The multiple regression analysis is used to establish a multiple regression model between the operating parameters and to obtain the quantitative relationship between the operating parameters. The multivariate statistical analysis is to analyze the multivariate characteristics of the operating parameters using multivariate statistical methods; the multivariate statistical methods include multivariate analysis of variance and discriminant analysis.

4. The coal mine power grid operation optimization method based on energy storage composite control as described in claim 1, characterized in that, In S30, the power balance optimization control monitors the power flow of the coal mine power grid. When a power imbalance occurs, the charging and discharging power of the energy storage system is adjusted to achieve dynamic power balance in the coal mine power grid. The power quality optimization control monitors voltage dips and harmonics in the coal mine power grid. For voltage dips, it adjusts the discharge rate of the energy storage system, including accelerating the discharge rate of the energy storage system, to provide reactive power support to the coal mine power grid. For the harmonics of the voltage, the harmonic current in the coal mine power grid is filtered by the energy storage system.

5. The coal mine power grid operation optimization method based on energy storage composite control as described in claim 2, characterized in that, The statistical measures of the operating parameters are calculated in the aforementioned statistical analysis, and are obtained according to the following formula: ;in, This represents the mean; In the formula, Indicates the first One running parameter, Indicates the total number of running parameters; ； In the formula, Represents variance. Indicates the first One running parameter, Indicates the total number of running parameters; This represents the mean.

6. The method for optimizing coal mine power grid operation based on energy storage composite control as described in claim 1, characterized in that, If the operating parameters are different from the operating parameters in the database, the regular changes in the operating parameters collected in the early initial period are calculated based on the operating parameters of the mid-term initial period, and the results are obtained according to the calculation method of absolute change, as shown below: ； In the formula, Indicates absolute change. This indicates the operating parameters during the initial period of the medium term. Indicates the operating parameters during the initial period of the medium term; It also includes calculations based on the correlation coefficient, as shown below: ； In the formula, This represents the correlation coefficient of the operating parameters in the initial period. The correlation coefficient represents the operating parameters during the initial period of the medium term. This represents the covariance of the operating parameters during the initial period of the early stage and the initial period of the middle stage. and This represents the standard deviation of the operating parameters during the initial period and the initial period during the middle period.

7. The method for optimizing coal mine power grid operation based on energy storage composite control as described in claim 6, characterized in that, Based on the calculation results, if the operating parameters collected in the initial period change towards the operating parameters in the intermediate initial period, it is determined that the coal mine power grid is developing towards a stable operating state. Otherwise, a calculation period is preset based on the changes in the collected operating parameters in the initial period. This includes calculating the confidence level of the changes in the operating parameters in the initial period towards the intermediate initial period every 10 seconds. If the calculated confidence level exceeds 50%, it is determined that the operating parameters of the coal mine power grid will change towards the intermediate initial period. Otherwise, the energy storage control optimization of the coal mine power grid is initiated.

8. A system applied to the coal mine power grid operation optimization method based on energy storage composite control as described in claim 1, characterized in that, include: The data acquisition module is used to collect operating parameters of the coal mine power grid. These operating parameters include those of key components of the coal mine power grid, such as power sources, transmission lines, and power distribution equipment. An electrical model is constructed based on the operating parameters of these key components. The operating parameters include power, load, current, and voltage. A feature extraction module, which responds to the data acquisition module, is used to perform feature analysis on the operating parameters and configure the energy storage system of the coal mine power grid based on the analyzed features. The data analysis module obtains the regular changes of the operating parameters based on the feature analysis of the operating parameters, and optimizes the energy storage control of the coal mine power grid based on the regular changes. The energy storage control optimization includes power balance optimization control and power quality optimization control. A data fusion processing module, comprising a differentiation unit, a processing unit, and a determination unit; The differentiation unit is used to differentiate the regular changes, including the regular changes during shift handover periods, the regular changes during peak production periods, the regular changes during equipment maintenance periods, and the regular changes during off-peak night periods, and to analyze the correlation between the differentiated regular changes and the changes in the operating parameters of the coal mine power grid. The processing unit is used to generate datasets about different regular changes based on the correlation influence, collect operating parameters corresponding to the regular changes in each dataset, obtain a set of operating parameters that appear most frequently from the operating parameters, and mark the operating parameters as reference operating parameters, wherein the number of reference operating parameters is at least 10. The determination unit is used to acquire the regular changes corresponding to the reference operating parameters, and to preset a strategy for optimizing the energy storage control of the coal mine power grid based on the regular changes; when the operating parameters of the coal mine power grid collected in a future time period are the same as the reference operating parameters, it is determined that the coal mine power grid is in the state of the corresponding regular change.

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