A method, apparatus, device and medium for controlling active power

Abstract

The application discloses a kind of active power control method, device, equipment and medium, comprising: obtaining preset base constraint condition, and with the output change of active power source in new energy base is reduced as optimization target, determine base objective function;The base constraint condition is based on the optimization of the base objective function, determine the first active power prediction value of new energy equipment in active power source and the target active power of thermal power generating set;The first active power prediction value is based on the optimization of preset cluster constraint condition, determine the second active power of new energy equipment cluster;The second active power is based on the optimization of preset station constraint condition, determine the target active power of new energy equipment station.This scheme carries out active power optimization of base level, cluster level, station level by hierarchical method, realizes the coordinated optimization configuration of station level.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system operation and control, and particularly relates to an active power control method, device, equipment and medium. BACKGROUND

[0002] Under the background of constructing a new power system mainly based on new energy, newly-built new energy stations are characterized by large installed capacity and regional cluster grid connection, and a new development mode of new energy bases sending power out through extra-high voltage power grids has gradually formed in the Three North regions. New energy bases contain multiple power sources and may have multiple combinations, including wind storage, light storage, wind-light storage, and thermal power.

[0003] In the prior art, for new energy power generation equipment, the active power is usually optimized and controlled according to short-term and ultra-short-term prediction time scales of day-ahead and day-ahead. However, due to the randomness and time sequence characteristics of wind speed and light, the active power output of wind power and photovoltaic grid connection has strong uncertainty in a short time scale and has an anti-peaking characteristic in a long time scale. At present, the installed capacity of wind power equipment and photovoltaic equipment in large-scale new energy bases is relatively large, so the existing active power regulation method is not suitable for large-scale new energy bases and it is difficult to ensure the stability of regional power grids. SUMMARY

[0004] Therefore, the embodiments of the present application provide an active power control method, device, equipment and medium to provide a method for regulating active power in a large-scale new energy base and ensure the stability of power grid operation.

[0005] According to a first aspect, the embodiments of the present application provide an active power control method, comprising:

[0006] obtaining a preset base constraint condition and determining a base target function with the optimization target of reducing the output change of active power sources in the new energy base;

[0007] optimizing the base target function based on the base constraint condition to determine a first active power prediction value of new energy equipment in the active power source and a target active power of thermal power units;

[0008] optimizing the first active power prediction value based on a preset cluster constraint condition to determine a second active power of a new energy equipment cluster;

[0009] optimizing the second active power based on a preset station constraint condition to determine a target active power of a new energy equipment station.

[0010] The method for controlling active power provided by the embodiment of the application optimizes the base target function by presetting base constraint conditions, so as to obtain the first active power prediction value of the new energy equipment and the target active power of the thermal power unit. Considering the nature of the new energy equipment, the first active power prediction value is further optimized to obtain the second active power of the new energy equipment cluster in the base, and the second active power is further optimized to obtain the target active power of the new energy equipment station. The method optimizes the active power at the base level, cluster level and station level by the hierarchical method, and realizes the coordinated and optimized configuration at the station level.

[0011] In some embodiments, the base target function is determined by taking the reduction of the output change of the active power source in the new energy base as the optimization target, and includes:

[0012] The total capacity of the active power source cluster is obtained.

[0013] The base target function is constructed based on the ratio of the total power of the active power source cluster to the total capacity and a preset first period.

[0014] In some embodiments, the base target function is determined according to the following formula:

[0015]

[0016] Wherein, N w represents the number of active power source clusters, P w,t represents the total active power output by the active power source in t preset first periods, P w_s,t represents the active power output by the energy storage equipment in t preset first periods, S w represents the total capacity of the active power source, S w_s represents the total capacity of the energy storage equipment, λ1represents the penalty function of the energy storage output in t preset first periods, T r represents the total reporting time, T th represents the first period.

[0017] In some embodiments, the first active power prediction value is optimized based on preset cluster constraint conditions to determine the second active power of the new energy equipment cluster, and includes:

[0018] The difference between the first active power prediction value and the second active power of the new energy equipment cluster is calculated.

[0019] The ratio of the difference to the total capacity of the new energy equipment cluster is calculated, and the cluster target function is determined by taking the ratio as the optimization target.

[0020] The cluster target function is optimized based on a preset second period and the preset cluster constraint conditions to determine the second active power of the new energy equipment cluster.

[0021] In some embodiments, the cluster objective function is determined according to the following formula:

[0022]

[0023] wherein P i,ref1 represents the first active power prediction value, P i,t1 represents the second active power of the new energy equipment cluster after t1 preset second periods, P i_pre,t1 represents the predicted maximum available of the new energy equipment cluster after t1 preset second periods, S i represents the total capacity of the new energy equipment cluster i, λ2 represents the penalty function of the new energy curtailment after t2 preset second periods, T l represents the preset second period, T th represents the preset first period, N s represents the number of new energy equipment clusters.

[0024] In some embodiments, the second active power is optimized based on the preset station constraint condition to determine the target active power of the new energy equipment station, comprising:

[0025] calculating the difference between the target active power of the new energy equipment station and the total active power of the new energy equipment;

[0026] calculating the ratio of the difference to the total capacity of each new energy equipment, and taking the ratio as the optimization target to determine the equipment objective function;

[0027] optimizing the equipment objective function based on a preset third period and a preset constraint condition to determine the active power of the new energy equipment, the new energy equipment including wind power equipment, photovoltaic equipment, and energy storage equipment.

[0028] In some embodiments, the equipment objective function is determined according to the following formula:

[0029]

[0030] wherein P k,ref2 represents the second active power, P k,t2 represents the target active power output by the new energy equipment station after t2 preset third periods, P k_pre,t2 represents the predicted maximum available of the new energy equipment station after t2 preset third periods, P k_storage,t2 represents the active power output by the energy storage equipment station after t2 preset third periods, S krepresents the total capacity of the new energy equipment, λ3 represents the penalty function of new energy curtailment after t3 preset third periods, λ4 represents the penalty function of energy storage output after t3 preset third periods, T l represents a preset second period, T s represents a preset third period, N f represents the number of new energy equipment stations.

[0031] According to the second aspect, an embodiment of the present application provides a device for controlling active power, which comprises:

[0032] a condition obtaining module, configured to obtain preset base constraint conditions, and determine a base target function with the optimization target of reducing the output change of active power sources in a new energy base;

[0033] a first power determining module, configured to optimize the base target function based on the base constraint conditions, and determine a first active power prediction value of new energy equipment and a target active power of thermal power generating units in the active power sources;

[0034] a first optimization module, configured to optimize the first active power prediction value based on preset cluster constraint conditions, and determine a second active power of a new energy equipment cluster;

[0035] a second optimization module, configured to optimize the second active power based on preset station constraint conditions, and determine a target active power of a new energy equipment station.

[0036] According to the third aspect, an embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory and the processor are in communication connection with each other, the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the method for controlling active power in the first aspect or any one of the embodiments of the first aspect.

[0037] According to the fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make the computer execute the method for controlling active power in the first aspect or any one of the embodiments of the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0039] Figure 1 is a flowchart of a new energy base active power optimization method according to an embodiment of the present application;

[0040] Figure 2 is a structural block diagram of a new energy base active power optimization device according to an embodiment of the present application;

[0041] Figure 3 is a hardware structure schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0042] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in a clear and complete manner with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0043] Most of the prior art centers only perform active power optimization control on new energy equipment in a new energy equipment station, and the involved equipment is single, and how to perform active power optimization when multiple power sources are involved in a large-scale new energy base scenario is not considered. The present scheme considers the characteristics of each active power source of new energy, performs large-scale optimization on new energy equipment from different time scales and scales, and realizes active power distribution at the station level of the new energy equipment station. See the following embodiments for details.

[0044] According to an embodiment of the present application, a control method for active power is provided. It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0045] In the present embodiment, a control method for active power is provided, Figure 1 is a flowchart of a control method for active power according to an embodiment of the present application, as Figure 1 shown, the flowchart includes the following steps:

[0046] S11, a preset base constraint condition is obtained, and a base target function is determined with the optimization target of reducing the output change of active power sources in the new energy base.

[0047] The base constraint condition is set for the active power optimization distribution of various active power sources in the new energy base, and the base constraint condition can be set according to the operating parameters, voltage upper and lower limit values, power upper and lower limit values and the like of each active power source. The active power sources in the new energy base can include thermal power, new energy equipment and the like, and the new energy equipment includes wind power equipment, photovoltaic equipment, energy storage equipment and the like. The new energy base includes a plurality of active power source clusters, and the active power source cluster can include a plurality of active power source stations, wherein one active power source cluster or station can include one or more than one active power source, and the specific combination of each device is not limited here. First, a coordinated optimization control model of the active power source, i.e., a base target function, is established. Specifically, a long-time-scale thermal power-new energy coordinated optimization control model can be constructed, and the long-time scale can be hourly. The day-ahead, intra-day wind and light power prediction, wind and light complementary characteristics and the adjustable output size of the thermal power unit are comprehensively considered to construct the base target function for the active power distribution of each active power source. Since the active power of the energy storage equipment in the new energy equipment also needs to be considered, a penalty function for the energy storage output can be added to the base target function.

[0048] S12, optimizing the base target function based on the base constraint condition to determine the first active power prediction value of the new energy equipment in the active power source and the target active power of the thermal power unit.

[0049] The base target function is optimized according to the base constraint condition to obtain the first active power prediction value of all new energy equipment in the base and the target active power of the thermal power unit under the condition that the base target function takes the minimum value, and the active power of the thermal power unit does not need to be optimized again subsequently.

[0050] Since the base target function in this step is set in a long-time scale, and since the wind and light complementary characteristics need to be obtained through a certain amount of historical data accumulation, the uncertainty of the wind and light output in the long-time scale is high, and the first active power prediction value needs to be further optimized. The new energy base includes a new energy equipment cluster, and the new energy equipment cluster includes a wind power equipment cluster, a photovoltaic equipment cluster, an energy storage equipment cluster and the like.

[0051] S13, optimizing the first active power prediction value based on a preset cluster constraint condition to determine the second active power of the new energy equipment cluster.

[0052] In this step, the first active power prediction value of the new energy equipment obtained in S12 is optimized, and the first active power prediction value is distributed to each new energy equipment cluster.

[0053] Specifically, the first active power prediction value can be optimized by establishing an objective function, the first active power prediction value is taken as an input of the objective function, and a second active power of a new energy equipment cluster is output, the new energy equipment cluster can include a wind power equipment cluster, a photovoltaic equipment cluster and an energy storage equipment cluster.

[0054] In the power optimization distribution process of the present step, a minute-level calculation period can be used in consideration of the nature of the new energy equipment, for example, 15 minutes can be set.

[0055] S14, optimizing the second active power based on a preset field station constraint condition to determine a target active power of a new energy equipment field station.

[0056] The new energy equipment cluster is composed of new energy equipment field stations, and the second active power is distributed to the new energy equipment field stations to obtain the target active power of the new energy equipment field stations.

[0057] The active power control method provided by the embodiment of the present application optimizes the base target function based on the preset base constraint condition, so as to obtain the first active power prediction value of the new energy equipment and the target active power of the thermal power unit. Considering the nature of the new energy equipment, the first active power prediction value is further optimized to obtain the second active power of the new energy equipment cluster in the base, and the second active power is further optimized to obtain the target active power of the new energy equipment field station. The present scheme realizes the coordinated and optimized allocation of the field station level by using the hierarchical method to optimize the active power of the base level, the cluster level and the field station level.

[0058] In some embodiments, Figure 1 S12 in the above formula includes:

[0059] S21, obtaining a total capacity of an active power source cluster;

[0060] S22, constructing a base target function based on a ratio of total power to total capacity of the active power source cluster and a preset first period.

[0061] The total capacity of the active power source is determined according to the actual power source in the new energy base, the preset first period is set to be a hour level in the present embodiment, for example, one hour. The change of the output of the new energy base is taken as the coordinated optimization control target, and a penalty function of the energy storage output is added.

[0062] In some embodiments, the base target function is determined according to the following formula:

[0063]

[0064] Wherein, N w represents the number of the active power source cluster, P w,tP represents the total active power output by the active power source in t preset first periods w_s,t S represents the active power output by the energy storage device in t preset first periods w S represents the total capacity of the active power source w_s S represents the total capacity of the energy storage device, and T represents a penalty function of the energy storage output in t preset first periods r T represents the total reporting duration th T represents the first period.

[0065] In this embodiment, the step adopts a long-time-scale prediction period, T r , and T th may be 4 hours and 1 hour respectively. The total reporting duration represents the total time span, that is, the result is reported once every 4 hours, and the prediction is performed once every 1 hour, and the prediction is performed four times in the total reporting duration.

[0066] In some embodiments, the preset base constraint condition is determined according to the following formula:

[0067]

[0068] P represents the total active power output by the active power source in t preset first periods w,t P represents the total active power output by the active power source in t preset first periods w_wind,t P represents the total active power output by the active power source in t preset first periods w_PV,t P represents the total active power output by the active power source in t preset first periods w_th,t P represents the first active power prediction value of the wind power device and the photovoltaic device in the active power source in t preset first periods, and P represents the target active power of the thermal power unit w_s,t S represents the active power output by the energy storage device in t preset first periods w_th,max P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_th,min P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_th,max P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_th,min P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_s,max P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_s,min P represents the upper limit value of the active power output by the thermal power unit, and P represents the lower limit value of the active power output by the thermal power unit w_s,t SOC represents the SOC prediction value of the energy storage device in the t preset first period w_s,max SOC represents the SOC prediction value of the energy storage device in the t preset first period w_s,min SOC represents the upper limit value of the SOC of the energy storage device, and SOC represents the lower limit value of the SOC of the energy storage device.

[0069] In some embodiments, Figure 1 S13 in the formula (1) includes the following steps:

[0070] S31, calculating the difference between the first active power prediction value and the second active power of the new energy device cluster.

[0071] S32, calculate a ratio of the difference value to a total capacity of the new energy device cluster, and determine a cluster target function with the ratio as an optimization target.

[0072] In some embodiments, the station target function is determined according to the following formula:

[0073]

[0074] wherein P i,ref1 represents the first active power prediction value, P i,t1 represents the second active power of the new energy device cluster in t1 preset second periods, P i_pre,t1 represents the predicted maximum available power of the new energy device cluster in t1 preset second periods, S i represents the total capacity of the new energy device cluster i, and λ2 represents a penalty function of new energy curtailment in t2 preset second periods, T l represents the preset second period, T th represents the preset first period, N s represents the number of new energy device clusters.

[0075] In this embodiment, the preset second period is minute level, and can be set to 15 minutes, and the specific duration is not limited.

[0076] S33, optimize the cluster target function based on the preset second period and the preset cluster constraint condition, and determine the second active power of the new energy device cluster.

[0077] In some embodiments, the preset cluster constraint condition comprises:

[0078]

[0079] wherein P i,t1 represents the second active power output by the new energy device cluster i in t1 preset second periods, P i_wind,t1 , P i_PV,t1 , P i_storage,t1 respectively represent the second active power of the wind power device cluster, the photovoltaic device cluster and the energy storage device cluster in the new energy device cluster i in t1 preset second periods, ΔP min_wind , ΔP max_wind respectively represent upper and lower limit values of the wind power device station output active power change amount, ΔP min_PV , ΔP max_PV respectively represent upper and lower limit values of the photovoltaic device station output active power change amount, ΔP min_storage , ΔP max_storage respectively represent upper and lower limit values of the energy storage device output active power change amount.

[0080] In some embodiments, Figure 1 The method further includes the following steps:

[0081] S41, calculating a difference between a target active power of a new energy equipment station and a total active power of the new energy equipment.

[0082] S42, calculating a ratio of the difference to a total capacity of each new energy equipment, and determining an equipment objective function with the ratio as an optimization objective.

[0083] In some embodiments, the equipment objective function is determined according to the following formula:

[0084]

[0085] wherein P k,ref2 represents a second active power, P k,t2 represents a target active power output by the new energy equipment station in t2 preset third periods, P k_pre,t2 represents a predicted maximum active power of the new energy equipment station in t2 preset third periods, P k_storage,t2 represents an active power output by the energy storage equipment station in t2 preset third periods, S k represents a total capacity of the new energy equipment, λ3 represents a penalty function of new energy curtailment in t3 preset third periods, λ4 represents a penalty function of energy storage output in t3 preset third periods, T l represents a preset second period, T s represents a preset third period, N f represents a number of new energy equipment stations.

[0086] S43, optimizing the equipment objective function based on preset third periods and preset constraint conditions to determine an active power of the new energy equipment, the new energy equipment including wind power equipment, photovoltaic equipment, and energy storage equipment.

[0087] In some embodiments, the preset constraint conditions include:

[0088]

[0089] wherein P k,t2 represents a target active power output by the new energy equipment station k in t2 preset third periods, P k_wind,t2 , P k_PV,t2 , P k_storage,t2 respectively represent target active powers of the wind power equipment station, the photovoltaic equipment station, and the energy storage equipment station in t2 preset third periods, ΔP min_wind , ΔP max_wind respectively represent upper and lower limit values of the wind power equipment output active power variation, ΔP min_PV , ΔPmax_PV These represent the upper and lower limits of the change in active power output of the photovoltaic equipment, ΔP and ΔP, respectively. min_storage ΔP max_storage These represent the upper and lower limits of the change in the active power output of the energy storage device, respectively.

[0090] The active power control method provided by this invention takes into account that the adjustment time of thermal power units is much slower than that of wind, solar, and energy storage units, and the adjustment accuracy takes a long time. Therefore, a long-term base objective function is established to output the target active power of thermal power units. The first active power prediction value of the new energy equipment cluster is then optimized a second time, with a prediction period of minutes, to obtain the target active power of each new energy power station. Furthermore, a method for adjusting the active power of new energy equipment in the power station is proposed to achieve coordinated and optimized configuration of active power from different power sources. This method has high feasibility and economic efficiency in practice, and to a certain extent, provides a guarantee for the stability of the regional power grid.

[0091] This embodiment also provides an active power control device for implementing the above embodiments and implementation methods; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0092] This embodiment provides an active power control device, including:

[0093] The condition acquisition module is used to acquire preset base constraints and determine the base objective function with the optimization objective of reducing the output variation of active power sources in the new energy base;

[0094] The first power determination module is used to optimize the objective function of the base based on the base constraints, and determine the first active power prediction value of the new energy equipment in the active power source and the target active power of the thermal power unit.

[0095] The first optimization module is used to optimize the first active power prediction value based on preset cluster constraints to determine the second active power of the new energy equipment cluster.

[0096] The second optimization module is used to optimize the second active power based on preset station constraints to determine the target active power of the new energy equipment station.

[0097] In this embodiment, the active power control device is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0098] Further function description of each module is the same as the above corresponding embodiment, and will not be repeated here.

[0099] The embodiment of the present application also provides an electronic device, which has the above Figure 2 active power control device.

[0100] Please refer to Figure 3 , Figure 3 is a structural schematic diagram of an electronic device provided by an optional embodiment of the present application, as Figure 3 shown, the electronic device can include: at least one processor 601, for example, a CPU (Central Processing Unit, central processor), at least one communication interface 603, a memory 604, and at least one communication bus 602. Wherein, the communication bus 602 is used to realize the connection communication between the components. Wherein, the communication interface 603 can include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 603 can also include a standard wired interface, a wireless interface. The memory 604 can be a high-speed RAM memory (Random Access Memory, volatile random access memory), and can also be a non-volatile memory, for example, at least one disk memory. The memory 604 can also be at least one storage device located away from the aforementioned processor 601. Wherein the processor 601 can combine Figure 2 the device described in the description, the memory 604 stores an application program, and the processor 601 calls the program code stored in the memory 604 for executing any method step described above.

[0101] Wherein, the communication bus 602 can be a peripheral component interconnect (peripheral component interconnect, PCI for short) bus or an extended industry standard architecture (extended industry standard architecture, EISA for short) bus, etc. The communication bus 602 can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, Figure 3 only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0102] The memory 604 can include a volatile memory, such as a random-access memory (RAM), and / or can include a non-volatile memory, such as a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD). The memory 604 can also include a combination of the above-mentioned types of memories.

[0103] The processor 601 can be a central processing unit (CPU), a network processor (NP), or a combination of the CPU and the NP.

[0104] The processor 601 can further include a hardware chip. The hardware chip can be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD can be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0105] Optionally, the memory 604 is further configured to store program instructions. The processor 601 can invoke the program instructions to implement the method for controlling active power as shown in the embodiments of the present application.

[0106] The embodiment of the present application also provides a non-transitory computer storage medium, the computer storage medium stores computer executable instructions, the computer executable instructions can execute the active power control method in any method embodiment described above. Wherein, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid state drive (SSD) and the like; the storage medium can also include a combination of the above types of memories.

[0107] Although the embodiments of the present application are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A method of controlling active power, characterized by, The method comprises the following steps: acquiring preset base constraints, and determining a base target function with the optimization objective of reducing the output change of active power sources in a new energy base; optimizing the base target function based on the base constraints to determine a first active power prediction value of new energy equipment in the active power sources and a target active power of thermal power generating units; optimizing the first active power prediction value based on preset cluster constraints to determine a second active power of a new energy equipment cluster; optimizing the second active power based on preset station constraints to determine a target active power of a new energy equipment station; determining the base target function with the optimization objective of reducing the output change of active power sources in the new energy base comprises the following steps: acquiring the total capacity of an active power source cluster; wherein, N w represents the number of active power clusters, P w,t represents the total active power output by the active power sources over t preset first periods, P w_s,t represents the active power output by the energy storage devices over t preset first periods, S w represents the total capacity of the active power sources, S w_s represents the total capacity of the energy storage devices, constructing the base target function based on the ratio of the total power of the active power source cluster to the total capacity and a preset first period; 1represents a penalty function of the energy storage output over t preset first periods, T r represents the total reporting duration, T th represents the preset first period.

2. The method of claim 1, wherein, the base target function is determined according to the following formula: the method for optimizing the first active power prediction value based on the preset cluster constraints to determine the second active power of the new energy equipment cluster comprises the following steps: calculating the difference between the first active power prediction value and the second active power of the new energy equipment cluster; calculating the ratio of the difference to the total capacity of the new energy equipment cluster, and determining a cluster target function with the ratio as the optimization objective; 3. The method of claim 2, wherein, optimizing the cluster target function based on a preset second period and the preset cluster constraints to determine the second active power of the new energy equipment cluster. wherein, P i,ref1 represents the first active power prediction value, P i,t1 represents the second active power of the new energy equipment cluster after t1 preset second periods, P i_pre,t1 represents the predicted maximum available of the new energy equipment cluster after t1 preset second periods, S i represents the total capacity of the new energy equipment cluster i, the cluster target function is determined according to the following formula: 2 represents the penalty function of new energy curtailment after t2 preset second periods, T l represents the preset second period, T th represents the preset first period, N s represents the number of new energy equipment clusters.

4. The method of claim 2, wherein, the method for optimizing the second active power based on the preset station constraints to determine the target active power of the new energy equipment station comprises the following steps: calculating the difference between the target active power of the new energy equipment station and the total active power of the new energy equipment; calculating the ratio of the difference to the total capacity of each new energy equipment, and determining an equipment target function with the ratio as the optimization objective; optimizing the equipment target function based on a preset third period and the preset constraints to determine the active power of the new energy equipment, wherein the new energy equipment comprises wind power equipment, photovoltaic equipment and energy storage equipment.

5. The method of claim 4, wherein, the equipment target function is determined according to the following formula: wherein, P k,ref2 P2 represents the second active power, P k,t2 P3 represents the target active power output by the new energy equipment station in t2 preset third periods, P k_pre,t2 P4 represents the predicted maximum available of the new energy equipment station in t2 preset third periods, P k_storage,t2 P5 represents the active power output by the energy storage equipment station in t2 preset third periods, S k P6 represents the total capacity of the new energy equipment, the equipment target function is determined according to the following formula: 3 represents a penalty function of new energy curtailment in t3 preset third periods, The method comprises the following steps: 4 represents a penalty function of energy storage output in t3 preset third periods, T l t1 represents a preset second period, T s t2 represents a preset third period, N f n represents the number of new energy equipment stations.

6. A device for controlling active power, characterized in that a condition acquisition module is configured to acquire preset base constraints, and determine a base target function with the optimization objective of reducing the output change of active power sources in a new energy base; a first power determination module is configured to optimize the base target function based on the base constraints to determine a first active power prediction value of new energy equipment in the active power sources and a target active power of thermal power generating units; a first optimization module is configured to optimize the first active power prediction value based on preset cluster constraints to determine a second active power of a new energy equipment cluster; a second optimization module is configured to optimize the second active power based on preset station constraints to determine a target active power of a new energy equipment station. ​ The base target function is determined by taking the change in the output of the active power source in the new energy base as an optimization target, including: obtaining total capacity of the active power source cluster; constructing the base target function based on the ratio of total power of the active power source cluster to the total capacity and a preset first period; The base target function is determined according to the following formula: wherein, N w represents the number of active power clusters, P w,t represents the total active power output by the active power sources over t preset first periods, P w_s,t represents the active power output by the energy storage devices over t preset first periods, S w represents the total capacity of the active power sources, S w_s represents the total capacity of the energy storage devices, Including: 1 represents a penalty function of the energy storage output over t preset first periods, T r represents the total reporting duration, T th represents the preset first period.

7. An electronic device, comprising: A memory and a processor, which are in communication connection with each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the active power control method in any one of claims 1-5. The computer readable storage medium stores computer instructions for causing a computer to execute the active power control method in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, ​

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