CN104659799A - Fuzzy control method of battery energy storage system for restraining wind power fluctuation - Google Patents

Abstract

The present invention relates to a fuzzy control method of a battery energy storage system for smoothing wind power fluctuations. The method includes (1) calculating the output power change value; (2) obtaining the state of charge of a lithium battery; (3) The system needs to stabilize the frequency band of power fluctuations to determine the appropriate filter time constant; (4) The reference value of the absorbed power of the energy storage system plus the current output power of wind power to obtain a smoothed power output; use a high-pass filter to filter the power command of the hybrid energy storage system Get its high-frequency fluctuation component. By adjusting the filter time constant of the low-pass filter in real time, the invention can effectively ensure that the state of charge of the battery is maintained within a limited range while stabilizing the power fluctuation of the wind turbine as much as possible, and avoid overcharging or overdischarging of the battery.

Description

A fuzzy control method for battery energy storage system to stabilize wind power fluctuations

technical field

The invention relates to a method for smooth control and release of wind power generation power, in particular to a fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations.

Background technique

The volatility and randomness of wind power generation are large, and it is easy to have adverse effects on the stability of the power grid and the quality of power after grid-connected operation. Relevant research results show that centralized configuration of a certain capacity energy storage system at the outlet of the wind farm can effectively stabilize the power fluctuation of the wind farm, and the centralized access method is easy to manage, and the required capacity is relatively small. Spectrum analysis of renewable energy sources determines the scope of energy storage compensation, and proposes a method for determining the power and capacity of energy storage systems that can meet the system power output fluctuation rate and SOC constraints. On this basis, it is very important to design a control method that can effectively stabilize wind power fluctuations while taking into account the health management requirements of energy storage systems.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention proposes a fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations. Specifically, the battery energy storage system is connected to the AC bus of the doubly-fed wind turbine connected to the grid. The monitoring system collects the active power output by the fan and the three-phase voltage and current of the AC bus. The control algorithm adjusts the filter time constant through the fuzzy controller according to the state of charge of the lithium battery and the change value of the output power of the fan, and gradually changes the output power of the battery. , so that the state of charge is stabilized within a limited range, while smoothing the output power of the fan as much as possible.

The object of the present invention is to adopt following technical scheme to realize:

A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations, the improvement is that the method includes

(1) Calculate the output power change value;

(2) Obtain the state of charge of the lithium battery;

(3) Determine the appropriate filter time constant according to the power fluctuation frequency band that the battery energy storage system needs to stabilize;

(4) The reference value of the absorbed power of the energy storage system is added to the current output power of wind power to obtain the smoothed power output; the high-pass filter is used to filter the power command of the hybrid energy storage system to obtain its high-frequency fluctuation component.

Preferably, the step (1) includes obtaining the power change value from the difference between the output power value of the fan in the current sampling period and the smoothed output power value in the previous sampling period.

Preferably, the step (2) includes obtaining the current state of charge of the lithium battery from the sampling of the energy storage system.

Further, the state of charge of the lithium battery is calculated by the current integration method:

$\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; \&Integral;</span>}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; t</span>}}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dt</span>}$

That is, the state of charge of the SOC battery at the current moment is the sum of the initial state of charge and the integral of the current, t ₀ is the initial time, and t is the current time.

Preferably, the step (3) includes inputting the power change value and the state of charge of the lithium battery into the fuzzy controller, and the filtering time constant calculated by the controller is in the order of seconds to minutes.

Preferably, the step (4) includes calculating the reference value of the absorbed power of the energy storage system by the digital low-pass filter according to the filter time constant calculated by the fuzzy controller, and obtaining the smoothed power output.

Further, when the power change value is positive and the power change value of the wind turbine is relatively large, the filter time constant is increased, and the energy storage system is used to stabilize the power fluctuation;

If the power change value of the wind turbine is small, then on the basis of meeting the smoothing requirements, the grid-connected scheduling requirements are met, and the filter time constant is reduced; the same is true when the power change value is negative.

Furthermore, when the state of charge of the battery is high:

In the state of charging, the filter time constant is reduced to weaken the stabilizing effect of the energy storage system;

In the discharge state, the filter time constant is increased to enhance the stabilizing effect of the energy storage system;

If the state of charge of the battery is higher than the upper limit, only the battery is allowed to discharge;

When the battery's state of charge is low:

In the discharge state, reduce the filter time constant;

In the charging state, increase the filter time constant;

If the battery state of charge is below the lower limit, only the battery is allowed to charge.

Compared with the prior art, the beneficial effects of the present invention are:

The present invention uses a fuzzy controller to adjust the filter time constant of the low-pass filter in real time according to the change value of the output power of the wind turbine and the state of charge of the battery, and can effectively ensure the charge of the battery while stabilizing the power fluctuation of the wind turbine as much as possible. Conditions are maintained within limits to avoid overcharging or overdischarging the battery.

The invention connects the battery energy storage system to the AC busbar of the doubly-fed wind turbine connected to the grid. The monitoring system collects the active power output by the fan and the three-phase voltage and current of the AC bus. The control algorithm adjusts the filter time constant through the fuzzy controller according to the state of charge of the lithium battery and the change value of the output power of the fan, and gradually changes the output power of the battery. , so that the state of charge is stabilized within a limited range, while smoothing the output power of the fan as much as possible. The present invention applies a fuzzy controller, and by adjusting the filter time constant of the low-pass filter in real time, while stabilizing the power fluctuation of the wind turbine as much as possible, it can effectively ensure that the state of charge of the battery is maintained within a limited range, and avoid overcharging or overcharging of the battery. discharge.

Description of drawings

Fig. 1 is a structural diagram of a fuzzy control method for a battery energy storage system to stabilize wind power fluctuations provided by the present invention.

Fig. 2 is a flow chart of a fuzzy control method for a battery energy storage system for smoothing wind power fluctuations provided by the present invention.

Detailed ways

The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

As shown in Figure 1, it is a structural diagram of a wind power system connected to a battery energy storage system. The energy storage system is connected to the grid-connected AC bus of the doubly-fed wind turbine. The active power emitted by the fan is P _w , the power absorbed by the energy storage system is P _BAT , and the smoothed output power of the fan is P _OUT . The monitoring system collects the active power output by the fan and the three-phase voltage and current of the AC bus, and calculates the reference power P _{BAT_ref} to be absorbed by the energy storage system by the control algorithm, and the energy storage system controls the energy storage converter to absorb the corresponding power according to the reference power .

Figure 2 shows the schematic diagram of fan power smoothing control. The steps of the power smoothing algorithm are as follows:

Step 1. The difference between the output power value of the fan in the current sampling period and the smoothed output power value in the previous sampling period is obtained to obtain the power change value ΔP;

Step 2, the current state of charge SOC of the lithium battery is obtained by sampling the energy storage system;

Step 3, input the power change value ΔP and the state of charge SOC of the lithium battery into the fuzzy controller, and the controller calculates the appropriate filter time constant τ:

Step 4, the digital low-pass filter calculates the reference value P _{BAT_ref} of the absorbed power of the energy storage system according to the filter time constant τ calculated by the fuzzy controller, and obtains the smoothed power output P _OUT .

In the above steps, the SOC of the lithium battery in the energy storage system is related to factors such as the temperature of the battery, discharge rate, battery life, and self-discharge. The above factors are not considered here, and only the lithium battery is assumed to be in an ideal state , use the current integration method (ampere-hour method) to calculate the state of charge:

$\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; \&Integral;</span>}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; t</span>}}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dt</span>}$

Low-pass filtering uses a first-order Butterworth low-pass filter. Referring to the principles and methods in signal analysis and processing, the output power fluctuations of wind turbines include high-frequency parts and low-frequency parts. Among them, the fluctuation of the low-frequency part is relatively slow, and the power conversion rate is small. Although it will cause interference to the power system after being injected into the power grid, the power system has enough time to respond. However, the power change rate of the high-frequency part is large, and it will bring a short-term large impact after being injected into the power grid. The power system cannot respond in time, which is not conducive to the safe operation of the power system. Therefore, referring to the filtering principle in signal processing, introducing a low-pass filter can filter out high-frequency components in wind power fluctuations, reduce the power change rate, and stabilize the power output of wind turbines. By applying the energy storage system and changing the output power of the wind turbine through its charge and discharge, the low-pass filtering of the output power of the wind turbine can be realized to achieve the purpose of stabilizing fluctuations.

The function of the fuzzy controller is to obtain the appropriate filter time constant τ according to the power change value and the state of charge of the battery, so as to dynamically stabilize the output power of the wind turbine in real time, and at the same time control the power absorbed by the energy storage system and the state of charge of the battery .

From the perspective of power change value, when the power change value is positive, if the power change value of the wind turbine is large, then increase the filter time constant, and use the energy storage system to stabilize the power fluctuation as much as possible; if the power change value of the wind turbine If is smaller, on the basis of meeting the smoothing requirements, the filter time constant should be appropriately reduced to reduce the burden on the energy storage system. The same applies when the power change value is negative.

From the point of view of the state of charge of the battery, when the state of charge of the battery is high, if it is in the state of charge, the filter time constant will be reduced, and the stabilization effect of the energy storage system will be weakened, thereby reducing the power absorbed by the energy storage system. Avoid the rapid increase of the battery state of charge; if it is in the discharge state, increase the filter time constant to enhance the stabilization effect of the energy storage system, thereby increasing the power released by the energy storage system and accelerating the decline of the battery state of charge; if the battery If the state of charge is higher than the upper limit, only the battery is allowed to discharge to prevent the battery from being overcharged. Vice versa, when the state of charge of the battery is low, if it is in the discharge state, then reduce the filter time constant; if it is in the charge state, then increase the filter time constant appropriately; if the battery state of charge is lower than If the lower limit is set, only the battery is allowed to be charged to prevent the battery from being over-discharged.

Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Those of ordinary skill in the art can still modify or equivalently replace the specific implementation methods of the present invention with reference to the above embodiments. Any modifications or equivalent replacements departing from the spirit and scope of the present invention are within the protection scope of the claims of the pending application of the present invention.

Claims (8)

1. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations, characterized in that the method includes (1) Calculate the output power change value; (2) Obtain the state of charge of the lithium battery; (3) Determine the appropriate filter time constant according to the power fluctuation frequency band that the battery energy storage system needs to stabilize; (4) The reference value of the absorbed power of the energy storage system is added to the current output power of wind power to obtain the smoothed power output; the high-pass filter is used to filter the power command of the hybrid energy storage system to obtain its high-frequency fluctuation component. 2. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 1, wherein the step (1) includes comparing the output power value in the current sampling period of the wind turbine with the previous The difference between the smoothed output power values within the sampling period is used to obtain the power change value. 3. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 1, wherein said step (2) includes obtaining the current state of charge of the lithium battery by sampling the energy storage system . 4. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 3, wherein the state of charge of the lithium battery is calculated using the current integration method: $\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; SOC</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{<span\; class="notranslate">\; \&Integral;</span>}_{{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}}^{\mathrm{<span\; class="notranslate">\; t</span>}}\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; dt</span>}$ That is, the state of charge of the SOC battery at the current moment is the sum of the initial state of charge and the integral of the current, t ₀ is the initial time, and t is the current time. 5. A kind of fuzzy control method of the battery energy storage system that smooths wind power fluctuation as claimed in claim 1, it is characterized in that, described step (3) comprises inputting the state of charge of power change value and lithium battery into fuzzy In the controller, the filter time constant calculated by the controller, the time constant is from second to minute. 6. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 1, wherein said step (4) includes a digital low-pass filter based on the filter time calculated by the fuzzy controller Constant, calculate the reference value of the absorbed power of the energy storage system, and obtain the smoothed power output. 7. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 6, wherein when the power change value is positive and the power change value of the wind turbine is relatively large, the filter is increased Time constant, using the energy storage system to stabilize power fluctuations; If the power change value of the wind turbine is small, then on the basis of meeting the smoothing requirements, the grid-connected scheduling requirements are met, and the filter time constant is reduced; the same is true when the power change value is negative. 8. A fuzzy control method for a battery energy storage system that stabilizes wind power fluctuations as claimed in claim 6, wherein when the state of charge of the battery is relatively high: In the state of charging, the filter time constant is reduced to weaken the stabilizing effect of the energy storage system; In the discharge state, the filter time constant is increased to enhance the stabilizing effect of the energy storage system; If the state of charge of the battery is higher than the upper limit, only the battery is allowed to discharge; When the battery's state of charge is low: In the discharge state, reduce the filter time constant; In the charging state, increase the filter time constant; If the battery state of charge is below the lower limit, only the battery is allowed to charge.