System and method for improving reactive power regulation capability of thermal power through network construction type energy storage

Abstract

The invention relates to the technical field of electric power system control, and provides a system and a method for improving thermal power reactive power regulation capability through network construction type energy storage, and the method comprises the following steps: 1, installing a network construction type energy storage system at a grid-connected point of a booster station of a thermal power plant, and collecting the data of power grid voltage, thermal power generating unit reactive power and energy storage charge state in real time; 2, constructing a multi-objective optimization function, and converting the multi-objective optimization function into a single-objective function for real-time solution by adopting a weighted summation method; 3, starting a cooperative control strategy of the network-building energy storage system and the thermal power generating unit based on a real-time solving result when the sudden change of the voltage of the power grid is detected; and step 4, executing the cooperative control strategy in real time, and dynamically updating and optimizing a solving result according to the state change of the system. According to the scheme, by optimizing the reactive power output characteristics of the energy storage system and the excitation parameters of the thermal power generating unit, the overall reactive power response speed of the system is increased, transient overvoltage is restrained, and safe and stable operation of a power grid is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system control, in particular to a system and method for improving the reactive power regulation capability of thermal power by grid-connected energy storage. BACKGROUND

[0002] With the large-scale grid connection of new energy, the problem of reactive power balance and voltage stability of power system is increasingly prominent. As the traditional main power source, the reactive power regulation capability of thermal power unit has an important influence on the voltage level of the power grid. However, due to the slow response speed of the excitation system, the thermal power unit is difficult to provide or absorb dynamic reactive power in time when the power grid occurs transient fault (such as short circuit, load mutation, etc.), which easily causes transient overvoltage or under-voltage, threatening the safe and stable operation of equipment and system.

[0003] At present, static reactive power compensation devices (such as SVC, STATCOM) or synchronous phase modulators are often used to enhance the reactive power regulation capability of the system, but such devices have limitations such as high investment cost and complex operation and maintenance. Grid-connected energy storage systems (such as battery energy storage, super capacitor, etc.) can effectively make up for the deficiency of thermal power units in dynamic reactive power regulation due to their fast response and flexible control characteristics. However, there is currently a lack of control strategies that can realize the collaborative optimization of energy storage systems and thermal power units, and the complementary potential of both in reactive power support has not been fully utilized, which restricts the improvement of overall regulation performance. SUMMARY

[0004] To solve the problems in the background art, the present application proposes a system and method for improving the reactive power regulation capability of thermal power by grid-connected energy storage, which optimizes the reactive power output characteristics of the energy storage system and the excitation parameters of the thermal power unit, improves the overall reactive power response speed of the system, suppresses transient overvoltage, and ensures the safe and stable operation of the power grid.

[0005] To achieve the above-mentioned purpose, the present application adopts the following scheme: The system and method for improving the reactive power regulation capability of thermal power by grid-connected energy storage comprises the following steps: Step 1: Install a grid-connected energy storage system at the grid connection point of the booster station of the thermal power plant, and real-time collect data of the grid voltage, the reactive power of the thermal power unit and the state of charge of the energy storage; Step 2: Construct a multi-objective optimization function, which takes the minimum transient overvoltage peak value as the core target, and is constructed in combination with the thermal power unit efficiency and energy storage life loss, and is expressed as,

[0006] The weighted summation method is used to convert it into a single objective function for real-time solution:

[0007] In the formula, This represents the peak value of the transient overvoltage. For the efficiency of thermal power units; This is due to energy storage lifespan loss; These are the weighting coefficients; Step 3: When a sudden change in grid voltage is detected, the coordinated control strategy between the grid-type energy storage system and the thermal power unit is activated based on the results obtained in real time in Step 2. Step 4: Execute the collaborative control strategy in real time and dynamically update and optimize the solution results according to changes in system state.

[0008] Optionally, in step 1, the reactive power output model of the grid-type energy storage system is expressed as:

[0009] The reactive power model of a thermal power unit is represented as follows:

[0010] In the formula, This refers to the reactive power of the energy storage system. This refers to the voltage at the grid connection point. The equivalent reactance of the converter; For control angle; This is the DC side voltage; This refers to the reactive power of thermal power units. For the excitation electromotive force; For the angle of attack; It is a synchronous reactance.

[0011] Optionally, the weighting coefficients are dynamically adjusted according to the system operating scenario: in high overvoltage risk scenarios, the weighting coefficients are set to... In scenarios where economic efficiency is prioritized, the following settings should be made: .

[0012] Optionally, the energy storage lifetime loss is modeled based on the charge / discharge depth and rate of the grid-type energy storage system, and its expression is:

[0013] In the formula, This is the energy storage charge / discharge rate coefficient; This refers to the depth of charge / discharge coefficient for energy storage. The current charge / discharge current for energy storage; This is the rated charge and discharge current for energy storage; This refers to the depth of charge and discharge for energy storage.

[0014] Optionally, by adjusting the energy storage charge / discharge rate coefficient and depth of charge / discharge coefficient of energy storage inhibit transient overvoltage peak value, wherein the transient overvoltage peak value is related to the energy storage charge-discharge rate coefficient positive correlation, the transient overvoltage peak value is related to the energy storage charge-discharge depth coefficient negative correlation.

[0015] Optionally, in step 3, the determination of the grid voltage mutation is determined according to the voltage amplitude deviation and the voltage change rate, and when the change amount of the grid voltage in the preset time window exceeds the threshold value, the grid voltage mutation is determined.

[0016] Optionally, in step 3, the cooperative control strategy includes: if the voltage rises more than 1.05 p.u., control the grid-forming energy storage system to absorb reactive power at the maximum rate, and optimize the PID parameters of the excitation system of the thermal power unit; if the voltage decreases to below 0.95 p.u., control the grid-forming energy storage system to release rated reactive power, and increase the excitation current of the thermal power unit.

[0017] The system for improving the reactive power regulation capability of thermal power by grid-forming energy storage includes an energy storage module, a data acquisition module, a multi-objective optimization decision module, and a cooperative control execution module. The energy storage module is arranged at the grid connection point of the booster station of the thermal power plant to provide fast reactive power support. The data acquisition module is used to acquire real-time grid voltage, thermal power unit reactive power, and energy storage SOC data. The multi-objective optimization decision module is electrically connected to the data acquisition module to establish and solve a multi-objective optimization function and generate optimized control parameters. The cooperative control execution module is electrically connected to the data acquisition module and the multi-objective optimization decision module. When the grid voltage is mutated, the cooperative control execution module generates a reactive power control instruction for the energy storage module and an excitation parameter adjustment instruction for the thermal power unit according to the optimized control parameters.

[0018] Optionally, the energy storage module includes a 100MWh lithium battery and a 50MW bidirectional converter.

[0019] The present application has the beneficial effects that: first, the control method provided by the present application forms a complete process of data acquisition, optimal decision, strategy execution and dynamic adjustment, optimizes the reactive power output characteristics of the energy storage system and the excitation parameters of the thermal power unit, improves the overall reactive power response speed of the system, suppresses the transient overvoltage, and ensures the safe and stable operation of the power grid, specifically: step 1 "installing the energy storage system + data acquisition" as the basis, provides data input for subsequent optimization and control; step 2 "multi-objective optimization" as the core decision, provides the "optimal adjustment direction" for cooperative control, which can specifically guide the reactive power adjustment amount of the grid-forming energy storage system and the adjustment range of the excitation parameters of the thermal power unit, step 3 "start cooperative control when voltage suddenly changes" as the trigger condition, to determine the execution time of the strategy, and step 4 "dynamically update the optimization result" as the closed-loop optimization, which can adapt to the system state changes and ensure the adjustment effect.

[0020] Moreover, the control system provided by the present application, which includes an energy storage module, a data acquisition module, a multi-objective optimization decision module and a cooperative control execution module, not only effectively implements the predetermined control method, but also provides an efficient and high economic value solution to the problem of insufficient reactive power regulation capacity of the thermal power unit. BRIEF DESCRIPTION OF DRAWINGS

[0021] Fig. 1 The flowchart of the control method of the present application; Fig. 2 The energy storage system access schematic diagram in the embodiment of the present application; Fig. 3 The voltage fluctuation comparison chart in the embodiment of the present application, wherein represents the voltage fluctuation curve without connecting the grid-forming energy storage system; represents the voltage fluctuation curve after connecting the grid-forming energy storage system. DETAILED DESCRIPTION

[0022] In order to make the present application clearer and more understandable, the following describes the present application in detail with reference to the accompanying drawings and embodiments, it should be understood that the embodiments given are only one of the implementation manners, and do not represent all the embodiments.

[0023] Embodiment one In combination Figs. 1-3 The present embodiment provides a method for improving the reactive power regulation capacity of thermal power by grid-forming energy storage, including the following steps: Step 1, install a grid-connected energy storage system at the booster station of the thermal power plant, and collect real-time data of grid voltage, thermal power unit reactive power and state of charge (SOC) of the energy storage system, to provide data input for subsequent optimization and control. This embodiment creatively links two models representing fast response (grid-connected energy storage system) and slow response (thermal power unit) through a unified optimization framework to solve specific transient voltage problems. The reactive power output model of the grid-connected energy storage system is represented as:

[0024] The reactive power model of the thermal power unit is represented as:

[0025] In the formula, is the reactive power of the energy storage system; is the grid point voltage; is the equivalent reactance of the converter; is the control angle; is the DC side voltage; is the reactive power of the thermal power unit; is the excitation electromotive force; is the power angle; is the synchronous reactance.

[0026] The reactive power output model of the grid-connected energy storage system is used to calculate the reactive power output of the grid-connected energy storage system under different voltages and control angles, and the reactive power model of the thermal power unit is used to quantify the reactive power regulation potential of the thermal power unit.

[0027] Step 2, construct a multi-objective optimization function and convert it into a single-objective function using the weighted summation method for real-time solution. The "multi-objective optimization" in this step is the core decision-making link of this embodiment, and its core value lies in providing a clear "optimal regulation direction" for the coordinated control of the grid-connected energy storage system and the thermal power unit. Specifically, it can guide the reactive power regulation amount of the grid-connected energy storage system (such as determining the reactive power value that the energy storage should absorb or release), the adjustment range of the excitation parameters of the thermal power unit, and provide decision-making basis for precise control of the coordinated operation of the two.

[0028] The multi-objective optimization function takes the minimum of the transient overvoltage peak value as the core target, and combines the thermal power unit efficiency and energy storage life loss to construct the multi-objective optimization function, which is represented as:

[0029] In the formula, is the transient overvoltage peak value; is the thermal power unit efficiency; is the energy storage life loss.

[0030] The maximum deviation of the grid bus voltage obtained by real-time measurement can be expressed as:

[0031] Defined as the ratio of reactive power output to total losses, it can be expressed as:

[0032] In the formula, This refers to active power loss.

[0033] Based on the charging and discharging depth and rate modeling of the aforementioned grid-type energy storage system, it can be expressed as:

[0034] In the formula, This is the energy storage charge / discharge rate coefficient; This refers to the depth of charge / discharge coefficient for energy storage. The current charge / discharge current for energy storage; This is the rated charge and discharge current for energy storage; This refers to the depth of charge and discharge for energy storage.

[0035] By adjusting the energy storage charge / discharge rate coefficient and depth of charge / discharge coefficient of energy storage It can suppress transient overvoltage peak values, wherein the transient overvoltage peak value is related to the energy storage charge / discharge rate coefficient. Positively correlated, the peak value of the transient overvoltage is related to the depth of charge / discharge coefficient of the energy storage. Negative correlation. To demonstrate the accuracy of this conclusion, as one example, see Table 1 below: Table 1. Peak values ​​of transient overvoltages after changing control parameters.

[0036] From the data in Table 1 above, we can obtain the energy storage charge / discharge rate coefficient. Energy storage charge / discharge depth coefficient With the initial value, the peak transient overvoltage is 1.33 pu. Based on this, the peak value of the transient overvoltage is... and The value is adjusted, in With the parameters remaining unchanged, Adjust up or down; in With the parameters remaining unchanged, Adjust upwards or downwards. When When the voltage is increased, the peak value of the transient overvoltage decreases. When the voltage is lowered, the peak value of the transient overvoltage decreases. That is, the peak value of the transient overvoltage is... Positive correlation Negative correlation, which proves the energy storage life loss The energy storage charge and discharge rate coefficient The energy storage charge and discharge depth coefficient The accuracy of the influence mode of the control parameter on the transient overvoltage. Therefore, when the voltage transient fluctuation occurs, the optimization of the energy storage charge and discharge rate coefficient The energy storage charge and discharge depth coefficient , can improve the reactive power regulation capability of the thermal power energy storage system, and can effectively reduce the transient overvoltage peak value, such as Fig. 3 The voltage fluctuation comparison chart of the thermal power transmission line, from which it can be seen that: Indicates the voltage fluctuation curve without accessing the network type energy storage system: when not accessing, the transient overvoltage peak value is high (up to 1.35 p.u.) after the grid voltage mutation, and the voltage fluctuation duration is long (>0.5s), which cannot effectively suppress the transient voltage anomaly. Indicates the voltage fluctuation curve after accessing the network type energy storage system: after accessing, with the help of the fast reactive power regulation capability of the network type energy storage system, the transient overvoltage peak value is significantly reduced (reduced to below 1.12 p.u.), and the voltage fluctuation duration is greatly shortened (shortened to within 0.2s), which directly reflects the suppression effect of the embodiment on the voltage fluctuation of the thermal power transmission line.

[0037] Further, the multi-objective is converted into a single-objective optimization problem by a weighted summation method, that is, formula (3) is converted into:

[0038] In the formula, is a weight coefficient, which can be dynamically adjusted according to actual needs. Among them, corresponds to the safety control target of "minimizing the transient overvoltage peak value", corresponds to the economic control target of "maximizing the thermal power unit operation efficiency", corresponds to the equipment protection target of "minimizing the life loss of the network type energy storage system". When the system is in the post-fault recovery period of the power grid, or in the high overvoltage risk scenario of frequent voltage fluctuation caused by large-scale grid connection of new energy, the safety control target of "minimizing the transient overvoltage peak value" has the highest priority, at this time the weight relationship is , to give priority to the controllability of the transient overvoltage, and then consider the thermal power efficiency and the energy storage life. When the system is in the steady-state operation of the power grid, the voltage fluctuation is gentle, and there is no obvious overvoltage risk, the economic target of "maximizing the thermal power unit operation efficiency" and the equipment protection target of "minimizing the life loss of the network type energy storage system" are set to a higher priority, at this time the weight relationship is , preferentially reduce the energy consumption of thermal power and the loss of energy storage, and improve the economy and durability of the overall collaborative control; for slight voltage fluctuations in this scenario, the grid can be regulated by conventional means without sacrificing economy or equipment life.

[0039] Therefore, by constructing a multi-objective optimization model with the minimum transient overvoltage peak as the core, combining parameter sensitivity analysis, hierarchical optimization strategy and robust design, deep collaborative control of thermal power and energy storage is achieved. This model significantly improves the economy and adaptability of the system while suppressing overvoltage, providing a technical guarantee for the stable operation of high-proportion new energy power grids.

[0040] Step 3: When a grid voltage mutation is detected, the collaborative control strategy of the grid-forming energy storage system and the thermal power unit is started based on the results obtained in Step 2.

[0041] In this step, the grid voltage mutation is the condition that triggers the collaborative control strategy, which determines the execution time of the strategy. The determination of the grid voltage mutation needs to consider both the voltage amplitude deviation and the voltage change rate. When the change in the grid voltage within a predetermined time window exceeds the threshold, it is determined that the grid voltage has mutated, specifically: First, the amplitude determination criterion takes the rated voltage of the thermal power plant step-up station grid connection point (usually 1 p.u.) as the reference. When the voltage amplitude deviates from the rated voltage by more than 5%, i.e. voltage > 1.05 p.u. (overvoltage mutation) or voltage < 0.95 p.u. (under-voltage mutation), it is preliminarily determined that the voltage has mutated.

[0042] Second, the change rate determination criterion is that when the voltage change rate (dV / dt) ≥ 2% / ms (i.e. the voltage change amplitude exceeds 2% of the rated voltage per millisecond), even if the voltage amplitude does not yet meet the ±5% deviation threshold, it is still determined that the voltage has mutated, in order to avoid subsequent amplitude loss of control caused by rapid voltage changes.

[0043] Third, the duration auxiliary determination criterion is that after the above amplitude or change rate meets the conditions, if the duration exceeds 2 grid cycles, it is confirmed that the voltage mutation is triggered, thereby excluding false positives caused by transient interference signals and ensuring the effectiveness of the determination result.

[0044] Based on the optimization decisions obtained in Step 2, the collaborative control is performed. Specifically, the collaborative control strategy includes: if the voltage rises above 1.05 p.u., control the grid-forming energy storage system to absorb reactive power at the maximum rate, and optimize the PID parameters of the thermal power unit excitation system; if the voltage drops below 0.95 p.u., control the grid-forming energy storage system to release rated reactive power, and increase the excitation current of the thermal power unit.

[0045] Step 4: Real-time execution of the coordinated control strategy and dynamic updating of the optimization solution according to system state changes. This step is a closed-loop optimization to adapt to system state changes and ensure the adjustment effect.

[0046] Therefore, the above four steps form a complete process of data collection, optimization decision-making, strategy execution, and dynamic adjustment, which optimizes the reactive power output characteristics of the energy storage system and the excitation parameters of the thermal power unit, improves the overall reactive power response speed of the system, suppresses transient overvoltage, and ensures the safe and stable operation of the power grid.

[0047] Embodiment Two The embodiment provides a system for improving the reactive power regulation capability of thermal power by network construction type energy storage, which is used to implement the control method in Embodiment One and comprises an energy storage module, a data collection module, a multi-objective optimization decision-making module, and a coordinated control execution module. The modules are connected through electrical connection or a data bus to form a closed-loop control system.

[0048] The energy storage module is arranged at the grid connection point of the booster station of the thermal power plant. The core function is to provide fast and flexible reactive power support to compensate for the slow response of the thermal power unit. In the embodiment, a lithium battery cluster with a rated capacity of 100 MWh is installed at the grid connection point of the booster station of the thermal power plant. A bidirectional converter with a rated power of 50 MW is directly connected to the grid connection point. The converter can quickly access / exit the power grid. The converter has independent reactive power adjustment capability and forms a "fast-slow" coordinated response mechanism with the thermal power unit. The converter cabinet is designed with an IP54 protection level, and is equipped with a temperature and humidity sensor (sampling frequency 1 Hz) and an automatic cooling fan. When the ambient temperature exceeds 40℃, the automatic cooling fan is started.

[0049] The data collection module is used to collect real-time grid voltage (including amplitude, change rate, and other key parameters), thermal power unit reactive power, and energy storage SOC data, to ensure that all control decisions are based on real-time and accurate operating data, and to provide a reliable data foundation for subsequent optimization and execution. The module specifically comprises a voltage sensor, a reactive power transmitter, an energy storage BMS, an edge gateway, auxiliary temperature and humidity sensors, and vibration sensors. Further, in the embodiment, the sampling frequency of the voltage and current signals is set to 500 Hz, the collection frequency of the reactive power, SOC, and other state quantities is 10 Hz, and the collection frequency of the environmental parameters (temperature, humidity, and vibration) is 1 Hz.

[0050] The multi-objective optimization decision module is electrically connected with the data acquisition module, constructs a multi-objective optimization function (covering three objectives of transient overvoltage control, thermal power unit efficiency and energy storage life loss) based on the collected real-time data, solves the function through a weighted summation method (combining scene dynamic adjustment weight), generates optimized control parameters considering safety, economy and equipment protection, and determines reactive power regulation amount of the energy storage module and adjustment value of the excitation parameter of the thermal power unit, thereby providing accurate decision basis for the collaborative control. In the embodiment, the module takes an industrial computer as a hardware platform and internally embeds an optimization algorithm program.

[0051] The collaborative control execution module is also integrated in the industrial controller and is electrically connected with the data acquisition module and the multi-objective optimization decision module. On one hand, the module receives the voltage state signal of the data acquisition module in real time and quickly identifies the mutation of the grid voltage. On the other hand, based on the optimized control parameters output by the multi-objective optimization decision module, the module synchronously generates two types of instructions: a reactive power control instruction for the energy storage module, which determines the value of the absorbed or released reactive power, and an excitation parameter adjustment instruction for the thermal power unit, which determines the key parameters of the excitation system of the thermal power unit, thereby realizing the collaborative response of the energy storage and the thermal power.

[0052] Therefore, the control system provided in the embodiment not only effectively realizes the predetermined control method, but also provides an efficient and high economic value solution for solving the problem of insufficient reactive power regulation capacity of the thermal power unit through the empowerment of the optimization algorithm.

[0053] The specific embodiments of the application are described in detail above with reference to the drawings, but the application is not limited to the described embodiments. For those skilled in the art, various changes, modifications, replacements and variations of the embodiments can be made without departing from the principles and spirits of the application, and still fall within the protection scope of the application.

Claims

1. A method for improving the reactive power regulation capability of thermal power by grid-forming energy storage, characterized in that: The method comprises the following steps: Step 1, installing a grid-connected energy storage system at the grid connection point of the booster station of the thermal power plant, and collecting data of grid voltage, reactive power of the thermal power unit and state of charge of the energy storage in real time; Step 2, constructing a multi-objective optimization function, which takes the minimum peak value of transient overvoltage as the core target, and is constructed in combination with the efficiency of the thermal power unit and the life loss of the energy storage, and is expressed as The weighted summation method is used to convert it into a single objective function for real-time solving: In the formula, is a transient overvoltage peak value; is a thermal power unit efficiency; is a storage energy life loss; is a weight coefficient; Step 3, when detecting a sudden change in grid voltage, starting the cooperative control strategy of the grid-connected energy storage system and the thermal power unit based on the result obtained by real-time solving in step 2; Step 4, real-time execution of the cooperative control strategy, and dynamic updating of the optimization solving result according to the change of system state.

2. The method of claim 1, wherein the method comprises: In step 1, the reactive power output model of the grid-connected energy storage system is expressed as: The reactive power model of the thermal power unit is expressed as: In the formula, is the reactive power of the energy storage system; is the grid-connected point voltage; is the equivalent reactance of the converter; is the control angle; is the DC side voltage; is the reactive power of the thermal power unit; is the excitation electromotive force; is the power angle; is the synchronous reactance.

3. The method for improving the reactive power regulation capability of thermal power by network-constructed energy storage according to claim 1, characterized in that: The weight coefficient is dynamically adjusted according to a system operation scene, and is set as in a high overvoltage risk scene .

4. The method for improving the reactive power regulation capability of thermal power by network-constructed energy storage according to claim 1, characterized in that: The life loss of the energy storage is modeled based on the depth and rate of charge and discharge of the grid-connected energy storage system, and its expression is: In the formula, is the energy storage charge and discharge rate coefficient; is the energy storage charge and discharge depth coefficient; is the current energy storage charge and discharge current; is the rated energy storage charge and discharge current; is the energy storage charge and discharge depth.

5. The method for improving the reactive power regulation capability of thermal power by network-constructed energy storage according to claim 4, characterized in that: by adjusting the energy storage charge and discharge rate coefficient and the energy storage charge and discharge depth coefficient transient overvoltage peaks are suppressed, wherein the transient overvoltage peaks are positively correlated with the energy storage charge and discharge rate coefficient and negatively correlated with the energy storage charge and discharge depth coefficient .

6. The method for improving the reactive power regulation capability of thermal power by network-constructed energy storage according to claim 1, characterized in that: In step 3, the determination of the sudden change in grid voltage is based on the voltage amplitude deviation and the voltage change rate, and when the change amount of grid voltage in the preset time window exceeds the threshold value, it is determined that the grid voltage has a sudden change.

7. The method for improving the reactive power regulation capability of thermal power by network-constructed energy storage according to claim 1, characterized in that: In step 3, the cooperative control strategy includes: if the voltage rises more than 1.05 p.u., controlling the grid-connected energy storage system to absorb reactive power at the maximum rate, and optimizing the PID parameters of the excitation system of the thermal power unit; if the voltage decreases to below 0.95 p.u., controlling the grid-connected energy storage system to release rated reactive power, and increasing the excitation current of the thermal power unit.

8. The system for improving the reactive power regulation capability of thermal power by grid-forming energy storage according to any one of claims 1-8, wherein: The system comprises an energy storage module, a data acquisition module, a multi-objective optimization decision module and a cooperative control execution module, the energy storage module is arranged at the grid connection point of the booster station of the thermal power plant, and is used to provide fast reactive power support; the data acquisition module is used to collect grid voltage, reactive power of the thermal power unit and energy storage SOC data in real time, the multi-objective optimization decision module is electrically connected with the data acquisition module, and is used to establish and solve a multi-objective optimization function, and generate optimized control parameters; the cooperative control execution module is electrically connected with the data acquisition module and the multi-objective optimization decision module, and when the grid voltage suddenly changes, generates a reactive power control instruction for the energy storage module and an excitation parameter adjustment instruction for the thermal power unit according to the optimized control parameters.

9. The system for improving the reactive power regulation capability of thermal power of network construction type energy storage according to claim 8, characterized in that: The energy storage module comprises 100MWh lithium batteries and 50MW bidirectional converters.

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