A coordinated control strategy for distributed grid-connected energy storage considering safe operation constraints

Abstract

A distributed network-forming energy storage coordinated control strategy considering safe operation constraints includes the following steps: S1: Obtain the state of charge of each energy storage and the frequency deviation of the grid-connected power point. Considering the safe operation constraints, construct a fuzzy controller based on the frequency deviation and the state of charge of the energy storage to obtain an adaptively variable active loop droop coefficient k p ; S2: Obtain the grid-connected point voltage and current of each network-forming energy storage, and calculate the active power P and reactive power Q actually output by the energy storage; S3: According to the active power P and reactive power Q calculated in step S2 and the active loop droop coefficient k obtained in step S1 p Calculate the grid-connected point phase and voltage; S4: According to the grid-connected point phase and voltage obtained in step 3, control the energy storage inverter through voltage-current double closed-loop control and PWM modulation. By introducing fuzzy control, the droop coefficient can adaptively change according to the frequency deviation, the state of charge of the energy storage, and the frequency modulation dead zone, realizing system frequency regulation and the balanced and reasonable distribution of the active power of the distributed network-forming energy storage.

Description

Technical Field

[0001] The present invention relates to the technical field of AC power grids, and particularly to a coordinated control strategy for distributed network-forming energy storage considering safe operation constraints. Background Art

[0002] The power generation capacity of new energy is limited by the changes in wind power and sunlight, resulting in limited regulation ability and difficulty in maintaining the balance between power supply and demand and the stability of system voltage and frequency. Therefore, the development of large-scale energy storage systems has become a key step in building a new power system.

[0003] In the new power system, since a large number of synchronous generators are replaced by new energy grid-connected units, showing a trend of low inertia and weak damping, an energy storage system based on network-forming control converters (i.e., network-forming energy storage) can independently construct voltage and frequency and provide inertia support, becoming an important guarantee for the stable and reliable operation of the new power system. However, relying on a single centralized network-forming energy storage control has relatively high safety risks, and long-distance transmission lines may not be able to meet the power quality requirements of end-user loads. Distributed network-forming energy storage has become a research hotspot for ensuring the safe and stable operation of the new power system under the background of a high proportion of new energy installed capacity due to its advantages in geographical layout, scale expansion, etc.

[0004] At present, the research on network-forming energy storage in the new power system mainly focuses on the dynamic response and active support capabilities of a single centralized energy storage during faults and transient processes, without considering the continuous support capabilities of energy storage and the coordinated control of distributed energy storage after this process. In addition, the coordinated control of distributed energy storage based on droop characteristics is mostly applied in DC microgrids. In AC systems, the influence mechanism of droop coefficients and line impedances on power distribution is not yet clear, and there is also a lack of verification of the overload capacity of the proposed control strategy. Therefore, there is an urgent need to develop a coordinated control strategy for distributed network-forming energy storage applied to AC power systems to achieve reasonable power distribution under safe operation. Summary of the Invention

[0005] The purpose of the present invention is to propose a coordinated control strategy for distributed network-forming energy storage considering safe operation constraints in view of the deficiencies of the prior art. By introducing fuzzy control, the droop coefficient adaptively changes according to frequency deviation, energy storage state of charge, and frequency modulation dead zone, realizing system frequency regulation and the balanced and reasonable distribution of active power of distributed network-forming energy storage.

[0006] To achieve the above object, the present invention adopts the following technical solution: A coordinated control strategy for distributed network-forming energy storage considering safe operation constraints, characterized by including:

[0007] S1: Obtain the state of charge of each energy storage and the frequency deviation of the grid-connected power point. Considering the safe operation constraints, construct a fuzzy controller based on the frequency deviation and the state of charge of the energy storage to obtain the adaptively variable active loop droop coefficient k p ;

[0008] S2: Obtain the grid-connected voltage and current of each grid-forming energy storage, and calculate the active power P and reactive power Q actually output by the energy storage;

[0009] S3: According to the active power P and reactive power Q calculated in step S2 and the active loop droop coefficient k obtained in step S1 p Calculate the grid-connected phase and voltage;

[0010] S4: According to the grid-connected phase and voltage obtained in step 3, control the energy storage inverter through voltage-current double closed-loop control and PWM modulation.

[0011] The safe operation constraints include:

[0012] State of charge safe operation limit: Maintain the state of charge in the range of 0.2 to 0.8. For values below 0.2, forced charging will be performed, and for values above 0.8, forced discharging will be performed;

[0013] Frequency modulation dead zone: The set frequency modulation dead zone is within (50 - 0.033Hz, 50 + 0.033Hz);

[0014] Overload capacity: The distributed grid-forming energy storage system can operate stably for a long time under 1.1 times the overload capacity, and the distributed grid-forming energy storage system can operate stably for more than 10s under 1.2 times the overload capacity.

[0015] Considering the safe operation constraints, construct a fuzzy controller based on the frequency deviation and the state of charge of the energy storage to obtain the adaptively variable active loop droop coefficient k p , and the specific steps are as follows:

[0016] Determine the input and output physical quantities

[0017] Based on the safe operation constraint conditions, determine that the input quantities of the fuzzy controller are the reference frequency value ω ref and the deviation Δω of the frequency value ω and the state of charge SOC of the energy storage unit i , and the output quantity is the adaptively variable active loop droop coefficient k p ;

[0018] Divide the numerical ranges of the input and output quantities into multiple fuzzy subsets, and each fuzzy subset corresponds to a fuzzy interval;

[0019] Determine the fuzzy controller structure

[0020] According to the determined input and output physical quantities, the fuzzy controller is determined as a two-variable one-dimensional fuzzy controller;

[0021] Determine the membership function of the fuzzy subset

[0022] Use the triangular membership function as the membership function of the input and output;

[0023] Set the universe of discourse of the frequency deviation Δω as: {-2.5, -1.5, -0.5, 0.5, 1.5, 2.5}; the state of charge SOC of the energy storage unit i The universe of discourse of is: {0, 20, 40, 60, 80, 100}; the active power loop droop coefficient k of the output p The universe of discourse of is: {1e-4, 3.75e-4, 7.5e-4, 1.125e-3, 1.5e-3};

[0024] Establish fuzzy control rules

[0025] Fuzzy inference

[0026] Adopt the Mamdani fuzzy inference method, and obtain the corresponding membership value of the active power loop droop coefficient k according to the fuzzy inference rules p :

[0027]

[0028] Among them, A 1 The membership value corresponding to Δω generation, B 1 The membership value corresponding to SOC i The membership value corresponding to the generated, C 1 The membership value corresponding to the active power loop droop coefficient k p The membership value of, T 2 Is the row vector transformation, and R is the fuzzy relationship;

[0029] Defuzzification:

[0030] Select the element with the highest membership degree in the fuzzy inference result subset as the output value;

[0031] If there are multiple output values in the output domain V, expressed as v j , corresponding to the maximum membership degree, then take the average value of all outputs with the maximum membership degree:

[0032]

[0033] Among them, N represents the total number of outputs with the same maximum membership degree, v j Represents the jth element with the maximum membership degree, μ v (v) All membership values, v 0 Represents the active power loop droop coefficient kp The required value.

[0034] Establish fuzzy control rules, specifically:

[0035] Under the discharge condition, according to the larger |Δω|, the SOC of the energy storage unit i is larger, the energy storage output is more, and the degree of decrease in the droop coefficient is greater; the smaller |Δω|, the state of charge SOC of the energy storage unit i is smaller, the degree of decrease in the droop coefficient is smaller, and the following fuzzy logic inference rules are established:

[0036] When the input deviation |Δω| is NB and the state of charge SOC of the energy storage unit i is {NB, NS, Z, PS, PB}, the corresponding output active power loop droop coefficient k p subsets are {PB, PB, PB, PB, NB};

[0037] When the input deviation |Δω| is NS and the state of charge SOC of the energy storage unit i is {NB, NS, Z, PS, PB}, the corresponding output active power loop droop coefficient k p subsets are {PB, PS, PS, Z, NB};

[0038] When the input deviation |Δω| is Z and the state of charge SOC of the energy storage unit i is {NB, NS, Z, PS, PB}, the corresponding output active power loop droop coefficient k p subsets are {PB, Z, Z, Z, NB};

[0039] When the input deviation |Δω| is PS and the state of charge SOC of the energy storage unit i is {NB, NS, Z, PS, PB}, the corresponding output active power loop droop coefficient k p subsets are {PB, Z, NS, NS, NB};

[0040] When the input deviation |Δω| is PB and the state of charge SOC of the energy storage unit i is {NB, NS, Z, PS, PB}, the corresponding output active power loop droop coefficient k p subsets are {PB, NB, NB, NB, NB};

[0041] Wherein: NB (Negative Big) is used to describe that the value of the input or output quantity is significantly negative and is a relatively large part among all negative values; NS (Negative Small) describes that the value of the input or output quantity is negative and is a relatively small negative value; Z (Zero) is used to describe that the value of the input or output quantity is close to zero; PS (Positive Small) describes that the value of the input or output quantity is positive and is a relatively small positive value; PB (Positive Big) is used to describe that the value of the input or output quantity is positive and is a relatively large part among all positive values.

[0042] Step S2 specifically includes:

[0043] Obtain the grid connection point voltage and current of each grid-forming energy storage;

[0044] Convert the grid connection point voltage and current from the three-phase stationary coordinate system (abc) to the two-phase rotating coordinate system (dq), and calculate the active power P and reactive power Q actually output by the energy storage through the following formula;

[0045]

[0046] Where, U od is the d-axis component of the grid connection point voltage, U oq is the q-axis component of the grid connection point voltage, I od is the d-axis component of the grid connection point current, I oq is the q-axis component of the grid connection point current.

[0047] Step S3 includes:

[0048] Design the power outer loop to adopt droop control, which includes two parts: active power control and reactive power control, and is specifically expressed as:

[0049]

[0050] Where, ω 0 is the rated frequency, ω is the grid connection point frequency; k p and k q are the droop coefficients of active power-frequency and reactive power-voltage control respectively, P is the actual output value of the active power of the converter, and Q is the actual output value of the reactive power of the converter;

[0051] Calculate the reference value E of the grid connection point voltage amplitude through the droop control formula ;

[0052] Calculate the reference value θ of the grid connection point phase through the formula θ = ∫ωdt.

[0053] Step S4 is specifically:

[0054] After receiving the reference values of the voltage amplitude and frequency phase of the grid connection point, the voltage outer loop outputs the current reference value of the current inner loop through PI control and decoupling;

[0055] After the inner current loop passes through PI control and decouples to output the voltage amplitude command, the output voltage amplitude command is combined with the phase information and, through PWM modulation, the inverter switching signals are generated.

[0056] The decoupling process of the outer voltage loop is as follows:

[0057]

[0058] Among them, C f represents the filter capacitor, U d and U q are the voltages of the grid connection point on the d-axis and q-axis respectively, i gd and i gq are the current feedback values of the grid side on the d-axis and q-axis respectively. and are the output values of the PI controller of the outer voltage loop, and the expression is:

[0059]

[0060] Among them, k vP is the proportional coefficient of the PI controller of the voltage loop, k vl is the integral coefficient of the PI controller, U dref and U qref are the voltage reference values output by the droop control strategy.

[0061] The decoupling process of the inner current loop is as follows:

[0062]

[0063] Among them, L represents the filter inductor, i d and i q are the currents of the grid connection point on the d-axis and q-axis respectively, U gd and U gq are the voltage feedback values of the grid side on the d-axis and q-axis respectively. and are the output values of the PI controller of the inner current loop, and the expression is:

[0064]

[0065] Among them, k iP is the proportional coefficient of the PI controller of the current loop, k il is the integral coefficient of the PI controller of the current loop, i dref and i qref are the current reference values.

[0066] Compared with the prior art, the advantages of the present invention are:

[0067] 1. The present invention adopts an energy storage system based on a network-forming converter. Since it can autonomously construct voltage and frequency and provide inertia support, it helps to stabilize the new power system. At the same time, it reveals the influence mechanism of the droop coefficient and line impedance on power distribution in the AC system, considering that the power distribution of the distributed network-forming energy storage is inversely proportional to both the droop coefficient and the line impedance. When the droop coefficient is much larger than the line impedance, it becomes the main factor affecting power distribution. At this time, reasonable power distribution of the energy storage can be achieved by controlling the droop coefficient.

[0068] 2. The present invention fully considers factors such as frequency deviation, energy storage state of charge, frequency modulation dead zone, and overload capacity, and proposes a coordinated control strategy for distributed network-forming energy storage considering safe operation constraints. By introducing fuzzy control, the droop coefficient adaptively changes according to frequency deviation, energy storage state of charge, and frequency modulation dead zone, realizing system frequency regulation and balanced and reasonable distribution of active power of distributed network-forming energy storage, and verifying the overload capacity of the proposed control strategy. Description of the Drawings

[0069] Figure 1 is the topology diagram of a single network-forming energy storage system in this embodiment;

[0070] Figure 2 is the droop control block diagram of the network-forming energy storage in this embodiment;

[0071] Figure 3 is the voltage and current double closed-loop control block diagram of the distributed network-forming energy storage system in this embodiment;

[0072] Figure 4 is the overall topology diagram of the distributed network-forming energy storage system in this embodiment;

[0073] Figure 5 is the schematic diagram of the design steps of the fuzzy controller in this embodiment;

[0074] Figure 6 is the specific control block diagram of the fuzzy controller in this embodiment;

[0075] Figure 7 is the flowchart of the control method of the present invention. Detailed Embodiment

[0076] The present invention will be further described below in conjunction with the drawings in the specification and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0077] The topology of a single network-forming energy storage system, as Figure 1 shown, the output of the energy storage power station is direct current, which needs to be converted into alternating current by an inverter, and then passes through a filtering link composed of a resistor R, an inductor L, and a capacitor C on the inverter side, and finally is g connected to the grid through the line impedance Z.

[0078] The overall structure of the distributed network-forming energy storage system is as follows Figure 4 As shown, the system consists of multiple key components that cooperate with each other to achieve efficient electrical energy storage and distribution. To implement the coordinated control strategy of the distributed network-forming energy storage, the present invention proposes a fuzzy control strategy based on frequency deviation and energy storage state of charge considering the safe operation constraints. The overall network-forming control strategy is divided into two parts: a power outer loop and an inner loop control. The outer loop adopts droop control, and the inner loop adopts a double closed-loop control of voltage and current. By sampling the state of charge of each energy storage and the frequency deviation of the grid-connected point, considering the safe operation constraints, a fuzzy controller based on frequency deviation and energy storage state of charge is constructed to obtain an adaptively variable active loop droop coefficient k p ; Sample the grid-connected point current and voltage in the system, calculate the actual active power and reactive power output by the inverter, and then according to Figure 2 the (a) network-forming energy storage active-frequency loop droop control block diagram in Figure 2 and the (b) reactive-voltage loop droop control block diagram in Figure 7 as shown, specifically:

[0079] S1: Obtain the state of charge of each energy storage and the frequency deviation of the grid-connected point. Considering the safe operation constraints, construct a fuzzy controller based on frequency deviation and energy storage state of charge to obtain an adaptively variable active loop droop coefficient k p ;

[0080] The safe operation constraints are as follows:

[0081] State of charge safe operation limit: The energy storage battery cannot be overcharged or over-discharged to protect the battery cells and avoid safety accidents. Generally, it is maintained in the range of 0.2 - 0.8. To achieve this, the droop coefficient is associated with the state of charge, and a droop coefficient that adapts to the state of charge is designed. The overall control objective is that in the case of increased system power surplus and rising frequency, the energy storage battery is in the charging state, and the charging power should be limited when the state of charge is high to prevent overcharging; in the case of insufficient system power and decreasing frequency, the energy storage battery is in the discharging state, and the discharging power should be limited when the state of charge is low to prevent over-discharging.

[0082] Frequency modulation dead zone: To improve stability and economy when the system frequency fluctuates slightly and prevent the system from frequently changing the control of the droop coefficient when the frequency is small, a frequency modulation dead zone needs to be set. The frequency modulation dead zone set in this invention patent is within (50 - 0.033Hz, 50 + 0.033Hz).

[0083] Overload capacity: In this invention patent, considering the system overload capacity, the system can operate stably for a long time under 1.1 times the overload capacity, and can operate stably for more than 10 s under 1.2 times the overload capacity.

[0084] Considering the safe operation constraints, a fuzzy controller based on frequency deviation and energy storage state of charge is constructed to obtain an actively droop coefficient k that can adaptively change p The specific steps are as follows:

[0085] The design process of the fuzzy controller mainly includes six steps, as Figure 5 shown. Since fuzzy control can imitate human reasoning and decision-making behaviorally, fuzzy control is combined with droop control to continuously change the droop coefficient. The control block diagram of this process is as Figure 6 shown. Since the active power output of the energy storage is inversely proportional to the droop coefficient, adjusting the droop coefficient means adjusting the active power output of the energy storage. The establishment of the fuzzy control steps includes:

[0086] Determine the input and output physical quantities: Determine the input quantities of the fuzzy controller as the reference frequency value ω ref and the deviation Δω of the frequency value ω and the state of charge SOC of the energy storage unit i , and the output quantity is the actively droop coefficient k p . Divide the numerical ranges of the input and output quantities into multiple fuzzy subsets, and each fuzzy subset corresponds to a fuzzy interval. The fuzzy subsets of the input and output in the fuzzy controller are all {NB, NS, Z, PS, PB}, that is, negative large, negative small, zero, positive small, positive large. In the discharge mode, the frequency regulation range of the energy storage unit is -2.5 Hz to 2.5 Hz, the range of the energy storage SOC i is 0 to 100%, and the droop coefficient regulation range is 1e-4 to 1.5e-3. Therefore, set the universe of discourse of the frequency deviation to: {-2.5, -1.5, -0.5, 0.5, 1.5, 2.5}; the universe of discourse of the energy storage SOC i is: {0, 20, 40, 60, 80, 100}; the universe of discourse of the output droop coefficient m p is: {1e-4, 3.75e-4, 7.5e-4, 1.125e-3, 1.5e-3}.

[0087] Determine the fuzzy controller structure: According to the input variables as the reference frequency value ω ref and the deviation Δω of the frequency value ω and the energy storage SOC i , and the output variable is the droop coefficient k of the active loop p , the designed fuzzy controller is determined as a two-variable one-dimensional fuzzy controller;

[0088] Determine the membership function of the fuzzy subset: Use the triangular membership function as the membership function for the input and output;

[0089] Establish fuzzy control rules: The basic idea of the distributed network - forming energy storage power distribution strategy is: in the case of discharging, according to the larger |Δω|, the higher the SOC of the energy storage unit i the more the energy storage output, and the greater the degree of decrease in the droop coefficient; the smaller |Δω|, the lower the SOC of the energy storage unit i the smaller the degree of decrease in the droop coefficient. According to the above principles, establish the fuzzy logic inference rules shown in the following table.

[0090]

[0091] In the table: NB (Negative Big) is used to describe that the value of the input or output quantity is significantly negative and is a relatively large part among all negative values; NS (Negative Small) describes that the value of the input or output quantity is negative and is a relatively small negative value; Z (Zero) is used to describe that the value of the input or output quantity is close to zero; PS (Positive Small) describes that the value of the input or output quantity is positive and is a relatively small positive value; PB (Positive Big) is used to describe that the value of the input or output quantity is positive and is a relatively large part among all positive values.

[0092] Adopt the Mamdani fuzzy inference method to adjust the droop coefficient to the target value in a timely manner. Based on the fuzzy control rules, obtain the fuzzy relation R. According to the given inputs A1 and B1, the corresponding output C1 is:

[0093]

[0094] where, A 1 corresponds to the membership value generated by Δω, B 1 corresponds to the state of charge SOC of the energy storage unit i generates the membership value, C 1 corresponds to the membership value of the active power loop droop coefficient k p and T 2 is the row - vector transformation, and R is the fuzzy relation.

[0095] Defuzzification: Defuzzification is achieved by using the maximum membership degree method, where the element with the highest membership degree in the fuzzy inference result set is selected as the output value; if there are multiple output values in the output domain V, denoted as v j ,, corresponding to the maximum membership degree, then take the average of all output values with the maximum membership degree:

[0096]

[0097] where, N represents the total number of outputs with the same maximum membership degree. v j, represents the j-th element with the maximum membership degree. μ v (v) All membership degree values. v 0 Represents the required value of the active loop droop coefficient k p of.

[0098] According to the design of the fuzzy controller, the fuzzy control inference result that satisfies the fuzzy control rules is obtained. In the discharging state, when |Δω| is the same, the droop coefficient decreases as the SOC increases; under the same SOC condition, the droop coefficient decreases as |Δω| increases.

[0099] S2: Obtain the grid-connected point voltage and current of each grid-forming energy storage, and calculate the active power P and reactive power Q actually output by the energy storage;

[0100] Specifically: Obtain the grid-connected point voltage and current of each grid-forming energy storage;

[0101] Convert the grid-connected point voltage and current from the three-phase stationary coordinate system (abc) to the two-phase rotating coordinate system (dq), and calculate the active power P and reactive power Q actually output by the energy storage through the following formula;

[0102]

[0103] Among them, U od is the d-axis component of the grid-connected point voltage, U oq is the q-axis component of the grid-connected point voltage, I od is the d-axis component of the grid-connected point current, I oq is the q-axis component of the grid-connected point current.

[0104] S3: Calculate the grid-connected point phase and voltage according to the active power P and reactive power Q calculated in step S2 and the active power loop droop coefficient k p obtained in step S1;

[0105] The steps specifically include:

[0106] Construct the power outer loop of the grid-forming control strategy. The outer loop adopts droop control, which includes two parts: active power control and reactive power control. The specific strategy can be expressed as:

[0107]

[0108] Among them, ω 0 is the rated frequency, k p and k q are the active-frequency and reactive-voltage control droop coefficients respectively, P is the actual output value of the active power of the converter, Q is the actual output value of the reactive power of the converter, and the droop control block diagram as shown in Figure 2 can be drawn according to the relationship.

[0109] By the droop control formula Calculate the reference value E of the grid connection point voltage amplitude;

[0110] Calculate the reference value θ of the grid connection point phase by the formula θ = ∫ωdt.

[0111] S4: According to the grid connection point phase and voltage obtained in step 3, control the energy storage inverter through voltage-current double closed-loop control and PWM modulation.

[0112] The specific steps are as follows:

[0113] After receiving the reference values of the grid connection point voltage amplitude, frequency and phase, the voltage outer loop outputs the current reference value of the current inner loop through PI control and decoupling; after the current inner loop outputs the voltage amplitude command through PI control and decoupling, combine the output voltage amplitude command with the phase information, and generate the inverter switching signal through PWM modulation. Combining the output voltage amplitude command with the phase information is the prior art, and its general steps are: 1) Calculate the modulation amplitude of the voltage amplitude command; 2) Calculate the phase difference; 3) Convert to the duty cycle; 4) Generate the PWM signal, which will not be introduced in detail in this implementation.

[0114] Construct the inner loop control of the grid-forming control strategy. The inner loop adopts voltage-current double closed-loop control. The voltage amplitude, phase and frequency output by the droop control link also need to pass through the inner loop control to generate the voltage vector command and give it to the PWM module. Because the double closed-loop control strategy has a fast response speed, the present invention selects the voltage-current double closed-loop control strategy. In the voltage-current double closed-loop control strategy, the voltage is used as the outer loop and the current is used as the inner loop. The specific control block diagram is as Figure 3 shown.

[0115] After receiving the reference values of the voltage amplitude, frequency and phase output by the droop control link, the voltage loop outputs the current reference value of the current inner loop through PI control and decoupling. After the current loop outputs the voltage amplitude command through PI control and decoupling, combine the output voltage amplitude command with the phase information, and generate the inverter switching signal through the PWM module. In this way, a complete internal control structure of the grid-forming energy storage power station is formed.

[0116] For the convenience of control and calculation, the decoupling process of the voltage components on the d-axis and q-axis is as follows:

[0117]

[0118] Among them, C f represents the filter capacitor, U d and U q are the voltages on the d-axis and q-axis respectively, i gd and i gq are the current feedback values on the d-axis and q-axis respectively, and is the output value of the voltage outer-loop PI controller, and the expression is:

[0119]

[0120] where k vP is the proportional coefficient of the PI controller of the voltage loop, and k vl is the integral coefficient of the PI controller, and U dref and U qref are the voltage reference values output by the droop control strategy.

[0121] There is also a coupling relationship between the d-axis and q-axis current components, and the decoupling process is as follows:

[0122]

[0123] where L represents the filter inductor, and i d and i q are the d-axis and q-axis voltages of the grid connection point respectively, and U gd and U gq are the voltage feedback values of the grid side d-axis and q-axis respectively, and are the output values of the current inner-loop PI controller, and the expression is:

[0124]

[0125] where k iP is the proportional coefficient of the current loop PI controller, and k il is the integral coefficient of the current loop PI controller, and i dref and i qref are the current reference values.

[0126] In a specific application embodiment, the above-mentioned distributed network-forming energy storage collaborative control strategy is used to build a simulation model on the Matlab / Simulink simulation platform according to Figure 4 This simulation model has 3 groups of parallel energy storage units. First, the relationship between the system power distribution and the line impedance under traditional control is verified, then the relationship between the system power distribution and the energy storage SOC after adding the fuzzy control link is verified, and finally, whether the overload capacity of the system meets the requirements is verified, thereby verifying the feasibility of the coordinated control strategy.

[0127] As mentioned above, it is only an exemplary example of the present invention. It can be understood that the content described in the examples of this specification is only a list of the implementation forms of the inventive concept and does not impose any formal restrictions on the invention. Therefore, the protection scope of the present invention should not be limited to the specific forms described in the examples, but should also include the technical means made by those skilled in the art according to the inventive concept.

Claims

1. A distributed grid-type energy storage coordination control strategy considering safety operation constraints, characterized in that: include: S1: Obtain the state of charge of each energy storage and the frequency deviation of the grid-connected power point, consider the safety operation constraints, build a fuzzy controller based on frequency deviation and energy storage state of charge, and obtain the active loop droop coefficient k that can be adaptively changed p ; S2: Obtain the voltage and current of the grid connection point of each grid-type energy storage, and calculate the active power P and reactive power Q actually output by the energy storage; S3: Active power P and reactive power Q calculated in step S2 and active power loop droop coefficient k obtained in step S1 p Calculate the phase and voltage of the grid connection point; S4: According to the grid connection point phase and voltage obtained in step 3, the energy storage inverter is controlled through voltage and current double closed-loop control and PWM modulation; Considering the safety operation constraints, a fuzzy controller based on frequency deviation and energy storage charge state is constructed to obtain the active loop droop coefficient k that can be adaptively changed. p , the specific steps are: Determine the input and output physical quantities: Based on the safe operation constraints, the input of the fuzzy controller is determined as the reference frequency value ω ref The deviation Δω from the frequency value ω and the state of charge SOC of the energy storage unit i The output is the adaptively variable active loop droop coefficient k p ; The numerical range of input and output quantities is divided into multiple fuzzy subsets, each fuzzy subset corresponds to a fuzzy interval; Determine the fuzzy controller structure: According to the determined input and output physical quantities, the fuzzy controller is determined as a two-variable one-dimensional fuzzy controller; Determine the fuzzy subset membership function: Using the triangular membership function as the membership function for input and output; The domain of the frequency deviation Δω is set to: {-2.5, -1.5, -0.5, 0.5, 1.5, 2.5}; the state of charge SOC of the energy storage unit i The domain is: {0, 20, 40, 60, 80, 100}; the output active loop droop coefficient k p The domain is: {1e-4,3.75e-4,7.5e-4,1.125e-3,1.5e-3}; Establish fuzzy control rules; Fuzzy reasoning: The Mamdani fuzzy reasoning method is used to obtain the corresponding active loop droop coefficient k according to the fuzzy reasoning rules. p The membership value of is: Among them, A1 corresponds to the membership value generated by Δω, and B1 corresponds to SOC i The membership value generated, C1 corresponds to the active loop droop coefficient k p The membership value of , T2 is the row vector transformation, and R is the fuzzy relationship; Defuzzification: Select the element with the highest membership degree in the fuzzy inference result subset as the output value; If there are multiple output values ​​in the output domain V, they are represented by v j , corresponding to the maximum membership, then the average of all outputs with the maximum membership is taken: Where N represents the total number of outputs with the same maximum membership, v j represents the jth element with the maximum membership, μ v (v) All membership values, v0 represents the active loop droop coefficient k p The required value of Establish fuzzy control rules, specifically: According to the discharge condition, the larger |Δω| is, the greater the SOC of the energy storage unit is. i The larger |Δω| is, the more energy storage output is, and the greater the reduction in droop coefficient is. The smaller |Δω| is, the higher the state of charge SOC of the energy storage unit is. i The smaller it is, the smaller the reduction of the droop coefficient is. The following fuzzy logic reasoning rules are established: When the input deviation |Δω| is NB, the state of charge SOC of the energy storage unit i When {NB, NS, Z, PS, PB}, the corresponding output active loop droop coefficient k p The subsets are {PB, PB, PB, PB, NB}; When the input deviation |Δω| is NS, the state of charge SOC of the energy storage unit i When {NB, NS, Z, PS, PB}, the corresponding output active loop droop coefficient k p The subsets are {PB, PS, PS, Z, NB}; When the input deviation |Δω| is Z, the state of charge SOC of the energy storage unit i When {NB, NS, Z, PS, PB}, the corresponding output active loop droop coefficient k p The subsets are {PB, Z, Z, Z, NB}; When the input deviation |Δω| is PS, the state of charge SOC of the energy storage unit i When {NB, NS, Z, PS, PB}, the corresponding output active loop droop coefficient k p The subsets are {PB, Z, NS, NS, NB}; When the input deviation |Δω| is PB, the state of charge SOC of the energy storage unit i When {NB, NS, Z, PS, PB}, the corresponding output active loop droop coefficient k p The subsets are {PB, NB, NB, NB, NB}; Among them: NB negative large is used to describe that the value of the input or output is significantly negative, and the size is a larger part among all negative values; NS negative small describes that the value of the input or output is negative, and it is a relatively small negative value; Z zero: used to describe that the value of the input or output is close to zero; PS positive small describes that the value of the input or output is positive, and it is a relatively small positive value; PB positive large: used to describe that the value of the input or output is positive and it is a larger part among all positive values.

2. The distributed grid-type energy storage coordinated control strategy considering safety operation constraints according to claim 1 is characterized in that: Safe operating constraints include: Safe operation limit of state of charge: Maintain the state of charge in the range of 0.2 to 0.

8. Forced charging will be performed if the state of charge is below 0.2, and forced discharge will be performed if the state of charge is above 0.

8. FM dead zone: The set FM dead zone is within (50-0.033Hz, 50+0.033Hz); Overload capacity: The distributed grid-type energy storage system can operate stably for a long time at an overload capacity of 1.1 times, and the distributed grid-type energy storage system can operate stably for more than 10 seconds at an overload capacity of 1.2 times.

3. The distributed grid-type energy storage coordinated control strategy considering safety operation constraints according to claim 1 or 2, characterized in that: Step S2 specifically includes: Obtain the grid connection point voltage and current of each grid-type energy storage; The voltage and current at the grid connection point are converted from the three-phase stationary coordinate system abc to the two-phase rotating coordinate system dq, and the active power P and reactive power Q actually output by the energy storage are calculated by the following formulas; Among them, U od is the d-axis component of the grid-connected point voltage, U oq is the q-axis component of the grid-connected point voltage, I od is the d-axis component of the grid-connected point current, I oq It is the q-axis component of the grid-connected point current.

4. The distributed grid-type energy storage coordinated control strategy considering safety operation constraints according to claim 3 is characterized in that: Step S3 includes: The power outer loop is designed to adopt droop control, which includes active power control and reactive power control. The specific expression is: Where ω0 is the rated frequency, ω is the grid connection point frequency; k p and k q are the droop coefficients of active-frequency and reactive-voltage control respectively, P is the actual output value of active power of the converter, and Q is the actual output value of reactive power of the converter; Through the droop control formula The grid connection point voltage amplitude reference value E is calculated; The grid connection point phase reference value θ is calculated by the formula θ=∫ωdt.

5. The coordinated control strategy for distributed grid-type energy storage considering safety operation constraints according to claim 1, 2 or 4, characterized in that: Step S4 is specifically as follows: After receiving the reference values ​​of the voltage amplitude and frequency phase at the grid connection point, the voltage outer loop outputs the current reference value of the current inner loop through PI control and decoupling; After the current inner loop is PI controlled and decoupled from the output voltage amplitude command, the output voltage amplitude command is combined with the phase information and PWM modulated to generate the inverter switching signal.

6. The distributed grid-type energy storage coordinated control strategy considering safety operation constraints according to claim 5 is characterized in that: The decoupling process of the voltage outer loop is: Among them, C f Indicates the filter capacitor, U d and U q are the voltages of the d-axis and q-axis at the grid connection point, i gd and i gq are the current feedback values ​​of the grid-side d-axis and q-axis respectively, and is the output value of the voltage outer loop PI controller, expressed as: Among them, k vP is the proportional coefficient of the PI controller of the voltage loop, k vl is the integral coefficient of the PI controller, U dref and U qref It is the voltage reference value output by the droop control strategy.

7. The distributed grid-type energy storage coordinated control strategy considering safety operation constraints according to claim 6 is characterized in that: The decoupling process of the current inner loop is: Where, L represents the filter inductance, i d and i q are the currents of the d-axis and q-axis of the grid connection point, U gd and U gq are the voltage feedback values ​​of the grid-side d-axis and q-axis respectively, and is the output value of the current inner loop PI controller, expressed as: Among them, k iP is the proportional coefficient of the current loop PI controller, k il is the integral coefficient of the current loop PI controller, i dref and i qref is the current reference value.

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