Hybrid energy storage assisted thermal power generating unit frequency modulation method

Abstract

The invention relates to a hybrid energy storage assisted thermal power generating unit frequency modulation method, the hybrid energy storage comprises a lithium ion battery and a super capacitor, and the method comprises the following steps: monitoring and obtaining a power grid frequency deviation, an AGC instruction and SOC of the lithium ion battery and the super capacitor in a hybrid energy storage system; adopting variable k virtual droop control to adjust output of a lithium ion battery and a super capacitor in hybrid energy storage under respective SOC conditions; carrying out primary distribution on the hybrid energy storage output by taking the output of the super capacitor as priority; and according to the operation state of the super capacitor in the primary distribution result, performing secondary adjustment on the output distribution of the hybrid energy storage by adopting fuzzy logic. Compared with the prior art, the method fully considers the frequency modulation characteristics of each type of energy storage, carries out the secondary distribution of the output demands of each type of energy storage in combination with the charge state and the actual output level, enables the system to rapidly track the AGC instruction, and avoids the hidden danger of a power gap.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage frequency regulation control, and in particular to a method for frequency regulation of a hybrid energy storage-assisted thermal power unit based on fuzzy control. Background Art

[0002] Renewable energy, mainly photovoltaic power generation and wind power generation, is developing rapidly, and the traditional power system is gradually transforming into a new power system with high penetration of renewable energy. However, due to the influence of weather and light intensity, the output of renewable energy power generation is volatile and uncertain, which will seriously affect the stability of the grid frequency. Traditional thermal power generating units are limited by the ramp rate, and their response to such frequency stability issues is limited to a certain extent. They cannot quickly restore the frequency to a stable range and track the system's planned output. Therefore, more frequency regulation resources are needed to support the safe operation of the grid.

[0003] In terms of frequency regulation resources, battery energy storage is mostly energy-type energy storage, which can support long-term charging and discharging, but its power is relatively small; supercapacitors are representatives of power-type energy storage, which can achieve high-power charging and discharging, but the continuous charging and discharging time is relatively short. Therefore, the improvement of frequency regulation performance by using a single type of energy storage to assist thermal power units in frequency regulation is limited. In terms of control strategy, the fixed-k virtual droop control method cannot adjust the output level according to the power state of the energy storage device, which may cause the energy storage device to overcharge, over-discharge, and maintain high or low SOC states for a long time, thereby affecting the life of the energy storage; the variable frequency modulation coefficient method considering the frequency deviation limit constraint needs to set and calculate the frequency deviation limit and the frequency modulation coefficient constrained by it according to the load disturbance. When the load is variable or the application scenario is switched, the original limit and frequency modulation coefficient may become invalid, and the control strategy has certain limitations; the frequency modulation method considering the first-order inertia constant threshold of the thermal-storage combined unit first needs to obtain the typical primary frequency modulation curve of the power grid, and determine the first-order inertia constant threshold of the thermal-storage combined unit according to its power factor, maximum output constraint and other parameters. This method is affected by the representativeness of the typical primary frequency modulation curve and the accuracy and effectiveness of the calculation of each parameter. In terms of power distribution of hybrid energy storage, the filtering decomposition method is generally adopted, with batteries and supercapacitors taking on the low-frequency and high-frequency parts respectively. The disadvantage is that the energy storage device has the risk of overcharging and over-discharging. At the same time, low-frequency fluctuations may cause the battery to frequently switch between charging and discharging, affecting its service life. Summary of the invention

[0004] The purpose of the present invention is to overcome the difficulties existing in the above-mentioned existing thermal-storage combined frequency regulation control, such as the singleness of supporting energy storage, the singleness of participating frequency regulation mode, the complexity and difficulty of mixed output control, and the strong response combined frequency regulation performance of multiple energy storage states and power coupling, and proposes a method for hybrid energy storage-assisted thermal power units to participate in frequency regulation based on fuzzy control.

[0005] The purpose of the present invention can be achieved by the following technical solutions:

[0006] A hybrid energy storage assisting frequency modulation method for a thermal power unit, wherein the hybrid energy storage comprises a lithium-ion battery and a supercapacitor, and the method steps include:

[0007] Monitor and obtain grid frequency deviation, AGC instructions and SOC of lithium-ion batteries and supercapacitors in hybrid energy storage systems;

[0008] The variable k virtual droop control is used to adjust the output of lithium-ion batteries and supercapacitors in hybrid energy storage under their respective SOC conditions;

[0009] The output of the supercapacitor is prioritized, and the hybrid energy storage output is allocated once. The hybrid energy storage instruction ΔP HESS The difference between the AGC command and the unit output:

[0010] According to the operating status of the supercapacitor in the primary distribution result, fuzzy logic is used to make a secondary adjustment to the output distribution of the hybrid energy storage.

[0011] As a preferred technical solution, the frequency deviation Δf is calculated by the formula:

[0012]

[0013] Among them, ΔP is the load change; P G is the output of thermal power unit; P M is the total output of the hybrid energy storage system; P L is the active power consumed on the load side; M is the grid inertia time constant; D is the load damping coefficient.

[0014] As a preferred technical solution, the SOC calculation formulas of the lithium-ion battery and the supercapacitor are respectively:

[0015]

[0016] In the formula, SOC B，0 is the initial value of the state of charge of the lithium-ion battery; P B (k) is the output power of the lithium-ion battery at time k; E B，rated The capacity of lithium-ion batteries;

[0017]

[0018] In the formula, SOC SC，0 is the initial value of the supercapacitor charge state; P SC (k) is the output power of the supercapacitor at time k; E SC，rated is the capacity of the supercapacitor.

[0019] As a preferred technical solution, the variable k virtual droop control is used to adjust the output of the lithium-ion battery and the supercapacitor in the hybrid energy storage under their respective SOC conditions. The relationship between the energy storage output and the system frequency deviation is as follows:

[0020] ΔP e =-K e ×Δf

[0021] In the formula, K e is the virtual droop coefficient, which is calculated as follows:

[0022]

[0023] In the formula, K d is the virtual droop discharge coefficient; K c is the virtual droop charging coefficient;

[0024] The calculation formula of variable k virtual droop coefficient is:

[0025]

[0026] In the formula, K max is the maximum value of the virtual droop coefficient; SOC max , SOC high , SOC low and SOC min are the set maximum, upper, lower and lowest values ​​of SOC respectively; m and n are the frequency modulation adaptation coefficients.

[0027] As a preferred technical solution, when the hybrid energy storage instruction ΔP HESS When the power is less than the rated power capacity of the supercapacitor energy storage system, the supercapacitor will provide power alone.

[0028] As a preferred technical solution, when the hybrid energy storage instruction ΔP HESS When the power exceeds the rated power capacity of the supercapacitor and is less than the sum of the rated power capacities of the hybrid energy storage, the supercapacitor and battery energy storage system jointly output power, with the supercapacitor outputting at the maximum level and the battery energy storage system supplementing the output.

[0029] As a preferred technical solution, when the hybrid energy storage instruction ΔP HESS When the rated power capacity exceeds the sum of the supercapacitor and battery energy storage, the hybrid energy storage outputs at the rated power.

[0030] As a preferred technical solution, the fuzzy logic is based on the state of charge SOC of the supercapacitor. SC The absolute value of the hybrid energy storage command value and the difference between the rated power of the supercapacitor ΔP HESS-SC As the input of the fuzzy controller, the actual output demand of the lithium-ion battery As the output of the fuzzy controller.

[0031] As a preferred technical solution, the fuzzy control rules include:

[0032] When the supercapacitor's state of charge SOC SC When the power is lower than the first and second allocation threshold, the output demand of lithium-ion batteries is relatively large, and secondary allocation is performed;

[0033] When the supercapacitor's state of charge SOC SC The absolute value of the hybrid energy storage instruction is between the first and second secondary distribution thresholds, and the difference between the absolute value of the hybrid energy storage instruction and the rated power of the supercapacitor is ΔP HESS-SC When it is negative or zero, the lithium-ion battery does not produce power;

[0034] When the supercapacitor's state of charge SOC SC The absolute value of the hybrid energy storage instruction is between the first and second secondary distribution thresholds, and the difference between the absolute value of the hybrid energy storage instruction and the rated power of the supercapacitor is ΔP HESS-SC When it is positive, the output demand of lithium-ion battery is small and no secondary distribution is performed;

[0035] When the supercapacitor's state of charge SOC SC Higher than the second secondary distribution threshold, and the absolute value of the hybrid energy storage instruction is different from the rated power of the supercapacitor ΔP HESS-SC When it is negative or zero, the lithium-ion battery does not produce power;

[0036] When the supercapacitor's state of charge SOC SC Higher than the second secondary distribution threshold, and the absolute value of the hybrid energy storage instruction is different from the rated power of the supercapacitor ΔP HESS-SC When it is positive, the output demand of lithium-ion battery is small and no secondary distribution is performed.

[0037] As a preferred technical solution, the secondary distribution rule for the output of the lithium-ion battery is:

[0038] When ΔP HESS Greater than zero:

[0039] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is low, P B =ΔP HESS -P SC ;

[0040] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is low and P SC ≤P SC，rated When P B =ΔPHESS -P SC ;

[0041] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is low and P SC =P SC，rated When P B =0;

[0042] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =ΔP HESS -P SC，rated ;

[0043] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =0;

[0044] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS- When the SOC of the hybrid energy storage is high, P B =ΔP HESS -P SC，rated ;

[0045] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is high, P B =0;

[0046] When ΔP HESS Less than or equal to zero:

[0047] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is low, P B =|ΔP HESS |-P SC，rated ;

[0048] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is low, P B =0;

[0049] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =|ΔPHESS |-P SC，rated ;

[0050] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =0;

[0051] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is high, P B =|ΔP HESS |-P SC ;

[0052] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero, the SOC of the hybrid energy storage is high and P SC <P SC，rated , P B =|ΔP HESS |-P SC ;

[0053] The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is high and P SC =P SC，rated , P B =0.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The present invention adopts a power distribution mode in which supercapacitors take priority and lithium-ion batteries supplement the hybrid energy storage system, and the SOC of the hybrid energy storage system is well maintained while the system processing requirements are met to the greatest extent. The hybrid energy storage coordinated output secondary distribution method based on fuzzy logic fully considers the frequency modulation characteristics of various types of energy storage, and performs secondary distribution of the output requirements of various types of energy storage in combination with their charge states and actual output levels, so that the system can quickly track AGC instructions and avoid the hidden danger of power gap. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a flow chart of the method for hybrid energy storage-assisted thermal power generation units to participate in frequency modulation based on fuzzy control of the present invention;

[0057] Figure 2 It is a schematic diagram of the thermal storage frequency modulation control model containing hybrid energy storage of the present invention;

[0058] Figure 3This is a schematic diagram of the lithium-ion battery frequency modulation model of the present invention;

[0059] Figure 4 It is a schematic diagram of the supercapacitor frequency modulation model of the present invention;

[0060] Figure 5 It is a schematic diagram of a frequency modulation response model of a hybrid energy storage system of the present invention;

[0061] Figure 6 It is a schematic diagram of an equivalent control model of the hybrid energy storage system participating in secondary frequency modulation of the present invention. DETAILED DESCRIPTION

[0062] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0063] Example 1

[0064] The present invention proposes a method for hybrid energy storage to assist thermal power units in participating in frequency modulation based on fuzzy control, wherein the hybrid energy storage includes a lithium-ion battery energy storage system and a super battery energy storage system, and adopts a power distribution mode in which super capacitors take priority and lithium-ion batteries are supplemented. Fuzzy control can be used to optimize the power distribution between lithium-ion batteries and super capacitors, so that the SOC of the hybrid energy storage system is well maintained while meeting the system processing requirements to the greatest extent. Figure 1 As shown, the present invention is implemented by the following steps:

[0065] Step 1: Establish a thermal storage frequency regulation control model including a hybrid energy storage system;

[0066] The thermal storage frequency regulation control model with hybrid energy storage is as follows: Figure 2 As shown, P G is the output of thermal power unit; P M is the total output of the hybrid energy storage system, that is, P M =P B +P SC , where P B is the output of the lithium-ion battery, P SC is the output of the supercapacitor; P L is the active power consumed on the load side; M is the grid inertia time constant; D is the load damping coefficient; ΔP is the load change; Δf is the frequency change.

[0067] The first-order inertia model is used to describe the external characteristics of lithium-ion batteries when participating in frequency modulation, such as Figure 3 As shown, K B is the frequency regulation coefficient of lithium-ion battery; T Bis the first-order response time constant of lithium-ion batteries; ΔP B is the output power of the lithium-ion battery; ΔP AGC It is the AGC (Automatic Generation Control) control signal of the power grid.

[0068] The first-order inertia model is used to describe the external characteristics of supercapacitors when participating in frequency modulation, such as Figure 4 As shown, K SC is the frequency adjustment coefficient of the supercapacitor; T SC is the first-order response time constant of the supercapacitor; ΔP SC is the output power of the supercapacitor; ΔP AGC It is the AGC control signal of the power grid.

[0069] Step 2: Monitor and obtain grid frequency deviation, AGC instructions, and SOC of supercapacitors and lithium-ion batteries in the hybrid energy storage system;

[0070] like Figure 2 As shown in the figure, the load fluctuation value ΔP can be calculated from the output of the thermal power unit and the hybrid energy storage, as well as the system load disturbance. After the first-order inertia link of the system, the system frequency deviation Δf can be calculated. The calculation formula is:

[0071]

[0072] Where ΔP is the load change; P G is the output of thermal power unit; P M is the total output of the hybrid energy storage system; P L is the active power consumed on the load side; M is the grid inertia time constant; D is the load damping coefficient; B is the frequency deviation coefficient of the regional system.

[0073] like Figure 3 and Figure 4 As shown, the SOC calculation formulas for lithium-ion batteries and supercapacitors are:

[0074]

[0075] In the formula, SOC B，0 is the initial value of the state of charge of the lithium-ion battery; P B (k) is the output power of the lithium-ion battery at time k; E B，rated The capacity of a lithium-ion battery.

[0076]

[0077] In the formula, SOC SC，0 is the initial value of the supercapacitor charge state; P SC(k) is the output power of the supercapacitor at time k; E SC，rated is the capacity of the supercapacitor.

[0078] The calculation formula for the state of charge (SOC) of hybrid energy storage is:

[0079]

[0080] Where SOC0 is the initial value of the state of charge; P M (k) is the output power of the hybrid energy storage system at time k; E M，rated is the capacity of the hybrid energy storage system; SOC is the current state of charge.

[0081] Step 3: Based on the grid frequency, AGC instructions and the SOC calculation results of the supercapacitor and lithium-ion battery in the hybrid energy storage system, establish the hybrid energy storage output rules based on fuzzy logic.

[0082] In order to avoid overcharging or overdischarging of the energy storage system during long-term frequency regulation, variable k virtual droop control is adopted to adjust the output of lithium-ion batteries and supercapacitors in the hybrid energy storage under their respective SOC conditions. The relationship between energy storage output and system frequency deviation is as follows:

[0083] ΔP e =-K e ×Δf

[0084] In the formula, K e is the virtual droop coefficient, which is calculated as:

[0085]

[0086] In the formula, K d is the virtual droop discharge coefficient; K c is the virtual droop charging coefficient.

[0087] The principle of variable k virtual droop control is that when the SOC of the energy storage system is high, its charging (discharging) virtual droop coefficient should be smaller (larger), and vice versa. Therefore, the calculation formula of the virtual droop coefficient is:

[0088]

[0089] In the formula, K max is the maximum value of the virtual droop coefficient; SOC max , SOC high , SOC low and SOC min are the set maximum, upper, lower and lowest values ​​of SOC respectively, which determine the inflection point of the virtual droop coefficient changing with SOC; m and n are the frequency modulation adaptation coefficients.

[0090] When the hybrid energy storage system assists the thermal power unit in participating in primary frequency regulation, its equivalent control model is as follows: Figure 5 As shown, where ΔP g is the output of thermal power unit, ΔP L is the load disturbance, and Δf is the system frequency deviation.

[0091] The hybrid energy storage output is distributed once, and the hybrid energy storage command is defined as the difference between the AGC command and the unit output:

[0092] ΔP HESS =P AGC -P g

[0093] ΔP HESS =P SC +P B

[0094] Case ① When ΔP HESS When the power is smaller, that is, smaller than the rated power capacity of the supercapacitor energy storage system, the supercapacitor will produce power alone, that is:

[0095] When 0≤|ΔP HESS |≤P SC，rated hour,

[0096] P SC =ΔP HESS

[0097] Case ② When ΔP HESS When the rated power capacity exceeds the supercapacitor and is less than the sum of the rated power capacity of the hybrid energy storage, the supercapacitor and battery energy storage system jointly output power, with the supercapacitor outputting at the maximum level and the battery energy storage system supplementing the output, that is:

[0098] When P SC，rated ≤|ΔP HESS |≤P SC，rated +P B，rated hour,

[0099]

[0100] Case ③ When ΔP HESS When the rated power capacity exceeds the sum of the supercapacitor and battery energy storage, the hybrid energy storage outputs at the rated power, that is:

[0101] When P SC，rated +P B，rated ≤|ΔP HESS |When

[0102]

[0103] Since the supercapacitor configuration capacity in hybrid energy storage is usually limited, the above output distribution method has certain limitations, that is, when the supercapacitor SOC is low (high), its discharge (charge) output will be limited due to the influence of variable k virtual droop control. If the hybrid energy storage instruction is situation ① or ② at this time, the supercapacitor will be restricted by the control strategy and cannot output power, and the system output will always have a certain difference until the supercapacitor SOC recovers.

[0104] In order to solve the above problems, in terms of the output distribution of hybrid energy storage, the present invention adopts a hybrid energy storage coordinated output distribution method based on fuzzy logic, and uses fuzzy logic to perform secondary adjustment on the output distribution of hybrid energy storage according to the operating state of the supercapacitor. The specific steps are as follows:

[0105] Fuzzification: The state of charge SOC of the supercapacitor SC The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC As the input of the fuzzy controller, the actual output demand of the lithium-ion battery As the output of the fuzzy controller.

[0106] Where ΔP HESS-SC =|ΔP HESS |-P SC

[0107] Defining SOC SC and ΔP HESS-SC The fuzzy variables are abbreviated as NB, Z, and PB, and the definition is The fuzzy variables are abbreviated as VS, M, VL, where NB represents the lower SOC and ΔP of the supercapacitor. HESS-SC is negative; Z indicates that the supercapacitor SOC is moderate and ΔP HESS-SC is zero; PB indicates that the supercapacitor SOC is high and ΔP HESS-SC Positive; VS means that the output demand of lithium-ion battery is large at this time, and secondary distribution is needed; M means that the output of lithium-ion battery is not needed; VL means that the output demand of lithium-ion battery is small, and secondary distribution is not needed.

[0108] Furthermore, the fuzzy control rules are:

[0109]

[0110] Among them, the secondary distribution rule of lithium-ion battery output is:

[0111] 1. ΔP HESS >0

[0112] ΔP HESS- >0&SOC is low P B =ΔP HESS -PSC

[0113] ΔP HESS-SC ≤0&SOC is low&P SC ≤P SC，rated P B =ΔP HESS -P SC

[0114] ΔP HESS-SC ≤0&SOC is low&P SC =P SC，rated P B =0

[0115] ΔP HESS-SC >0&SOC is mid P B =ΔP HESS -P SC，rated ΔP HESS-SC ≤0&SOC is mid P B =0

[0116] ΔP HESS-SC >0&SOC is high P B =ΔP HESS -P SC，rated ΔP HESS-SC ≤0&SOC is high P B =0

[0117] 2、ΔP HESS ≤0

[0118] ΔP HESS- >0&SOC is low P B =|ΔP HESS |-P SC，rated ΔP HESS-SC ≤0&SOC is low P B =0

[0119] ΔP HESS-SC >0&SOC is mid P B =|ΔP HESS |-P SC，rated

[0120] ΔP HESS- ≤0&SOC is mid P B =0

[0121] ΔP HESS-SC >0&SOC is high P B =|ΔPHESS |-P SC

[0122] ΔP HESS- ≤0&SOC is high&P SC <P SC，rated P B =|ΔP HESS |-P SC

[0123] ΔP HESS-SC ≤0&SOC is high&P SC =P SC，rated P B =0

[0124] When the hybrid energy storage system assists the thermal power unit in participating in the secondary frequency regulation, its equivalent control model is as follows: Figure 6 As shown. In the formula, P agc P is the AGC command received by the crew; M Contribute to the hybrid energy storage system; P g Output for the unit; P total It is the combined active power output by the hybrid energy storage system and the unit.

[0125] The hybrid energy storage-assisted thermal power unit frequency regulation method based on fuzzy control proposed in the present invention takes into account the characteristics of different types of energy storage, combines supercapacitors and lithium-ion batteries into hybrid energy storage to improve the frequency regulation performance of the thermal energy storage combined frequency regulation system; proposes a hybrid energy storage coordinated output secondary distribution method based on fuzzy logic, fully considers the frequency regulation characteristics of various types of energy storage, and performs secondary distribution of the output requirements of various types of energy storage in combination with their charge state and actual output level, so that the system can quickly track AGC instructions and avoid the hidden danger of power gap.

[0126] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A hybrid energy storage assisted thermal power unit frequency modulation method, characterized in that: The hybrid energy storage includes a lithium-ion battery and a supercapacitor, and the method steps include: Monitor and obtain grid frequency deviation, AGC instructions and SOC of lithium-ion batteries and supercapacitors in hybrid energy storage systems; The variable k virtual droop control is used to adjust the output of lithium-ion batteries and supercapacitors in hybrid energy storage under their respective SOC conditions; The output of the hybrid energy storage is allocated once, with the supercapacitor output as the priority. The hybrid energy storage instruction ΔPH ESS The difference between the AGC command and the unit output: According to the operating status of the supercapacitor in the primary distribution result, fuzzy logic is used to make a secondary adjustment to the output distribution of the hybrid energy storage.

2. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: The frequency deviation Δf is calculated as follows: Among them, ΔP is the load change; P G is the output of the thermal power unit; P M is the total output of the hybrid energy storage system; P L is the active power consumed on the load side; M is the grid inertia time constant; D is the load damping coefficient.

3. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: The SOC calculation formulas of the lithium-ion battery and supercapacitor are: In the formula, SOC B，0 is the initial value of the state of charge of the lithium-ion battery; P B (k) is the output power of the lithium-ion battery at time k; E B，rated The capacity of lithium-ion batteries; In the formula, SOC SC，0 is the initial value of the supercapacitor charge state; P SC (k) is the output power of the supercapacitor at time k; E SC，rated is the capacity of the supercapacitor.

4. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: The variable k virtual droop control is used to adjust the output of the lithium-ion battery and the supercapacitor in the hybrid energy storage under their respective SOC conditions. The relationship between the energy storage output and the system frequency deviation is as follows: ΔP e =-K e ×Δf In the formula, K e is the virtual droop coefficient, which is calculated as follows: In the formula, K d is the virtual droop discharge coefficient; K c is the virtual droop charging coefficient; The calculation formula of variable k virtual droop coefficient is: In the formula, K max is the maximum value of the virtual droop coefficient; SOC max , SOC high , SOC low and SOC min are the set maximum, upper, lower and lowest values ​​of SOC respectively; m and n are the frequency modulation adaptation coefficients.

5. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: When the hybrid energy storage instruction ΔPH ESS When the power is less than the rated power capacity of the supercapacitor energy storage system, the supercapacitor will provide power alone.

6. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: When the hybrid energy storage instruction ΔPH ESS When the power exceeds the rated power capacity of the supercapacitor and is less than the sum of the rated power capacities of the hybrid energy storage, the supercapacitor and battery energy storage system jointly output power, with the supercapacitor outputting at the maximum level and the battery energy storage system supplementing the output.

7. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: When the hybrid energy storage instruction ΔPH ESS When the rated power capacity exceeds the sum of the supercapacitor and battery energy storage, the hybrid energy storage outputs at the rated power.

8. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 1, characterized in that: The fuzzy logic is based on the state of charge SOC of the supercapacitor. SC The absolute value of the hybrid energy storage command value and the difference between the rated power of the supercapacitor ΔP HESS-SC As the input of the fuzzy controller, the actual output demand of the lithium-ion battery As the output of the fuzzy controller.

9. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 8, characterized in that: The rules of the fuzzy control include: When the supercapacitor's state of charge SOC SC When the power is lower than the first and second allocation threshold, the output demand of lithium-ion batteries is relatively large, and secondary allocation is performed; When the supercapacitor's state of charge SOC SC The absolute value of the hybrid energy storage instruction is between the first and second secondary distribution thresholds, and the difference between the absolute value of the hybrid energy storage instruction and the rated power of the supercapacitor is ΔP HESS-SC When it is negative or zero, the lithium-ion battery does not produce power; When the supercapacitor's state of charge SOC SC The absolute value of the hybrid energy storage instruction is between the first and second secondary distribution thresholds, and the difference between the absolute value of the hybrid energy storage instruction and the rated power of the supercapacitor is ΔPH. ESS -When it is positive, the output demand of lithium-ion battery is small and no secondary distribution is performed; When the supercapacitor's state of charge SOC SC Higher than the second secondary distribution threshold, and the absolute value of the hybrid energy storage instruction and the supercapacitor rated power difference ΔPH E When it is negative or zero, the lithium-ion battery does not produce power; When the supercapacitor's state of charge SOC SC Higher than the second secondary distribution threshold, and the absolute value of the hybrid energy storage instruction is different from the rated power of the supercapacitor ΔP HESS-SC When it is positive, the output demand of lithium-ion battery is small and no secondary distribution is performed.

10. A hybrid energy storage assisted thermal power unit frequency modulation method according to claim 8, characterized in that: The secondary distribution rule for the lithium-ion battery output is: When ΔPH ESS Greater than zero: The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔPH ESS - is greater than zero and the SOC of the hybrid energy storage is low, P B =ΔP HESS -P SC ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is low and P SC ≤P SC，rated When P B =ΔP HESS -P SC ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is low and P SC =P SC，rated When P B =0; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =ΔP HESS -P SC，rated ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When it is less than or equal to zero and the state of charge SOC of the hybrid energy storage is medium, PB = 0; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔPH E When the SOC of the hybrid energy storage is high, P B =ΔP HESS -P SC，rated ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When PB is less than or equal to zero and the state of charge SOC of the hybrid energy storage is high, PB = 0; When ΔPH ESS Less than or equal to zero: The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is low, P B =|ΔP HESS |-P SC，rated ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When it is less than or equal to zero and the state of charge SOC of the hybrid energy storage is low, PB = 0; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is medium, P B =|ΔP HESS |-P SC，rated ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When it is less than or equal to zero and the state of charge SOC of the hybrid energy storage is medium, PB = 0; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC When the SOC of the hybrid energy storage is high, P B =|ΔP HESS |-P SC ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is high and P SC <P SC，rated , P B =|ΔP HESS |-P SC ; The absolute value of the hybrid energy storage instruction and the difference between the rated power of the supercapacitor ΔP HESS-SC Less than or equal to zero and the SOC of the hybrid energy storage is high and P SC =P SC，rated , P B =0.

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