Discharge power safety control method and system of new energy power station

Abstract

The invention discloses a discharge power safety control method and system for a new energy power station. The control method comprises the following steps: step 1, collecting multi-dimensional data in real time; 2, constructing a safety evaluation model fusing the discharge power, the equipment operation state and the power grid parameters by using the multi-dimensional data; 3, implementing different preliminary power regulation strategies based on an evaluation result of the safety evaluation model; 4, evaluating the stability of the power grid in real time; 5, performing dynamic optimization adjustment on the discharge power of the new energy power station by using an intelligent optimization algorithm; the system comprises a data acquisition module, a data processing and safety evaluation module, a power regulation execution module, a power grid stability monitoring module and a control decision module. The method has the beneficial effects that the safety risk of the discharge power can be evaluated more accurately through multi-dimensional data fusion, construction of the safety evaluation model and dynamic adjustment of the weight of each data dimension.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy power station safety, in particular to a discharge power safety control method and system for new energy power station. BACKGROUND

[0002] With the transformation of global energy structure to renewable energy, the installed capacity of wind power, photovoltaic and other new energy power stations is rapidly growing, however, new energy power generation has the characteristics of intermittency, volatility and randomness, and the instability of its discharge power will pose a challenge to the safe operation of the power grid; The current discharge power control technology of new energy power station mainly has the following limitations: the system only relies on single dimension data for safety evaluation, which is difficult to fully reflect the operation risk of the power station, the traditional power regulation mainly adopts single closed-loop control strategy, which only adjusts the single target of internal equipment safety or power grid stability, lacks the coordination optimization of the two, and the response to the change of power grid operation state is lagging behind, and it cannot real-time perceive voltage fluctuation, harmonic abnormality and other problems. SUMMARY

[0003] The purpose of the present application is to solve the above-mentioned problems, and therefore a discharge power safety control method and system for new energy power station are proposed.

[0004] The purpose of the present application can be realized by the following technical scheme: a discharge power safety control method for new energy power station, comprising: Step 1: Real-time acquisition of multi-dimensional data of discharge power data of new energy power station, operation state data of battery pack or power generation equipment, and real-time load data, voltage fluctuation data and frequency deviation data of power grid, and pre-processing of these data; Step 2: Using multi-dimensional data, a safety evaluation model is constructed which integrates discharge power, equipment operation state and power grid parameters; Step 3: Based on the evaluation results of the safety evaluation model, different preliminary power regulation strategies are implemented; Step 4: After completing the preliminary power regulation in step 3, the power grid is monitored in real time, including the voltage stability, frequency stability and harmonic content of the power grid, and the stability of the power grid is evaluated in real time by using the preset stability evaluation algorithm; Step 5: Combined with the stability evaluation results of step 4, the discharge power of new energy power station is dynamically optimized and regulated by using intelligent optimization algorithm.

[0005] Further, the safety evaluation model is: Each safety index is divided into five levels, corresponding to 1-5 points respectively, the basic weight coefficient of safety index is preset, and the weight is dynamically adjusted according to the fluctuation amplitude of real-time monitoring data, and when a certain index approaches the threshold, its weight automatically increases by 20%. The score corresponding to the real-time data is multiplied by the dynamic weight, all index scores are accumulated to obtain a comprehensive risk coefficient, and the safety level is divided according to the risk coefficient range, including low risk, medium risk and high risk.

[0006] Further, the stability evaluation algorithm adopts a hierarchical threshold comparison algorithm to evaluate the power grid stability, specifically: A voltage fluctuation threshold is set, the voltage amplitude needs to be maintained within the range of ±5% of the voltage fluctuation threshold, the voltage deviation rate is calculated, the real-time collected voltage value is compared with the voltage fluctuation threshold, if the deviation rate exceeds the threshold, it is marked as voltage abnormality, and the fluctuation duration is recorded, when the voltage abnormality lasts more than 10 seconds or the fluctuation amplitude exceeds ±10%, it is determined as a serious voltage problem, triggering an emergency feedback, a frequency fluctuation threshold is set, the frequency deviation is allowed to be ±0.2Hz, the frequency change rate is monitored in real time, if the frequency change rate exceeds the deviation range allowed by the frequency fluctuation threshold, it is marked as frequency abnormality, and if the frequency abnormality lasts more than 15 seconds, it is determined as a serious frequency problem, and immediately feedback to the adjustment system, a current harmonic distortion rate threshold is set, the single harmonic current content does not exceed 5% of the current harmonic distortion rate threshold, and the total harmonic distortion rate does not exceed 8%, when the single harmonic or total harmonic content exceeds the threshold and the duration exceeds 20 seconds, it is determined as harmonic abnormality.

[0007] The application also provides a discharge power safety control system of a new energy power station, which comprises a data acquisition module, a data processing and safety evaluation module, a power adjustment execution module, a power grid stability monitoring module and a control decision module.

[0008] Further, the data acquisition module is responsible for real-time acquisition of the discharge power of the new energy power station, the equipment operating state and the related parameter data of the power grid, and the collected data is transmitted to the data processing module through wired or wireless communication network after preprocessing.

[0009] Further, the data processing and safety evaluation module is used for storing the collected historical data and real-time data, and can perform fusion processing and safety risk evaluation on the real-time data, and output the current safety risk level.

[0010] Further, the power adjustment execution module is used for executing corresponding power adjustment operations according to the risk level output by the safety evaluation module and the instruction of the control decision module.

[0011] Further, the power grid stability monitoring module is used for real-time monitoring of the voltage, frequency and harmonic parameters of the power grid, and real-time transmission of the monitoring results to the control decision module.

[0012] Further, the control decision module is configured to receive data, process the risk level information output by the safety evaluation module and the power grid state information fed back by the power grid stability monitoring module, generate a power adjustment scheme by using an intelligent optimization algorithm, and send a control instruction to the power adjustment execution module to realize dynamic optimization adjustment of the discharge power.

[0013] Compared with the prior art, the present application has the following advantages: By multi-dimensional data fusion and construction of a safety evaluation model, the safety risk of the discharge power can be more accurately evaluated by dynamically adjusting the weight of each data dimension, solving the one-sidedness problem of traditional single data evaluation. Based on the risk level, the double closed-loop power adjustment strategy adjusts the power within the safety threshold range quickly according to the safety risk level in the inner loop for the safety of equipment operation, and dynamically optimizes the adjustment by using an intelligent optimization algorithm in the outer loop in combination with the power grid stability feedback, thereby improving the power grid adaptability and power station operation efficiency while ensuring safety. By real-time monitoring of the voltage, frequency and harmonics of the power grid and dynamic adjustment of the discharge power by using an intelligent algorithm, the discharge power of the new energy power station can adapt to the changes in the operation state of the power grid in real time, effectively improving the stability and reliability of the power grid. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to facilitate the understanding of those skilled in the art, the present application will be further described below with reference to the accompanying drawings.

[0015] Figure 1 A flowchart of a discharge power safety control method for a new energy power station according to the present application.

[0016] Figure 2 A composition diagram of a discharge power safety control system for a new energy power station according to the present application. DETAILED DESCRIPTION

[0017] The technical solutions of the present application will be described below in conjunction with the embodiments, obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0018] Please refer to Figure 1 As shown in the accompanying drawings, a discharge power safety control method and system for a new energy power station, comprising: Step one: Real-time collection of multi-dimensional data, through the sensors deployed in the new energy power station, real-time collection of discharge power data, battery pack or power generation equipment operation state data of the new energy power station, at the same time, real-time load data, voltage fluctuation data, frequency deviation data of the power grid are collected, and the data are pretreated to remove noise and abnormal values; Step two: using multi-dimensional data, constructing a safety evaluation model integrating discharge power, equipment operation state and power grid parameters; The safety evaluation model is: Each safety index is divided into five levels, corresponding to 1-5 points respectively; The following is the scoring method of discharge power: Below 80% of the rated value is 1 point, 80%-90% of the rated value is 2 points, 90%-100% of the rated value is 3 points, 100%-110% of the rated value is 4 points, and more than 110% of the rated value is 5 points; The following is the scoring method of equipment temperature: Below 80% of the lower limit of the safe temperature is 1 point, 80%-90% of the lower limit of the safe temperature is 2 points, within the safe temperature range is 3 points, 90%-100% of the upper limit of the safe temperature is 4 points, and more than the upper limit of the safe temperature is 5 points; The following is the evaluation method of power grid voltage: Below 80% of the lower limit of the allowable voltage is 1 point, 80%-90% of the lower limit of the allowable voltage is 2 points, within the allowable voltage range is 3 points, 90%-100% of the upper limit of the allowable voltage is 4 points, and more than the upper limit of the allowable voltage is 5 points; The basic weight coefficient of the safety index is set in advance, the discharge power weight is 0.4, the equipment temperature weight is 0.3, and the power grid voltage weight is 0.3, and the weight is dynamically adjusted according to the fluctuation amplitude of the real-time monitoring data, when a certain index approaches the threshold, the weight automatically floats by 20%; The score corresponding to the real-time data is multiplied by the dynamic weight, and the comprehensive risk coefficient is obtained by accumulating the scores of all indexes, and the safety level is divided according to the risk coefficient range, including low risk, medium risk and high risk, 0-1.5 is low risk, 1.5-3 is medium risk, and more than 3 is high risk; Step three: based on the evaluation results of the safety evaluation model, different preliminary power adjustment strategies are implemented. When the risk level is low, the current discharge power is kept stable, and only real-time monitoring is performed. When the risk level is medium, a preset power fine-tuning mechanism is started, and the discharge power is gradually reduced or increased according to a predetermined proportion, so that the power value is within the safe range. When the risk level is high, an emergency power adjustment program is triggered immediately to quickly adjust the discharge power to within the safe threshold range. During the adjustment process, the amplitude and time parameters of the adjustment are recorded in real time and fed back to the safety evaluation model for dynamic updating and optimization of the model. Step four: after completing the preliminary power adjustment in step three, the power grid is monitored in real time, including the voltage stability, frequency stability, and harmonic content of the power grid. A preset stability evaluation algorithm is used to evaluate the stability of the power grid in real time. The stability evaluation algorithm uses a hierarchical threshold comparison algorithm to evaluate the stability of the power grid. Specifically: Set the voltage fluctuation threshold, the voltage amplitude needs to be maintained within ±5% of the voltage fluctuation threshold, calculate the voltage deviation rate, compare the real-time collected voltage value with the voltage fluctuation threshold, if the deviation rate exceeds the threshold, mark it as voltage abnormality, and record the fluctuation duration. When the voltage abnormality lasts more than 10 seconds or the fluctuation amplitude exceeds ±10%, it is determined as a serious voltage problem, triggering an emergency feedback. Set the frequency fluctuation threshold to allow a frequency deviation of ±0.2 Hz, monitor the frequency change rate in real time. If the frequency change rate exceeds the allowed deviation range of the frequency fluctuation threshold, it is marked as frequency abnormality. If the frequency abnormality lasts more than 15 seconds, it is determined as a serious frequency problem and immediately fed back to the adjustment system. Set the current harmonic distortion rate threshold, the single harmonic current content does not exceed 5% of the current harmonic distortion rate threshold, and the total harmonic distortion rate does not exceed 8%. When a single harmonic or total harmonic content exceeds the threshold and the duration exceeds 20 seconds, it is determined as a harmonic abnormality. Step five: based on the stability evaluation results of step four, use an intelligent optimization algorithm to dynamically optimize and adjust the discharge power of the new energy power station. The dynamic optimization and adjustment method is to establish a multi-objective optimization function: ; Where, is the optimization target of power grid stability, , , are the voltage deviation rate, frequency deviation rate, and total harmonic distortion rate, , , are the corresponding weight coefficients, is the economic benefit target, is the power station discharge income, is the power adjustment cost. The power constraint condition is wherein P is the power station discharge power, , respectively the equipment rated minimum, maximum power; The power grid parameter constraint is to meet the voltage amplitude , frequency deviation , single harmonic content , total distortion rate ; According to the constraint condition, N particles are randomly generated in the feasible region, and each particle position represents a set of discharge power adjustment schemes, and the fitness value of each particle is calculated according to the objective function in step 1, and the higher the fitness value, the better the scheme, the current position of the particle is compared with the historical optimal position, and the individual optimal solution is updated The individual optimal solution of all particles is compared, and the global optimal solution is updated The particle velocity and position are updated by the formula and , wherein is the inertia weight, , is the learning factor, , is a random number, and when the maximum iteration number is reached or the fitness value converges, the global optimal solution is output as the final discharge power adjustment scheme.

[0019] The application also provides a discharge power safety control system of a new energy power station, which is applied to the control method and comprises a data acquisition module, a data processing and safety evaluation module, a power adjustment execution module, a power grid stability monitoring module and a control decision module. The data acquisition module is responsible for real-time acquisition of the discharge power of the new energy power station, the equipment operating state and the related parameter data of the power grid, and the acquired data is transmitted to the data processing module through wired or wireless communication network after pretreatment. The data processing and safety evaluation module is used for storing the collected historical data and real-time data, and can perform fusion processing and safety risk evaluation on the real-time data, and output the current safety risk level; the power adjustment execution module is used for executing corresponding power adjustment operation according to the risk level output by the safety evaluation module and the instruction of the control decision module. The power grid stability monitoring module is used for real-time monitoring of the voltage, frequency and harmonic parameters of the power grid, and transmitting the monitoring results to the control decision module in real time. ​The control decision module is used to receive data, process the risk level information output by the safety assessment module and the power grid status information fed back by the power grid stability monitoring module, generate a power regulation scheme using an intelligent optimization algorithm, and send control commands to the power regulation execution module to realize dynamic optimization and regulation of discharge power.

[0020] Example 1: A certain new energy power station has a rated discharge power of 1000kW, an equipment safe temperature range of 20-50℃, and a grid rated voltage of 380V. At a certain moment, the system collects the discharge power of 950kW (corresponding to 3 points), the equipment temperature of 52℃ (corresponding to 5 points), and the grid voltage of 395V (corresponding to 4 points). The initial weights are discharge power 0.4, equipment temperature 0.3, and grid voltage 0.3. Because the equipment temperature reaches a high-risk state, its weight is increased by 50% to 0.45. At this time, the risk coefficient = 3×0.4 + 5×0.45 + 4×0.3 = 4.35, which is judged as a high-risk level.

[0021] Example 2: Following the high-risk scenario in Example 1, the system immediately triggers an emergency power adjustment procedure, rapidly reducing the discharge power from 950kW to 850kW (80% below the rated value, corresponding to 1 point). After adjustment, the system records the adjustment range as 100kW and the adjustment time as 2 minutes, and feeds this data back to the safety assessment model to recalculate the risk coefficient. At this time, the equipment temperature drops to 48℃ due to the power reduction (corresponding to 3 points), and the grid voltage is 385V (corresponding to 3 points). The new risk coefficient = 1×0.4 + 3×0.3 + 3×0.3 = 2.2, and the risk level is reduced to medium risk.

[0022] Example 3: After initial power regulation, the power grid monitoring equipment collected a real-time voltage of 358V (below the allowable lower limit of 361V). The system marked the voltage as abnormal and started timing. When the voltage remained below the lower limit for 12 seconds, it was determined to be a serious voltage problem, and the abnormal information (voltage value 358V, abnormality lasting 12 seconds) was fed back to the power regulation system.

[0023] Example 4: In response to voltage anomaly feedback, the control decision module initiates a particle swarm optimization algorithm and sets the particle swarm size. The particle positions were initialized within the power adjustment range (500kW-1000kW). Calculations showed that particle scheme A (discharge power 880kW) achieved the objective function... Reduce voltage offset error, To ensure a certain return and achieve the highest fitness, the algorithm converges after 50 iterations, with an output of 880kW being the optimal adjustment scheme.

[0024] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments described. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to best explain the principles of the application and its practical application to thereby enable others skilled in the art to best utilize the application and get the best results from the application. The application is only limited by the claims and their full scope and equivalents.

Claims

1. A method for safe control of discharge power of a new energy power station, characterized in that, The application relates to a new energy power station safety risk assessment and power adjustment method and system. Step one: multi-dimensional data is used to collect discharge power data of a new energy power station, operation state data of a battery pack or a power generation device, and real-time load data, voltage fluctuation data and frequency deviation data of a power grid, and the data is pretreated; Step two: a safety evaluation model is constructed by using the multi-dimensional data, wherein the safety evaluation model is fused with discharge power, device operation state and power grid parameters; Step three: different preliminary power adjustment strategies are implemented based on the evaluation results of the safety evaluation model; Step four: after the preliminary power adjustment in step three is completed, the power grid is monitored in real time, including voltage stability, frequency stability and harmonic content of the power grid, and a preset stability evaluation algorithm is used to evaluate the stability of the power grid in real time; Step five: the discharge power of the new energy power station is dynamically optimized and adjusted by using an intelligent optimization algorithm in combination with the stability evaluation results in step four.

2. The discharge power safety control method of a new energy power station according to claim 1, characterized in that, The safety evaluation model is as follows: Each safety index is divided into five levels, corresponding to 1-5 points, and the basic weight coefficient of the safety index is preset, and the weight is dynamically adjusted according to the fluctuation amplitude of the real-time monitoring data, and when a certain index approaches a threshold value, the weight is automatically increased by 20%; The score corresponding to the real-time data is multiplied by the dynamic weight, and the comprehensive risk coefficient is obtained by accumulating the scores of all indexes, and the safety level is divided according to the risk coefficient range, including low risk, medium risk and high risk.

3. The method of claim 2, wherein the method further comprises: The stability evaluation algorithm adopts a hierarchical threshold comparison algorithm to evaluate the stability of the power grid, and specifically: A voltage fluctuation threshold is set, the voltage amplitude needs to be maintained within the range of plus or minus 5% of the voltage fluctuation threshold, the voltage offset rate is calculated, the real-time collected voltage value is compared with the voltage fluctuation threshold, if the offset rate exceeds the threshold, the voltage is marked as abnormal, and the fluctuation duration is recorded, if the voltage abnormality lasts more than 10 seconds or the fluctuation amplitude exceeds plus or minus 10%, it is determined that there is a serious voltage problem, an emergency feedback is triggered, a frequency fluctuation threshold is set, the frequency deviation is allowed to be plus or minus 0.2 Hz, the frequency change rate is monitored in real time, if the frequency change rate exceeds the allowed deviation range of the frequency fluctuation threshold, the frequency is marked as abnormal, if the frequency abnormality lasts more than 15 seconds, it is determined that there is a serious frequency problem, and the adjustment system is immediately fed back, a current harmonic distortion rate threshold is set, the single harmonic current content does not exceed 5% of the current harmonic distortion rate threshold, and the total harmonic distortion rate does not exceed 8%, if a single harmonic or total harmonic content exceeds the threshold and the duration exceeds 20 seconds, it is determined that there is a harmonic abnormality.

4. A discharge power safety control system of a new energy power station, applied to the control method of any one of claims 1-3, characterized in that, The system comprises a data acquisition module, a data processing and safety evaluation module, a power adjustment execution module, a power grid stability monitoring module and a control decision module.

5. The discharge power safety control system of a new energy power station according to claim 4, characterized in that, The data acquisition module is responsible for collecting the discharge power of the new energy power station, the operation state of the device and the related parameter data of the power grid in real time, and the collected data is transmitted to the data processing module through a wired or wireless communication network after being pretreated.

6. The discharge power safety control system of a new energy power station according to claim 5, characterized in that, The data processing and safety evaluation module is used for storing the collected historical data and real-time data, and can fuse and process the real-time data and evaluate the safety risk, and outputs the current safety risk level.

7. The discharge power safety control system of a new energy power station according to claim 6, characterized in that, The power adjustment execution module is configured to execute corresponding power adjustment operations according to the risk level output by the safety evaluation module and the instructions of the control decision module.

8. The discharge power safety control system of a new energy power station according to claim 7, characterized in that, The power grid stability monitoring module is configured to monitor the voltage, frequency and harmonic parameters of the power grid in real time, and transmit the monitoring results to the control decision module in real time.

9. The discharge power safety control system of a new energy power station according to claim 8, characterized in that, The control decision module is configured to receive data, process the risk level information output by the safety evaluation module and the power grid state information fed back by the power grid stability monitoring module, generate a power adjustment scheme by using an intelligent optimization algorithm, and send control instructions to the power adjustment execution module to realize dynamic optimization and adjustment of the discharge power.

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