A method for optimizing operation and maintenance of wind power generation system equipment

Abstract

The present invention discloses a method for optimizing the operation and maintenance of equipment in a wind power generation system, which is applied to the technical field of wind power generation. The method comprises the following steps: obtaining the historical and real-time operating parameters of each device in the wind power generation system, calculating the historical and real-time operating indicators, calculating the failure probability of the equipment, solving the operation and maintenance optimization scheme with the minimum total cost of maintenance and operation as the objective function; executing the operation and maintenance optimization scheme, judging the difference change rate between the real-time operating indicator and the historical operating indicator before executing the operation and maintenance optimization scheme, and continuing to execute if it is better than before executing the operation and maintenance optimization scheme, and adjusting the constraints of the model for re-optimization if it is worse than before optimization. The present invention can realize the accurate evaluation of the performance and health status of the equipment by collecting, integrating and analyzing the massive data generated by the equipment in the wind power generation system, and combining the equipment state optimization operation and maintenance scheme to reduce the operation and maintenance cost under the premise of ensuring the reliability of the operation of the power equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and more particularly to a method for optimizing operation and maintenance of wind power generation system equipment. Background Art

[0002] With the rapid development of the power industry, especially the popularization of smart grid construction and new energy access, the number and complexity of electrical equipment are growing, and equipment operation and maintenance management is facing unprecedented challenges. In the wind power generation system, a very important component is the power equipment. In order to ensure the normal operation of the distribution system, it is necessary to do a good job in the operation and maintenance of various power equipment. The operation and maintenance of power equipment is an important guarantee for improving the reliability of wind power generation operation and the utilization efficiency of equipment. At present, there are three main types of power equipment operation and maintenance: post-operation and maintenance, regular operation and maintenance, and status operation and maintenance. Post-operation and maintenance is to repair or replace the equipment after the equipment fails. Regular operation and maintenance is to perform maintenance at a certain time interval, which mainly depends on the equipment's own parameters and the maintenance experience of the maintenance personnel. Status operation and maintenance is a maintenance method that relies on status detection and diagnosis technology and formulates maintenance plans based on the equipment operation status. However, the traditional operation and maintenance method relies on manual inspection and regular maintenance, which is not only difficult to monitor the equipment operation status in real time, but also requires a lot of manpower and material resources as the maintenance intensity increases. Therefore, how to provide a method for optimizing the operation and maintenance of wind power system equipment is a problem that technicians in this field need to solve urgently. Summary of the invention

[0003] In view of this, the present invention provides a method for optimizing the operation and maintenance of wind power generation system equipment, which monitors the equipment operation status and optimizes the operation and maintenance plan based on historical and real-time status operation parameters, thereby reducing the operation and maintenance costs while ensuring the reliability of the power equipment operation.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for optimizing operation and maintenance of wind power generation system equipment comprises the following steps:

[0006] S1. Obtain the historical and real-time operating parameters of each device in the wind power generation system;

[0007] S2. Calculate historical and real-time status operation indicators based on the historical status operation parameters of the equipment;

[0008] S3. Calculate the failure probability of the equipment based on historical and real-time status operating indicators;

[0009] S4. Calculate the maintenance cost of each device based on the probability of equipment failure, and solve the operation and maintenance optimization plan with the minimum total maintenance cost as the objective function;

[0010] S5. Execute the operation and maintenance optimization plan and calculate the real-time status operation index based on the status operation parameters collected in real time during the operation of the equipment;

[0011] S6. Determine the difference change rate between the real-time status operating indicators and the historical status operating indicators before executing the operation and maintenance optimization plan. If the difference change rate after executing the operation and maintenance optimization plan is better than before executing the operation and maintenance optimization plan, continue to execute the operation and maintenance optimization plan. If it is worse than before optimization, adjust the constraints of the model and optimize again.

[0012] Optionally, S2 is specifically:

[0013] Q=q1w1+q2w2+…+q n w n

[0014] In the formula, Q is the state operation index, q1, q2, q n are the calculated values ​​of the state operation parameters, w1, w2, w n are the weights corresponding to the state operation parameters respectively.

[0015] Optionally, the weights of the status operation parameters are:

[0016]

[0017] In the formula, w k is the weight of the kth state operation parameter, k∈[1,n], and j is the fault degree coefficient of the state operation parameter.

[0018] Optional, S3 is:

[0019] P = ae Qc

[0020] Where P is the failure probability of the equipment, Q is the equipment status index, and a and c are the failure calculation parameters.

[0021] Optionally, the total maintenance and operation cost in S4 includes the loss load value and maintenance and operation fee caused by the maintenance and operation shutdown. The calculation of the total maintenance and operation cost is specifically as follows:

[0022]

[0023] Where E is the total cost of maintenance and repair, M is the total number of equipment, m∈[1,M], t is the total duration of an operation and maintenance cycle, i∈[1,t], B is the unit load value, is the load loss of device m in state s. When s=1, the device operates normally, and when s=0, the device stops operating. is the probability that device m is in state s, t i is the i-th unit duration in period t, is the maintenance cost of equipment m in the i-th unit time, is the state of device m at the i-th unit time.

[0024] Optionally, the constraints for solving the operation and maintenance optimization solution in S4 are: the output power of the wind power system is greater than a preset value, the single maintenance and operation shutdown duration of a device does not exceed a preset value, the total maintenance and operation cost of a device does not exceed a preset value, the number of maintenance and operation shutdowns of the same device in an operation and maintenance cycle does not exceed a preset value, the total maintenance and operation shutdown duration of the same device in an operation and maintenance cycle does not exceed a preset value, and equipment that cannot be shut down at the same time cannot be maintained and operated at the same time.

[0025] Optionally, the difference change rate λ after the operation and maintenance optimization solution is executed in S6 t Specifically:

[0026]

[0027] Difference change rate λ before executing the operation and maintenance optimization plan t-1 Specifically:

[0028]

[0029] In the formula, Q mt is the state operating parameter of device m within a period t after executing the operation and maintenance optimization plan, Q mt-1 is the state operating parameter of device m in the period t-1 before executing the operation and maintenance optimization plan, Q mt-2 is the state operation parameter of device m in period t-2, is the reference value within period t, is the reference value within period t-1.

[0030] It can be seen from the above technical solution that, compared with the prior art, the present invention provides a method for optimizing the operation and maintenance of equipment in a wind power generation system, which has the following beneficial effects: the present invention makes full use of the state operating parameters of the power equipment in the wind power generation system, and collects, integrates and deeply analyzes the massive historical and real-time data generated by the power equipment, and closely combines the operation and maintenance plan of the power equipment with the real-time state operating parameters of the power equipment, thereby achieving an accurate assessment of the performance and health status of the equipment, and optimizing the operation and maintenance plan based on the state of the equipment while reducing the operation and maintenance cost, thereby ensuring the reliability of the operation of the power equipment while reducing the operation and maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0032] Figure 1 This is a flow chart of the wind power generation system equipment operation and maintenance optimization method of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] The embodiment of the present invention discloses a method for optimizing the operation and maintenance of wind power generation system equipment. Figure 1 As shown, the following steps are included:

[0035] S1. Obtain the historical and real-time operating parameters of each device in the wind power generation system;

[0036] S2. Calculate historical and real-time status operation indicators based on the historical status operation parameters of the equipment;

[0037] S3. Calculate the failure probability of the equipment based on historical and real-time status operating indicators;

[0038] S4. Calculate the maintenance cost of each device based on the probability of equipment failure, and solve the operation and maintenance optimization plan with the minimum total maintenance cost as the objective function;

[0039] S5. Execute the operation and maintenance optimization plan and calculate the real-time status operation index based on the status operation parameters collected in real time during the operation of the equipment;

[0040] S6. Determine the difference change rate between the real-time status operating indicators and the historical status operating indicators before executing the operation and maintenance optimization plan. If the difference change rate after executing the operation and maintenance optimization plan is better than before executing the operation and maintenance optimization plan, continue to execute the operation and maintenance optimization plan. If it is worse than before optimization, adjust the constraints of the model and optimize again.

[0041] Furthermore, S2 is specifically:

[0042] Q=q1w1+q2w2+…+q n w n

[0043] In the formula, Q is the state operation index, q1, q2, q n are the calculated values ​​of the state operation parameters, w1, w2, w n are the weights corresponding to the state operation parameters respectively.

[0044] Furthermore, the weight of the state operation parameter is:

[0045]

[0046] In the formula, w k is the weight of the kth state operation parameter, k∈[1,n], and j is the fault degree coefficient of the state operation parameter.

[0047] In the embodiment of the present invention, the calculated value of the state operation parameter is obtained based on the comparison between the detected value of the state operation parameter and the standard value, and the fault degree coefficient of the state operation parameter is obtained by the influence caused by the fault, specifically:

[0048] Each state operation parameter involves multiple faults, and each fault may lead to multiple consequences. For example, a state parameter may lead to fault g1 and fault g2. The consequences of fault g1 and fault g2 are h. 11 、h 12 and h 21 、h 23 , then its influence coefficient j is:

[0049]

[0050] The impact coefficient of each consequence is derived from historical data.

[0051] Furthermore, S3 is specifically:

[0052] P = ae Qc

[0053] Where P is the failure probability of the equipment, Q is the equipment status index, and a and c are the failure calculation parameters.

[0054] In the embodiment of the present invention, the fault calculation parameters are obtained from historical data.

[0055] Furthermore, the total maintenance and operation cost in S4 includes the value of the lost load due to the maintenance and operation outage and the maintenance and operation fee;

[0056] The total cost of maintenance and operation is calculated as follows:

[0057]

[0058] Where E is the total cost of maintenance and repair, M is the total number of equipment, m∈[1,M], t is the total duration of an operation and maintenance cycle, i∈[1,t], B is the unit load value, is the load loss of device m in state s. When s=1, the device operates normally, and when s=0, the device stops operating. is the probability that device m is in state s, t i is the i-th unit duration in period t, is the maintenance cost of equipment m in the i-th unit time, is the state of device m at the i-th unit time.

[0059] Furthermore, the constraints for solving the operation and maintenance optimization plan in S4 are: the output power of the wind power system is greater than the preset value, the single maintenance and operation shutdown duration of a device does not exceed the preset value, the total maintenance and operation cost of a device does not exceed the preset value, the number of maintenance and operation shutdowns of the same device in an operation and maintenance cycle does not exceed the preset value, the total maintenance and operation shutdown duration of the same device in an operation and maintenance cycle does not exceed the preset value, and equipment that cannot be shut down at the same time cannot be maintained and operated at the same time.

[0060] Furthermore, the difference change rate λ after the operation and maintenance optimization solution is executed in S6 t Specifically:

[0061]

[0062] Difference change rate λ before executing the operation and maintenance optimization plan t-1 Specifically:

[0063]

[0064] In the formula, Q mt is the state operating parameter of device m within a period t after executing the operation and maintenance optimization plan, Q mt-1 is the state operating parameter of device m in the period t-1 before executing the operation and maintenance optimization plan, Q mt-2 is the state operation parameter of device m in period t-2, is the reference value within period t, is the reference value within period t-1.

[0065] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other. The above description of the disclosed embodiments enables professionals and technicians in this field to implement or use the present invention. Various modifications to these embodiments will be obvious to professionals and technicians in this field, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in this article, but will comply with the widest range consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing operation and maintenance of wind power generation system equipment, characterized in that: The following steps are involved: S1. Obtain the historical and real-time operating parameters of each device in the wind power generation system; S2. Calculate historical and real-time status operation indicators based on the historical status operation parameters of the equipment; S3. Calculate the failure probability of the equipment based on historical and real-time status operating indicators; S4. Calculate the maintenance cost of each device based on the probability of equipment failure, and solve the operation and maintenance optimization plan with the minimum total maintenance cost as the objective function; S5. Execute the operation and maintenance optimization plan and calculate the real-time status operation index based on the status operation parameters collected in real time during the operation of the equipment; S6. Determine the difference change rate between the real-time state operation index and the historical state operation index before executing the operation and maintenance optimization plan. If the difference change rate after executing the operation and maintenance optimization plan is better than before executing the operation and maintenance optimization plan, continue to execute the operation and maintenance optimization plan. If it is worse than before the optimization, adjust the constraint conditions of the model and optimize again. The total maintenance and operation cost in S4 includes the loss load value and maintenance and operation fee caused by the maintenance and operation shutdown. The calculation of the total maintenance and operation cost is as follows: Where E is the total cost of maintenance and repair, M is the total number of equipment, m∈[1,M], t is the total duration of an operation and maintenance cycle, i∈[1,t], B is the unit load value, is the load loss of device m in state s. When s=1, the device operates normally, and when s=0, the device stops operating. is the probability that device m is in state s, t i is the i-th unit duration in period t, is the maintenance cost of equipment m in the i-th unit time, is the state of device m at the i-th unit time; The constraints for solving the operation and maintenance optimization plan in S4 are: the output power of the wind power generation system is greater than the preset value, the single maintenance and operation shutdown duration of a device does not exceed the preset value, the total maintenance and operation cost of a device does not exceed the preset value, the number of maintenance and operation shutdowns of the same device in an operation and maintenance cycle does not exceed the preset value, the total maintenance and operation shutdown duration of the same device in an operation and maintenance cycle does not exceed the preset value, and equipment that cannot be shut down at the same time cannot be maintained and operated at the same time.

2. A method for optimizing operation and maintenance of wind power generation system equipment according to claim 1, characterized in that: S2 is specifically: Q=q1w1+q2w2+…+q n w n In the formula, Q is the state operation index, q1, q2, q n are the calculated values ​​of the state operation parameters, w1, w2, w n are the weights corresponding to the state operation parameters respectively.

3. A method for optimizing operation and maintenance of wind power generation system equipment according to claim 2, characterized in that: The weights of the state operation parameters are: In the formula, w k is the weight of the kth state operation parameter, k∈[1,n], and j is the fault degree coefficient of the state operation parameter.

4. A method for optimizing operation and maintenance of wind power generation system equipment according to claim 1, characterized in that: S3 is specifically: P=ae Qc Where P is the failure probability of the equipment, Q is the equipment status index, and a and c are the failure calculation parameters.

5. A method for optimizing operation and maintenance of wind power generation system equipment according to claim 1, characterized in that: The difference change rate λ after executing the operation and maintenance optimization plan in S6 t Specifically: Difference change rate λ before executing the operation and maintenance optimization plan t-1 Specifically: In the formula, Q mt is the state operating parameter of device m within a period t after executing the operation and maintenance optimization plan, Q mt-1 is the state operating parameter of device m in the period t-1 before executing the operation and maintenance optimization plan, Q mt-2 is the state operation parameter of device m in period t-2, is the reference value within period t, is the reference value within period t-1.

Images