CN110348695A - Flexibility evaluation method, device, equipment and storage medium of power system - Google Patents

Abstract

The invention discloses a method, device, equipment and storage medium for evaluating the flexibility of a power system, including: calculating the daily net load output data according to the historical load output of the power system and the output of renewable energy sources; filtering according to the preset WMMF The multi-scale decomposition algorithm of the multi-scale decomposition algorithm decomposes the intraday net load output data into several fluctuation components; calculates the probability of insufficient flexibility and the average cost of flexibility of the power system according to the fluctuation components; according to the probability of insufficient flexibility and the flexibility average cost to evaluate the power system and adjust the power of the power system. Adopting multiple embodiments solves the problems in the prior art that it is impossible to evaluate the proportion of renewable energy and the impact of flexibility cost on the flexibility adjustment of the power system.

Description

Flexibility assessment method, device, equipment and storage medium of power system

technical field

The present invention relates to the technical field of power system control, in particular to a flexibility evaluation method, device, equipment and storage medium of a power system.

Background technique

With environmental pollution and the gradual depletion of fossil energy, new energy has become one of the main types of power sources in various countries. However, the access of a large number of renewable energy sources (such as wind power generation, solar photovoltaic power generation, etc.) also brings problems to the safe and stable operation of the power system. In the scenario of high-proportion renewable energy grid-connected, renewable energy has output characteristics such as randomness, volatility, and intermittency, and the power system needs to reserve a certain margin of flexible adjustment capacity as a flexible rotating reserve.

Existing flexibility evaluation indicators focus on showing the overall flexibility adequacy of the power system from the comparison of power system flexibility resources and system flexibility requirements, and cannot reflect the proportion of various renewable energy sources in the power system to flexibility. The impact of regulation, and ignore the restriction of flexibility cost on power system flexibility regulation, so it is difficult to deal with the power fluctuation of power system after renewable energy is connected to the grid.

Contents of the invention

Embodiments of the present invention provide a flexibility assessment method, device, equipment, and storage medium of a power system, which can effectively solve the problems in the prior art that the proportion of renewable energy cannot be assessed and the impact of flexibility costs on the flexibility adjustment of the power system .

An embodiment of the present invention provides a method for evaluating the flexibility of a power system, including:

According to the historical load output of the power system and the output of renewable energy, the daily net load output data is obtained;

According to the multi-scale decomposition algorithm of the preset WMMF filter, the intraday net load output data is decomposed to obtain several kinds of fluctuation components;

calculating the probability of insufficiency of flexibility and the average cost of flexibility of the power system according to the fluctuation component;

Evaluate the power system and adjust the power of the power system according to the probability of insufficiency of flexibility and the average cost of flexibility.

As an improvement of the above scheme, the multi-scale decomposition algorithm based on the preset WMMF filter decomposes the intraday net load output data, specifically including:

Decomposing the intraday net load output data into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components;

By performing fluctuation identification on the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component, the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component The fluctuation component is divided into uphill climbing section and downhill climbing section respectively.

As an improvement of the above scheme, the establishment of the probability index of insufficiency of flexibility and the average cost index of flexibility of the power system according to the decomposed intraday net load output data specifically includes:

Obtain the flexibility requirements corresponding to the climbing section by counting the climbing amplitude of each climbing section;

Obtain the corresponding available flexible resources through the climbing time of each climbing section, the climbing operation point and the output characteristics of flexible resources;

Comparing the available flexibility resources and the flexibility requirements in each climbing section respectively to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections;

The probability of insufficiency in flexibility is calculated according to the inflexibility insufficiency climbing section and the total number of climbing sections;

The average cost of flexibility is calculated according to the available flexibility resources and the flexibility requirements in each climbing section.

As an improvement of the above solution, the average cost of flexibility is calculated according to the available flexibility resources and the flexibility requirements in each climbing section, specifically:

in, is the average cost of flexibility; D _i is the flexibility demand in the i-th climbing section; F _i,j , ΔF _i, are the callable amount and the actual callable amount of the j-th resource in the i-th climbing section, respectively ; C _j is the flexibility unit invocation cost of the jth resource.

Another embodiment of the present invention provides a flexibility evaluation device for a power system, which is characterized in that it includes:

The data acquisition module is used to calculate the daily net load output data according to the historical load output of the power system and the output of renewable energy;

The data decomposition module is used to decompose the intraday net load output data according to the multi-scale decomposition algorithm of the preset WMMF filter to obtain several fluctuation components;

A calculation module, configured to calculate the probability of insufficiency of flexibility and the average cost of flexibility of the power system according to the fluctuation component;

An evaluation module, configured to evaluate the power system and adjust the power of the power system according to the probability of insufficient flexibility and the average cost of flexibility.

As an improvement of the above scheme, the data decomposition module includes:

A fluctuation component acquisition module, configured to decompose the intraday net load output data into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components;

The fluctuation identification module is configured to identify the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component by respectively performing fluctuation identification on the minute-level fluctuation The component and the hour-level fluctuation component are respectively divided into an upward climbing segment and a downward climbing segment.

As an improvement of the above scheme, the calculation module includes:

The flexibility demand acquisition module is used to obtain the flexibility demand corresponding to the climbing section by counting the climbing amplitude of each climbing section;

The available flexible resource acquisition module is used to obtain the corresponding available flexible resources through the climbing time of each climbing section, the climbing operation point and the output characteristics of the flexible resources;

A statistical module, configured to compare the available flexibility resources and the flexibility requirements in each climbing section to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections;

Insufficient flexibility probability calculation module, used to calculate the insufficient flexibility probability according to the inflexible climbing section and the total number of climbing sections;

A flexibility average cost calculation module, configured to calculate and obtain the flexibility average cost according to the available flexibility resources and the flexibility requirements in each climbing section.

Another embodiment of the present invention provides a flexibility evaluation device for a power system, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor executes The computer program realizes the flexibility evaluation method of the power system.

Another embodiment of the present invention correspondingly provides a computer-readable storage medium, the computer-readable storage medium includes a stored computer program, wherein, when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute The flexibility assessment method of the described power system.

Compared with the prior art, the embodiment of the present invention discloses a power system flexibility evaluation method, device, equipment and storage medium, which decomposes the daily net load output data through the multi-scale decomposition algorithm of the preset WMMF filter , and calculate the probability of insufficiency of flexibility and the average cost of flexibility according to the decomposed intraday net load output data, and evaluate the flexibility of the power system through the probability of insufficiency of flexibility and the average cost of flexibility, so as to adjust the power of the power system , so that the power system can operate safely and stably.

Description of drawings

FIG. 1 is a schematic flowchart of a method for evaluating flexibility of a power system provided by an embodiment of the present invention;

Fig. 2 is a schematic flow chart of the multi-scale decomposition of the preset WMMF filter in an embodiment of the present invention;

Fig. 3 is a schematic diagram of multi-time scale fluctuation decomposition of the payload curve in an embodiment of the present invention;

Fig. 4 is a schematic diagram of obtaining flexibility requirements in an embodiment of the present invention;

Fig. 5 is a schematic structural diagram of a flexibility evaluation device for a power system provided by an embodiment of the present invention;

Fig. 6 is a schematic structural diagram of a power system flexibility evaluation device provided by an embodiment of the present invention.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

Referring to FIG. 1 , it is a schematic flowchart of a method for evaluating flexibility of a power system provided by an embodiment of the present invention.

An embodiment of the present invention provides a method for evaluating the flexibility of a power system, including:

S10. Calculate and obtain daily net load output data according to the historical load output of the power system and the output of renewable energy. Among them, the output of renewable energy can be: wind power output, photovoltaic output, etc.

Specifically, due to the addition of renewable energy (such as wind power generation and solar photovoltaic power generation), the volatility of the power system operation needs to be increased. Considering wind power output and photovoltaic output as negative load output, the power system’s The intraday net load output curve is formed by subtracting the historical load output curve from the wind power and photovoltaic output curves.

S20. Decompose the intraday net load output data according to the multi-scale decomposition algorithm of the preset WMMF filter to obtain several kinds of fluctuation components.

Specifically, the mathematical expression of the WMMF filter constructed based on the OCCO filter is:

In the formula, f is the input signal; g is the structural element; ° represents the opening operation; · represents the closing operation; Θ represents the corrosion operation; Indicates the expansion operation; is the weight of the filtering result of each scale structure element. In order to reduce the impact of noise in the filtering results of small-scale structural elements on the final filtering results, the weight The value of is determined by the variance value of the filtering noise at each scale.

In the formula is the variance of the filtered difference at scale s _i .

Specifically, referring to Fig. 2, the multi-scale decomposition algorithm of the preset WMMF filter is to construct the first-stage WMMF filter according to the original payload time series (original flexibility demand time series) F; based on the first-stage WMMF filter pair The time series F is filtered to output the time series Y, and then the difference between F and Y is used to output the high-frequency component H; the second-level WMMF filter is constructed according to the time series Y; the time series Y is filtered based on the second-level WMMF filter to output the intermediate frequency Component M, and then make a difference between Y and M to output the low frequency component L.

In this embodiment, the intraday net load output data is decomposed into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components.

Specifically, referring to Figure 3, the net load output data is divided into minute-level fluctuation components (corresponding to the high-frequency components in Figure 3) and ten-minute level fluctuation components (corresponding to the intermediate frequency component) and hour-level fluctuation component (corresponding to the low-frequency component in Figure 3), according to the above fluctuation components, the time-series curve of the fluctuation component on the hour-level time scale, the time-series curve of the fluctuation component on the time scale of more than ten minutes, and the minute-level time The time series curve of the fluctuation component under the scale.

By performing fluctuation identification on the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component, the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component The fluctuation component is divided into uphill climbing section and downhill climbing section respectively.

Specifically, wave identification is performed on the time-series curves of the above-mentioned fluctuation components respectively, and the time-series curves of the fluctuation components are divided into an upward climbing section and a downward climbing section.

S30. Calculate according to the fluctuation component the probability of insufficiency of flexibility and the average cost of flexibility of the power system.

Specifically, referring to FIG. 4 , the upward and downward flexibility requirements corresponding to the climbing section are obtained by counting the upward and downward climbing amplitudes of each climbing section.

The corresponding available flexible resources are obtained through the climbing time of each climbing section, the climbing operation point, and the output characteristics of the flexible resources. Among them, in the process of flexibility adjustment, resources that can adapt to flexibility requirements through output adjustment can be used as flexibility resources. In the power system, conventional units with rapid adjustment capability, pumped storage power stations, power electronic energy storage devices, demand-side response and renewable energy units with strong controllability can be used as flexible resources. All kinds of flexible resources have different output characteristics on different time scales.

Illustratively, taking a thermal power plant as an example, the size of flexible resources provided by output regulation at the time scale of minutes and tens of minutes is:

F _{G, +} ＝ min{P _{G, max} -P _{G, 0} , Δt×r _{m, +} }

F _{G, -} ＝ min {P _{G, 0} -P _{G, min} , Δt×r _{m, -} }

In the formula, F _{G, +} , F _{G, -} are the flexible resource size of the unit for upward and downward adjustment respectively; _PG,max , _PG,min and P _G,0 are the maximum operating output and the minimum operating output of the unit respectively and the current output; r _m,+ and r _m,- are the upward and downward climbing rates of the unit respectively; Δt is the climbing time.

The output adjustment capability of a thermal power plant on an hourly time scale is:

F _G,+ ＝PS G _,max

F _{G, -} = PS G _{, 0}

In the formula, _PSG,0 and _PSG,max are the current output and maximum adjustment capacity of the peaking unit respectively.

Specifically, the start-up mode of the power system is determined according to the daily net load output, and the flexible resources at each time scale are determined in combination with the operating status and output characteristics of various types of power sources. For the fluctuation components at each time scale, the flexible units (renewable energy units, etc.) at the corresponding scales are respectively selected to participate in the flexibility adjustment, thereby determining the size of the available flexible resources at each time scale.

The available flexibility resources in each climbing section are compared with the flexibility requirements to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections. Among them, the climbing section whose available flexibility resource is lower than the flexibility requirement is called the climbing section with insufficient flexibility.

The inflexibility probability is calculated according to the inflexible climbing section and the total number of climbing sections.

specifically, In the formula, n is the number of climbing sections with insufficient flexibility, and N is the total number of climbing sections of the power system.

The average cost of flexibility is calculated according to the available flexibility resources and the flexibility requirements in each climbing section. Among them, in each climbing section, through the economical allocation of flexible resources, the lowest total flexibility allocation cost is achieved. Therefore, the average call cost in all climbing sections is defined as the flexibility cost.

specifically,

in, is the average cost of flexibility; D _i is the flexibility demand in the i-th climbing section; F _i,j , ΔF _i, are the callable amount and the actual callable amount of the j-th resource in the i-th climbing section, respectively ; C _j is the flexibility unit invocation cost of the jth resource.

S40. Evaluate the power system according to the probability of insufficiency of flexibility and the average cost of flexibility, and adjust the power of the power system.

Specifically, the smaller the probability of insufficient flexibility E, the greater the probability that the system can meet the system flexibility requirements; flexibility cost A smaller value means that the system can meet the system flexibility requirements with a smaller adjustment cost.

Compared with the prior art, the embodiment of the present invention discloses a method for evaluating the flexibility of a power system, which decomposes the intraday net load output data through the multi-scale decomposition algorithm of the preset WMMF filter, and according to the decomposed intraday The net load output data calculates the probability of insufficiency of flexibility and the average cost of flexibility, and evaluates the flexibility of the power system through the probability of insufficiency of flexibility and the average cost of flexibility, so as to adjust the power of the power system so that the power system can be safe and stable running.

To facilitate understanding, take Hainan Power Grid as an example:

The invocation of various flexible resources is carried out at a certain time scale, and the output of the system's flexible resources participating in the adjustment at each time scale is related to its own output characteristics. Among them, thermal power units participate in flexible adjustments at different time scales according to their own unit characteristics. Gas-fired units with faster adjustment capabilities can participate in flexible adjustments at minute-level time scales. For some gas-fired units and some coal-fired units with slower output Units participate in flexibility adjustments within a time scale of ten to tens of minutes. In addition, thermal power standby units can participate in flexibility adjustments over an hour-level time scale; Peak resources participate in the flexibility adjustment of the system within the time scale of minutes to tens of minutes; pumped storage power plants, as peak-shaving power sources with excellent performance, can participate in flexibility adjustments on the time scale of minutes, and the flexible resources they provide The size is mainly affected by the capacity of the pumped storage power station; the power electronic energy storage device can participate in the flexibility adjustment within the time scale of minutes to tens of minutes, and the flexibility resources it provides depend on many factors, including the energy storage battery. Release time, efficiency and storage capacity, etc.; interrupt load can be used as the main demand-side response adjustment means to participate in the flexibility adjustment on the hour-level time scale; renewable energy with strong controllability can be considered as a certain confidence capacity. Considering that the controllable unit participates in the flexible adjustment on the time scale of more than ten minutes, it can also participate in the flexible adjustment on the hourly time scale by abandoning wind and light.

In practical applications, after calculating the flexibility indicators (ie, the probability of insufficient flexibility and the average cost of flexibility) at each time scale, the flexibility indicators at each time scale can also be calculated according to the evaluator's preference for each time scale. The weighted summation is used to obtain the overall flexibility insufficiency probability index and the flexibility average cost index of the power system comprehensively considering each time scale. The output flexibility evaluation results are shown in the table below:

The power system can be adjusted by observing the above index of insufficient flexibility probability. On each time scale, the probability of insufficient flexibility upward is smaller than the probability of insufficient flexibility downward. Resources are provided by thermal power plants. However, the upward climbing rate of the thermal power unit is greater than the downward climbing rate, and subject to the limitation of the minimum stable operating power, the downward adjustment ability of the thermal power unit is limited, so it is reflected in the probability index of insufficient flexibility that the probability of insufficient flexibility in the downward direction is greater than that in the upward direction. Insufficient flexibility probability. The average cost of upward flexibility is higher than the average cost of downward flexibility on the time scale of minutes and tens to tens of minutes, because the flexible resource takes into account the integration of wind power and photovoltaic power plants. The participation of confidence capacity and curtailed wind and solar capacity in downward flexibility regulation has a regulation cost much lower than that of thermal power, so the participation of wind and solar power reduces the average cost of system flexibility downward regulation. On the hour-level time scale, the average cost of upward flexibility is slightly lower than the average cost of downward flexibility, because the flexibility needs to be adjusted on this time scale are much greater than those in the previous short time scale. The adjustment task is mainly undertaken by the thermal power plant standby units, and the addition of controllable loads is considered in the upward flexibility resources, so that the average adjustment cost of the upward flexibility is reduced. Comparing the average cost of flexibility between different time scales horizontally, the average cost of flexibility on the hour-level time scale is much higher than the average cost of flexibility on the other two time scales, which also reflects that the start-stop peak shaving of thermal power units is an hourly The primary flexibility resource on the level time scale has a high adjustment cost. The flexibility of the power system is evaluated by the probability of insufficiency of flexibility and the average cost of flexibility, so as to adjust the power system and make the operation of the power system more stable and safe.

Referring to FIG. 5 , it is a schematic structural diagram of a flexibility evaluation device for a power system provided by an embodiment of the present invention.

An embodiment of the present invention provides a flexibility evaluation device for a power system, including:

The data acquisition module 10 is used to calculate and obtain intraday net load output data according to the historical load output of the power system and the output of renewable energy.

The data decomposition module 20 is used to decompose the intraday net load output data according to the multi-scale decomposition algorithm of the preset WMMF filter to obtain several kinds of fluctuation components.

A calculation module 30, configured to calculate the probability of insufficiency of flexibility and the average cost of flexibility of the power system according to the fluctuation component.

An evaluation module 40, configured to evaluate the power system according to the flexibility insufficiency probability and the flexibility average cost and adjust the power of the power system.

As an improvement of the above scheme, the data decomposition module includes:

A fluctuation component acquisition module, configured to decompose the intraday net load output data into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components.

The fluctuation identification module is configured to identify the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component by respectively performing fluctuation identification on the minute-level fluctuation The component and the hour-level fluctuation component are respectively divided into an upward climbing segment and a downward climbing segment.

As an improvement of the above scheme, the calculation module includes:

The flexibility demand obtaining module is used to obtain the flexibility demand corresponding to the climbing section by counting the climbing amplitude of each climbing section.

The available flexibility resource obtaining module is used to obtain the corresponding available flexible resources through the climbing time of each climbing section, the climbing operation point and the output characteristics of the flexible resources.

A statistical module, configured to compare the available flexibility resources and the flexibility requirements in each climbing section to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections.

The inflexibility probability calculation module is configured to calculate the inflexibility probability according to the inflexible climbing section and the total number of climbing sections.

A flexibility average cost calculation module, configured to calculate and obtain the flexibility average cost according to the available flexibility resources and the flexibility requirements in each climbing section.

Compared with the prior art, the embodiment of the present invention discloses a power system flexibility evaluation device, which decomposes the intraday net load output data through the multi-scale decomposition algorithm of the preset WMMF filter, and according to the decomposed intraday The net load output data calculates the probability of insufficiency of flexibility and the average cost of flexibility, and evaluates the flexibility of the power system through the probability of insufficiency of flexibility and the average cost of flexibility, so as to adjust the power of the power system so that the power system can be safe and stable running.

Referring to FIG. 6 , it is a schematic diagram of a terminal device for evaluating flexibility of a power system provided by an embodiment of the present invention. The terminal device for evaluating the flexibility of a power system in this embodiment includes: a processor, a memory, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, the steps in the above-mentioned embodiments of the flexibility evaluation method for each electric power system are realized. Alternatively, when the processor executes the computer program, the functions of the modules/units in the above device embodiments are implemented.

Exemplarily, the computer program may be divided into one or more modules/units, and the one or more modules/units are stored in the memory and executed by the processor to complete the present invention. The one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program in the flexibility evaluation terminal device of the power system.

The terminal equipment for evaluating the flexibility of the power system may be computing equipment such as desktop computers, notebooks, palmtop computers, and cloud servers. The flexibility evaluation terminal equipment of the power system may include, but not limited to, a processor and a memory. Those skilled in the art can understand that the schematic diagram is only an example of the flexibility assessment terminal equipment of the power system, and does not constitute a limitation on the flexibility assessment terminal equipment of the power system, and may include more or less components than those shown in the illustration , or combine certain components, or different components, for example, the flexibility evaluation terminal equipment of the electric power system may also include input and output equipment, network access equipment, bus and so on.

The so-called processor can be a central processing unit (Central Processing Unit, CPU), and can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf Programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc. The processor is the control center of the flexibility evaluation terminal equipment of the power system, and connects the entire * *Parts of the device/end equipment.

The memory can be used to store the computer programs and/or modules, and the processor realizes the power by running or executing the computer programs and/or modules stored in the memory and calling the data stored in the memory. The flexibility of the system evaluates various functions of the end equipment. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required by a function (such as a sound playback function, an image playback function, etc.) and the like; the storage data area may store Data created based on the use of the mobile phone (such as audio data, phonebook, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, A flash memory card (Flash Card), at least one magnetic disk storage device, flash memory device, or other volatile solid state storage devices.

Wherein, if the integrated modules/units of the power system flexibility evaluation terminal equipment are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the present invention realizes all or part of the processes in the methods of the above embodiments, and can also be completed by instructing related hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM, Read-Only Memory) , Random Access Memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

It should be noted that the device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physically separated. A unit can be located in one place, or it can be distributed to multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that they have a communication connection, which can be specifically implemented as one or more communication buses or signal lines. It can be understood and implemented by those skilled in the art without creative effort.

The above description is a preferred embodiment of the present invention, and it should be pointed out that for those skilled in the art, without departing from the principle of the present invention, some improvements and modifications can also be made, and these improvements and modifications are also considered Be the protection scope of the present invention.

Claims (9)

1. A method for assessing flexibility of an electric power system, comprising: According to the historical load output of the power system and the output of renewable energy, the daily net load output data is obtained; According to the multi-scale decomposition algorithm of the preset WMMF filter, the intraday net load output data is decomposed to obtain several kinds of fluctuation components; calculating the probability of insufficiency of flexibility and the average cost of flexibility of the power system according to the fluctuation component; Evaluate the power system and adjust the power of the power system according to the probability of insufficiency of flexibility and the average cost of flexibility. 2. The flexibility assessment method of power system as claimed in claim 1, is characterized in that, described intraday net load output data is decomposed according to the multi-scale decomposition algorithm of preset WMMF filter and obtains several kinds of fluctuation components , including: Decomposing the intraday net load output data into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components; By performing fluctuation identification on the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component, the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component The fluctuation component is divided into uphill climbing section and downhill climbing section respectively. 3. The flexibility evaluation method of the power system according to claim 2, wherein the calculation according to the fluctuation component to obtain the probability index of insufficient flexibility and the average cost index of flexibility of the power system specifically includes: Obtain the flexibility requirements corresponding to the climbing section by counting the climbing amplitude of each climbing section; Obtain the corresponding available flexible resources through the climbing time of each climbing section, the climbing operation point and the output characteristics of flexible resources; Comparing the available flexibility resources and the flexibility requirements in each climbing section respectively to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections; The probability of insufficiency in flexibility is calculated according to the inflexibility insufficiency climbing section and the total number of climbing sections; The average cost of flexibility is calculated according to the available flexibility resources and the flexibility requirements in each climbing section. 4. The flexibility evaluation method of electric power system as claimed in claim 3, is characterized in that, described according to described available flexibility resource and described flexibility requirement calculation in each climbing section obtains described flexibility average cost ,Specifically: in, is the average cost of flexibility; D _i is the flexibility demand in the i-th climbing section; F _i,j , ΔF _i,j are the callable amount and actual invocation of the j-th resource in the i-th climbing section, respectively amount; C _j is the flexibility unit invocation cost of the jth resource. 5. A flexibility assessment device for a power system, comprising: The data acquisition module is used to obtain daily net load output data according to the historical load output of the power system and the output of renewable energy; The data decomposition module is used to decompose the intraday net load output data according to the multi-scale decomposition algorithm of the preset WMMF filter; A calculation module, configured to calculate the probability of insufficiency of flexibility and the average cost of flexibility of the power system according to the decomposed intraday net load output data; An evaluation module, configured to evaluate the power system and adjust the power of the power system according to the probability of insufficient flexibility and the average cost of flexibility. 6. The flexibility evaluation device of electric power system as claimed in claim 5, is characterized in that, described data decomposition module comprises: A fluctuation component acquisition module, configured to decompose the intraday net load output data into minute-level fluctuation components, ten-minute-level fluctuation components, and hour-level fluctuation components; The fluctuation identification module is configured to identify the minute-level fluctuation component, the ten-minute-level fluctuation component, and the hour-level fluctuation component by respectively performing fluctuation identification on the minute-level fluctuation The component and the hour-level fluctuation component are divided into an upward climbing segment and a downward climbing segment, respectively. 7. The flexibility evaluation device of electric power system as claimed in claim 6, is characterized in that, described computing module comprises: The flexibility demand acquisition module is used to obtain the flexibility demand corresponding to the climbing section by counting the climbing amplitude of each climbing section; The available flexible resource acquisition module is used to obtain the corresponding available flexible resources through the climbing time of each climbing section, the climbing operation point and the output characteristics of the flexible resources; A statistical module, configured to compare the available flexibility resources and the flexibility requirements in each climbing section to obtain the number of climbing sections with insufficient flexibility and the total number of climbing sections; Insufficient flexibility probability calculation module, used to calculate the insufficient flexibility probability according to the inflexible climbing section and the total number of climbing sections; A flexibility average cost calculation module, configured to calculate and obtain the flexibility average cost according to the available flexibility resources and the flexibility requirements in each climbing section. 8. A flexibility evaluation device for a power system, characterized in that it includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor executes the computer program The program realizes the flexibility evaluation method of the power system according to any one of claims 1 to 4. 9. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute The flexibility evaluation method of the power system described in any one of 1 to 4.