A method and device for optimizing the dispatching of a wind-solar base

Abstract

The present application proposes an optimized scheduling method and device for a wind-solar base, which relates to the field of wind-solar unit scheduling, including: reporting the wind-solar power prediction results according to the prediction situation of the wind-solar base; formulating a scheduling curve for the wind-solar base according to the wind-solar power prediction results according to a preset confidence level, and issuing a scheduling plan; taking the scheduling curve of the wind power base as the target and following the principle of average curtailment of electricity, decomposing the scheduling instructions in the scheduling plan to determine the operating output curves of each wind-solar unit. The present invention adopting the above scheme can achieve accurate allocation of the output of the wind-solar base.

Description

Technical Field

[0001] This application relates to the field of wind-solar unit scheduling, and particularly to an optimization scheduling method and device for a wind-solar base. Background Art

[0002] With the continuous increase in the proportion of new energy connected to the grid, its advantages of environmental protection and disadvantages of uncertainty bring new problems to the optimal economic scheduling of the wind-solar system, and put forward higher requirements for how to achieve economic, environmental, and reliable scheduling operation. At present, the prediction technology of wind-solar power output is far from meeting the prediction error accuracy required by scheduling. Therefore, choosing a suitable method to accurately describe this uncertainty is the basis and hotspot of the current research on the scheduling of systems containing wind-solar bases. Summary of the Invention

[0003] In view of the above problems, an optimization scheduling method and device for a wind-solar base are proposed, by

[0004] A first aspect of this application proposes an optimization scheduling method for a wind-solar base, including:

[0005] Report the wind-solar power prediction result according to the prediction situation of the wind-solar base;

[0006] According to the wind-solar power prediction result, formulate a wind-solar base scheduling curve according to a preset confidence level, and issue a scheduling plan;

[0007] Taking the wind power base scheduling curve as the target and based on the principle of average curtailment, decompose the scheduling instructions in the scheduling plan to determine the operating output curves of each wind-solar unit.

[0008] Optionally, the wind-solar power prediction result includes:

[0009] Wind power prediction result, where P wind，pre，t is the wind power prediction result of the wind-solar base at time t;

[0010] Photovoltaic power prediction result, where P solar，pre，t is the photovoltaic power prediction result of the wind-solar base at time t.

[0011] Optionally, the step of formulating a wind-solar base scheduling curve according to the wind-solar power prediction result according to a preset confidence level and issuing a scheduling plan includes:

[0012]

[0013] where P sum，work，t is the issued wind-solar base scheduling curve.

[0014] Optionally, aiming at the dispatching curve of the wind power base and based on the principle of average curtailment, the dispatching instructions in the dispatching plan are decomposed, including:

[0015] Determine the output constraint conditions of the wind turbines;

[0016] Determine the output constraint conditions of the photovoltaic power generation;

[0017] According to the output constraint conditions of the wind turbines and the output constraint conditions of the photovoltaic power generation, aiming at the dispatching curve of the wind power base and based on the principle of average curtailment, the dispatching instructions in the dispatching plan are decomposed.

[0018] Optionally, the determination of the output constraint conditions of the wind turbines includes:

[0019] 0 ≤ P wind，work，t ≤ P wind，pre，t ,

[0020] 0 ≤ |P wind，work，t+1 - P wind，work，t | ≤ P′ wind ,

[0021] where P′ wind is the ramp rate of the wind turbine, and P wind，work，t is the operating value of the wind turbine at time t.

[0022] Optionally, the determination of the output constraint conditions of the photovoltaic power generation includes:

[0023] 0 ≤ P solar，work，t ≤ P solar，pre，t ,

[0024] where P solar，work，t is the operating value of the photovoltaic power generation at time t.

[0025] Optionally, according to the output constraint conditions of the wind turbines and the output constraint conditions of the photovoltaic power generation, aiming at the dispatching curve of the wind power base and based on the principle of average curtailment, the decomposition of the dispatching instructions in the dispatching plan includes:

[0026] Determine the curtailment of the wind-solar units;

[0027] Allocate the curtailment to each of the wind-solar units according to the first allocation rule, where the first allocation rule is from the first wind turbine to the last photovoltaic power generation;

[0028] Select the wind turbines and photovoltaic power generations that meet the preset conditions and perform re-allocation according to the second allocation rule, where the second allocation rule is from the first wind turbine that meets the preset conditions to the last photovoltaic power generation that meets the preset conditions.

[0029] Optionally, the determination of the curtailment of the wind-solar units includes:

[0030] P abandon，t =P winr，prre，t +P solar，pre，t -P sum，work，t ,

[0031] P' abandon，t =P abandon，t / (M + P),

[0032] where P abandon，t is the total curtailment power of the wind-solar unit at time t, P' abandon，t is the average curtailment power of each wind-solar unit at time t, M is the number of wind turbines, and P is the number of photovoltaic power stations.

[0033] Optionally, the curtailment power is distributed to each wind-solar unit according to the first distribution rule, where the first distribution rule starts from the first wind turbine and ends at the last photovoltaic unit, including:

[0034] Distribute the operating value of the wind turbine, where the operating value of the wind turbine satisfies:

[0035]

[0036] Distribute the operating value of the photovoltaic unit, where the operating value of the photovoltaic unit satisfies:

[0037]

[0038] Statistically calculate the undistributed curtailment power P abandonTemp，t at time t for the wind turbines and photovoltaic units, where the P abandonTemp，t satisfies:

[0039]

[0040]

[0041] Optionally, select the wind turbines and photovoltaic units that meet the preset conditions and perform re-distribution according to the second distribution rule, where the second distribution rule starts from the first wind turbine that meets the preset conditions and ends at the last photovoltaic unit that meets the preset conditions, including:

[0042] Select the wind turbines that meet the condition of P wind，work，t ≥P' abandonTemp，t and the photovoltaic units that meet the condition of P solar，work，t ≥P' abandonTemp，t for re-distribution, where P' abandonTemp，t is the curtailment power distributed to each wind-solar unit at the new round of time t, and the formula is:

[0043] P' abandonTemp，t =P abandonTemp ,t / (windTemp + solarTemp),

[0044] where windTemp is the number of wind turbines that meet the condition P wind，work，t ≥P′ abandonTemp，t and solarTemp is the number of photovoltaic units that meet the condition P solar，work，t ≥P′ abandonTemp，t condition;

[0045] Allocate the operating values of the wind turbines that meet the preset conditions, where the operating values of the wind turbines that meet the preset conditions satisfy:

[0046]

[0047] Allocate the operating values of the photovoltaic units that meet the preset conditions, where the operating values of the photovoltaic units that meet the preset conditions satisfy:

[0048]

[0049] Count the unallocated curtailment power P of the wind turbines and the photovoltaic units that meet the preset conditions at time t abandonTemp，t , where the P abandonTemp，t satisfies:

[0050]

[0051]

[0052] Optionally, perform cyclic allocation on the wind turbines and the photovoltaic units that meet the preset conditions until P abandonTemp，t is 0.

[0053] A second aspect of the present application provides an optimized scheduling device for a wind-solar base, including:

[0054] A prediction and reporting module, configured to report a wind-solar power prediction result according to the prediction situation of the wind-solar base;

[0055] A wind-solar base scheduling curve formulation module, configured to formulate a wind-solar base scheduling curve according to the wind-solar power prediction result with a preset confidence level, and issue a scheduling plan;

[0056] An output module, configured to decompose the scheduling instructions in the scheduling plan with the wind power base scheduling curve as the target and based on the principle of average curtailment, and determine the operating output curves of each wind-solar unit.

[0057] In a third aspect of the present application, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the method described in any one of the above first aspects is implemented.

[0058] In a fourth aspect of the present application, a non-transitory computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in any one of the above first aspects is implemented.

[0059] The technical solutions provided by the embodiments of the present application at least bring the following beneficial effects:

[0060] It is possible to accurately allocate the power output of the wind-solar base.

[0061] The additional aspects and advantages of the present application will be partially given in the following description, partially become apparent from the following description, or be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0063] Figure 1 is a flowchart of a method for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0064] Figure 2 is a flowchart of a method for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0065] Figure 3 is a flowchart of a method for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0066] Figure 4 is a flowchart of a method for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0067] Figure 5 is a flowchart of a method for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0068] Figure 6 is a block diagram of a device for optimizing the scheduling of a wind-solar base shown according to an exemplary embodiment of the present application;

[0069] Figure 7 is a block diagram of an electronic device. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0070] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0071] Figure 1 is a flowchart of a method for optimizing the scheduling of a wind-solar base according to an exemplary embodiment of the present application. As Figure 1 shown, it includes:

[0072] Step 101: Report the wind-solar power prediction results according to the prediction situation of the wind-solar base.

[0073] In the embodiments of the present application, the wind-solar power prediction results include:

[0074] The wind power prediction result, where P wind，pre，t is the power prediction result of the wind power of the wind-solar base at time t;

[0075] The photovoltaic power prediction result, where P solar，pre，t is the power prediction result of the photovoltaic power of the wind-solar base at time t.

[0076] In a possible embodiment, when the resolution is 15 minutes, n is 95; when the resolution is 1 hour, n is 23.

[0077] Step 102: Develop a scheduling curve for the wind-solar base according to the wind-solar power prediction results and issue a scheduling plan according to a preset confidence level.

[0078] In the embodiments of the present application, the scheduling curve of the wind-solar base should meet the following conditions:

[0079]

[0080] where P sum，work，t is the issued scheduling curve of the wind-solar base.

[0081] Step 103: Take the scheduling curve of the wind power base as the target and decompose the scheduling instructions in the scheduling plan according to the principle of average curtailment to determine the operation output curves of each wind-solar unit.

[0082] In the embodiments of the present application, according to the principle of average curtailment, when the scheduling curve of the wind-solar base meets the conditions, decompose the scheduling instructions in the scheduling plan. As Figure 2 shown, Step 103 further includes:

[0083] Step 201: Determine the output constraint conditions of the fan.

[0084] In the embodiments of the present application, the output constraint conditions of the fan are:

[0085] 0 ≤ P wind，work，t ≤ P wind，pre，t ,

[0086] 0 ≤ |P wind，work，t+1 - P wind，work，t | ≤ P′ wind ,

[0087] where P′ wind is the ramp rate of the wind turbine, and P wind，work，t is the operating value of the wind turbine at time t.

[0088] Step 202, determine the photovoltaic power output constraint conditions.

[0089] In the embodiment of the present application, the photovoltaic power output constraint conditions are:

[0090] 0 ≤ P solar，work，t ≤ P solar，pre，t ,

[0091] where P solar，work，t is the operating value of the photovoltaic at time t.

[0092] Step 203, according to the wind turbine power output constraint conditions and the photovoltaic power output constraint conditions, with the wind power base dispatch curve as the goal and the principle of average curtailment, decompose the dispatch instructions in the dispatch plan.

[0093] In the embodiment of the present application, determine the curtailment situation of the wind-solar units and allocate the curtailment to the wind-solar units. Specifically, as Figure 3 shown, Step 203 further includes:

[0094] Step 301, determine the curtailment of the wind-solar units.

[0095] In the embodiment of the present application, the curtailment of the wind-solar units is determined by the following formula:

[0096] P abandon，t = P wind，pre，t + P solar，pre，t - P sum，work，t ,

[0097] P′ abandon，t = P abandon，t / (M + P),

[0098] where P abandon，t is the total curtailment power of the wind-solar units at time t, P′ abandon，t is the average curtailment power of each wind-solar unit at time t, M is the number of wind turbines, and P is the number of photovoltaic power stations.

[0099] Step 302, allocate the curtailment to each wind-solar unit according to the first allocation rule, where the first allocation rule is from the first wind turbine to the last photovoltaic.

[0100] In the embodiment of the present application, after the operating values of the wind turbines and the photovoltaic are allocated, the unallocated abandoned power of the wind turbines and the photovoltaic is counted. As Figure 4 shown, step 302 further includes:

[0101] Step 401, allocate the operating value of the wind turbine, where the operating value of the wind turbine satisfies:

[0102]

[0103] Step 402, allocate the operating value of the photovoltaic, where the operating value of the photovoltaic satisfies:

[0104]

[0105] Step 403, count the unallocated abandoned power P abandonTemp，t , where P abandonTemp，t satisfies:

[0106]

[0107]

[0108] Step 303, select the wind turbines and the photovoltaic that meet the preset conditions, and perform reallocation according to the second allocation rule, where the second allocation rule starts from the first wind turbine that meets the preset conditions and ends at the last photovoltaic that meets the preset conditions.

[0109] In the embodiment of the present application, select the wind turbines that meet the condition of P wind，work，t ≥P′ abandonTemp，t and the photovoltaic that meets the condition of P solar，work，t ≥P′ abandonTemp，t for reallocation, where P′ abandonTemp，t is the abandoned power allocated to each wind-solar unit at the new round of time t, and the formula is as follows:

[0110]

[0111] where windTemp is the number of wind turbines that meet the condition of P wind，work，t ≥P′ abandonTemp，t and solarTemp is the number of photovoltaic that meets the condition of P solar，work，t ≥P′ abandonTemp，t condition.

[0112] The allocation process is as Figure 5 shown, including:

[0113] Step 501, allocate the operating value of the wind turbines that meet the preset conditions, where the operating value of the wind turbines that meet the preset conditions satisfies:

[0114]

[0115] Step 502: Allocate the operating values of the photovoltaics that meet the preset conditions, where the operating values of the photovoltaics that meet the preset conditions satisfy:

[0116]

[0117] Step 503: Statistically calculate the unallocated curtailment power P of the wind turbines and photovoltaics that meet the preset conditions at time t abandonTemp，t , where P abandonTemp，t satisfies:

[0118]

[0119]

[0120] Among them, the wind turbines and photovoltaics that meet the preset conditions are cyclically allocated until P abandonTemp，t is 0, and the allocation stops.

[0121] In a possible embodiment, when the solution period is one day, cycling t from 0 to n, with a resolution of 15 minutes, n is 95; with a resolution of 1 hour, n is 23, thereby obtaining the operating curves P wind，work，t and P solar，work，t of each wind power and photovoltaic unit, where 0 <= t <= n.

[0122] Through the above method, the embodiments of the present application can accurately allocate the output of the wind-solar base.

[0123] Figure 6 is a block diagram of a wind-solar base optimal scheduling device 600 shown according to an exemplary embodiment of the present application, including: a prediction and reporting module 610, a wind-solar base scheduling curve formulation module 620, and an output module 630.

[0124] The prediction and reporting module 610 is used to report the wind-solar power prediction results according to the prediction situation of the wind-solar base;

[0125] The wind-solar base scheduling curve formulation module 620 is used to formulate the wind-solar base scheduling curve according to the wind-solar power prediction results with a preset confidence level and issue the scheduling plan;

[0126] The output module 630 is used to target the wind power base scheduling curve and decompose the scheduling instructions in the scheduling plan based on the principle of average curtailment to determine the operating output curves of each wind-solar unit.

[0127] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0128] Figure 7 FIG. shows a schematic block diagram of an exemplary electronic device 700 that can be used to implement embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0129] As Figure 7 shown, the device 700 includes a computing unit 701 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 707 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0130] A plurality of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a magnetic disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0131] The computing unit 701 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 executes the various methods and processes described above, such as the voice command response method. For example, in some embodiments, the voice command response method can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the computing unit 701, one or more steps of the voice command response method described above can be executed. Alternatively, in other embodiments, the computing unit 701 can be configured to execute the voice command response method in any other suitable manner (e.g., by means of firmware).

[0132] The various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), system-on-a-chip systems (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor, that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0133] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0134] In the context of the present disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0135] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0136] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0137] A computer system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, solving the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system or a server combined with a blockchain.

[0138] It should be understood that various forms of processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitation is imposed herein.

[0139] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. An optimized scheduling method for a wind-solar base, characterized in that, including: Reporting the wind and light power prediction results according to the prediction of the wind and light base; Formulating a wind and light base dispatch curve according to the wind and light power prediction results with a preset confidence level, and issuing a dispatch plan; Determining the output constraints of wind turbines and the output constraints of photovoltaic panels; according to the output constraints of wind turbines and the output constraints of photovoltaic panels, taking the wind and light base dispatch curve as the target and following the principle of average curtailment, decomposing the dispatch instructions in the dispatch plan to determine the operating output curves of each wind and light unit; According to the output constraints of wind turbines and the output constraints of photovoltaic panels, taking the wind and light base dispatch curve as the target and following the principle of average curtailment, decomposing the dispatch instructions in the dispatch plan, including: determining the curtailment of wind and light units; allocating the curtailment to each wind and light unit according to the first allocation rule; selecting wind turbines and photovoltaic panels that meet the preset conditions and performing re-allocation according to the second allocation rule; wherein, the first allocation rule is from the first wind turbine to the last photovoltaic panel, and the second allocation rule is from the first wind turbine that meets the preset conditions to the last photovoltaic panel that meets the preset conditions; Determining the curtailment of wind and light units, including: ， ， Among them, is the total curtailment power of the wind-solar units at time t, is the average curtailment power of each of the wind-solar units at time t, M is the number of wind turbines, and P is the number of photovoltaic power stations; Selecting wind turbines and photovoltaic panels that meet the preset conditions and performing re-allocation according to the second allocation rule, wherein the second allocation rule is from the first wind turbine that meets the preset conditions to the last photovoltaic panel that meets the preset conditions, including: Select the wind turbines that meet the conditions and the photovoltaics that meet the conditions, and perform reallocation. Among them, the curtailed power allocated to each of the wind-solar units at the new round of time t is formulated as: ， Among them, is the number of fans that meet the conditions, is the number of photovoltaics that meet the conditions; Allocating the operating values of the wind turbines that meet the preset conditions, wherein the operating values of the wind turbines that meet the preset conditions satisfy: ； Allocating the operating values of the photovoltaic panels that meet the preset conditions, wherein the operating values of the photovoltaic panels that meet the preset conditions satisfy: ； Statistically calculate the unallocated curtailment power of the wind turbines and photovoltaics that meet the preset conditions at time t , where the satisfies: ， 。 2. The method according to claim 1, characterized in that The wind and light power prediction results include: Wind power prediction results, where, is the wind power prediction result of the wind-solar base at time t; Photovoltaic power prediction results, where is the predicted photovoltaic power of the wind-solar base at time t.

3. The method according to claim 1, characterized in that, The step of formulating a wind and light base dispatch curve according to the wind and light power prediction results with a preset confidence level and issuing a dispatch plan includes: ， Among them, is the scheduling curve of the wind-solar base issued.

4. The method according to claim 1, wherein Determining the output constraints of wind turbines, including: ， ， Among them, is the ramp rate of the fan, is the operating value of the fan at time t.

5. The method according to claim 1, characterized in that Determining the output constraints of photovoltaic panels, including: ， Among them, is the operating value of the photovoltaic at time t.

6. The method according to claim 1, wherein Allocating the curtailment to each wind and light unit according to the first allocation rule, wherein the first allocation rule is from the first wind turbine to the last photovoltaic panel, including: Allocating the operating values of the wind turbines, wherein the operating values of the wind turbines satisfy: ； Allocating the operating values of the photovoltaic panels, wherein the operating values of the photovoltaic panels satisfy: ； Statistically calculate the unallocated curtailed power of the wind turbine and photovoltaic at time t , where the satisfies: ， 。 7. The method according to claim 1, wherein The method further includes: Perform cyclic allocation on the fan and the photovoltaic that meet the preset conditions until it is 0.

8. An optimized scheduling device for a wind-solar base, characterized in that, including: A prediction and reporting module for reporting the wind and light power prediction results according to the prediction of the wind and light base; A wind and light base dispatch curve formulation module for formulating a wind and light base dispatch curve according to the wind and light power prediction results with a preset confidence level and issuing a dispatch plan; An output module for determining the output constraints of wind turbines and the output constraints of photovoltaic panels; according to the output constraints of wind turbines and the output constraints of photovoltaic panels, taking the wind and light base dispatch curve as the target and following the principle of average curtailment, decomposing the dispatch instructions in the dispatch plan to determine the operating output curves of each wind and light unit; According to the wind turbine output constraint condition and the photovoltaic output constraint condition, with the scheduling curve of the wind-solar base as the goal and the principle of average curtailment of electricity, decompose the scheduling instructions in the scheduling plan, including: determining the curtailment of electricity of the wind-solar units; allocating the curtailment of electricity to each of the wind-solar units according to the first allocation rule; selecting the wind turbines and photovoltaics that meet the preset conditions and performing re-allocation according to the second allocation rule; wherein, the first allocation rule is from the first wind turbine to the last photovoltaic, and the second allocation rule is from the first wind turbine that meets the preset conditions to the last photovoltaic that meets the preset conditions; Determining the curtailment of electricity of the wind-solar units includes: ， ， Among them, is the total curtailment power of the wind-solar power units at time t, is the average curtailment power of each of the wind-solar power units at time t, M is the number of wind turbines, and P is the number of photovoltaic power stations; Selecting the wind turbines and photovoltaics that meet the preset conditions and performing re-allocation according to the second allocation rule, wherein the second allocation rule is from the first wind turbine that meets the preset conditions to the last photovoltaic that meets the preset conditions, including: Select the wind turbines that meet the conditions and the photovoltaics that meet the conditions, and perform reallocation. Among them, the curtailed power allocated to each of the wind-solar units at the new round of time t is formulated as: ， Among them, is the number of fans that meet the conditions, is the number of photovoltaics that meet the conditions; Allocating the operating values of the wind turbines that meet the preset conditions, wherein the operating values of the wind turbines that meet the preset conditions satisfy: ； Allocating the operating values of the photovoltaics that meet the preset conditions, wherein the operating values of the photovoltaics that meet the preset conditions satisfy: ； Statistically calculate the unallocated curtailment power of the wind turbines and photovoltaics that meet the preset conditions at time t , where the satisfies: ， 。 9. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, the method described in any one of claims 1-7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the method described in any one of claims 1-7 is implemented.

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