CN114221390B - Power optimization control method considering service life of converter and output power quality - Google Patents

Abstract

The invention relates to a power optimization control method that takes into account the life of the converter and the quality of the output power, which includes establishing a fan model, a power loss model and a thermal network model based on the operating conditions of the fan, and constructing a model that is related to the life of the power converter and the quality of the output power. Two related objective functions; through the Pareto multi-objective optimization power control method used, the optimal solution set is obtained; finally, the hierarchical optimization method is used to select the optimal rotor angular speed and power factor angle. Compared with the existing technology, the present invention uses a multi-objective optimized power control method to actively adjust the active power and reactive power output on the generator side to smooth junction temperature fluctuations, is not limited to local information, and effectively extends the service life of the converter.

Description

A power optimization control method taking into account converter life and output power quality

Technical field

The present invention relates to the technical field of power converter control, and in particular to a power optimization control method that takes into account the life of the converter and the quality of output power.

Background technique

With the vigorous development of new energy power generation such as wind power and photovoltaics, the installed capacity of wind power has continued to increase in recent years, especially offshore wind power. With its abundant and stable wind resources, high utilization hours, and proximity to load centers, it will become a new energy source in the future. The focus of development in the power generation field. Since the operation and maintenance of offshore wind turbines is difficult, offshore wind speeds are variable, and there are a large number of power electronic devices in wind turbines, it is crucial to ensure low operation and high reliability.

The power converter is the most vulnerable component in the wind turbine system, which causes the failure rate of the wind power converter system to be as high as 50%. Particularly in offshore environments, changes in wind speed and temperature can create complex converter load conditions, such as overload conditions and system transients, leading to higher failure rates and premature failure before expected life is reached. The active power control method commonly used in wind power generation is maximum power point tracking (MPPT), and the reactive power control adopts the unit power factor (UPF) strategy. When the wind speed changes greatly, sudden wind speed changes and the application of the MPPT strategy will cause large fluctuations in the generator output power, leading to severe thermal cycles, resulting in IGBT module damage or even failure. This is because the wind turbine uses local information to maximize Power point tracking.

In the prior art, the document "Consideration of lifetime and fatigue load in windturbine control" (JGNjiri, N.Beganovic, MHDo, and D. Renew. Energy, vol. 131, pp. 818–828, 2019) proposed a new scheme to extend the life of wind energy conversion systems by integrating an online damage assessment model into a control strategy that reduces structural loads. Document "A novel MPPT method forenhancing energy conversion efficiency taking power smoothing into account" (J.Liu, H.Meng, Y.Hu, Z.Lin, and W.Wang, Energy Convers.Manag., vol.101, pp. 738–748, 2015) proposed a new maximum power point tracking method to improve the energy conversion efficiency of large wind turbines, and at the same time, according to the fluctuation of wind speed, power smoothing was used as the second control objective to reduce the fluctuation. However, it does not consider the cumulative damage of the wind turbine system under the long-term mission profile, nor does it quantify the impact of improvement strategies on the turbine life. The document "Effect of wind speed on wind turbine power converter reliability" (K.Xie, Z.Jiang, andW.Li, IEEE Trans.Energy Convers., vol.27, no.1, pp.96–104, 2012) proposed A new wind power converter system failure rate model and reliability evaluation technology, which considers the influence of the wind speed task curve, proves that the reliability performance of the wind power converter system is closely related to the task curve, but does not give a conclusion based on it. An optimized control method to increase the life of the converter.

Contents of the invention

The purpose of the present invention is to overcome the above-mentioned shortcomings of the prior art and provide a power optimization control method that takes into account the life of the converter and the quality of the output power, so as to effectively smooth the IGBT device junction temperature fluctuations and extend the service life of the converter.

The object of the present invention can be achieved through the following technical solutions:

A power optimization control method that takes into account converter life and output power quality includes the following steps:

Divide the power control strategy working range of the wind turbine according to the load area;

Obtain the fan operating condition parameters and load them into the preset fan model together with the corresponding power control strategy to obtain the electrical parameters of the fan;

Input the electrical parameters of the fan into the preset power loss model and thermal network model for iteration, and obtain the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device, thereby obtaining the life loss of the power device through the preset life consumption model. ;

Calculate the output power quality based on the electrical parameters of the fan;

Through the preset multi-objective optimization function and its constraint conditions, the life loss and output power quality of the power device are optimized and calculated to obtain the optimal rotor angular speed and power factor angle for wind turbine control.

Further, the acquisition process of the life loss of the power device is specifically:

The thermal cycle is proposed from the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device, and the low-frequency junction temperature rise time t _on is obtained;

Calculate the life of the power device based on the low-frequency junction temperature rise time t _on . The calculation expression of the life of the power device is:

In the formula, N _f is the number of thermal cycles to failure; t _on is the junction temperature rise time; I is the root mean square value of the current on each aluminum bonding wire; U is the voltage level, D is the bonding wire diameter; k , β ₁ -β ₆ are model parameters;

Therefore, the linear cumulative damage model is used to predict the life loss of the power device. The calculation expression of the life loss of the power device is:

In the formula, C _LF and C _LL correspond to the life consumption caused by low-frequency thermal cycle and fundamental frequency thermal cycle respectively, N _f,j is the number of cycle failure cycles calculated for the jth thermal cycle, and N _j is the corresponding number of thermal cycles; N is the total number of thermal cycles.

Further, the voltage total harmonic distortion rate is used to measure the power quality, and the calculation expression of the power quality is:

In the formula, V _THD is the power quality, that is, the voltage total harmonic distortion rate, V1 is the effective value of the fundamental voltage, and Vn is the effective value of the nth harmonic voltage.

Further, the expression of the multi-objective optimization function is:

In the formula, ω and are design variables, representing the rotor angular speed and power factor angle respectively;

The constraints are:

_{0≤Tj≤Tjmax _}

_{0≤ω≤ωmax _}

In the formula, T _j is the junction temperature of the power device, T _jmax is the maximum allowable operating temperature of the device; ω _max is the maximum rotor angular speed, is the maximum/minimum power factor.

Further, the process of optimizing the calculation of the life loss and output power quality of the power device includes:

Through the multi-objective optimization function and its constraint conditions, variable optimization is performed. If the junction temperature is greater than T _jmax , the design variables are modified and the optimization calculation is repeated until the junction temperature T _j meets the constraint conditions, and all feasible solutions are found to form a feasible solution. solution set;

Determine the Pareto front of the converter based on the Pareto dominance relationship;

The hierarchical optimization method is used to sort the objective functions hierarchically according to importance to determine the optimal rotor angular speed and power factor angle.

Further, the fan operating conditions parameters include wind speed and ambient temperature curves.

Further, the control variables of the corresponding power control strategy include rotor angular velocity and power factor.

Further, the electrical parameters of the wind turbine include output power, output frequency, voltage, and peak phase current of the machine-side and grid-side converters.

Further, the power loss taken into account by the power loss model includes the power loss of the IGBT and the power loss of the diode.

Further, the thermal network model is a Foster thermal network model.

Compared with the existing technology, the present invention uses a multi-objective optimized power control method to actively adjust the active power and reactive power output on the generator side to smooth junction temperature fluctuations, is not limited to local information, and effectively extends the service life of the converter.

Description of the drawings

Figure 1 is a schematic flowchart of a power optimization control method that takes into account the life of the converter and the output power quality provided in an embodiment of the present invention.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, rather than all embodiments. The components of the embodiments of the invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations.

Therefore, the following detailed description of the embodiments of the invention provided in the appended drawings is not intended to limit the scope of the claimed invention, but rather to represent selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of the present invention.

It should be noted that similar reference numerals and letters represent similar items in the following figures, therefore, once an item is defined in one figure, it does not need further definition and explanation in subsequent figures.

Example 1

This embodiment provides a power optimization control method that takes into account the life of the converter and the output power quality, including the following steps:

Divide the power control strategy working range of the wind turbine according to the load area;

Obtain the fan operating condition parameters and load them into the preset fan model together with the corresponding power control strategy to obtain the electrical parameters of the fan;

Input the electrical parameters of the fan into the preset power loss model and thermal network model for iteration to obtain the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device, and then obtain the life loss of the power device through the preset life consumption model;

Calculate the output power quality based on the electrical parameters of the wind turbine;

Through the preset multi-objective optimization function and its constraints, the life loss and output power quality of the power device are optimized and calculated, and the optimal rotor angular speed and power factor angle are obtained for wind turbine control.

As shown in Figure 1, the specific implementation process of this plan includes the following steps:

Step 1: Divide the active power control strategy and reactive power control strategy working intervals according to the load area:

Step 11: When the wind speed distribution is in the full load area, the wind turbine operates in a constant active power state, and there is no room for wind resource abandonment. The active power control strategy cannot be used to optimize junction temperature fluctuations;

Step 12: When the wind speed is lower than the cut-in wind speed, the wind turbine operates in the no-load area and cannot convert wind energy. The active power control strategy cannot be used to optimize junction temperature fluctuations.

Step 13: As long as the wind speed is higher than the cut-in wind speed, the reactive power control strategy can be used to optimize the junction temperature fluctuation.

Step 2: Obtain the fan operating conditions parameters:

Wind speed (v) and ambient temperature (T _a ) curves obtained from the SCADA system.

Step 3: Substitute the fan operating conditions parameters and the control variables under the corresponding control strategy into the fan model to obtain the electrical parameters of the fan:

Step 31: The control variables under the corresponding control strategy include rotor angular velocity ω and power factor

Step 32: The electrical parameters of the wind turbine include output power P _t , output frequency f _G , voltage U _G , and peak phase current _Im of the machine-side and grid-side converters.

Step 4: Input the electrical parameters of the fan into the power loss model and thermal network model for iteration, and obtain the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device:

Step 41: The power loss of the IGBT module (power device) includes the power loss _PT,loss of the IGBT and the power loss _{PD,loss of} the diode;

Step 42: The thermal network model uses the Foster thermal network model;

Step 5: Bring low-frequency and fundamental frequency thermal cycles into the life consumption model to obtain the life loss of the power device:

Step 51: Use the rainflow counting method to extract the thermal cycle in the low-frequency junction temperature curve, and obtain the low-frequency junction temperature rise time t _on ; for the fundamental frequency thermal cycle, t _on is the conduction time of the power device when the fundamental frequency period is t _on ;

Step 52: Use the bayer model to calculate the life of the IGBT module:

Among them, N _f is the number of thermal cycles to failure; t _on is the junction temperature rise time; I is the root mean square value of the current on each aluminum bonding wire; U is the voltage level, D is the bonding wire diameter; k, β ₁ -β ₆ are model parameters.

Step 53: Use the linear cumulative damage model to predict the life consumption of the IGBT module:

Among them, C _LF and C _LL correspond to the life consumption caused by low-frequency thermal cycle and fundamental frequency thermal cycle respectively. N _f,j is the number of cycle failure cycles calculated for the jth thermal cycle, N _j is the corresponding number of thermal cycles; N is the total number of thermal cycles. For low-frequency thermal cycles, N _j can be obtained using the rainflow counting method. For the fundamental frequency thermal cycle, since the sampling interval is 1 minute, within one interval, N _j =60f.

Step 6: Calculate the output power quality using the electrical parameters of the fan:

The voltage total harmonic distortion rate (VTHD) is used to measure the output power quality, which is not higher than 2%. The calculation formula is:

Among them, V1 is the effective value of the fundamental voltage, and Vn is the effective value of the nth harmonic voltage.

Step 7: Establish a multi-objective optimization function with converter life and output power quality as optimization objectives, and select constraints:

The multi-objective optimization function is:

Among them, ω and are design variables, representing the rotor angular speed and power factor angle respectively, reflecting the power factor vector and reactive power control strategy of the active power generation side.

The constraints are:

Among them, T _j is the junction temperature of the power device, T _jmax is the maximum allowable operating temperature of the device; ω _max is the maximum rotor angular speed, is the maximum/minimum power factor.

Step 8: Optimize the rotor angular speed and power factor angle based on the Pareto algorithm:

Step 81: According to the parameters and the model obtained in steps 1-7, if the junction temperature is greater than T _jmax , modify the design variables and repeat the above steps until the junction temperature T _j meets the constraint conditions, find all feasible solutions and form a feasible solution set .

Step 82: Determine the Pareto front of the converter according to the Pareto dominance relationship.

Step 83: Use the hierarchical optimization method to sort the objective functions hierarchically according to importance to determine the optimal rotor angular speed and power factor angle.

The preferred specific embodiments of the present invention are described in detail above. It should be understood that those skilled in the art can make many modifications and changes based on the concept of the present invention without creative efforts. Therefore, any technical solutions that can be obtained by those skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention and on the basis of the prior art should be within the scope of protection determined by the claims.

Claims (9)

1. A power optimization control method that takes into account the life of the converter and the quality of the output power, characterized in that it includes the following steps: Divide the power control strategy working range of the wind turbine according to the load area; Obtain the fan operating condition parameters and load them into the preset fan model together with the corresponding power control strategy to obtain the electrical parameters of the fan; Input the electrical parameters of the fan into the preset power loss model and thermal network model for iteration, and obtain the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device, thereby obtaining the life loss of the power device through the preset life consumption model. ; Calculate the output power quality based on the electrical parameters of the fan; Through the preset multi-objective optimization function and its constraints, the life loss and output power quality of the power device are optimized and calculated to obtain the optimal rotor angular speed and power factor angle for wind turbine control; The specific process of obtaining the life loss of the power device is as follows: The thermal cycle is proposed from the low-frequency and fundamental frequency junction temperature fluctuation curves of the power device, and the low-frequency junction temperature rise time t _on is obtained; Calculate the life of the power device based on the low-frequency junction temperature rise time t _on . The calculation expression of the life of the power device is: In the formula, N _f is the number of thermal cycles to failure; t _on is the junction temperature rise time; I is the root mean square value of the current on each aluminum bonding wire; U is the voltage level, D is the bonding wire diameter; k , β ₁ -β ₆ are model parameters; Therefore, the linear cumulative damage model is used to predict the life loss of the power device. The calculation expression of the life loss of the power device is: In the formula, C _LF and C _LL correspond to the life consumption caused by low-frequency thermal cycle and fundamental frequency thermal cycle respectively, N _f,j is the number of cycle failure cycles calculated for the jth thermal cycle, and N _j is the corresponding number of thermal cycles; N is the total number of thermal cycles. 2. A power optimization control method taking into account the life of the converter and the output power quality according to claim 1, characterized in that the voltage total harmonic distortion rate is used to measure the power quality, and the calculation of the power quality is The expression is: In the formula, V _THD is the power quality, that is, the voltage total harmonic distortion rate, V1 is the effective value of the fundamental voltage, and Vn is the effective value of the nth harmonic voltage. 3. A power optimization control method taking into account converter life and output power quality according to claim 1, characterized in that the expression of the multi-objective optimization function is: In the formula, ω and are design variables, representing the rotor angular speed and power factor angle respectively; The constraints are: _{0≤Tj≤Tjmax _ 0≤ω≤ωmax _} In the formula, T _j is the junction temperature of the power device, T _jmax is the maximum allowable operating temperature of the device; ω _max is the maximum rotor angular speed, is the maximum/minimum power factor. 4. A power optimization control method taking into account the life of the converter and the output power quality according to claim 3, characterized in that the process of optimizing the calculation of the life loss and output power quality of the power device include: Through the multi-objective optimization function and its constraint conditions, variable optimization is performed. If the junction temperature is greater than T _jmax , the design variables are modified and the optimization calculation is repeated until the junction temperature T _j meets the constraint conditions, and all feasible solutions are found to form a feasible solution. solution set; Determine the Pareto front of the converter based on the Pareto dominance relationship; The hierarchical optimization method is used to sort the objective functions hierarchically according to their importance to determine the optimal rotor angular speed and power factor angle. 5. A power optimization control method taking into account converter life and output power quality according to claim 1, characterized in that the fan operating conditions parameters include wind speed and ambient temperature curves. 6. A power optimization control method taking into account converter life and output power quality according to claim 1, characterized in that the control variables of the corresponding power control strategy include rotor angular velocity and power factor. 7. A power optimization control method taking into account converter life and output power quality according to claim 1, characterized in that the electrical parameters of the wind turbine include output power, output frequency, voltage, machine side and network The peak phase current of the side converter. 8. A power optimization control method taking into account the life of the converter and the output power quality according to claim 1, characterized in that the power loss taken into account by the power loss model includes the power loss of the IGBT and the power of the diode. loss. 9. A power optimization control method taking into account converter life and output power quality according to claim 1, characterized in that the thermal network model is a Foster thermal network model.