CN108412696B - Wind power plant power and voltage regulation and control system containing energy storage and capacity configuration optimization method thereof - Google Patents
Wind power plant power and voltage regulation and control system containing energy storage and capacity configuration optimization method thereof Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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- F03D9/10—Combinations of wind motors with apparatus storing energy
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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- F03D17/00—Monitoring or testing of wind motors, e.g. diagnostics
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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
Technical Field
The application relates to a wind power plant power and voltage regulation system containing energy storage and a capacity configuration optimization method thereof.
Background
Energy is an important material foundation for human survival and development, is critical to national life and national security, and is a primary field of technological innovation service and application. Efficient, clean, low carbon has become the dominant direction of energy development in the world today. Today, wind power generation is favored as a representative of green energy, and has been in a trend of high-speed development.
At present, the influence of large-scale wind power grid connection on power grid dispatching and control is mainly represented by problems such as active regulation and reactive voltage control, such as capacity configuration of standby equipment, reactive voltage support of grid connection points, how to cope with low voltage ride through, and the like. The main reason for this problem is that when the wind farm is operating in maximum power tracking (MPPT) mode, the active output varies with changes in wind speed. At this time, the fluctuation and randomness of the wind speed change are amplified and then are led into wind power active output. The regulation range of wind power reactive output is changed along with the change of the active power, and when the active power is in a certain range, the system needs to absorb the reactive power from the power grid, and the fluctuation problem of the regulation range of the wind power plant reactive power is more serious due to the influence of factors such as low voltage ride through protection action of the unit under the fault condition. Therefore, sufficient standby equipment is arranged in the wind power plant, the reactive power regulation range is enlarged while the active fluctuation of wind power is effectively smoothed, the voltage supporting capacity of a point of parallel connection (PCC) is improved, and the method becomes an important way for further development of wind power generation technology.
Through the searching and finding of the publications in the prior art, as in the publication number CN 105449715A, the current reactive power regulation range of the wind power plant is analyzed through a mathematical model, and the reactive power regulation capacity is reported to a regulation center to regulate reactive power regulation reference quantity; publication number CN105720611A proposes a reactive power control method, which can rapidly adjust reactive power through reactive power compensation equipment, increase reactive power of a wind turbine generator set, replace reactive power output of the reactive power compensation equipment and provide more margin for the reactive power compensation equipment; literature [ research on SVG-based wind farm reactive power compensation economic operation method ] performs reactive power distribution with the aim of reducing network loss and improving power generation according to actual reactive power generation capacity of a fan and an SVG reactive power compensation device. Publication number CN103337001a proposes a method for stabilizing wind power output fluctuations using energy storage. Although the method effectively improves grid-connected power and voltage regulation capability of the wind farm, certain defects exist at the same time:
1) SVG has the ability to rapidly adjust reactive power output, but it still has the problems of high cost per unit capacity, low service life, and immature technology. In order to ensure stable voltage of grid-connected points of the wind power plant, the wind power plant has reactive compensation capability with larger capacity. SVG is used as reactive compensation of a wind farm, the required SVG has large installed capacity, and the purchase cost and the operation cost are high.
2) The storage battery, the super capacitor and other electric energy storage devices are utilized, so that the output of active power of the wind power plant can be effectively smoothed, and the effects of peak clipping and valley filling are achieved. However, the conventional energy storage device has high cost, and the high-power electronic converter for the energy storage access system has the problems of high price and poor stability, so that the energy storage is difficult to be applied in a large-scale wind power plant.
3) At present, researches on compressed air energy storage mainly focus on output control of active power, but reactive power regulation and control functions are not involved.
Disclosure of Invention
In order to solve the problems, the application provides a wind power plant power and voltage regulation system with energy storage and a capacity configuration optimization method thereof.
In order to achieve the above purpose, the present application adopts the following technical scheme:
the utility model provides a wind farm power, voltage regulation and control system that contain energy storage, includes motor, multistage compressor, high-pressure gas storage jar, multistage turboexpander, reducing gear, electromagnetic clutch and the generator that connects gradually, be provided with the heat exchanger between the multistage compressor, motor and generator all connect the wind farm, be provided with the pre-heater between the multistage turboexpander, be provided with the energy storage converter between the input of heat exchanger and pre-heater, be provided with heat storage device and gas boiler between the output of heat exchanger and pre-heater; and a static reactive power generator is arranged in the output of the wind power plant.
When the active power output by the wind farm is greater than the dispatching power at the grid side, a compressed energy storage mode is started, the redundant electric energy drives the motor to drive the multi-stage compressor, air is compressed and stored in the high-pressure air storage tank, each stage of heat exchangers are arranged between each stage of compressors, waste heat in each stage of compression process is recovered, the electromagnetic clutch is disconnected by the expansion part, and the compressed air energy storage output power is regulated by the energy storage converter.
When the output active power of the wind power plant is smaller than that of the grid-side dispatching and the energy storage allowance of the compressed air is provided, 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.
The multistage turboexpander is coaxially connected, and the multistage compressor is coaxially connected.
Preferably, each compressor of the multistage compressor is adiabatic compression.
When the power grid load is in a valley, the power grid dispatching power is larger than the output power of the wind power plant, the compressed air energy storage is in a compressed energy storage mode, and redundant wind power 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 that active power is output for stabilizing 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.
The wind farm capacity configuration and optimization operation method based on the system 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) And solving the constructed optimization targets under the constructed constraint conditions by utilizing a multi-target optimization algorithm.
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.
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.
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 ordering is performed, with the non-dominant level being 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.
A wind farm adopts the regulation and control system or the optimization method.
Compared with the prior art, the application has the beneficial effects that:
(1) The regulation and control system provided by the application can fully exert the advantages of large energy storage capacity of compressed air, long service life, low cost, flexible output of active power and reactive power and the like, realize active smoothing and reactive power compensation of the output power of the wind power plant, effectively improve the power quality of the grid-connected point and improve the reactive margin of the system;
(2) Meanwhile, the application provides and establishes a mathematical model of a compressed air energy storage and regulation wind power plant power voltage system; active and reactive planning of a wind power plant power regulation system containing compressed air energy storage is designed according to the optimized energy storage configuration parameters so as to realize optimal operation of the system;
(3) The application designs a whole set of method from structure to optimal operation control, which is simple and easy, combines the power quality analysis theory of the power system and is applicable to the optimal design of different types of wind power plant systems.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application.
FIG. 1 is a schematic diagram of a power and voltage regulation system of a wind farm with compressed air energy storage;
FIG. 2 shows an optimal planning flow of compressed air energy storage power based on chaotic multi-objective optimization;
FIG. 3 illustrates wind farm generated power versus grid connected power;
FIG. 4 is a schematic diagram showing the effects of the compensation without reactive compensation, with conventional single reactive compensation, and with the novel method of the present application;
fig. 5 is a schematic diagram of reactive margin after conventional single reactive compensation and the new method of the present application.
The specific embodiment is as follows:
the application will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
In the present application, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", etc. refer to an orientation or a positional relationship based on that shown in the drawings, and are merely relational terms, which are used for convenience in describing structural relationships of various components or elements of the present application, and do not denote any one of the components or elements of the present application, and are not to be construed as limiting the present application.
In the present application, terms such as "fixedly attached," "connected," "coupled," and the like are to be construed broadly and refer to either a fixed connection or an integral or removable connection; can be directly connected or indirectly connected through an intermediate medium. The specific meaning of the terms in the present application can be determined according to circumstances by a person skilled in the relevant art or the art, and is not to be construed as limiting the present application.
As introduced by the background technology, the prior art simply uses SVG as reactive power compensation of the wind power plant, the required SVG has large installed capacity, and the purchase cost and the operation cost are high; the application provides an adjusting method for improving reactive margin of a system while ensuring grid-connected power quality by utilizing the advantages of compressed air energy storage, active and reactive power adjusting capability, large energy storage capacity, low cost and long service life.
In an exemplary embodiment of the application, as shown in fig. 1, a wind farm power regulation system structure containing compressed air energy storage is provided, and the wind farm power regulation system structure comprises an electric motor (1), a multi-stage compressor (2), a high-pressure air storage tank (3), a multi-stage turbine expander (4), a reduction gear (5), an electromagnetic clutch (6), a high-speed generator (7), an energy storage converter (8), a heat storage device (9), a gas boiler (10), an expander interstage heat exchanger (preheater) (11), a compressor interstage heat exchanger (12), a heat storage medium cooling (13) and SVG. The energy storage device comprises a motor (1), a multistage compressor (2), a high-pressure air storage tank (3), a multistage turbine expander (4), a reduction gear (5), an electromagnetic clutch (6) and a generator (7) which are sequentially connected, wherein a heat exchanger (12) is arranged between the multistage compressor (2), the motor and the generator are both connected with a wind power plant, a preheater (12) is arranged between the multistage turbine expander (4), an energy storage converter is arranged between the heat exchanger (11) and the input of the preheater (12), and a heat storage device (9) and a gas boiler (10) are arranged between the heat exchanger (11) and the output of the preheater (12); a Static Var Generator (SVG) is configured in the wind farm output.
And when the active power output by the wind power plant is larger than the dispatching power of the network side, starting a compressed energy storage mode. The redundant electric energy drives the motor (1) to drive the multistage coaxial compressor (2), and air is compressed and stored in the high-pressure air storage tank (3). The compressor is designed for adiabatic compression. The heat exchangers (12) are arranged between the compressors at all levels, recover the waste heat in the compression process at all levels and store the waste heat in the heat storage tank (9). The expansion part cuts off the electromagnetic clutch (6), and the energy storage output power of the compressed air is regulated through the energy storage converter (8), so that reactive power output is regulated and controlled. When the output active power of the wind power plant is smaller than that of the grid-side dispatching and the compressed air energy storage has energy storage allowance, the compressed air energy storage works in an expansion mode to output active power. The high-pressure air in the air storage tank sequentially passes through the preheating device (11) and the expansion machine (4) and then drives the power generation system to generate power. The heat source required by the preheating device is supplied by compressed heat storage medium after being heated by a gas boiler.
The system also comprises a power factor adjusting and distributing device, wherein the power factor adjusting and distributing device comprises a wireless remote PCC voltage detecting device, a reactive current detecting module and an instruction current synthesizing module, the wireless remote PCC voltage detecting device detects the PCC grid-connected point voltage of the wind power plant and the current wind power plant active output, the reactive current detecting module collects the reactive current of the wind power plant, and the instruction current synthesizing module calculates and distributes the reactive output of the wind power unit, the compressed air energy storage converter and the reactive compensator.
Furthermore, the system also comprises a four-quadrant operation multifunctional converter capable of dynamically adjusting active and reactive power output, the converter can absorb or emit reactive power while storing or releasing energy by receiving the instruction of the power factor adjusting and distributing device, and the proportion of the reactive power can be adjusted.
A capacity configuration and optimal operation control method for energy storage access wind power plant based on active voltage multi-objective comprises the following steps:
step one: aiming at the characteristics of a doubly-fed generator of a wind power plant, the wind speed distribution characteristics, the operation characteristics of a Static Var Generator (SVG), and the network side active power and voltage regulation and control requirements, a wind power plant power regulation and control system for storing energy containing compressed air is designed (shown in figure 1);
step two: 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;
step three: determining an optimization variable, an optimization target and constraint conditions of operation control of the energy storage power regulation system containing compressed air;
step four: and acquiring the installed capacity of the wind power plant, the wind speed characteristic of the place where the wind power plant is located, and network side pair active power and voltage scheduling data. The method for optimizing the operation of the active and reactive voltages is designed, and in the step two of solving the optimizing model by utilizing a chaotic multi-objective optimizing algorithm, the modeling process mainly comprises the following steps:
1) 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 gas constant, 287.1J/(kg.K); 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.
2) 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 of gas, 287.1J/ k g·K)；λ 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.
In the third step, the optimization variables include:
1) Compressed air energy storage output active power P CAES (t) and reactive power Q CAES (t)；
2) Direct-drive wind turbine generator system power factor;
3) SVG output reactive duty ratio
5. In the third step, the optimization targets include:
1) Voltage deviation accumulation
2) Reactive margin:
3) Energy storage balance: f (F) 3 ＝min|SOC caes (T)-SOC caes (1)|
Fig. 2 is a chaotic multi-objective optimization solution algorithm. The method comprises the following specific steps:
1): selecting the maximum evolution algebra, population scale and chaos control parameters;
2): according to the logistic mapping chaotic model, a chaotic sequence is initialized to optimize a variable population P t ；
3): for population P t Non-dominant ordering is performed, with the non-dominant level being the fitness of each solution. Selecting, crossing and mutating double tournaments to generate offspring population Q t Scale N.
4): will father population P t And offspring population Q t Are combined into a population R t For R t The non-dominant ordering is performed to determine the total non-dominant solution front F.
5): calculating the crowding distance of F, sorting the crowding distance of F, and selecting N-P with the best sorting t+1 I solutions;
6): and judging whether the evolutionary population reaches the optimum or not by judging whether the number of individuals with the non-inferior grade of 1 in the population is equal to the number of the population or not. When the two sub-population groups are equal, selecting the first 10% of the sub-population groups to perform self-adaptive chaotic refinement search;
7): repeating 3) to 5) until the maximum iteration number of the chaotic optimization is reached.
8): and outputting the optimal solution set.
Fig. 3-5 are schematic diagrams of the effects of smoothing active power and compensating reactive power by using compressed air energy storage and direct-drive wind turbines. The graph is the comparison of wind power output power and grid-connected power. As is apparent from fig. 3, due to the intervention of compressed air energy storage, the smoothness of the grid-connected power is greatly improved compared with the generated power. Fig. 4 compares the effect and reactive margin after compensation without reactive compensation, conventional single reactive compensation and the new method proposed by the present patent with fig. 5. Simulation examples fully prove that the reactive power loss of the system can be fully compensated by utilizing the abandoned wind power stored by the compressed air energy storage and adjusting the power factor of the direct-drive wind turbine generator, the grid-connected point voltage is stabilized, and meanwhile, the reactive margin of the system is ensured.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
While the foregoing description of the embodiments of the present application has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the application, but rather, it is intended to cover all modifications or variations within the scope of the application as defined by the claims of the present application.
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.
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