Wind farm energy management system based on wind turbine major component temperatures

Abstract

The present application relates to a kind of wind farm energy management systems based on wind turbine unit major component temperature, temperature prediction is carried out by measuring temperature, and then the deterioration degree of major component is calculated, power generation of wind turbine unit in wind farm is controlled according to the deterioration degree, can effectively balance the health status of each unit, solve the problem that part of unit is stopped due to high temperature when wind farm carries out power regulation, and then improve the whole farm power generation.The present application is updated by setting the iteration of field level operation temperature benchmark library, and the predicted value of each wind turbine component temperature in field level operation temperature benchmark library is found by using component temperature measurement value.According to the predicted temperature value, the deterioration degree of component is calculated, combined with the total power instruction of wind farm issued under AGC system and component deterioration degree, energy management system can intelligently distribute the active set value of each wind turbine unit in wind farm, send the active set value of wind turbine to each wind turbine master control system, realize the power coordination control function of wind farm.

Description

Technical Field

[0001] This invention relates to the field of wind power generation and wind energy utilization technology, and in particular to a wind farm energy management system based on the temperature of large components of a wind turbine generator set, for the purpose of wind farm energy management. Background Technology

[0002] Wind power is a clean energy source, but it also has characteristics such as strong intermittency, random fluctuations, low predictability, and low dispatchability. When wind power generation accounts for a small proportion, it can be ignored in grid operation and control due to the inherent capacity of the grid system. However, when wind power generation accounts for a large proportion, it must be incorporated into the regular dispatch system, integrated into various steps such as grid power generation planning, online dispatch, and real-time control. Currently, energy management systems have become standard equipment in wind farms to control the output of wind turbines, making wind farm power generation adjustable and controllable. Current energy management systems only aim to meet grid requirements and do not consider the sub-health state of the wind turbines themselves. Due to differences in manufacturing, maintenance, components, and wind resources, the health status of major components in each unit varies after several years of operation. Therefore, balancing the health status of each unit while regulating wind farm power is of great significance and is an important direction for improving the quality and efficiency of wind power generation. Summary of the Invention

[0003] In view of the above situation and to overcome the shortcomings of the existing technology, the purpose of this invention is to provide a wind farm energy management and control method based on the temperature of large components of wind turbine generators. By measuring the temperature to predict the temperature, the degradation degree of the large components is calculated, and the power generation of wind turbine generators in the wind farm is coordinated and controlled according to the degradation degree. This can effectively balance the health status of each unit, solve the problem of some units shutting down due to high temperature when the wind farm adjusts the power, and thus improve the overall power generation of the wind farm.

[0004] The technical solution solved by this invention is:

[0005] A wind farm energy management and control system based on the temperature of major components of a wind turbine generator set. The system includes a temperature measurement and prediction system, a farm-level operating temperature reference library, an energy management system, a wind turbine main control system, and an AGC system, wherein:

[0006] Temperature measurement and prediction system: measures ambient temperature, gearbox oil sump temperature, gearbox bearing temperature, generator bearing temperature, main bearing temperature, pitch bearing temperature, and inverter temperature, and calibrates and judges each temperature; searches the field-level operating temperature reference library based on ambient temperature, component temperature, unit power, and unit speed, and performs matching prediction;

[0007] Field-level operating temperature benchmark library: Based on the unit's historical ambient temperature, component temperature, and unit power statistics, the benchmark values ​​of component temperature under various conditions are fitted to generate a field-level operating database, which is continuously updated and iterated;

[0008] Energy Management System: Based on temperature prediction values, the system calculates the component degradation degree and combines the total power command of the wind farm issued by the AGC system with the component degradation degree to intelligently allocate the active power setpoint of each wind turbine in the wind farm. The active power setpoint of the wind turbine is sent to the main control system of each wind turbine to realize the power coordination control function of the wind farm.

[0009] Wind turbine main control system: Adjusts the active power of the wind turbine according to the active power setpoint issued by the energy management system and maintains the operation in this state;

[0010] AGC system: Automatic Generation Control System for Wind Power Stations, which receives grid dispatch instructions.

[0011] Compared to existing technologies, this invention predicts temperature by measuring temperature, then calculates the degradation degree of major components. Based on the degradation degree, it coordinates and controls the power generation of wind turbines within the wind farm, effectively balancing the health status of each unit and solving the problem of some units shutting down due to high temperatures during power regulation, thereby increasing the overall power generation of the wind farm. This invention establishes a continuously updated and iterative farm-level operating temperature benchmark library. Using component temperature measurements, it searches for predicted temperatures of each wind turbine component in the benchmark library. Based on the predicted temperature values, it calculates the component degradation degree. Combining the total power command of the wind farm issued by the AGC system with the component degradation degree, the energy management system intelligently allocates the active power setpoint for each wind turbine in the wind farm and sends the active power setpoint to the main control system of each turbine, realizing the wind farm power coordination control function. On the one hand, the system adopts a dynamically updated field-level operating temperature reference library. After simulating and calculating the initial value of the field-level operating temperature reference library, it is dynamically updated as the unit operating time increases, reducing the inaccuracy of the field-level operating temperature reference library caused by wind farm operation and maintenance. On the other hand, the system uses the calculation of component degradation degree to coordinate with the allocation of active power commands of the wind farm energy management system, which reduces the degree of component degradation, extends the service life of components, and also improves the long-term control accuracy of the wind farm, resulting in good economic benefits. Attached Figure Description

[0012] Figure 1 This is a diagram illustrating the architecture of the wind farm energy management system based on the temperature of major components of a wind turbine generator, as described in this invention.

[0013] Figure 2 This is a block diagram of the control algorithm of the present invention.

[0014] Figure 3 The simulation result of this invention is shown in the diagram: total power.

[0015] Figure 4 The simulation effect diagram of the present invention: gearbox oil tank temperature. Detailed Implementation

[0016] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings and examples.

[0017] This invention discloses a wind farm energy management system based on the temperature of major components of a wind turbine generator. The system includes a temperature measurement and prediction system, a farm-level operating temperature reference library, an energy management system, a wind turbine main control system, and an AGC system, wherein:

[0018] Temperature measurement and prediction system: measures ambient temperature, gearbox oil sump temperature, gearbox bearing temperature, generator bearing temperature, main bearing temperature, pitch bearing temperature, and inverter temperature, and calibrates and judges each temperature; searches the field-level operating temperature reference library based on ambient temperature, component temperature, unit power, and unit speed, and performs matching prediction;

[0019] Field-level operating temperature benchmark library: Based on the unit's historical ambient temperature, component temperature, and unit power statistics, the benchmark values ​​of component temperature under various conditions are fitted to generate a field-level operating database, which is continuously updated and iterated;

[0020] Energy Management System: Based on temperature prediction values, the system calculates the component degradation degree and combines the total power command of the wind farm issued by the AGC system with the component degradation degree to intelligently allocate the active power setpoint of each wind turbine in the wind farm. The active power setpoint of the wind turbine is sent to the main control system of each wind turbine to realize the power coordination control function of the wind farm.

[0021] Wind turbine main control system: Adjusts the active power of the wind turbine according to the active power setpoint issued by the energy management system and maintains the operation in this state;

[0022] AGC system: Automatic Generation Control System for Wind Power Stations, which receives grid dispatch instructions.

[0023] For system simplicity, the measured values ​​of ambient temperature, gearbox oil sump temperature, gearbox bearing temperature, generator bearing temperature, main bearing temperature, pitch bearing temperature, and inverter temperature are all read from the wind farm SCADA system. Figure 1 As shown.

[0024] The calculation process for the initial value of the field-level operating temperature reference library is as follows:

[0025] Step 1: Handle abnormal ambient temperatures. If the temperature difference between the current moment and the previous moment exceeds 2°C, then set the current temperature value to the previous moment's value.

[0026] Step 2: If the ambient temperature is below -20℃, set it to -20℃; if the ambient temperature is above 40℃, set it to 40℃.

[0027] Step 3: Take the average of the ambient temperature and unit power over 10 minutes to obtain the 10-minute average ambient temperature and the 10-minute average unit power.

[0028] Step 4: Divide the 10-minute average ambient temperature into compartments with an interval of 2℃, ranging from [-20℃ to 40℃]; divide the 10-minute average unit power into compartments with an interval of 200kW, ranging from [0kW to 2000kW].

[0029] Step 5: Obtain the component temperature values ​​for each ambient temperature compartment and unit power compartment, and perform cluster fitting to fit the component temperature and power center values;

[0030] Step 6: Centered on the component temperature and power center value, denoted as T c (i,j), obtain the upper and lower limits of the percentage of the total number of component temperature points in this compartment as 80%, denoted as T respectively; u (i,j),T d (i,j), where i and j are the number of environmental bays and the number of unit power bays, respectively, and T u (i,j)-T d (i,j) represents the minimum value; and the field-level operating temperature reference library is obtained:

[0031]

[0032] The iterative calculation process for the field-level operating temperature reference library is as follows:

[0033] Step 1: Obtain un-iterated data, with the start time being the unit startup time and the end time being the unit shutdown time;

[0034] Step 2; Search data. If the component temperature exceeds the alarm value, do not proceed to the next step; otherwise, proceed to Step 3.

[0035] Step 3: Search and calculate the duration for which the average unit power exceeds 1800kW for 10 minutes. If it is less than 1 hour, do not proceed to the next step; otherwise, proceed to Step 4.

[0036] Step 4: Obtain the correction matrix using the initial value calculation method of the field-level operating temperature reference library:

[0037]

[0038] Step 5: Set the field-level operating temperature reference library as follows:

[0039]

[0040] Step 6: The center value of component temperature and power is the center T. c(i,j) is set to T c (i,j)*0.95+T c(k+1) (i,j)*0.05.

[0041] The calculation process of the temperature measurement and prediction system is as follows:

[0042] Step 1: Calculate the 10-minute average of real-time ambient temperature and unit power;

[0043] Step 2: Based on the real-time ambient temperature and the 10-minute average of the unit power, search the field-level operating temperature benchmark library to obtain the benchmark value T for the current storage location. u (i,j);

[0044] Step 3: Calculate the 10-minute average of the real-time component temperature, denoted as: T l , where l is the marking of the component;

[0045] Step 4: Predicted component temperature T when the computer group is operating at full capacity l p Calculation method: T l p =T / -T u (i,j)+T u (i,n).

[0046] The calculation process of the energy management system is as follows:

[0047] Active power allocation is based on the active power of the wind farm set by the power grid dispatch, the operating status of each wind turbine in the wind farm, and the individual characteristics of each wind turbine to control the output power of each wind turbine unit in the wind farm; such as Figure 2 As shown: The difference between the measured power and the grid dispatch power is used as the input of the PI controller. The output of the PI controller is transmitted to the total power command. The total power command is calculated based on the margin capacity of the controllable wind turbines and the command result is distributed to the controllable units.

[0048] Specifically, the following steps are included:

[0049] Step 1: Based on whether the wind turbine units are controllable by the energy management system, all wind turbines in the wind farm are divided into two categories: controllable units and uncontrollable units;

[0050] Among them, the non-controllable wind turbines under the energy management system include wind turbines with communication loss, specific wind turbines, and faulty wind turbines; the controllable wind turbines under the energy management system include standby wind turbines and operating generating wind turbines.

[0051] Step 2: Based on these two types of wind turbines, intelligently allocate the active power value of each wind turbine unit; the main algorithm flow is as follows:

[0052] This represents the power generation capacity of the z-th generating unit. For the z-th unit's curtailment margin, the non-controllable wind turbine units in the energy management system have both a power generation margin and a curtailment margin of 0 and do not participate in energy management control. For the standby wind turbines of the controllable wind turbine units in the energy management system, the power generation margin is calculated based on wind speed, wind angle, and wind power curves, while the curtailment margin is 0. The other wind turbines of the controllable wind turbine units in the energy management system calculate their initial power generation margin based on pitch angle and current power. Initial power rationing margin Subtract the minimum power output at the current wind speed from the current power generation; then calculate the power generation margin based on the degradation level. and power rationing margin

[0053] If the measured power is greater than the dispatched power, the current power command for the unit is: If the measured power is less than the dispatched power, the current power command for the unit is:

[0054] The process for calculating the degree of degradation is as follows:

[0055] Step 1: Predict T based on the temperature of major components of the wind turbine l p Calculate the degradation degree F of major components of the wind turbine l The method for calculating the degradation degree of a single component is as follows: Among them, T a ,T f These are the alarm temperature and fault temperature values ​​of the measured signal, respectively;

[0056] Step 2: Calculate the deterioration degree F of multiple components. The calculation method is the average of the sum of the squares of the deterioration degrees of each component.

[0057] The calculation process for the power generation surplus and power curtailment surplus is as follows:

[0058] Step 1: When the degradation degree F > 0.3, the current generating capacity of the unit is 0;

[0059] When the degradation degree F ≤ 0.3, the current generating capacity of the unit is... for:

[0060] When the degradation degree F < 0.1, the current power curtailment margin of the unit is 0;

[0061] When the degradation degree F ≥ 0.1, the current unit's power curtailment margin is... for:

[0062] This invention will be applied to a 300MW wind farm, which has 150 wind turbines of 2MW each. Hardware-in-the-loop testing has been completed. One energy management server controls five PLC controllers. Each controller is configured with a simulation system for the cooling and temperature rise of the gearbox oil tanks of 30 wind turbine units, with one wind turbine cooling simulation system set to a fault state. The farm-level operating temperature benchmark library is calculated based on one year of data from the wind farm. The gearbox oil tank temperature alarm value is set to 80 degrees Celsius, and the fault temperature limit is set to 85 degrees Celsius. The wind speed is set to turbulent wind with an average of 9 m / s and a wind angle of 0°C. The initial gearbox temperature is set to 62°C, and the ambient temperature is set to 25°C. Simulation process: The initial grid dispatch command is 200MW. After 5 minutes, the grid dispatch command gradually increases to 250MW. The gearbox oil tank temperature of the faulty unit gradually rises until it reaches 85 degrees Celsius, at which point the unit shuts down. Due to the unit's shutdown, the measured power on the grid decreases to approximately 248.5MW. After optimizing the algorithm, simulations were performed under the same conditions. Because the unit's oil bath temperature was higher than the matching value in the field-level operating temperature benchmark library due to the cooling system failure, power was limited in advance. The gearbox oil bath temperature gradually increased to around 73℃ and then stopped rising, reaching an equilibrium point. The power output decreased to around 249.5MW. Figure 3 and Figure 4 As shown. Simulation test results show that: the present invention predicts temperature by measuring temperature, then calculates the degradation degree of large components, and coordinates the power generation of wind turbines in the wind farm based on the degradation degree. This can effectively balance the health status of each unit, solve the problem of some units shutting down due to high temperature when the wind farm adjusts its power, and thus improve the overall power generation of the wind farm.

Claims

1. A wind farm energy management system based on the temperature of large components of a wind turbine generator set, characterized in that, The system includes a temperature measurement and prediction system, a field-level operating temperature reference library, an energy management system, a wind turbine main control system, and an AGC system, among which: Temperature measurement and prediction system: measures ambient temperature, gearbox oil sump temperature, gearbox bearing temperature, generator bearing temperature, main bearing temperature, pitch bearing temperature, and inverter temperature, and calibrates and judges each temperature; searches the field-level operating temperature reference library based on ambient temperature, component temperature, unit power, and unit speed, and performs matching prediction; Field-level operating temperature benchmark library: Based on the unit's historical ambient temperature, component temperature, and unit power statistics, the benchmark values ​​of component temperature under various conditions are fitted to generate a field-level operating database, which is continuously updated and iterated; Energy Management System: Based on temperature prediction values, the system calculates the component degradation degree and combines the total power command of the wind farm issued by the AGC system with the component degradation degree to intelligently allocate the active power setpoint of each wind turbine in the wind farm. The active power setpoint of the wind turbine is sent to the main control system of each wind turbine to realize the power coordination control function of the wind farm. Wind turbine main control system: Adjusts the active power of the wind turbine according to the active power setpoint issued by the energy management system and maintains operation; AGC system: Automatic Generation Control System for Wind Power Stations, which receives grid dispatch instructions; If the measured power is greater than the dispatched power, the current power command for the unit is: If the measured power is less than the dispatched power, the current power command for the unit is: ; in, This represents the initial power generation margin. This is the initial power rationing margin; The calculation process for power generation surplus and power curtailment surplus is as follows: Step 1: Degradation At that time, the current generating capacity of the unit is 0; Degradation At that time, the current generating capacity of the unit is... for: ; Degradation At that time, the current power rationing margin of the unit is 0; Degradation At that time, the current power rationing margin of the unit for: .

2. The wind farm energy management system based on the temperature of large components of a wind turbine generator as described in claim 1, characterized in that, The calculation process for the initial value of the field-level operating temperature reference library is as follows: Step 1: Handle abnormal ambient temperatures. If the temperature difference between the current moment and the previous moment exceeds 2°C, then set the current temperature value to the previous moment's value. Step 2: If the ambient temperature is below -20°C, set it to -20°C; if the ambient temperature is above 40°C, set it to 40°C. Step 3: Take the average of the ambient temperature and unit power over 10 minutes to obtain the 10-minute average ambient temperature and the 10-minute average unit power. Step 4: Divide the 10-minute average ambient temperature into compartments with an interval of 2°C, ranging from [-20°C to 40°C]; divide the 10-minute average unit power into compartments with an interval of 200kW, ranging from [0kW to 2000kW]. Step 5: Obtain the component temperature values ​​for each ambient temperature compartment and unit power compartment, and perform cluster fitting to fit the component temperature and power center values; Step 6: Centered on the component's temperature and power center value, record it as... Obtain the upper and lower limits of the percentage of the total number of component temperature points in this compartment as 80%, and denote them as follows: ,in, i, j These are the number of environmental bays and the number of unit power bays, respectively; and the field-level operating temperature reference library is obtained: 。 3. The wind farm energy management system based on the temperature of large components of a wind turbine generator set according to claim 2, characterized in that, The iterative calculation process for the field-level operating temperature reference library is as follows: Step 1: Obtain un-iterated data, with the start time being the unit startup time and the end time being the unit shutdown time; Step 2; Search data. If the component temperature exceeds the alarm value, do not proceed to the next step; otherwise, proceed to Step 3. Step 3: Search and calculate the duration for which the average unit power exceeds 1800kW for 10 minutes. If it is less than 1 hour, do not proceed to the next step; otherwise, proceed to Step 4. Step 4: Obtain the correction matrix using the initial value calculation method of the field-level operating temperature reference library: Step 5: Set the field-level operating temperature reference library as follows: Step 6: The center value of component temperature and power is the center. Set as .

4. The wind farm energy management system based on the temperature of large components of a wind turbine generator set according to claim 2 or 3, characterized in that, The calculation process of the temperature measurement and prediction system is as follows: Step 1: Calculate the 10-minute average of real-time ambient temperature and unit power; Step 2: Based on the real-time ambient temperature and the 10-minute average of the unit power, search the field-level operating temperature benchmark library to obtain the benchmark value for the current storage location. ; Step 3: Calculate the 10-minute average of the real-time component temperature, and record it as: T l ,in l This is the marking for the component; Step 4: Predicted component temperatures when the computer group is operating at full capacity Calculation method: .

5. The wind farm energy management system based on the temperature of large components of a wind turbine generator as described in claim 1, characterized in that, The calculation process of the energy management system is as follows: The active power allocation is based on the active power of the wind farm set by the power grid dispatch, the operating status of each wind turbine in the wind farm, and the individual characteristics of each wind turbine to control the output power of each wind turbine in the wind farm. Specifically, the following steps are included: Step 1: Based on whether the wind turbine units are controllable by the energy management system, all wind turbines in the wind farm are divided into two categories: controllable units and uncontrollable units; Among them, the non-controllable wind turbines under the energy management system include wind turbines with communication loss, specific wind turbines, and faulty wind turbines; the controllable wind turbines under the energy management system include standby wind turbines and operating generating wind turbines. Step 2: Based on these two types of wind turbines, intelligently allocate the active power value of each wind turbine unit; the main algorithm flow is as follows: This represents the power generation capacity of the z-th generating unit. For the first unit's curtailment margin, the non-controllable wind turbine units in the energy management system have both a power generation margin and a curtailment margin of 0 and do not participate in energy management control. For the standby wind turbines of the controllable wind turbine units in the energy management system, the power generation margin is calculated based on wind speed, wind angle, and wind power curves, while the curtailment margin is 0. The other wind turbines of the controllable wind turbine units in the energy management system calculate their initial power generation margin based on pitch angle and current power. The initial power rationing margin Subtract the minimum power output at the current wind speed from the current power generation; then calculate the power generation margin based on the degradation level. and power rationing margin ; The process for calculating the degree of degradation is as follows: Step 1: Predict the temperature of major components of the wind turbine. Calculate the degree of degradation of major components of the wind turbine F l The method for calculating the degradation degree of a single component is as follows: ,in, These are the alarm temperature and the fault temperature values, respectively. Step 2: Calculate the degradation degree of multiple components F The calculation method is the average of the sum of the squares of the deterioration degree of each component.

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