CN108412696B - Wind power plant power and voltage regulation and control system containing energy storage and capacity configuration optimization method thereof - Google Patents

Abstract

The application discloses a wind power plant power and voltage regulation system with energy storage and a capacity configuration optimization method thereof, when a power grid load is in a valley, power grid dispatching power is larger than wind power plant output power, compressed air energy storage is in a compressed energy storage mode, and redundant wind power energy is converted into high-pressure air energy for storage; meanwhile, after high-pressure high-temperature air generated in the compression process passes through the heat exchanger, heat is stored in the heat storage chamber through heat conduction oil and is used for preheating expansion air; when the output power of the wind power plant is larger than the set fluctuation, the air storage tank releases high-pressure air to expand and generate power, and meanwhile, the high-pressure air absorbs the heat of the high-temperature heat conduction oil through the heat exchanger in the expansion process and converts the heat into electric energy so as to stabilize the fluctuation; when the output power of the wind power plant is larger than a set value, the reactive power is output by adjusting the power factor of the direct-driven wind power plant, the compressed air energy storage and the output power of the static reactive power generator, so that the reactive margin of the reactive power compensation equipment is increased while the voltage stability is ensured.

Description

Wind farm power and voltage control system including energy storage and its capacity allocation optimization method

Technical field

The invention relates to a wind farm power and voltage control system containing energy storage and a method for optimizing its capacity configuration.

Background technique

Energy is an important material basis for human survival and development. It is related to the national economy, people's livelihood and national security. It is also the primary field of scientific and technological innovation services and applications. Efficiency, cleanliness, and low carbon have become the mainstream direction of energy development in the world today. Nowadays, wind power generation is favored as a typical representative of green energy and has shown a trend of rapid development.

At present, the impact of large-scale wind power grid connection on grid dispatch and control is mainly reflected in issues such as active power regulation and reactive power and voltage control, such as the capacity configuration of backup equipment, reactive power and voltage support at grid connection points, and how to deal with low voltage ride-through, etc. . The main reason for this problem is that when the wind farm operates in maximum power tracking (MPPT) mode, the active power output changes with the change of wind speed. At this time, the volatility and randomness of wind speed changes are amplified and introduced into the active power output of wind power. The adjustment range of wind power reactive power output changes with the change of active power, and when the active power is within a certain range, the system needs to absorb reactive power from the grid, coupled with the influence of factors such as the low voltage ride-through protection action of the unit under fault conditions, The problem of fluctuations in the reactive power regulation range of wind farms is even more serious. To this end, it has become an important way to further develop wind power technology by configuring sufficient backup equipment in the wind farm to effectively smooth the fluctuations of wind power active power and at the same time expand the adjustment range of reactive power to improve the voltage support capacity of the grid connection point (PCC).

After searching the public literature of the existing technology, it was found that, for example, the patent number CN 105449715 A analyzes the current reactive power adjustment range of the wind farm through a mathematical model, and reports the modified reactive power adjustment capability to the control center to adjust the reactive power adjustment reference amount; the patent number CN 105449715 A CN105720611A proposes a reactive power control method that quickly adjusts reactive power through reactive power compensation equipment, while increasing the reactive power of wind turbines, replacing the reactive power output of the reactive power compensation equipment, and providing more margin for the reactive power compensation equipment; Literature [Research on Economic Operation Method of Reactive Power Compensation in Wind Farms Based on SVG] Based on the actual reactive power generation capabilities of wind turbines and SVG reactive power compensation devices, reactive power distribution is performed with the goal of reducing network losses and increasing power generation. Publication No. CN103337001A proposes a method of using energy storage to smooth wind power output fluctuations. Although the above method has effectively improved the grid-connected power and voltage regulation capabilities of the wind farm, it also has certain shortcomings:

1) SVG has the ability to quickly adjust reactive power output, but it still has problems such as high unit capacity cost, low service life, and immature technology. In order to ensure voltage stability at the grid-connected point of the wind farm, the wind farm should have a large capacity of reactive power compensation capability. Using SVG as reactive power compensation for wind farms requires a large installed capacity of SVG and high purchase and operating costs.

2) The use of electrical energy storage devices such as batteries and supercapacitors can effectively smooth the active power output of wind farms and at the same time play the role of peak shaving and valley filling. However, the cost of conventional energy storage devices is high, and the high-power power electronic converters used in energy storage access systems have problems such as high price and poor stability, making it difficult to apply energy storage on a large scale in large wind farms.

3) Current research on compressed air energy storage mainly focuses on the output control of active power, but does not involve the reactive power control function.

Contents of the invention

In order to solve the above problems, the present invention proposes a wind farm power and voltage control system containing energy storage and its capacity configuration optimization method. The present invention uses compressed air energy storage to have both active and reactive power adjustment capabilities and large energy storage capacity. With the advantages of low cost and long life, it can effectively adjust the output power of the wind farm and improve the reactive power margin of the system while ensuring the quality of grid-connected power.

In order to achieve the above objects, the present invention adopts the following technical solutions:

A wind farm power and voltage control system containing energy storage, including a motor, a multi-stage compressor, a high-pressure gas storage tank, a multi-stage turbine expander, a reduction gear, an electromagnetic clutch and a generator connected in sequence. The multi-stage A heat exchanger is provided between the compressors, the motor and the generator are both connected to the wind farm, a preheater is provided between the multi-stage turboexpanders, and a preheater is provided between the heat exchanger and the input of the preheater. Energy storage converter, a heat storage device and a gas boiler are arranged between the heat exchanger and the output of the preheater; a static var generator is configured in the output of the wind farm.

When the wind farm output active power is greater than the grid-side dispatching power, the compression energy storage mode is started. The excess electric energy drives the motor to drive the multi-stage compressor, compresses the air and stores it in a high-pressure gas storage tank. The heat exchangers at each stage are placed in various stages of compression. Between the machines, the waste heat of the compression process at each stage is recovered, the electromagnetic clutch is disconnected in the expansion part, and the compressed air energy storage output power is adjusted through the energy storage converter.

When the active power output of the wind farm is less than the grid-side dispatch and the compressed air energy storage has energy storage margin, the high-pressure air in the high-pressure gas storage tank passes through the preheater and expander in sequence and drives the generator to generate electricity.

The multistage turboexpander is coaxially connected, and the multistage compressor is coaxially connected.

Preferably, each compressor of the multi-stage compressor adopts adiabatic compression.

A wind farm power and voltage regulation method including energy storage. When the grid load is at a low point, the grid dispatching power is greater than the wind farm output power, and the compressed air energy storage is in compression energy storage mode, converting excess wind power energy into high-pressure air energy storage ;At the same time, after the high-pressure and high-temperature air generated during the compression process passes through the heat exchanger, the heat is stored in the heat storage chamber through the thermal oil to preheat the expansion air;

When the output power of the wind farm fluctuates more than the set value, the gas storage tank releases high-pressure air to expand and generate electricity. At the same time, during the expansion process, the high-pressure gas absorbs the heat of the high-temperature thermal oil through the heat exchanger and converts it into electrical energy, thereby outputting active power for use. Smooth fluctuations;

When the output power of the wind farm is greater than the set value, the power factor of the direct drive wind turbine, the reactive power output of the compressed air energy storage and the output of the static reactive power generator are adjusted to ensure voltage stability while increasing the reactive power compensation equipment. reactive power margin.

The wind farm capacity configuration and optimized operation method based on the above system includes the following steps:

(1) Based on the compressed air energy storage and wind power equipment models, establish a wind farm power control system model including compressed air energy storage;

(2) Obtain the installed capacity of the wind farm, wind speed characteristics of the location of the wind farm, grid-side active power, and voltage dispatch data, and determine the optimization variables, optimization goals, and constraints for the operation control of the compressed air energy storage power regulation system;

(3) Use the multi-objective optimization algorithm to solve the constructed optimization objective under the constructed constraints.

In step (1), the modeling process includes:

1) Characteristics of direct drive generator: The direct drive unit can generate a certain amount of reactive power through the full power converter, and can operate normally under the power factor of [-0.95, +0.95] for a long time;

2) The input power of the compressed air energy storage compression module at time t is:

In the formula, eta _ai is the isentropic efficiency of the compression process at each stage; eta _m is the mechanical efficiency of the motor; N _c is the number of compression stages; q _com (t) is the mass flow rate of air, in kg/s; R _g is the gas Constant; λ _c,i is the pressure ratio of each stage compressor, and P _out,i ,P _in,i are the inlet and outlet pressures of the compressor respectively; _Ti is the inlet temperature of the compressor at each stage, and γ is the adiabatic index of the air;

3) The compressed air energy storage expansion module outputs active power:

In the formula, eta _ti is the isentropic efficiency of the expansion process at each stage; eta _e is the efficiency of the power generation system; N _t is the expansion stage; q(t) is the mass flow rate of high-pressure air, in kg/s; R _g is the gas Constant; λ _t,i is the pressure ratio of the expander at each stage, Ti _is the inlet temperature of the expander at each stage, and γ is the adiabatic index of the air.

In the step (2), the optimization variables include:

The compressed air energy storage outputs active power, reactive power and absorbed active power at each dispatch moment; the power factor of the direct-drive wind turbine;

Optimization goals include:

SVG reactive power margin, energy storage SOC balance and smoothness of delivered active power;

Optimization constraints include:

Active power balance constraint, reactive power balance constraint, unit output power constraint, compressed air energy storage output active power constraint, compressed air energy storage output reactive power constraint, compressed air energy storage remaining capacity constraint and compressed air energy storage output power power Factor constraints.

In the step (3), the optimization model solving process includes the following steps:

3-1) Select the maximum evolutionary generation, population size and chaos control parameters;

3-2) According to the logistic mapping chaos model, the chaotic sequence initialization optimizes the variable population P _t ;

3-3) Perform non-dominated sorting on the population P _t . The non-dominated level is the fitness of each solution. Perform double-league selection, crossover and mutation to generate a descendant population Q _t with a scale of N;

3-4) Combine the parent population P _t and the offspring population Q _t to form the population R _t , and perform non-dominated sorting on R _t to determine all non-dominated solution fronts;

3-5) Calculate the crowding distance of the non-dominated solution frontier, sort F by the crowding distance, and select the N-|P _t | solutions with the best ranking;

3-6) By judging whether the number of individuals with non-inferiority level 1 in the population is equal to the number of the population, it is judged whether the evolved population has reached the optimal level. When equal, the first few percentages of the offspring population are selected for adaptive chaos refinement. search;

3-7) Repeat 3-3) to 3-5) until the maximum number of iterations of chaos optimization;

3-8) Output the optimal solution set.

A wind farm adopts the above control system or optimization method.

Compared with the prior art, the beneficial effects of the present invention are:

(1) The control system provided by the present invention can give full play to the advantages of large compressed air energy storage capacity, long life, low cost, flexible output of active and reactive power, realize active smoothing and reactive power compensation of the wind farm output power, and effectively improve While improving the power quality at the grid connection point, it also improves the reactive power margin of the system;

(2) At the same time, the present invention provides and establishes a mathematical model of the compressed air energy storage regulating wind farm power and voltage system; designs the active and reactive power planning of the wind farm power regulating system containing compressed air energy storage according to the optimized energy storage configuration parameters, so as to Achieve optimal operation of the system;

(3) The present invention designs a complete set of methods from structure to optimized operation control. This method is simple and easy to implement. Combined with the power quality analysis theory of power systems, it can be applied to the optimization design of different types of wind farm systems.

Description of drawings

The description and drawings that constitute a part of this application are used to provide a further understanding of this application. The illustrative embodiments and their descriptions of this application are used to explain this application and do not constitute an improper limitation of this application.

Figure 1 shows a schematic structural diagram of a wind farm power and voltage control system containing compressed air energy storage;

Figure 2 shows the optimal planning process of compressed air energy storage power based on chaotic multi-objective optimization;

Figure 3 shows the wind farm generated power and grid-connected power;

Figure 4 shows a schematic diagram of the effects after no reactive power compensation, traditional single reactive power compensation and the new method proposed in the present invention;

Figure 5 shows a schematic diagram of the reactive power margin after traditional single reactive power compensation and the new method proposed in the present invention.

Detailed ways:

The present invention will be further described below in conjunction with the accompanying drawings and examples.

It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meanings commonly understood by one of ordinary skill in the art to which this application belongs.

It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, the singular forms are also intended to include the plural forms unless the context clearly indicates otherwise. Furthermore, it will be understood that when the terms "comprises" and/or "includes" are used in this specification, they indicate There are features, steps, operations, means, components and/or combinations thereof.

In the present invention, terms such as "upper", "lower", "left", "right", "front", "back", "vertical", "horizontal", "side", "bottom", etc. The orientation or positional relationship is based on the orientation or positional relationship shown in the drawings. It is only a relative word determined to facilitate the description of the structural relationship of various components or elements of the present invention. It does not specifically refer to any component or element of the present invention and cannot be understood as a reference to the present invention. Limitations of Invention.

In the present invention, terms such as "fixed", "connected", "connected", etc. should be understood in a broad sense, indicating that it can be a fixed connection, an integral connection or a detachable connection; it can be a direct connection or an intermediate connection. Media are indirectly connected. For relevant scientific researchers or technicians in the field, the specific meanings of the above terms in the present invention can be determined according to specific circumstances, and should not be understood as limitations of the present invention.

As introduced in the background technology, there are existing technologies that simply use SVG for reactive power compensation in wind farms. The required SVG installed capacity is large, and the purchase and operating costs are high. The cost of energy storage devices is high, and it is used for energy storage access systems. High-power power electronic converters have the disadvantages of high price and poor stability. In order to solve the above technical problems, this application proposes a method that uses compressed air to store energy that has both active and reactive power adjustment capabilities, large energy storage capacity, and low cost. , has the advantage of long life, effectively adjusts the output power of the wind farm, and improves the reactive power margin of the system while ensuring the quality of grid-connected power.

In a typical implementation of the present application, as shown in Figure 1, a wind farm power control system structure containing compressed air energy storage is provided, including a motor (1), a multi-stage compressor (2), and a high-pressure storage system. Gas tank (3), multi-stage turboexpander (4), reduction gear (5), electromagnetic clutch (6), high-speed generator (7), energy storage converter (8), heat storage device (9) , gas boiler (10), expander interstage heat exchanger (preheater) (11), compressor interstage heat exchanger (12), heat storage medium cooling (13), SVG. The electric motor (1), multi-stage compressor (2), high-pressure gas storage tank (3), multi-stage turbine expander (4), reduction gear (5), electromagnetic clutch (6) and generator (7) are connected in sequence , a heat exchanger (12) is provided between the multi-stage compressors (2), the motor and generator are both connected to the wind farm, and a preheater is provided between the multi-stage turboexpanders (4) (12), an energy storage converter is provided between the input of the heat exchanger (11) and the preheater (12), and a heat storage converter is provided between the output of the heat exchanger (11) and the preheater (12). Device (9) and gas boiler (10); a static var generator (SVG) is configured in the wind farm output.

When the wind farm output active power is greater than the grid-side dispatch power, the compressed energy storage mode is activated. The excess electric energy drives the motor (1) to drive the multi-stage coaxial compressor (2), which compresses the air and stores it in a high-pressure gas storage tank (3). The compressor is designed for adiabatic compression. The heat exchangers (12) at each stage are placed between the compressors at each stage to recover the waste heat from the compression process at each stage and store it in the heat storage tank (9). The expansion part disconnects the electromagnetic clutch (6), and adjusts the compressed air energy storage output power through the energy storage converter (8) to realize the control of reactive power output. When the active power output of the wind farm is less than the grid-side dispatch and the compressed air energy storage has energy storage margin, the compressed air energy storage works in the expansion mode to output active power. The high-pressure air in the gas storage tank passes through the preheating device (11) and the expander (4) in sequence, and then drives the power generation system to generate electricity. The heat source required by the preheating device is supplied by the compressed heat storage medium after being heated by the gas boiler.

The system also includes a power factor adjustment and distribution device. The power factor adjustment and distribution device includes a wireless remote PCC voltage detection device, a reactive current detection module and a command current synthesis module. The wireless remote PCC voltage detection device detects the wind farm PCC grid connection point voltage and the current The active power output of the wind farm is collected by the reactive current detection module. The reactive current detection module collects the reactive current of the wind farm. The command current synthesis module calculates and allocates the reactive power output of the wind turbine, compressed air energy storage converter, and reactive compensator. .

Furthermore, the system also includes a four-quadrant operation multifunctional converter that can dynamically adjust active and reactive power output. By receiving instructions from the power factor adjustment and distribution device, the converter can absorb energy while storing or releasing energy. Or emit reactive power, and the reactive power ratio can be adjusted.

A method for capacity configuration and optimal operation control of energy storage connected to wind farms based on multi-objective active voltage, including the following steps:

Step 1: Based on the wind farm doubly-fed generator characteristics, wind speed distribution characteristics, static var generator (SVG) operating characteristics, grid-side active power and voltage regulation requirements, design a wind farm power system with compressed air energy storage Control system (shown in Figure 1);

Step 2: Based on the compressed air energy storage and wind power equipment model, establish a wind farm power control system model including compressed air energy storage;

Step 3: Determine the optimization variables, optimization objectives and constraints for the operation control of the compressed air energy storage power regulation system;

Step 4: Obtain the wind farm installed capacity, wind speed characteristics of the wind farm location, grid-side active power, and voltage dispatch data. Design an active and reactive voltage optimization operation method, and use the chaotic multi-objective optimization algorithm to solve the optimization model. In step 2, the modeling process mainly includes:

1) The input power of the compressed air energy storage compression module at time t is:

In the formula, eta _ai is the isentropic efficiency of the compression process at each stage; eta _m is the mechanical efficiency of the motor; N _c is the number of compression stages; q _com (t) is the mass flow rate of air, in kg/s; R _g is the gas Constant, 287.1J/(kg·K); λ _c,i is the pressure ratio of the compressor at each stage, and P _out,i and P _in,i are the inlet and outlet pressures of the compressor respectively; _Ti is the inlet temperature of the compressor at each stage, and γ is the adiabatic index of the air.

2) The compressed air energy storage expansion module outputs active power:

In the formula, eta _ti is the isentropic efficiency of the expansion process at each stage; eta _e is the efficiency of the power generation system; N _t is the expansion stage; q(t) is the mass flow rate of high-pressure air, in kg/s; R _g is the gas Constant, 287.1J/( ^k g·K); λ _t,i is the pressure ratio of the expander at each stage, Ti _is the inlet temperature of the expander at each stage, and γ is the adiabatic index of the air.

In step three, the optimization variables include:

1) Compressed air energy storage outputs active power P _CAES (t) and reactive power Q _CAES (t);

2) Power factor of direct drive wind turbine;

3) SVG output reactive power ratio

5. In step three, the optimization goals include:

1) Voltage deviation accumulation

2) Reactive power margin:

3) Energy storage balance: F ₃ =min|SOC _caes (T)-SOC _caes (1)|

Figure 2 is a multi-objective optimization solution algorithm based on chaos. Specific steps are as follows:

1): Select the maximum evolutionary generation, population size and chaos control parameters;

2): According to the logistic mapping chaos model, the chaotic sequence is initialized to optimize the variable population P _t ;

3): Perform non-dominated sorting on the population P _t . The non-dominated level is the fitness of each solution. Perform two-branch league selection, crossover and mutation to generate a descendant population Q _t with a scale of N.

4): Combine the parent population P _t and the offspring population Q _t into the population R _t , perform non-dominated sorting on R _t to determine all non-dominated solution fronts F.

5): Calculate the crowding distance of F, sort F by the crowding distance, and select the N-|P _t+1 | solutions with the best ranking;

6): By judging whether the number of individuals with non-inferiority level 1 in the population is equal to the number of the population, judge whether the evolved population has reached the optimal level. When equal, the top 10% of the offspring population are selected for adaptive chaos refinement search;

7): Repeat 3) to 5) until the maximum number of iterations of chaos optimization.

8): Output the optimal solution set.

Figures 3 to 5 are schematic diagrams of the effects of using compressed air energy storage and direct-drive wind turbines to regulate smooth active power and compensate for reactive power. Among them, the picture shows the comparison between wind power output power and grid-connected power. It can be clearly seen from Figure 3 that due to the intervention of compressed air energy storage, the smoothness of the grid-connected power is greatly improved compared with the generated power. Figure 4 and Figure 5 compare the effects and reactive power margin of reactive power compensation, traditional single reactive power compensation and the new method proposed in this patent. The simulation example fully proves that the use of compressed air energy storage to store abandoned wind power and adjust the power factor of direct-driven wind turbines can fully compensate for the system's reactive power loss, stabilize the voltage at the grid connection point, and ensure the system's reactive power margin.

The above descriptions are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included in the protection scope of this application.

Although the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, they do not limit the scope of the present invention. Those skilled in the art should understand that based on the technical solutions of the present invention, those skilled in the art do not need to perform creative work. Various modifications or variations that can be made are still within the protection scope of the present invention.

Claims (8)

1. A wind farm capacity configuration and optimization operation method of a wind farm power and voltage regulation system containing energy storage is characterized by comprising the following steps: the method comprises the following steps:

(1) According to the compressed air energy storage and wind power generation equipment model, establishing a wind power plant power regulation system model containing compressed air energy storage;

(2) Acquiring installed capacity of a wind power plant, wind speed characteristics of the wind power plant, network side pair active power and voltage scheduling data, and determining optimization variables, optimization targets and constraint conditions of operation control of a compressed air-containing energy storage power regulation system;

(3) Solving the constructed optimization targets under the constructed constraint conditions by utilizing a multi-target optimization algorithm;

the power and voltage regulation and control system of the wind farm with energy storage comprises a motor, a multi-stage compressor, a high-pressure air storage tank, a multi-stage turboexpander, a reduction gear, an electromagnetic clutch and a generator which are sequentially connected, wherein a heat exchanger is arranged between the multi-stage compressor, the motor and the generator are both connected with the wind farm, a preheater is arranged between the multi-stage turboexpander, an energy storage converter is arranged between the heat exchanger and the input of the preheater, and a heat storage device and a gas boiler are arranged between the heat exchanger and the output of the preheater; and a static reactive power generator is arranged in the output of the wind power plant.

2. The method as claimed in claim 1, wherein: when the output active power of the wind power plant is larger than the dispatching power of the grid side, the wind power plant power and voltage regulating and controlling system with energy storage starts a compressed energy storage mode, redundant electric energy drives a motor to drive a multi-stage compressor, air is compressed and stored in a high-voltage air storage tank, heat exchangers at all stages are arranged between the compressors at all stages, waste heat in compression processes at all stages is recovered, an electromagnetic clutch is disconnected by an expansion part, and the compressed air energy storage output power is regulated by an energy storage converter.

3. The method as claimed in claim 1, wherein: and when the wind power plant output active power is smaller than the grid-side dispatching and the compressed air energy storage has energy storage allowance, the high-pressure air in the high-pressure air storage tank sequentially passes through the preheater and the expander and then drives the generator to generate power.

4. The method as claimed in claim 1, wherein: the multistage turboexpander is coaxially connected, and the multistage compressor is coaxially connected.

5. The method as claimed in claim 1, wherein: in the step (1), the modeling process includes:

1) Direct drive generator characteristics: the direct-drive unit can generate a certain reactive power through a full-power converter and can normally operate for a long time under the power factors of [ -0.95, +0.95 ];

2) the input power of the compressed air energy storage compression module at the moment t is as follows:

wherein eta is _a.i Isentropic efficiency of each stage of compression process; η (eta) _m Mechanical efficiency for the motor; n (N) _c Is the number of compression stages; q _com (t) is the mass flow of air in kg/s; r is R _g Is a constant gas; lambda (lambda) _c,i Is the pressure ratio of each stage of compressor, andP _out,i ，P _in,i respectively the inlet air pressure and the outlet air pressure of the compressor; t (T) _i For each stage of compressor inlet temperature, γ is the adiabatic index of air;

3) The compressed air energy storage expansion module outputs active power:

wherein eta is _t.i Isentropic efficiency of each stage of expansion process; η (eta) _e Is the efficiency of the power generation system; n (N) _t Is the expansion series; q (t) is the mass flow rate of the high-pressure air, and the unit is kg/s; r is R _g Is a constant gas; lambda (lambda) _t,i T is the pressure ratio of each stage of expansion machine _i For each stage of expander inlet temperature, γ is the adiabatic index of air.

6. The method as claimed in claim 1, wherein: in the step (2), the optimization variables include:

the compressed air energy storage at each scheduling moment outputs active power, reactive power and absorbs the active power; direct-drive wind turbine generator system power factor;

the optimization targets include:

SVG reactive margin, energy storage SOC balance and smoothness of active power delivery;

the optimization constraint conditions include:

active power balance constraint, reactive power balance constraint, unit output power constraint, compressed air energy storage output active power constraint, compressed air energy storage output reactive power constraint, compressed air energy storage residual capacity constraint and compressed air energy storage output power factor constraint.

7. The method as claimed in claim 1, wherein: in the step (3), the optimization model solving process includes the steps of:

3-1) selecting the maximum evolution algebra, population scale and chaos control parameters;

3-2) initializing and optimizing variable population P according to a logistic mapping chaotic model and a chaotic sequence _t ；

3-3) population P _t Non-dominant ranking is performed, and the non-dominant level is the fitness of each solution; selecting, crossing and mutating double tournaments to generate offspring population Q _t The scale is N;

3-4) the parent population P _t And offspring population Q _t Are combined into a population R _t For R _t Determining all non-dominant solution fronts by non-dominant sorting;

3-5) calculating the crowding distance of the non-dominant solution front surface, sorting the crowding distance of F, and selecting N-P with the best sorting _t I solutions;

3-6) judging whether the number of individuals with the non-inferior grade of 1 in the population is equal to the number of the population, judging whether the evolved population is optimal, and selecting the former percentages of the child population to carry out self-adaptive chaotic refinement search when the numbers are equal to each other;

3-7) repeating the steps 3-3) to 3-5) until the maximum iteration number of the chaotic optimization is reached;

3-8) outputting the optimal solution set.

8. A wind farm, characterized by: use of a method according to any one of claims 1-7.