A coordinated control method of a flywheel energy storage array

Abstract

The application discloses a kind of coordinated control methods of flywheel energy storage array, it is related to flywheel control technical field, the method includes: obtaining data;Wherein, the data includes: power grid frequency deviation and the state data of each flywheel;Total power demand is calculated based on the power grid frequency deviation;Available power of each flywheel is calculated based on the flywheel state data;The distribution power of each flywheel is optimized by model predictive control;Controller sends distribution power to each flywheel, and flywheel adjusts power by converter.By the processing scheme of the present application, by introducing dynamic health assessment and model predictive control, power distribution can be optimized, and array performance can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of flywheel control, in particular to a coordinated control method of flywheel energy storage array. BACKGROUND

[0002] Flywheel energy storage system is a high-efficiency kinetic energy storage technology, which stores energy through rotating flywheels, and is suitable for power grid frequency modulation, renewable energy smoothing and other fields.

[0003] The existing flywheel energy storage array control method mostly adopts simple power distribution strategies such as average distribution or priority-based distribution, but ignores the individual differences of flywheel units, resulting in shortened overall life and reduced efficiency of the array.

[0004] In addition, the existing method lacks dynamic assessment of flywheel health status, and cannot adapt to real-time changing working conditions, thereby limiting the reliability and economy of the array.

[0005] Therefore, the above-mentioned existing coordinated control method of flywheel energy storage array has obvious inconvenience and defects, and needs to be further improved. How to create a new coordinated control method of flywheel energy storage array has become the current industry's goal for improvement. SUMMARY

[0006] Therefore, the present application provides a coordinated control method of flywheel energy storage array, which at least partially solves the problems existing in the prior art.

[0007] The present application provides a coordinated control method of flywheel energy storage array, which comprises the following steps:

[0008] Obtaining data; wherein the data includes grid frequency deviation and state data of each flywheel;

[0009] Calculating total power demand based on the grid frequency deviation;

[0010] Calculating the available power of each flywheel based on the flywheel state data;

[0011] Optimizing the distribution power of each flywheel through model predictive control;

[0012] The controller sends the distribution power to each flywheel, and the flywheel adjusts the power through the converter.

[0013] According to a specific implementation mode of the present application, the state data of each flywheel includes rotational speed and health index;

[0014] The health index is calculated by the following formula :

[0015] ;

[0016] in, For time At that time, the first Health indicators of each flywheel unit; It is a constant; For flywheel Cumulative running time; It is the attenuation constant.

[0017] According to a specific implementation of an embodiment of this disclosure, the calculation of total power demand based on grid frequency deviation includes:

[0018] Calculate time based on the following formula Total power demand of the power grid :

[0019] ;

[0020] in, This is the gain coefficient; This refers to the power grid frequency deviation.

[0021] According to a specific implementation of this disclosure, the step of calculating the available power of each flywheel based on the flywheel state data includes:

[0022] Calculate each flywheel based on the following formula. Available power :

[0023] ;

[0024] in, For flywheel Moment of inertia; This refers to the flywheel speed; The energy conversion efficiency coefficient; As a health indicator.

[0025] According to a specific implementation of this disclosure, the step of optimizing the power distribution of each flywheel through model predictive control includes:

[0026] Calculate the minimum total loss based on the following formula. :

[0027] ;

[0028] in, The total number of flywheels in the flywheel energy storage array. ; For flywheel index, ; for time a power value allocated to the flywheel ; an energy conversion efficiency coefficient of the flywheel ; a health weight coefficient; for time a health indicator of the flywheel .

[0029] According to a specific implementation manner of the embodiment of the present disclosure, the method further comprises:

[0030] constraining the power value allocated to the flywheel to satisfy ;

[0031] when in the discharging phase, ;

[0032] when in the charging phase, ;

[0033] wherein, total power demand of the power grid at time ; available power of the flywheel at time .

[0034] According to a specific implementation manner of the embodiment of the present disclosure, the method further comprises:

[0035] minimizing total loss considering future state changes within a prediction time domain prediction:

[0036] ;

[0037] wherein, time index; prediction time domain; total number of flywheels in the flywheel energy storage array; flywheel index; power planned to be allocated to the flywheel at future moment; an energy conversion efficiency coefficient of the flywheel ; energy loss due to insufficient efficiency when the power is allocated; a health weight coefficient; a health indicator of the flywheel at future moment.

[0038] ​According to a specific implementation of an embodiment of this disclosure, calculation is performed based on the following method. :

[0039] ;

[0040] in, For time Time Flywheel Health indicators; This is the health degradation coefficient; For the future Time, plan allocated to flywheel power, .

[0041] According to a specific implementation of an embodiment of this disclosure, the method further includes:

[0042] Check the feasibility of the optimization results; where the total available power is less than the total power demand of the grid, allocate the power of each flywheel proportionally based on the following formula: ;

[0043] When the flywheel's health index is less than 0.2, its power allocation is set to zero.

[0044] According to a specific implementation of an embodiment of this disclosure, the method further includes:

[0045] Determine whether the difference between the total available power and the total power demand of the grid is less than the upper limit of the total power allocation error; if it is greater than the upper limit of the total power allocation error, recalculate the flywheel allocation weight.

[0046] The coordinated control method for flywheel energy storage arrays in this disclosure, by introducing dynamic health assessment and model predictive control, can achieve proactive lifespan management and loss balancing, significantly improving economic efficiency; it also enhances system control accuracy and operational reliability, while balancing efficiency and lifespan to achieve global optimization. Furthermore, this invention, based on an optimization algorithm, is not dependent on specific hardware topologies or flywheel models. Only model parameters need to be updated to apply it to different types of flywheel units or hybrid energy storage systems, making it easy to scale to larger arrays. This provides core technical support for constructing large-scale, long-life, and highly reliable flywheel energy storage power stations. Attached Figure Description

[0047] Figure 1 A schematic flowchart of a coordinated control method for a flywheel energy storage array provided in an embodiment of this disclosure;

[0048] Figure 2 A flowchart illustrating a coordinated control method for a flywheel energy storage array provided in this embodiment of the present disclosure. Detailed Implementation

[0049] The embodiments of the present disclosure will be described in detail below with reference to the drawings.

[0050] The following detailed description of the application is provided for the purpose of understanding by those skilled in the art. It is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and are not all the embodiments. The present disclosure can also be implemented or applied by other different specific embodiments, and the details in the specification can be modified or changed based on different views and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present disclosure.

[0051] It should be noted that the aspects described herein can be embodied in a wide variety of forms and that any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, one of ordinary skill in the art should appreciate that one aspect described herein can be implemented independently of any other aspects and that two or more of these aspects can be combined in various ways. Further, an apparatus and / or method can be implemented using other structures and / or functionality in addition to or other than one or more of the aspects set forth herein.

[0052] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, one skilled in the art will understand that the described aspects can be practiced without these specific details.

[0053] The embodiment of the present application provides a coordinated control method of flywheel energy storage array, which dynamically evaluates the health state of each flywheel and optimizes power distribution based on model predictive control. Specifically, it includes the following steps: real-time monitoring of power grid demand and flywheel state; predicting short-term demand; calculating the available power of each flywheel based on health indicators; optimizing power distribution to minimize total loss; and executing control, thereby improving the life and efficiency of the array, suitable for high dynamic applications such as grid frequency modulation.

[0054] Figure 1 The schematic diagram of the coordinated control method of flywheel energy storage array provided by the embodiment of the present disclosure.

[0055] Figure 2 The schematic diagram of the coordinated control method of flywheel energy storage array provided by the embodiment of the present disclosure. Figure 1 The schematic diagram of the coordinated control method of flywheel energy storage array provided by the embodiment of the present disclosure.

[0056] As shown in Figure 1At step S110, data is acquired; wherein the data includes grid frequency deviation and state data of each flywheel.

[0057] More specifically, the grid frequency deviation and the state data of each flywheel are monitored by the controller; the state data of each flywheel mainly includes rotational speed and health index .

[0058] The health index is calculated by the following formula :

[0059]

[0060] wherein, is the time , the health index of the i-th flywheel unit, ranging from 0 to 1, the closer to 1, the higher the health degree; is a constant; is the cumulative running time of the flywheel ; and is a decay constant, representing the decay rate of the health index over time, when there is historical data of the same type of flywheel, the relationship between running time and performance degradation is established based on statistical analysis (such as Weibull analysis in reliability engineering) of the historical data, and an average value is back calculated.

[0061] More specifically, next goes to step S120.

[0062] At step S120, total power demand is calculated based on the grid frequency deviation.

[0063] More specifically, based on the real-time monitored grid frequency data, the total power demand is calculated and determined, the frequency deviation is quantified as an operable power value, and individual differences are fully considered when power is allocated, so as to avoid flywheel overload or premature failure.

[0064] In the embodiment of the present application, the total power demand of the grid at time is calculated based on the grid frequency deviation :

[0065]

[0066] wherein, is a gain coefficient, which is set based on the grid standard IEEE Std 1547-2018 (for example, based on typical frequency modulation demand, =1000kW / Hz). When​​ When, it indicates the discharge demand; when The time indicates the charging requirement.

[0067] Next, proceed to step S130.

[0068] In step S130, the available power of each flywheel is calculated based on the flywheel state data.

[0069] More specifically, the available power of a flywheel depends on its current speed and health status. Calculating the available power (the maximum power that can be safely provided) of each flywheel individually can prevent overuse of unhealthy flywheels and extend the array's lifespan.

[0070] In this embodiment of the invention, each flywheel is calculated based on the following formula. Available power :

[0071]

[0072] in, For flywheel The moment of inertia is obtained from the flywheel product manual; This refers to the flywheel speed; The energy conversion efficiency coefficient is obtained through experimental data, and is preferably 0.95 in this invention; As a health indicator.

[0073] Next, proceed to step S140.

[0074] In step S140, the power distribution of each flywheel is optimized by model predictive control.

[0075] More specifically, Model Predictive Control (MPC) is used to optimize power allocation. The optimization objective is to optimize power allocation in the prediction time domain. Minimize total loss to meet internal requirements Predicting the time domain It can be 5 seconds, or other preset time spans.

[0076] In this embodiment of the invention, the loss model includes flywheel loss and health degradation, and the total loss is minimized based on the following formula:

[0077]

[0078] in, The total number of flywheels in the flywheel energy storage array. ; For flywheel index, ; For time At that time, it is allocated to the flywheel. The power value, when A positive value indicates discharge (power output to the grid), when A negative value indicates charging (absorbing power from the grid); For flywheel The energy conversion efficiency coefficient; This is a health weighting coefficient; For time Time Flywheel Health indicators.

[0079] Constraints:

[0080]

[0081] (Discharge)

[0082] (Charge)

[0083] in, For time Total power demand of the power grid at that time; For time Time Flywheel Available power.

[0084] More specifically, this step employs a model predictive control (MPC) framework, combined with flywheel health status, to achieve intelligent power distribution.

[0085] 4.1 Construct an objective function and constraints that minimize total losses while satisfying power requirements and the capacity limitations of each flywheel.

[0086] Calculate the minimum total loss based on the following formula. :

[0087]

[0088] in, The total number of flywheels in the flywheel energy storage array. ; For flywheel index, ; For time At that time, it is allocated to the flywheel. The power value, when A positive value indicates discharge (power output to the grid), when A negative value indicates charging (absorbing power from the grid); For flywheel The energy conversion efficiency coefficient; For health weighting coefficients, ; t is time t is the flywheel health indicator, , t is the decay constant, obtained by accelerated life testing; t is the cumulative operating time; t is the real-time temperature; t is the speed fluctuation coefficient; t is the vibration amplitude.

[0089] Constraints:

[0090]

[0091] (discharge)

[0092] (charge)

[0093] where, t is time t is the total power demand of the grid; t is the available power of the flywheel

[0094] The following step is described in detail by example.

[0095] When the grid frequency deviation requires the flywheel array to release power, the flywheel array has 2 flywheels.

[0096] Flywheel 1:

[0097] Flywheel 2:

[0098] t is the prediction time domain

[0099] Substitute into the total loss minimization formula:

[0100]

[0101] The total loss minimization is:

[0102]

[0103] Constraints:

[0104]

[0105]

[0106] ​​

[0107] From the above, it can be seen that the "loss coefficient" of flywheel 1 (0.07) is less than that of flywheel 2 (0.08), so flywheel 1 should be given more power.

[0108] Under the constraint condition, flywheel 1 is full-load working:

[0109] According to the power balance constraint, flywheel 2 needs to allocate: = 200-150 = 50kW, which is also within its available power range.

[0110] Therefore, the optimal solution is: , .

[0111] 4.2 Extend single-time optimization to multi-time prediction optimization, considering future state changes in the prediction time domain .

[0112] The extended optimization is:

[0113]

[0114] wherein, is the time index; is the prediction time domain; is the total number of flywheels in the flywheel energy storage array; is the flywheel index; is the power planned to be allocated to flywheel at future time; is the energy conversion efficiency coefficient of flywheel ; is the energy loss due to insufficient efficiency when power is allocated; is the health weight coefficient; is the health index of flywheel at future time.

[0115] is calculated based on the following method: :

[0116]

[0117] wherein, is the health index of flywheel at time ; is the health decay coefficient; is the power planned to be allocated to flywheel at future time, .

[0118] 4.3 Solve the optimization problem using linear programming or quadratic programming algorithms.

[0119] Algorithm inputs: objective function coefficients, constraint matrix, boundary conditions.

[0120] Algorithm outputs: optimal power allocation values . Solution process is transparent: based on optimization theory (e.g. Kuhn-Tucker conditions), ensuring reproducibility.

[0121] 4.4 Check the feasibility of the optimization results:

[0122] When the total available power is insufficient ( ), then proportionally allocate ( ).

[0123] When the health status of a flywheel is extremely poor ( ), set its allocated power to zero to avoid failure.

[0124] 4.5 Verify the feasibility of the allocation results:

[0125] Verify that the allocation results meet all constraints:

[0126] Total power balance: , Power balance tolerance.

[0127] Individual power limits: .

[0128] Power balance tolerance is shown in Table 1.

[0129] Table 1 Values of power balance tolerance

[0130]

[0131] If the verification fails, go back to step 4.3 to re-solve until the verification succeeds.

[0132] More specifically, proceed to step S150.

[0133] At step S150, the controller sends the allocated power to each flywheel, which adjusts the power through the inverter.

[0134] More specifically, the controller sends the power set value to each flywheel, which adjusts the power through the inverter. At the same time, update the health index .

[0135] ​The coordinated control method of the flywheel energy storage array in the embodiments of the present disclosure can realize active life management and balanced loss through the introduction of dynamic health assessment and model predictive control, greatly improving the economy; improve the system control accuracy and operation reliability, while taking into account the efficiency and life, and realize the global optimization. Moreover, the present application takes the optimization algorithm as the core, does not depend on a specific hardware topology or flywheel model, and only needs to update the model parameters, so it can be applied to different types of flywheel units or hybrid energy storage systems, and is easy to extend to larger arrays, providing core technical support for building large, long-life and high-reliability flywheel energy storage power stations.

[0136] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present disclosure, which should be covered within the protection scope of the present disclosure.

Claims

1. A coordinated control method for a flywheel energy storage array, characterized in that, The method comprises the following steps: acquiring data; wherein the data comprises grid frequency deviation and state data of each flywheel; calculating total power demand based on the grid frequency deviation; calculating available power of each flywheel based on the state data of the flywheel; optimizing allocated power of each flywheel through model predictive control; the controller sends allocated power to each flywheel, and the flywheel adjusts power through a converter; the optimization of the allocated power of each flywheel through model predictive control comprises: The total loss is minimized based on the following equation : ； wherein, is the total number of flywheels in the flywheel energy storage array, ; is the flywheel index, ; is the time at which the power value assigned to the flywheel ; is the energy conversion efficiency coefficient of the flywheel ; is the health weight coefficient; is the health indicator of the flywheel at time ; The method further comprises: In the prediction horizon Minimizing total loss considering future state changes Prediction: ； wherein, is a time index; is a prediction horizon; is the total number of flywheels in the flywheel energy storage array; is a flywheel index; is the power allocated to the flywheel at a future time instant; is the energy conversion efficiency coefficient of the flywheel ; is the energy loss due to inefficiency in power allocation; is a health weight coefficient; is the health indicator of the flywheel at a future time instant; Based on the following method calculations : ； wherein is time ; and a health indicator of the flywheel; is a health degradation coefficient; is a future time instant, the power planned to be allocated to the flywheel, ; The method further comprises: checking the feasibility of the optimization result; wherein when the total available power is less than the total power demand of the power grid, the power of each flywheel is proportionally allocated based on the following formula: ; when the health index of the flywheel is less than 0.2, the allocated power of the flywheel is set to zero.

2. The coordinated control method of a flywheel energy storage array according to claim 1, wherein, The state data of each flywheel comprises rotational speed and health index; The health indicator is calculated by the following equation : ； in, For time At that time, the first Health indicators of each flywheel unit; It is a constant; For flywheel Cumulative running time; It is the attenuation constant.

3. The coordinated control method of a flywheel energy storage array of claim 1, wherein, calculating total power demand based on the grid frequency deviation comprises: Time is calculated based on the following equation total power demand of the power grid at the time : ； wherein, is a gain coefficient; is a grid frequency deviation.

4. The coordinated control method of a flywheel energy storage array of claim 1, wherein, calculating available power of each flywheel based on the state data of the flywheel comprises: The available power of each flywheel is calculated based on the following formula : P = 1 / 2 * I * ω2 : ； in, For flywheel Moment of inertia; This refers to the flywheel speed; The energy conversion efficiency coefficient; As a health indicator.

5. The coordinated control method of a flywheel energy storage array of claim 1, wherein, The method further comprises: power value assigned to the flywheel constraints are performed, satisfying ; When in the discharging phase, ; When in the charging phase, ; wherein, is the time total power demand of the power grid at time is the time available power of the flywheel at time is the time 6. The coordinated control method of a flywheel energy storage array of claim 1, wherein, The method further comprises: judging whether the difference between total available power and total power demand of the grid is less than an upper limit of total power allocation error; wherein when the difference is greater than the upper limit of total power allocation error, the flywheel allocation weight is recalculated.

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