A stability control method for gravity energy storage system

Abstract

The invention discloses a stability control method for a gravity energy storage system, which belongs to the field of gravity energy storage technology, and comprises: step A, extracting the stator voltage output by the speed loop and the current loop PI controller and measuring the three-phase current of the motor, and transforming the coordinates into the αβ subspace; step B, designing the switch function, and dynamically obtaining its optimal parameters according to the fuzzy logic controller; step C, designing a sliding mode observer based on compensated back electromotive force, inputting the stator voltage component and the stator current component obtained in step A into the sliding mode observer, and obtaining an estimated back electromotive force; step D, filtering the estimated back electromotive force through a complex coefficient filter; step E, using a notch phase-locked loop to solve the estimated rotor angle from the estimated back electromotive force information. The invention avoids phase lag and improves the accuracy of rotor position estimation; the speed drop is small after a sudden disturbance, the system has strong robustness, and the system operation efficiency and stability are effectively improved.

Description

Technical Field

[0001] The invention belongs to the technical field of gravity energy storage, and in particular relates to a stability control method for a gravity energy storage system. Background Art

[0002] With the large-scale access of new energy power to the existing power system, it has brought great challenges to the stable operation of the existing power transmission grid. Therefore, energy storage technology, as a key means of storing and managing new energy, has received widespread attention. Among them, as one of the most important technologies in power energy storage technology, gravity energy storage system has gradually become an important part of new energy storage technology due to its unique advantages and potential. Permanent magnet synchronous motor (PMSM) is often used as a motor generator in gravity energy storage system. It has strict restrictions on the speed of permanent magnet synchronous motor. The lifting speed of heavy objects too fast will cause the gravity energy storage system to overload, and the speed of heavy objects too slow will reduce the energy storage efficiency of the gravity energy storage system. Therefore, it is necessary to accurately control the operating speed of permanent magnet synchronous motor; the accurate rotor position information of permanent magnet synchronous motor can ensure that the gravity energy storage system reaches the corresponding position accurately when lifting and releasing heavy objects, fully realize the storage and release of energy, and realize the efficient operation of energy management system. However, the rotor position sensor is sensitive to temperature and electromagnetic noise, and is prone to failure when operating outdoors, which directly affects the stability and reliability of the gravity energy storage system.

[0003] Based on the stable operation of the on-site energy storage system, it is urgent to improve the stability and reliability of the gravity energy storage system. Summary of the invention

[0004] Based on the technical problems existing in the prior art, the present invention provides a stability control method for a gravity energy storage system, which solves the problems of poor stability and poor operating efficiency of the existing gravity energy storage system; by using the new switching function designed by the present invention and combining it with fuzzy logic control to perform parameter adaptive adjustment, a new sliding mode observer algorithm based on compensating back electromotive force is adopted, and the back electromotive force estimation can be made more accurate through the observer of the present invention, thereby effectively improving the rotor position estimation accuracy and reducing speed fluctuations, thereby improving the energy utilization rate of the gravity energy storage system.

[0005] According to the technical solution of the present invention, the present invention provides a method for controlling the stability of a gravity energy storage system, which comprises the following steps:

[0006] Step A, extracting the stator voltage output by the speed loop and current loop PI controller of the permanent magnet synchronous motor, and measuring the three-phase current of the permanent magnet synchronous motor, and transforming the coordinates into the αβ subspace to obtain the stator voltage component and stator current component of the α and β axes;

[0007] Step B, designing the switching function, and dynamically obtaining the optimal parameters of the switching function according to the fuzzy logic controller;

[0008] Step C, combining the switching function in step B, designing a sliding mode observer based on compensating back electromotive force, inputting the stator voltage component and the stator current component obtained in step A into the sliding mode observer, and obtaining an estimated back electromotive force;

[0009] Step D, filtering the estimated back electromotive force obtained in step C through a complex coefficient filter to obtain estimated back electromotive force information;

[0010] Step E: Calculate the estimated rotor angle from the estimated back electromotive force information obtained in step D using a notch phase-locked loop.

[0011] Furthermore, step A includes: extracting the dq-axis stator voltage output by the current loop PI controller, and obtaining the stator current in the natural coordinate system from the inverter output through ADC sampling, and the stator voltage and stator current are respectively transformed into the αβ subspace through coordinate transformation.

[0012] Furthermore, the switching function designed in step B is:

[0013] ,

[0014] in, x is the stator current error value, a It is a characteristic parameter that is positively correlated with the slope of the curve. c is the width of the piecewise function switching boundary layer, and e is the natural base; a and c The size of is adaptively adjusted through the fuzzy logic controller.

[0015] Furthermore, the sliding mode observer designed in step C is:

[0016] ,

[0017] in, is the estimated value of stator current; u s is the stator voltage; S is the sliding surface function; g is the compensation coefficient; l is the sliding mode switching gain, and its value is determined according to Lyapunov stability; or is the first adjustment coefficient, 0< or <1; r is the second adjustment coefficient, 0< r <1; A and B are coefficient matrices, , ; R s is the stator resistance; L s is the stator inductance;

[0018] The permanent magnet synchronous motor equation is:

[0019] ,

[0020] in, i α , i β are the stator current components of the α and β axes, u α , u β are the stator voltage components of the α and β axes, e α , e β is the extended back EMF component of the α and β axes, and is the estimated back EMF component of the α and β axes;

[0021] Combined with the permanent magnet synchronous motor equation, the estimated back EMF is:

[0022] .

[0023] Furthermore, step D includes: using the phase difference-free filtering function of the complex coefficient filter to filter out the high-order harmonics in the estimated back electromotive force, and the transfer function is:

[0024] ,

[0025] in, is the estimated back EMF obtained by the sliding mode observer in step C, is the estimated back EMF output by the complex coefficient filter, β is the bandwidth of the control system, is the rotor electrical angular velocity estimated by the system, s is the Laplace operator.

[0026] Furthermore, step E includes: using the notch function of the second-order generalized integrator to filter out the 5th and 7th harmonics still existing in the estimated back electromotive force under extreme conditions for redundancy processing, and the transfer function is:

[0027] ,

[0028] in, u o ( s ) is the signal output, u i ( s ) is the signal input quantity, oh ris the resonant frequency of the second-order generalized integrator, k sogi is a coefficient related to the system bandwidth, s is the Laplace operator.

[0029] Compared with the prior art, the beneficial technical effects of the stability control method of a gravity energy storage system of the present invention are as follows:

[0030] The present invention improves the inherent jitter deficiency of the traditional sliding mode observer; moreover, a smooth and stable back electromotive force waveform can be obtained through a novel sliding mode observer and a complex coefficient filter without introducing a phase delay, thereby optimizing the control system and improving the rotor position estimation accuracy.

[0031] This method can improve the problem of large estimated back-EMF harmonics, avoid phase lag and improve the accuracy of rotor position estimation; the speed drop is small after a sudden disturbance, the system is highly robust, and the operating efficiency of the gravity energy storage system is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a system block diagram of the gravity energy storage system stability control method provided by the present invention.

[0033] Figure 2 It is a structural diagram of a novel sliding mode observer of the gravity energy storage system stability control method provided by the present invention.

[0034] Figure 3 It is a notch phase-locked loop structure diagram of the high-precision sensorless control method for the permanent magnet synchronous motor of the gravity energy storage system provided by the present invention.

[0035] Figure 4 The present invention provides a waveform diagram of rotor position, speed error and estimated back electromotive force of the permanent magnet synchronous motor of the gravity energy storage system provided by the present invention. DETAILED DESCRIPTION

[0036] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0037] It should be noted that when an element is referred to as being "fixed to" or "arranged on" another element, it may be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element. In the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0038] It should be understood that the orientation or position relationship indicated by terms such as "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0039] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0040] The present invention provides a stability control method for a gravity energy storage system, which belongs to the technical field of gravity energy storage and aims to solve the problems of poor stability and operation efficiency of the prior art. The present invention designs a new switching function, combines fuzzy logic control to perform parameter adaptive adjustment, and proposes a new sliding mode observer algorithm based on compensated back electromotive force. The observer can make the back electromotive force estimation more accurate, thereby effectively improving the rotor position estimation accuracy and reducing the speed fluctuation, and improving the energy utilization rate of the gravity energy storage system. First, the three-phase measured current is extracted and transformed into the αβ subspace, and the αβ axis stator voltage output by the PI controller is extracted. Then, an improved switching function based on the fuzzy logic controller is designed, combined with a new sliding mode observer based on compensated back electromotive force and a complex coefficient filter, to obtain the estimated back electromotive force information without phase difference. Finally, the phase-locked loop with a built-in notch filter is used to solve the rotor position information. The method of the present invention can improve the problem of large estimated back electromotive force harmonics, ensure no phase delay and improve the rotor position estimation accuracy; the speed drop is small after the sudden disturbance, the system has strong robustness, and can effectively improve the operation efficiency of the gravity energy storage system.

[0041] The gravity energy storage system stability control method proposed in the present invention adopts a position sensorless control method, which can be used as redundant protection when the rotor position sensor fails, reducing maintenance requirements, which is very important for improving the stable operation of the power system.

[0042] The sliding mode observer (SMO) algorithm in the prior art is a position sensorless control method based on extended back electromotive force estimation. It is widely used in PMSM sensorless control due to its advantages of good dynamic performance, strong robustness, and insensitivity to parameter changes and disturbances. However, the traditional sliding mode observer (SMO) will cause jitter in the sliding trajectory due to the inherent discontinuity of the switching function and the fixed parameters. There are a large number of harmonics in the extended back electromotive force, which affects the rotor position estimation and the smooth speed control, thereby reducing the operating efficiency of the energy storage system. The present invention provides a stability control method for a gravity energy storage system to overcome the above-mentioned defects.

[0043] The following structure, combined with the accompanying drawings, further illustrates the stability control method of the gravity energy storage system.

[0044] See also Figure 1 A method for controlling the stability of a gravity energy storage system according to an embodiment of the present invention includes the following steps A to E.

[0045] Step A, extract the stator voltage output by the speed loop and current loop PI controller and measure the three-phase current of the motor, and transform the coordinates into the αβ subspace respectively; obtain the stator voltage components of the α and β axes u α , u β and stator current components i α , i β .

[0046] Specifically, in step A, the dq axis stator voltage output by the PI controller is extracted, and the stator current iabc in the natural coordinate system is obtained from the inverter output after ADC sampling, and the coordinates are transformed into the αβ subspace respectively. More specifically, the method for obtaining the αβ axis stator voltage and stator current in step A is, for example: the dq axis given voltages ud* and uq* are obtained from the PI controller outputs of the speed loop and the current loop respectively, and the inverse Park coordinate transformation is used to obtain u α and u β , its transformation matrix is:

[0047] ,in, i e is the rotor position electrical angle;

[0048] The stator current iabc in the natural coordinate system is obtained from the inverter output through ADC sampling and then obtained through Clark transformation. i α and i β , its transformation matrix is:

[0049] .

[0050] Step B, design a new switching function and dynamically obtain its optimal parameters (adaptive adjustment parameters) according to the fuzzy logic controller.

[0051] Specifically, the expression of the new switching function designed in step B is:

[0052] ,

[0053] in, x is the stator current error value, a It is a characteristic parameter that is positively correlated with the slope of the curve. c is the width of the piecewise function switching boundary layer, and e is the natural base; a The larger the value, the faster the function changes around zero; a The smaller the value, the smoother the function curve and the better it can suppress the vibration phenomenon. c Although increasing can slow down the vibration, it will reduce the approach speed of the state variable. When the energy storage system operates under different working conditions, the stator current error value is different, and a trade-off needs to be made between robustness and rapidity. a and c The size of is adaptively adjusted through the fuzzy logic controller.

[0054] Step C, according to the sliding mode variable structure theory, combined with the switching function in step B, a new sliding mode observer based on compensating back electromotive force is designed, and the stator voltage component and stator current component obtained in step A are input into the new sliding mode observer to obtain the estimated back electromotive force (is a vector, including and two components).

[0055] Specifically, the mathematical equation of the permanent magnet synchronous motor in the stationary coordinate system is:

[0056] ,

[0057] in, i α , i β are the stator current components of the α and β axes, u α , u β are the stator voltage components of the α and β axes, R s is the stator resistance, L s is the stator inductance, e α , eβ is the extended back EMF component of the α and β axes, and is the estimated back EMF component of the α and β axes;

[0058]

[0059] in, oh e is the rotor electrical angular velocity; ψ f is the permanent magnet flux linkage value; i e is the rotor position in electrical degrees.

[0060] The sliding mode observer designed in step C is:

[0061] ,

[0062] in, is the estimated value of stator current; u s is the stator voltage; S is the sliding surface function; g is the compensation coefficient; l is the sliding mode switching gain, g and l The value of is determined according to Lyapunov stability; or is the first adjustment coefficient, 0< or <1; r is the second adjustment coefficient, 0< r <1; A and B are coefficient matrices, , ; R s is the stator resistance; L s is the stator inductance;

[0063] g and l The value of is determined by Lyapunov stability theory: g >0, l >max{| e α |,| e β |}.

[0064] Subtracting this from the permanent magnet synchronous motor equation, we get:

[0065] ,

[0066] in, is the first derivative of the sliding surface function; is the error value of the α-axis stator current, , is the estimated value of the α-axis stator current; is the error value of the β-axis stator current, , is the estimated value of the β-axis stator current;

[0067] Combined with sliding mode variable structure theory, the estimated back electromotive force is:

[0068] Its structure is as follows Figure 2 shown.

[0069] Step D, filtering the estimated back electromotive force obtained in step C through a complex coefficient filter; in other words, using the complex coefficient filter to filter the estimated back electromotive force Perform phase-free filtering.

[0070] More specifically, the specific method of filtering the back electromotive force output by the sliding mode observer using the complex coefficient filter in step D is: The complex coefficient filter is input to obtain a smoother estimated back EMF by using its ability to suppress high-order harmonic signals and its non-attenuation and non-delay characteristics for fundamental signals. , the transfer function of the complex coefficient filter is:

[0071] ,

[0072] in, is the estimated back EMF obtained by the sliding mode observer in step C, is the estimated back EMF output by the complex coefficient filter, β is the bandwidth of the control system, is the rotor electrical angular velocity estimated by the system, s is the Laplace operator, j Is an imaginary unit.

[0073] Step E, using the estimated back EMF obtained from step D using a notch phase locked loop The information is resolved to estimate the rotor angle.

[0074] More specifically, the specific method of using the notch phase-locked loop to calculate and estimate the rotor angle in step E is: The input phase-locked loop uses the notch function of the second-order generalized integrator (SOGI) to filter out the 5th and 7th harmonics in the estimated back EMF under extreme conditions. The transfer function of the second-order generalized integrator is:

[0075] ,

[0076] in, u o ( s ) is the signal output (Laplace transform), u i ( s ) is the Laplace transform of the signal input, oh r is the resonant frequency of the second-order generalized integrator, k sogi is a coefficient related to the system bandwidth, s is the Laplace operator. When the absolute error between the estimated rotor angle and the actual angle is less than π / 6, the rotor position phase-locked loop converges and the harmonics can be filtered out. Its structure is as follows Figure 3 shown.

[0077] By estimating the precise rotor angle through step E, it can be ensured that the permanent magnet synchronous electric generator for gravity energy storage accurately reaches the highest point and the lowest point when lifting and releasing the heavy block, so as to fully realize the conversion of gravitational potential energy and electrical energy, optimize the energy flow scheduling, reduce energy loss, and improve the efficiency of the energy storage system.

[0078] In the embodiment, the system is initially set to a given speed of 1000 r / min, and then stepped to 2000 r / min at 1 second. The permanent magnet synchronous motor rotor position comparison waveform, speed error waveform, and estimated back electromotive force waveform are shown in FIG. Figure 4 Obviously, the method of the present invention can achieve good estimation accuracy under various given speeds.

[0079] In summary, the stability control method of the gravity energy storage system of the present invention improves the shortcomings of the inherent jitter of the traditional sliding mode observer; and, a smooth and stable back-electromotive force waveform can be obtained through a new sliding mode observer and a complex coefficient filter without introducing a phase delay, thereby optimizing the control system and improving the accuracy of the rotor position estimation; therefore, the method can improve the problem of large estimated back-electromotive force harmonics, avoid phase lag and improve the accuracy of the rotor position estimation; the speed drop is small after a sudden disturbance, the system has strong robustness, and the operating efficiency of the gravity energy storage system is effectively improved.

[0080] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for controlling the stability of a gravity energy storage system, characterized in that: It includes the following steps: Step A, extracting the stator voltage output by the speed loop and current loop PI controller of the permanent magnet synchronous motor, and measuring the three-phase current of the permanent magnet synchronous motor, and transforming the coordinates into the αβ subspace to obtain the stator voltage component and stator current component of the α and β axes; Step B, designing the switching function, and dynamically obtaining the optimal parameters of the switching function according to the fuzzy logic controller; Step C, combining the switching function in step B, designing a sliding mode observer based on compensating back electromotive force, inputting the stator voltage component and the stator current component obtained in step A into the sliding mode observer, and obtaining an estimated back electromotive force; Step D, filtering the estimated back electromotive force obtained in step C through a complex coefficient filter to obtain estimated back electromotive force information; Step E, using a notch phase-locked loop to calculate an estimated rotor angle from the estimated back electromotive force information obtained in step D; Among them, in step A, the method for obtaining the αβ axis stator voltage and stator current is: obtain the dq axis given voltage ud* and uq* from the PI controller output of the speed loop and the current loop respectively, and obtain them through inverse Park coordinate transformation u α and u β , its transformation matrix is: ,in, θ e is the rotor position electrical angle; The stator current iabc in the natural coordinate system is obtained from the inverter output through ADC sampling and then obtained through Clark transformation. i α and i β , its transformation matrix is: ； The switching function designed in step B is: ， in, x is the stator current error value, a It is a characteristic parameter that is positively correlated with the slope of the curve. γ is the width of the piecewise function switching boundary layer, and e is the natural base; a and γ The size of is adaptively adjusted through the fuzzy logic controller; The sliding mode observer designed in step C is: ， in, is the estimated value of stator current; u s is the stator voltage; S is the sliding surface function; ζ is the compensation coefficient; λ is the sliding mode switching gain; ζ and λ The value of is determined according to Lyapunov stability. ζ > 0, λ > max{| e α |,| e β |}; η is the first adjustment coefficient, 0< η <1; r is the second adjustment coefficient, 0< r <1; A and B are coefficient matrices, , ; R s is the stator resistance; L s is the stator inductance; The permanent magnet synchronous motor equation is: ， in, i α , i β are the stator current components of the α and β axes, u α , u β are the stator voltage components of the α and β axes, e α , e β is the extended back EMF component of the α and β axes, and is the estimated back EMF component of the α and β axes; Combined with the permanent magnet synchronous motor equation, the estimated back EMF is: 。 2. The method for controlling the stability of a gravity energy storage system according to claim 1, characterized in that: Step D includes: using the phase difference-free filtering function of the complex coefficient filter to filter out the high-order harmonics existing in the estimated back electromotive force, and its transfer function is: ， in, is the estimated back EMF obtained by the sliding mode observer in step C, is the estimated back EMF output by the complex coefficient filter, β is the bandwidth of the control system, is the rotor electrical angular velocity estimated by the system, s is the Laplace operator.

3. The method for controlling the stability of a gravity energy storage system according to claim 1, characterized in that: Step E includes: converting the back electromotive force estimated in step D into The input phase-locked loop uses the notch function of the second-order generalized integrator to filter out the 5th and 7th harmonics that still exist in the estimated back EMF under extreme conditions for redundancy processing. Its transfer function is: ， in, u o ( s ) is the signal output, u i ( s ) is the signal input quantity, ω r is the resonant frequency of the second-order generalized integrator, k sogi is a coefficient related to the system bandwidth, s is the Laplace operator.

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