A multi-flywheel compound power control method under power output saturation constraint

Abstract

The application discloses a kind of multi-flywheel compound power control methods under the constraint of power output saturation, which comprises the following steps: constructing the dynamics model of flywheel energy storage unit, calculating the total output power of flywheel energy storage system, setting the control target of its energy storage system power tracking and energy balance based on the total output power of flywheel energy storage system;Set the command generator, set the distributed observer of each flywheel energy storage unit according to the command generator;Set the average consistency algorithm of each flywheel energy storage unit;According to the distributed command generator and the distributed observer, set the controller for each flywheel energy storage unit, complete the double-target control of power tracking and energy balance of flywheel energy storage system.The application considers the actual dynamic model of flywheel, can keep its power tracking and energy balance under flywheel model and unstable communication network, realize the double-target control of flywheel power tracking and energy balance under the constraint of power output saturation.

Description

Technical Field

[0001] This invention relates to the field of collaborative control technology for energy storage systems, and specifically to a multi-flywheel composite power control method under power output saturation constraints. Background Technology

[0002] Energy storage systems are a crucial component of the future smart grid. There are many types of energy storage systems, such as batteries, supercapacitors, and hydropower. Based on differences in the external characteristics of energy storage, distributed energy storage can be divided into energy-type and power-type systems. High power density is the main advantage of power-type energy storage, which mainly includes superconducting magnetic energy storage and flywheels; energy-type energy storage systems have high energy storage density, mainly including compressed air energy storage and chemical battery energy storage. Among all types of energy storage systems, flywheels have advantages such as high energy density, fast response speed, low maintenance cost, long service life, and environmental friendliness compared to other energy storage devices. Moreover, flywheels have lower requirements for implementation in practice; for example, the location and size requirements for flywheel operation are lower compared to other energy storage devices.

[0003] Flywheel energy storage systems are energy storage devices that convert electromechanical energy. This system uses physical methods to store energy, achieving the mutual conversion and storage of electrical energy and the mechanical kinetic energy of a high-speed rotating flywheel through a bidirectional electric / generator reversible motor. Flywheel energy storage systems have been applied in aerospace, UPS power supplies, transportation, wind power generation, and the nuclear industry. With the continuous advancement of composite material technology, magnetic support technology, integrated motor-generator technology, and multidisciplinary optimization design technology, there is increasing attention being paid to flywheel energy storage technology, and related new technologies are constantly emerging.

[0004] A drawback of flywheels is their relatively low power density per unit. To address this, one possible approach is to connect multiple flywheels together to form a flywheel energy storage matrix system. Currently, there are many important applications for flywheel energy storage systems, such as supporting wind turbine systems and offshore power generation systems. Energy management in energy storage systems typically involves multiple control objectives and constraints, with two being the most fundamental. Firstly, because the energy storage system needs to promptly support the grid in releasing or absorbing electrical energy, its total output power must meet the power command from the upper-level grid. Secondly, the energy levels of each energy unit within the energy storage system should remain balanced. In this way, the rate power capacity of the energy storage system can always be maintained at its maximum value.

[0005] Existing control methods for flywheel energy storage systems (such as a load balance control method for a flywheel energy storage system, patent publication number CN112600228A) involve multiple flywheels in the flywheel energy storage system, but the communication network is fixed. Therefore, they cannot be directly applied to flywheel matrix energy storage systems under unstable communication network conditions. The literature (H.Cai, Power Tracking and State-of-Energy Balancing of an Energy Storage System by Distributed Control, IEEE Access, vol.8, pp.170261-170270, 2020.) considers an energy storage system composed of multiple energy storage units, but its energy storage unit model is a simplified first-order integrator model, which cannot be directly applied to flywheel matrix energy storage systems under unstable communication network conditions, unknown global system information, and flywheel output power saturation constraints. Moreover, for flywheel matrix energy storage systems under unstable communication network conditions, unknown global system information, and flywheel output power saturation constraints, there is currently no feasible distributed control scheme that can achieve dual-objective control of power tracking and load balance.

[0006] Therefore, there is an urgent need for a flywheel matrix energy storage system that can be directly applied to flywheel matrix energy storage systems under unstable communication network conditions, unknown global system information, and flywheel output power saturation constraints, and a dual-objective control method that can achieve power point tracking and load balance for such energy storage systems. Summary of the Invention

[0007] To overcome the defects and shortcomings of existing technologies, this invention provides a multi-flywheel composite power control method under power output saturation constraints. The flywheel consensus algorithm proposed in this invention overcomes the dependence on global system information and considers the power output saturation constraints of a single flywheel, realizing local power tracking and making the control strategy more practical. The overall power output of the energy storage system meets the specified reference power, and the energy state of all energy storage units is balanced.

[0008] To achieve the above objectives, the present invention adopts the following technical solution:

[0009] This invention provides a multi-flywheel composite power control method under power output saturation constraints, comprising the following steps:

[0010] A dynamic model of the flywheel energy storage unit is constructed, the total output power of the flywheel energy storage system is calculated, and the control objectives of power point tracking and load balance of the energy storage system are set based on the total output power of the flywheel energy storage system.

[0011] Configure the command generator, and configure the distributed observer for each flywheel energy storage unit according to the command generator;

[0012] Define the average consensus algorithm for each flywheel energy storage unit;

[0013] Based on the distributed command generator and distributed observer, a controller is set for each flywheel energy storage unit to achieve the dual objective control of power point tracking and load balance of the flywheel energy storage system.

[0014] As a preferred technical solution, the dynamic model for constructing the flywheel energy storage unit specifically includes:

[0015] The energy state of the i-th flywheel at time t is defined as follows:

[0016]

[0017] In the formula ω i (t) represents the angular velocity of the i-th flywheel at time t. Let ω be the load-speed coefficient of the i-th flywheel. i，max This represents the maximum permissible rotational speed of the i-th flywheel during operation.

[0018] The dynamic model of the i-th flywheel energy storage unit is as follows:

[0019]

[0020]

[0021]

[0022]

[0023] In the formula I i B vi P i，put (t) represent the moment of inertia, damping coefficient, and output power of the i-th flywheel at time t, respectively; With ψ i (t) represents the desired state of charge and the desired derivative of the state of charge for the i-th flywheel, respectively, where ι is the proportional gain; u i (t) represents the control input of the i-th flywheel. P represents the control input of the i-th flywheel when the output power is not saturated. i (t) represents the output power of the i-th flywheel. and P i (t) represent the upper and lower limits of the output power of the i-th flywheel, respectively. φ i The derivative of (t) at time t, P represents i，put (t) is the derivative of (t) at time t.

[0024] As a preferred technical solution, the total output power of the flywheel energy storage system is calculated, and control targets for power point tracking and load balance are set based on the total output power of the flywheel energy storage system. Specifically, these targets include:

[0025] At time t, the total output power of the flywheel energy storage system is:

[0026]

[0027] In the formula, P i，put (t) represents the output power of the i-th flywheel at time t, and the number of flywheels is N.

[0028] The controller for each energy storage unit has the following dual-objective control expression for power point tracking and load balance:

[0029]

[0030]

[0031] In the formula P FESMS (t) and P REF (t) represents the total output power and the reference value of the total output power of the flywheel energy storage system at time t, respectively. i (t) represents the energy state of the i-th flywheel at time t, φ j (t) represents the energy state of the j-th flywheel at time t.

[0032] As a preferred technical solution, the instruction generator specifically includes:

[0033] The instruction generator is set as follows:

[0034]

[0035] P REF (t)=C0ξ0(t)

[0036] Where ξ0(t) represents the internal state of the instruction generator, A0 and C0 are constant matrices, and P REF (t) represents the reference power input to the flywheel energy storage system. Let ξ0(t) be the derivative of the function at time t.

[0037] As a preferred technical solution, a distributed observer is configured for each flywheel energy storage unit based on the command generator, specifically including:

[0038] The distributed observer for the i-th flywheel is configured as follows:

[0039]

[0040]

[0041]

[0042] P i，REF (t)=C i (t)ξ i (t)

[0043] Among them, A i (t) represents the observation value of the coefficient matrix A0 of the i-th distributed instruction generator, A j (t) represents the observed value of the coefficient matrix A0 of the j-th distributed instruction generator, μ A C represents the observer gain of the coefficient matrix A0. i (t) represents the observation of the coefficient matrix C0 of the i-th distributed instruction generator, C j (t) represents the observed value of the coefficient matrix C0 of the j-th distributed instruction generator, μ C ξ represents the observer gain of the coefficient matrix C0. i (t) represents the observation of the internal state matrix ξ0(t) of the i-th distributed instruction generator, ξ j (t) represents the observation of the internal state matrix ξ0(t) of the j-th distributed instruction generator, μ ξ P represents the observer gain of the internal state matrix ξ0(t). i，REF (t) represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel. If the i-th distributed observer can obtain the information of the j-th distributed observer at time t, then a ij (t) = 1, otherwise, a ij (t) = 0, where N represents the number of flywheels. and Represent functions A respectively i (t), C i (t), ξ i (t) is the derivative of (t) at time t.

[0044] As a preferred technical solution, an average consensus algorithm is set for each flywheel energy storage unit, specifically including:

[0045]

[0046]

[0047]

[0048]

[0049] Where, ρ i (t) and Let ρ represent the first consistency coefficient and the second consistency coefficient of the i-th flywheel, respectively. j (t) and ρ represents the first and second consistency coefficients of the j-th flywheel. i (0) represents ρ i The initial value of (t), express initial value, This represents the consistency state of the i-th flywheel. μ represents the consistency state of the j-th flywheel. ρ , and This represents the first consistency gain, the second consistency gain, and the third consistency gain. express The initial value of φ i (0) represents the i-th flywheel energy state φ i The initial value of (t) is such that if the i-th flywheel can obtain information about the j-th flywheel at time t, then a ij (t) = 1, otherwise, a ij (t) = 0, N represents the number of flywheels, I i B vi and γ i Let represent the moment of inertia, damping coefficient, and charge-speed coefficient of the i-th flywheel, respectively. Represent the function ρ respectively i (t), The derivative at time t.

[0050] As a preferred technical solution, the local tracking control settings for the flywheel energy storage system are as follows:

[0051]

[0052]

[0053] in, With ψ i (t) represents the desired state of charge and the desired derivative of the state of charge for the i-th flywheel, respectively; κ is the proportional gain; I i B vi and φ i (t) represent the moment of inertia, damping coefficient, and charge state at time t of the i-th flywheel, respectively. i，REF (t) represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel; ρ represents the consistency state of the i-th flywheel. i (t) and ξ represents the first and second consistency coefficients of the i-th flywheel;i (t) represents the observation of the internal state matrix ξ0(t) of the i-th distributed instruction generator, and N represents the number of flywheels. Representing functions respectively φ i (t), P i，REF (t) is the derivative of (t) at time t.

[0054] As a preferred technical solution, the flywheel energy storage system includes a communication network, a command generator, several energy storage units, and a power grid, wherein the energy storage unit is a flywheel.

[0055] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0056] (1) Under the conditions of unknown global system information, unstable communication network and saturation constraint of flywheel output power, this invention proposes for the first time a feasible distributed control method and local power tracking control for flywheel energy storage system composed of multiple flywheels, so as to achieve dual objective control of power tracking and load balance.

[0057] (2) The present invention adopts a technical solution that combines distributed observers and consensus algorithms, which solves the technical problems of distributed estimation of global command information and distributed estimation of average coefficient of flywheel energy storage system under unstable communication conditions, and achieves the technical effect of simultaneously realizing power tracking and load balance. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the multi-flywheel composite power control method under power output saturation constraints in this embodiment.

[0059] Figure 2 This is a schematic diagram of the energy storage system structure in this embodiment;

[0060] Figure 3 This is a diagram of the energy storage unit switching communication network in the simulation of this embodiment;

[0061] Figure 4(a) is a simulation result curve of the flywheel load energy state changing with time in this embodiment;

[0062] Figure 4(b) is a simulation result curve of the output power of each flywheel changing with time in this embodiment;

[0063] Figure 4(c) is a simulation result curve of the total output power changing with time in this embodiment;

[0064] Figure 4(d) is a simulation result curve showing the change of error between total output power and reference power over time in this embodiment. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0066] This embodiment provides a multi-flywheel composite power control method under power output saturation constraints. On the one hand, the overall power output of the energy storage system meets the specified reference power; on the other hand, the state of charge of all energy storage units is balanced, realizing flywheel power tracking and state of charge balance control under power output saturation constraints. The method specifically includes the following steps:

[0067] S1: Construct a dynamic model of the flywheel energy storage unit, calculate the total output power of the flywheel energy storage system, and set the control targets for power tracking and load balance of the energy storage system based on the total output power of the flywheel energy storage system;

[0068] like Figure 2 As shown, the flywheel energy storage system includes a communication network, a distributed command generator, several energy storage units, and a power grid, with the energy storage unit being a flywheel.

[0069] like Figure 3 As shown, this embodiment uses 6 flywheel energy storage units, where node 0 represents the command generator.

[0070] In this embodiment, the dynamic model of the energy storage unit is as follows:

[0071] The energy state of the i-th flywheel at time t is defined as follows:

[0072]

[0073] In the formula ω i (t) represents the angular velocity of the i-th flywheel at time t. Let ω be the load-speed coefficient of the i-th flywheel. i，max This represents the maximum permissible rotational speed of the i-th flywheel during operation.

[0074] The dynamic model of the i-th flywheel energy storage unit is as follows:

[0075]

[0076]

[0077]

[0078]

[0079] In the formula I i B vi P i，put(t) represent the moment of inertia, damping coefficient, and output power of the i-th flywheel at time t, respectively; With ψ i (t) represents the desired state of charge and the desired derivative of the state of charge for the i-th flywheel, respectively, where ι is the proportional gain; u i (t) represents the control input of the i-th flywheel. P represents the control input of the i-th flywheel when the output power is not saturated. i (t) represents the output power of the i-th flywheel. and P i (t) represents the upper and lower limits of the output power of the i-th flywheel, respectively; φ i The derivative of (t) at time t, P represents i，put (t) is the derivative of (t) at time t.

[0080] The control objective of the energy storage system for each energy storage unit's controller is:

[0081] At time t, the total output power of the flywheel energy storage system is:

[0082]

[0083] In the formula, P i，put (t) represents the output power of the i-th flywheel at time t, and the number of flywheels is N.

[0084] The controller for each energy storage unit has the following dual-objective control expression for power point tracking and load balance:

[0085]

[0086]

[0087] In the formula P FESMS (t) and P REF (t) represents the total output power and the reference value of the total output power of the flywheel energy storage system at time t, respectively. i (t) represents the energy state of the i-th flywheel at time t, φ j (t) represents the energy state of the j-th flywheel at time t.

[0088] S2: Set the command generator, and set the distributed observer for each flywheel energy storage unit according to the command generator;

[0089] In this embodiment, the flywheel distributed observer is configured as follows:

[0090] The instruction generator is set as follows:

[0091]

[0092] P REF (t)=C0ξ0(t)

[0093] In the formula, ξ0(t) represents the internal state of the instruction generator, A0 and C0 are constant matrices, and P... REF (t) represents the reference power input to the flywheel energy storage system. Let ξ0(t) be the derivative of the function at time t.

[0094] Assuming the communication network is undirected, the distributed observer configuration for the i-th flywheel is as follows:

[0095]

[0096]

[0097]

[0098] P i，REF (t)=C i (t)ξ i (t)

[0099] Among them, A i (t) represents the observation value of the coefficient matrix A0 of the i-th distributed instruction generator, A j (t) represents the observed value of the coefficient matrix A0 of the j-th distributed instruction generator, μ A C represents the observer gain of the coefficient matrix A0. i (t) represents the observation of the coefficient matrix C0 of the i-th distributed instruction generator, C j (t) represents the observed value of the coefficient matrix C0 of the j-th distributed instruction generator, μ C ξ represents the observer gain of the coefficient matrix C0. i (t) represents the observation of the internal state matrix ξ0(t) of the i-th distributed instruction generator, ξ j (t) represents the observation of the internal state matrix ξ0(t) of the j-th distributed instruction generator, μ ξ P represents the observer gain of the internal state matrix ξ0(t). i，REF (t) represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel. If the i-th distributed observer can obtain the information of the j-th distributed observer at time t, then a ij (t) = 1, otherwise, a ij (t) = 0, the number of flywheels is N. and Represent functions A respectively i (t), C i (t), ξi (t) is the derivative of (t) at time t.

[0100] S3: Define the average consensus algorithm for each flywheel energy storage unit;

[0101] Assuming the communication network is undirected, the average consensus algorithm for the i-th flywheel is defined as follows:

[0102]

[0103]

[0104]

[0105]

[0106] In the formula ρ i (t) and Let ρ represent the first consistency coefficient and the second consistency coefficient of the i-th flywheel, respectively. j (t) and ρ represents the first and second consistency coefficients of the j-th flywheel. i (0) represents ρ i The initial value of (t), express initial value, This represents the consistency state of the i-th flywheel. μ represents the consistency state of the j-th flywheel. ρ , and This represents the first consistency gain, the second consistency gain, and the third consistency gain. express The initial value of φ i (0) represents the i-th flywheel energy state φ i The initial value of (t) is such that if the i-th flywheel can obtain information about the j-th flywheel at time t, then a ij (t) = 1, otherwise, a ij (t) = 0, the number of flywheels is N, I i B vi and γ i Let represent the moment of inertia, damping coefficient, and charge-speed coefficient of the i-th flywheel, respectively. Represent the function ρ respectively i (t), The derivative at time t.

[0107] S4: Based on the distributed command generator and distributed observer, a controller is set for each flywheel energy storage unit to complete the dual-objective control of power tracking and load balance of the flywheel energy storage system.

[0108] The system's local tracking control settings are as follows:

[0109]

[0110]

[0111] In the formula With ψ i (t) represents the desired state of charge and the desired derivative of the state of charge for the i-th flywheel, respectively; κ is the proportional gain; I i B vi and φ i (t) represent the moment of inertia, damping coefficient, and charge state at time t of the i-th flywheel, respectively. i，REF (t) represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel; ρ represents the consistency state of the i-th flywheel. i (t) and ξ represents the first and second consistency coefficients of the i-th flywheel; i (t) represents the observation value of the internal state matrix ξ0(t) of the i-th distributed instruction generator; the number of flywheels is N. Representing the function φ i (t), P i，REF (t) is the derivative of (t) at time t.

[0112] In this embodiment, a distributed control scheme is set up for the flywheel-based energy storage system to meet the dual objectives of power point tracking and load balance. The actual dynamic model of the flywheel and the saturation of the flywheel output power are taken into account. The energy storage system can maintain its power point tracking and load balance under the conditions of unknown global system information, unstable communication network and flywheel output power saturation constraints, and the dual control objectives of the system are achieved.

[0113] In this embodiment, the simulation parameters are set as follows:

[0114] The physical parameters of the six flywheels are designed as follows:

[0115] Flywheel 1: I1 = 1.2 kg·m 2 B v1 =1.03×10 -3 ω 1，max = 950 rad / s

[0116] Flywheel 2: I2 = 1.1 kg·m 2 B v2 =0.98×10 -3 ω 2，max =1100rad / s

[0117] Flywheel 3: I3 = 1.3 kg·m 2 B v3 =0.9×10 -3 ω 3，max =1200rad / s

[0118] Flywheel 4: I4 = 1.0 kg·m 2 B v4 =1.05×10 -3 ω 4，max =900rad / s

[0119] Flywheel 5: I5 = 0.9 kg·m 2 B v5 =0.95×10 -3 ω 5，max =800rad / s

[0120] Flywheel 6: I6 = 0.8 kg·m 2 B v6 =1×10 -3 ω 6，max =1000rad / s

[0121] The initial system values ​​are given as follows:

[0122]

[0123]

[0124]

[0125] P REF，i (0) = A i (0) = C i (0)=ξ i (0) = 0, where i = 1, 2, 3, 4

[0126] P i (t) = -10kW, where i = 1, 2, 3, 4

[0127] The control gain is set as follows:

[0128] μ S =μ C =μ η =μ α =μ β =μ ψ =100

[0129] κ=ι=1

[0130] The instruction generator is designed as follows:

[0131]

[0132] P REF (t)=(1 0)ξ0(t)

[0133]

[0134] Communication network switching period T p =1s; Define power error P e (t)=P REF (t)-P FESMS (t).

[0135] As shown in Figure 4(a), after a period of time, the difference in the state of charge of each energy storage unit is close to zero, indicating that the energy balance target has been achieved. As shown in Figure 4(b), each flywheel is affected by the output power saturation constraint, and the output power is limited to the range of -10kW to 10kW, not exceeding its upper and lower limits. As shown in Figure 4(c), the total output power of the system tracks the reference power after a period of time. At the same time, as shown in Figure 4(d), the error between the total output power and the reference power returns to zero after a certain period of time, indicating that the system has simultaneously achieved power point tracking. In summary, the energy storage system maintains its power point tracking and energy balance under the conditions of flywheel model, flywheel output power saturation, unknown global system information, and unstable communication network, thus achieving the dual control objectives of the system.

[0136] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A multi-flywheel composite power control method under power output saturation constraints, characterized in that, Includes the following steps: A dynamic model of the flywheel energy storage unit is constructed, the total output power of the flywheel energy storage system is calculated, and the control objectives of power point tracking and load balance of the energy storage system are set based on the total output power of the flywheel energy storage system. The dynamic model for constructing the flywheel energy storage unit specifically includes: At time t The energy state of a flywheel is defined as follows: ； In the formula Indicates the first The angular velocity of the flywheel at time t Let be the load-speed coefficient of the i-th flywheel. This represents the maximum permissible rotational speed of the i-th flywheel during operation; No. The dynamic model of a flywheel energy storage unit is as follows: ； In the formula They represent the first The moment of inertia, damping coefficient, and output power of each flywheel at time t; and They represent the first The expected state of charge and the derivative of the expected state of charge for each flywheel. For proportional gain; Indicates the first Control input for each flywheel This indicates the first time when the output power is not saturated. Control input for each flywheel Indicates the first Each flywheel output power, and They represent the first The upper and lower limits of the output power of each flywheel. express The derivative at time t, express The derivative at time t; Configure the command generator, and configure the distributed observer for each flywheel energy storage unit according to the command generator; Define the average consensus algorithm for each flywheel energy storage unit; Based on the distributed command generator and distributed observer, a controller is set for each flywheel energy storage unit to complete the dual objective control of power tracking and load balance of the flywheel energy storage system; The local tracking control settings for the flywheel energy storage system are as follows: ； in, and They represent the first The expected state of charge and the derivative of the expected state of charge for each flywheel; For proportional gain; , and They represent the first The moment of inertia, damping coefficient, and time of rotation of each flywheel The state of charge energy, This represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel; Indicates the first The consistency state of each flywheel and Indicates the first The first and second consistency coefficients of each flywheel; Represents the internal state matrix of the i-th distributed instruction generator. Observations Indicates the number of flywheels. , , Representing functions respectively , , The derivative at time t.

2. The multi-flywheel composite power control method under power output saturation constraint according to claim 1, characterized in that, Calculate the total output power of the flywheel energy storage system, and set its power point tracking and load balance control targets based on the total output power of the flywheel energy storage system. Specifically, this includes: At time t, the total output power of the flywheel energy storage system is: ； In the formula, Indicates the time t at the th... The output power of each flywheel, the number of flywheels is ; The controller for each energy storage unit has the following dual-objective control expression for power point tracking and load balance: ； In the formula and Let represent the total output power and the reference value of the total output power of the flywheel energy storage system at time t, respectively. Indicates the time t at the th... The state of charge of each flywheel Indicates the time t at the th... The energy state of a flywheel.

3. The multi-flywheel composite power control method under power output saturation constraint according to claim 1, characterized in that, The setting instruction generator specifically includes: The instruction generator is set as follows: ； in, This refers to the internal state of the instruction generator. and It is a constant matrix. This represents the reference power input to the flywheel energy storage system. Representation function The derivative at time t.

4. The multi-flywheel composite power control method under power output saturation constraint according to claim 1, characterized in that, The distributed observer for each flywheel energy storage unit is configured according to the command generator, specifically including: No. The distributed observer settings for each flywheel are as follows: ； in, Indicates the first A distributed instruction generator coefficient matrix Observations Indicates the first A distributed instruction generator coefficient matrix Observations Represents the coefficient matrix Observer gain, Indicates the first A distributed instruction generator coefficient matrix Observations Indicates the first A distributed instruction generator coefficient matrix Observations Represents the coefficient matrix Observer gain, Represents the internal state matrix of the i-th distributed instruction generator. Observations Indicates the first Internal state matrix of a distributed instruction generator Observations Represents the internal state matrix Observer gain, This represents the power reference value output by the i-th distributed instruction generator to the i-th flywheel. Distributed observers at time... To obtain the first Information from a distributed observer, then ,otherwise, express , , and Representing functions respectively , , The derivative at time t.

5. The multi-flywheel composite power control method under power output saturation constraint according to claim 1, characterized in that, The average consensus algorithm for each flywheel energy storage unit is defined, specifically including: ； in, and They represent the first The first and second consistency coefficients of each flywheel and Indicates the first The first and second consistency coefficients of each flywheel express initial value, express initial value, Indicates the first The consistency state of each flywheel Indicates the first The consistency state of each flywheel , and This represents the first consistency gain, the second consistency gain, and the third consistency gain. express initial value, Indicates the energy state of the i-th flywheel. The initial value, if the first Each flywheel at any moment To obtain the first Information about each flywheel, then ,otherwise, express , , and They represent the first The moment of inertia, damping coefficient, and charge-speed coefficient of each flywheel. , , Representing functions respectively , , The derivative at time t.

6. The multi-flywheel composite power control method under power output saturation constraint according to any one of claims 1-5, characterized in that, The flywheel energy storage system includes a communication network, a command generator, several energy storage units, and a power grid, with the energy storage unit being a flywheel.

Images