Two-stage pumped storage unit optimization adjustment method, system and equipment

Abstract

This invention discloses a method, system, and equipment for optimizing and adjusting a two-stage pumped storage unit. The method includes, according to... D day T The basic data of the operation before the time point is obtained. T +4 to T +24-hour short-term forecast value of new energy; according to the above D day T Basic data before the time, T +4 to T +24-hour short-term forecast of new energy sources, to obtain a certain moment t The target output of thermal power plants, based on a certain moment t Determine peak and off-peak periods for the target output of thermal power plants; construct a system that considers... n A dynamic programming optimization algorithm is used to optimize the output of thermal power units in each pumping-storage conversion interval, resulting in the first-stage optimized output of pumped storage units. When the water level reaches its upper limit, the pumped storage units replace the hydropower units in frequency regulation capacity, resulting in the second-stage optimized output of pumped storage units. This invention takes into account both frequency regulation and peak shaving functions, and can improve the problem of the difficulty in effectively executing the day-ahead plan of pumped storage units under the current scenario of continuous large-scale renewable energy generation.

Description

Technical Field

[0001] This invention belongs to the field of large power grid dispatching and operation, and specifically relates to a method, system and equipment for optimizing and adjusting two-stage pumped storage units. Background Technology

[0002] Pumped storage units, as technologically mature and cost-effective large-scale energy storage devices in the power grid, are key supporting equipment for ensuring the safe and stable operation of the power system and the transformation of the energy structure. In terms of power balance regulation, during periods of low grid load, the units operate in motor mode, consuming surplus grid energy to pump water from the lower reservoir to the upper reservoir, realizing the conversion and storage of electrical energy into gravitational potential energy. During periods of high load, the units switch to generator mode, using water released from the upper reservoir to drive turbine generators to generate electricity, supplementing the power grid and effectively smoothing load fluctuations and alleviating the spatial and temporal mismatch between power supply and demand. In terms of grid frequency regulation and peak shaving, thanks to their rapid start-up and shutdown speeds and flexible operating mode switching, pumped storage units can quickly respond to grid frequency deviations, maintaining the system frequency within the rated range by adjusting output, thus improving the grid's frequency regulation capability. Simultaneously, they can accurately track load changes according to dispatch instructions, undertaking deep peak shaving tasks for the grid, providing stable operating conditions for baseload power sources such as thermal power units and nuclear power units, and reducing wind and solar curtailment rates.

[0003] The pumped-storage hydroelectric power units in the Northeast China power grid are relatively large and play a crucial role in grid frequency regulation and peak shaving. However, due to the high proportion of renewable energy in the Northeast grid, coupled with the uncontrollable, volatile, and unpredictable nature of renewable energy power generation leading to significant short-term intraday power forecasting errors, the day-ahead power projection curves of pumped-storage units are often difficult to execute effectively within a single day. Furthermore, under the current model, when renewable energy generation is high and the reservoir capacity of pumped-storage power plants reaches its limit, pumped-storage units can only be passively shut down, failing to fully utilize their frequency regulation and peak shaving functions and hindering the absorption of renewable energy. Summary of the Invention

[0004] The purpose of this invention is to provide a method, system, and equipment for optimizing and adjusting two-stage pumped storage units, which also takes into account frequency regulation and peak shaving functions, and can improve the problem that pumped storage units are difficult to effectively execute day-ahead plans under the current scenario of continuous large-scale generation of new energy.

[0005] To achieve the above objectives, the solution of the present invention is:

[0006] A method for optimizing and adjusting a two-stage pumped storage unit includes,

[0007] according to D day T The basic data of the operation before the time point is obtained. T +4 to T +24-hour short-term forecast of new energy sources; among which... DFor the day the power grid actually operates, T This refers to a specific integer moment on the day the power grid is actually in operation.

[0008] According to the above D day T Basic data before the time, T +4 to T +24-hour short-term forecast of new energy sources, to obtain a certain moment t thermal power target output F ( t According to a certain moment t thermal power target output F ( t Determine peak and off-peak periods;

[0009] Define one adjacent peak period and one adjacent trough period as one pumping-storage unit pumping-out switching interval. M n Constructing a set of peak and off-peak power generation intervals , t n For the first n A single extraction and conversion interval period F n For the first n Thermal power output during each extraction and conversion interval period S t ( n ) is the first n Peak power generation of thermal power plants during peak periods L t ( n ) is the first n The maximum peak power output of thermal power during peak periods S d ( n ) is the first n Off-peak electricity volume of thermal power plants during off-peak periods L d ( n ) is the first n The lowest off-peak electricity for thermal power during off-peak periods; construction considerations n The output of thermal power units in each extraction and conversion zone F n ( t The dynamic programming optimization algorithm was used to solve the problem and obtain the output of the first pumped storage unit. W w ( t );

[0010] When the water level reaches its upper limit, the pumped storage unit will replace the hydroelectric generator unit using frequency regulation capacity to obtain the output of the second pumped storage unit. ;

[0011] The dynamic programming optimization algorithm is as follows:

[0012]

[0013] In the formula, M 1 represents the first set of peak and trough intervals for thermal power generation. W t (0) represents the initial pumpable reservoir capacity. W d (0) represents the initial power generation capacity of the reservoir; f 0 is the basic thermal power output allocation algorithm. f 1 represents the peak thermal power redistribution algorithm;

[0014] The basic thermal power output allocation algorithm f 0 includes, based on off-peak hours for thermal power generation T 低 Pumping demand electricity P n and peak hours of thermal power T 尖 Pumpable power P a The amount of electricity used to pump water was obtained. This leads to the optimized target output of thermal power plants. f 0;

[0015] The peak thermal power redistribution algorithm f 1. Including, based on off-peak periods of thermal power generation T 低 Pumping demand electricity P n and peak hours of thermal power T 尖 Pumpable power P a The amount of electricity used to pump water was obtained. This leads to the optimized target output of thermal power plants. f 1.

[0016] Among them, according to D day T The basic data of the operation before the time point is obtained. T +4 to T +24-hour short-term forecast values ​​for new energy sources, including,

[0017] D day T Before a certain time, acquire basic operational data; wherein, the basic data includes, T to T +4-hour ultra-short-term forecast value for new energy D gc ,T to T new energy short-term prediction value for +24 hours D g , T to T load short-term prediction value for +24 hours D a , T to T nuclear power plant output value for +24 hours D b , T to T cross-region DC planned value for +24 hours D c , T to T small thermal power plant output value for +24 hours D e , T to T hydropower plant output value for +24 hours D d , T to T system frequency modulation capacity value for +24 hours D f ; the sampling interval of the basic data is 15 minutes;

[0018] based on the basic data, obtaining T new energy short-term prediction value for +4 to T +24 hours,

[0019]

[0020] in the formula, t is a certain time on the actual operation day of the power grid, and the time interval is 15 minutes; D gx is the corrected T new energy short-term prediction value for +4 to T +24 hours.

[0021] wherein, according to the basic data before the D day T time, T new energy short-term prediction value for +4 to T +24 hours, the thermal power target output at a certain time t is obtained, F ( t ), including,

[0022] the thermal power target output at a certain time t is calculated according to the following formula, F ( t ),

[0023]

[0024] In the formula, D a ( t (for a certain moment) t Short-term load forecasts D b ( t (for a certain moment) t The planned output of nuclear power plants, D c ( t (for a certain moment) t The planned value of cross-regional DC transmission, D d ( t (for a certain moment) t The planned output value of hydropower. D e ( t (for a certain moment) t The planned output value of small thermal power plants, D f ( t (for a certain moment) t The system frequency regulation capacity value, D g ( t )for T to T At some point within +4 hours t Short-term forecasts for new energy sources D gx ( t )for T +4 to T At some point within 24 hours t Short-term forecasts for new energy sources.

[0025] Among them, according to a certain moment t thermal power target output F ( t Determine peak and off-peak hours, including:

[0026] At a certain moment t thermal power target output F ( t (and the minimum generating capacity of thermal power) F 2( t )Compare;

[0027] judge F ( t )> F 2( t )hour, tThe time intervals are the peak times for thermal power generation, and the time intervals consisting of consecutive peak times for thermal power generation are called peak periods. T 尖 ;

[0028] judge F ( t )< F 2( t )hour, t The time at which thermal power generation is at its lowest point is called the off-peak time. A period consisting of consecutive off-peak times of thermal power generation is called the off-peak period. T 低 .

[0029] Among them, the basic thermal power output allocation algorithm f The specific content of 0 includes,

[0030] Calculate the off-peak period of thermal power T 低 Pumping demand This allows us to obtain the electricity required for pumping water. ,in, W max This is the maximum pumping power of the pumped storage unit. W This is the total reservoir capacity of the pumped storage units. g For pumped storage units, the reservoir capacity-pumping power conversion function is used.

[0031] Calculate peak periods for thermal power generation T 尖 Pumpable power ;in, delta This refers to the average energy conversion efficiency of pumped storage units. W t This refers to the pumpable reservoir capacity of the pumped storage unit;

[0032] Calculate pumping power and according to Solving for x The target output of thermal power is the intermediate-state thermal power output. ;

[0033] The peak thermal power redistribution algorithm f The specific content of 1 includes,

[0034] Calculate the off-peak period of thermal power T 低 Pumping demand This allows us to obtain the electricity required for pumping water. ;

[0035] Calculate peak periods for thermal power generation T 尖 Pumping capacity Thus, the pumpable electricity is obtained. ;

[0036] Calculate pumping power Another Solving for x The target output of thermal power is the intermediate-state thermal power output. .

[0037] Specifically, when the water level reaches its upper limit, the pumped-storage unit will replace the hydroelectric unit using frequency regulation capacity to obtain the output of the second pumped-storage unit. ,include,

[0038] When the water level is determined to have reached its upper limit, pumped-storage units replace hydroelectric units in frequency regulation capacity, thus incorporating more renewable energy sources. S 'for,

[0039]

[0040] The output of the second pumped storage unit for:

[0041]

[0042] In the formula, T 抽 for T 抽蓄 Pumping periods during the time period, T 发 for T 抽蓄 During the power generation period of the time period, T 抽 + T 发 = T 抽蓄 , T 抽蓄 This refers to the period when the pumped storage unit's reservoir capacity reaches its upper limit and the system's peak-shaving and power rationing measures have not been lifted.

[0043] A two-stage pumped storage unit optimization and adjustment system includes,

[0044] The module for obtaining short-term forecasts of new energy is configured to... D day T The basic data of the operation before the time point is obtained. T +4 to T +24-hour short-term forecast of new energy sources; among which... D For the day the power grid actually operates, T This refers to a specific integer moment on the day the power grid is actually in operation.

[0045] The time period segmentation module is configured to, based on the above... D day TBasic data before the time, T +4 to T +24-hour short-term forecast of new energy sources, to obtain a certain moment t thermal power target output F ( t According to a certain moment t thermal power target output F ( t Determine peak and off-peak periods;

[0046] The first optimization module is configured to define one adjacent peak period and one adjacent trough period as one pumping-storage unit pumping-storage conversion interval. M n Constructing a set of peak and off-peak power generation intervals , t n For the first n A single extraction and conversion interval period F n For the first n Thermal power output during each extraction and conversion interval period S t ( n ) is the first n Peak power generation of thermal power plants during peak periods L t ( n ) is the first n The maximum peak power output of thermal power during peak periods S d ( n ) is the first n Off-peak electricity volume of thermal power plants during off-peak periods L d ( n ) is the first n The lowest off-peak electricity for thermal power during off-peak periods; construction considerations n The output of thermal power units in each extraction and conversion zone F n ( t The dynamic programming optimization algorithm was used to solve the problem and obtain the output of the first pumped storage unit. W w ( t );as well as,

[0047] The second optimization module is configured to, when it determines that the water level has reached its upper limit, replace the hydroelectric generator unit with the frequency regulation capacity to obtain the output of the second pumped storage unit. ;

[0048] The dynamic programming optimization algorithm is as follows:

[0049]

[0050] In the formula, M 1 is the first peak valley interval set of thermal power, W t (0) is the initial state of the pumpable reservoir capacity, W d (0) is the initial state of the pumpable reservoir capacity; f 0 is a basic thermal power output distribution algorithm, f 1 is a peak thermal power redistribution algorithm;

[0051] The basic thermal power output distribution algorithm f 0 includes, according to the pumped water demand power of the thermal power valley period T 低 The pumped water demand power of the thermal power valley period P n And the pumped water power of the thermal power peak period T 尖 The pumped water power of the thermal power peak period P a , the pumped water power is obtained , and the optimized thermal power target output f 0 is obtained;

[0052] The peak thermal power redistribution algorithm f 1 includes, according to the pumped water demand power of the thermal power valley period T 低 The pumped water demand power of the thermal power valley period P n And the pumped water power of the thermal power peak period T 尖 The pumped water power of the thermal power peak period P a , the pumped water power is obtained , and the optimized thermal power target output f 1 is obtained.

[0053] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor; the processor executes the computer program to implement the steps of the two-stage pumped storage unit optimization adjustment method as described above.

[0054] A computer readable storage medium stores a computer program; the computer program is executed by a processor to implement the steps of the two-stage pumped storage unit optimization adjustment method as described above.

[0055] After the above scheme, the beneficial effects of the present application are: in the scenario of large new energy daily prediction error and continuous large new energy generation, the present application can fully play the peak regulation and frequency regulation role of pumped storage units through daily optimization of pumped storage unit curves, and promote new energy consumption. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 is a flowchart of the present application;

[0057] Figure 2 is the output optimization curve of pumped storage units under the scenario of continuous large-scale new energy generation. DETAILED DESCRIPTION

[0058] The technical solutions and beneficial effects of the present application will be described in detail below in combination with the drawings.

[0059] The two-stage pumped storage unit plan rolling adjustment optimization method proposed in the present application is mainly applied to the optimization scheduling of pumped storage units under the scenario of continuous large-scale new energy generation. In the first stage, when the power grid has the demand for pumped storage units to pump water to absorb new energy, the pumped storage units that have not pumped water should be operated to maximize the use of the pumpable reservoir capacity of pumped storage power stations. When there is a space for conventional power generation during the period of large-scale new energy generation, and it is estimated that new energy will be generated again in a few hours, the power grid needs to quickly pump water to lower the reservoir water level to free up the reservoir capacity as soon as possible to be ready for pumping water again and maximize the absorption of new energy. In the second stage, considering the multi-year regulation characteristics of the main reservoirs in the Northeast power grid, the water storage in the reservoir after the unit shutdown will not cause the rapid rise of the water level. At this time, only the water supply task units of conventional hydropower are retained, and the frequency modulation capacity of the power grid is borne by the pumped storage units. The frequency modulation capacity of the pumped storage units is determined according to the actual operation demand of the power grid. After the pumped storage units release a certain reservoir capacity during frequency modulation operation, they are converted again to pump water to absorb new energy.

[0060] Figure 1 is a flowchart of the present application, and the specific steps are as follows:

[0061] S1: D day T , obtain the basic data for operation, including: T to T +4 hours of new energy ultra-short-term prediction value D gc , T to T +24 hours of new energy short-term prediction value D g , T to T +24 hours of load short-term prediction value D a , T to T +24 hours of nuclear power plan output value D b , T to T +24 hours of cross-region DC plan valueD c 、 T to T +24 hours of small thermal power plan output value D e 、 T to T +24 hours of hydropower plan output value D d 、 T to T +24 hours of system frequency modulation capacity value D f , thermal power minimum generating capacity F 2; the sampling interval of the basic data is 15 minutes, D is the actual operation day of the power grid, T is a certain integer time on the actual operation day of the power grid;

[0062] S2: correction T +4 to T +24 hours of new energy short-term prediction value, the calculation formula is:

[0063]

[0064] In the formula, t is a certain time on the actual operation day of the power grid, and the time interval is 15 minutes; D gx is the corrected T +4 to T +24 hours of new energy short-term prediction value;

[0065] S3: D day T time, obtain the pumpable reservoir capacity of pumped storage units W t , the pumpable reservoir capacity of pumped storage units W d , the total reservoir capacity of pumped storage units W , the maximum pumpable power of pumped storage units W max , the average energy conversion rate of pumped storage units delta , the reservoir capacity-pumped power conversion function of pumped storage units g ;

[0066] S4: calculate the thermal power target output t at a certain time F ( t ), the calculation formula is:

[0067]

[0068] S5: Judgment F ( t )> F 2( t )hour, t The time intervals are the peak times for thermal power generation, and the time intervals consisting of consecutive peak times for thermal power generation are called peak periods. T 尖 , No. n Peak power generation during peak periods , No. n Maximum peak power of thermal power during peak periods ;

[0069] S6: Judgment F ( t )< F 2( t )hour, t The time at which thermal power generation is at its lowest point is called the off-peak time. A period consisting of consecutive off-peak times of thermal power generation is called the off-peak period. T 低 , No. n Off-peak electricity volume of thermal power during off-peak periods , No. n The lowest off-peak electricity for thermal power during off-peak periods ;

[0070] S7: The operation process is divided into two stages. In the first stage, one adjacent peak period and one trough period are defined as one pumping-storage unit pumping-storage conversion interval. M n Constructing a set of peak and off-peak power generation intervals , t n For the first n A single extraction and conversion interval period F n For the first n Thermal power output during the extraction and conversion period; establishing considerations n The output of thermal power units in each extraction and conversion zone F n ( t The dynamic programming optimization algorithm is used to optimize and solve the problem. The dynamic programming optimization algorithm is as follows:

[0071]

[0072] In the formula, M 1 represents the first set of peak and trough intervals for thermal power generation. W t (0) represents the initial pumpable reservoir capacity. W d (0) represents the initial power generation capacity of the reservoir. f 0 is the basic thermal power output allocation algorithm.f 1 is a peak thermal power redistribution algorithm;

[0073] the basic thermal power output distribution algorithm f 0 includes:

[0074] calculating the pumping demand of the thermal power valley period T 低 pumping demand , pumping demand power ;

[0075] calculating the pumpable capacity of the thermal power peak period T 尖 pumpable capacity , pumpable power ;

[0076] calculating the pumping power , in addition , the solution is x is the intermediate state thermal power output, the optimized thermal power target output .

[0077] the peak thermal power redistribution algorithm f 1 includes:

[0078] calculating the pumping demand of the thermal power valley period T 低 pumping demand , pumping demand power ;

[0079] calculating the pumpable capacity of the thermal power peak period T 尖 pumpable capacity , pumpable power ;

[0080] calculating the pumping power , in addition , the solution is x is the intermediate state thermal power output, the optimized thermal power target output .

[0081] S8: Calculate the pumped storage unit output after the first stage optimization ;

[0082] S9: In the second stage, the pumped storage unit replaces the conventional hydroelectric unit to use the frequency modulation capacity, and the additional new energy S ' is:

[0083]

[0084] calculating the pumped storage unit output after the second stage optimization is:

[0085]

[0086] In the formula, T 抽 is T 抽蓄 pumping period in the period, T 发 is T 抽蓄 power generation period in the period, T 抽 + T 发 = T 抽蓄 , T 抽蓄 is a period in which the upper limit of the pumped storage unit storage capacity is reached and the system peak shaving power limitation is not removed.

[0087] Figure 2 is a pumped storage unit optimization calling case under the condition that new energy continuously generates a lot on a certain day, the blue curve is a new energy peak shaving blocked curve, and the yellow curve is a pumped storage unit output curve after optimization, and from 2:30 to 16:00, the power grid continuously exists new energy peak shaving blocking. Among them, from 2:30 to 11:30, the first stage optimization method is adopted, and the principle of maximizing the use of the upper reservoir storage capacity of the pumped storage power station is adopted, and the pumped storage unit continuously runs in the pumping condition until the water level reaches the upper limit and cannot pump, and then stops. From 11:45 to 15:30, the second stage optimization method is adopted: among them, from 11:45 to 14, only the water supply task unit of the conventional hydropower is reserved, the output is at the lowest, the pumped storage unit replaces the conventional hydropower unit to run in the frequency modulation mode, and at the same time, part of the upper reservoir storage capacity is released by generating operation; from 14 to 15:30, it is predicted that the subsequent peak shaving power limitation is removed, the pumped storage unit is switched from the power generation condition to the pumping condition, and the pumped storage unit is used to consume new energy, and the conventional hydropower unit runs in the frequency modulation mode. From 16:00 to 18:00, the power grid has a power generation space, the pumped storage unit is used to drop the upper reservoir water level, and the pumped storage unit is switched from the pumping condition to the power generation condition, so as to leave enough upper reservoir storage capacity for the subsequent new energy generation period.

[0088] The embodiment of the application also provides a two-stage pumped storage unit optimization adjustment system, comprising,

[0089] The new energy short-term prediction value acquisition module is configured to obtain the new energy short-term prediction value from 4 to 24 hours before the operation basis data of the moment, wherein the sampling interval of the basis data is 15 minutes, D day T moment, the new energy short-term prediction value from 4 to 24 hours before the operation basis data of the moment, wherein the sampling interval of the basis data is 15 minutes, T T D is the actual operation day of the power grid, T ​​for an integer time on the actual operation day of the power grid;

[0090] The time period division module is configured to obtain the thermal power target output at the time according to the base data before the time, D day T , T +4 to T +24 hours of new energy short-term prediction value, obtain the thermal power target output at the time t , F determine the peak period and the valley period according to the thermal power target output at the time t . t F t .

[0091] The first optimization module is configured to obtain the first pumped storage unit output W w ( t ) in the pumping stage; and,

[0092] The second optimization module is configured to determine the second stage when the water level reaches the upper limit, replace the pumped storage unit with the hydroelectric unit to use the frequency modulation capacity, and obtain the second pumped storage unit output .

[0093] The embodiment of the present application also provides another computer device, which comprises a processor and a memory configured to store a computer program capable of running on the processor; wherein the processor is configured to run the computer program to execute the method steps in the foregoing embodiments.

[0094] In practical application, the processor comprises a field programmable gate array (FPGA), and the processor can be a central processing unit (CPU) or a digital signal processor (DSP). It can be understood that for different devices, the electronic device for realizing the function of the processor can also be other devices, and the embodiment of the present application is not limited in this regard.

[0095] ​​The above-mentioned memory can be a volatile memory (volatile memory), such as a random access memory (RAM, Random-Access Memory); or a non-volatile memory (non-volatile memory), such as a read-only memory (ROM, Read-Only Memory), a flash memory, a hard disk (HDD, Hard Disk Drive) or a solid state disk (SSD, Solid-State Drive); or a combination of the above-mentioned kinds of memories, and provides instructions and data to the processor.

[0096] In an exemplary embodiment, the present embodiment also provides a computer readable storage medium for storing a computer program.

[0097] Optionally, the computer readable storage medium can be applied to any one of the methods in the present embodiment, and the computer program causes the computer to execute the corresponding processes realized by the processor in each method of the present embodiment. For the sake of brevity, it will not be repeated here.

[0098] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as object-oriented programming language Java and interpreted scripting language JavaScript.

[0099] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system) and computer program product of the present embodiment. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of the flow and / or block in the flowchart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device that implements the functions specified in the flowchart and / or block diagram. Figure 1 The device for realizing the functions specified in one flow or multiple flows and / or blocks Figure 1 The device for realizing the functions specified in one flow or multiple flows and / or blocks

[0100] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the Figure 1 function specified in the flow or flows and / or blocks Figure 1 of the block or blocks.

[0101] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that are executed on the computer or other programmable apparatus provide steps for implementing the Figure 1 function specified in the flow or flows and / or blocks ​ of the block or blocks.

[0102] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments by those skilled in the art once they learn of the basic inventive concepts. Therefore, the appended claims are intended to cover all such additional variations and modifications as fall within the scope of the application.

[0103] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A two-stage pumped storage unit optimization adjustment method, characterized in that: Comprising, According to D day T the operation basis data before the time, obtain T +4 to T +24 hours of new energy short-term prediction value; wherein, D for the actual operation of the grid on the day, T for the actual operation of the grid on the day According to the above D day T , the operation basis data before the time point, T +4 to T +24 hours of new energy short-term prediction value, the thermal power target output t of a time point F ( t ), according to the thermal power target output t of a time point F ( t ) to determine the peak period and the valley period; Define one adjacent peak period and one adjacent trough period as one pumping-storage unit pumping-out switching interval. M n Constructing a set of peak and off-peak power generation intervals , t n For the first n A single extraction and conversion interval period For the first n Thermal power output during each extraction and conversion interval period S t ( n ) is the first n Peak power generation of thermal power plants during peak periods L t ( n ) is the first n The maximum peak power output of thermal power during peak periods S d ( n ) is the first n Off-peak electricity volume of thermal power plants during off-peak periods L d ( n ) is the first n The lowest off-peak electricity for thermal power during off-peak periods; construction considerations n The output of thermal power units in each extraction and conversion zone F n ( t The dynamic programming optimization algorithm was used to solve the problem and obtain the output of the first pumped storage unit. W w ( t ); When the water level reaches the upper limit, the pumped storage unit replaces the hydroelectric unit to use the frequency modulation capacity, and the second pumped storage unit output is obtained ; wherein the dynamic programming optimization algorithm is, ， In the formula, M 1 is the first peak valley interval set of thermal power, W t (0) is the initial state of the pumpable reservoir capacity, W d (0) is the initial state of the pumpable reservoir capacity; f 0 is the base thermal power output allocation algorithm, f 1 is the peak thermal power redistribution algorithm; The base thermal power output distribution algorithm f 0 includes, according to the thermal power low valley period T 低 pumping demand power P n and the thermal power peak period T 尖 pumpable power P a , obtaining the pumping power , and further obtaining the optimized thermal power target output f 0; The peak fire power redistribution algorithm f 1 includes, according to the fire power low period T 低 Pump demand power P n And the fire power peak period T 尖 Pumpable power P a , get the pumping power , and then get the optimized fire power target output f 1; The base thermal power output distribution algorithm f The specific content of 0 includes, Computing the pumped storage demand during the low valley period of thermal power T 低 of pumped storage demand , and then the pumped storage demand power , wherein, W max is the maximum pumped power of the pumped storage unit, W is the total storage capacity of the pumped storage unit, g is the storage capacity-pumped power conversion function of the pumped storage unit; Computing peak period of thermal power T 尖 pumped hydro capacity , ; wherein, delta is the average energy conversion rate of pumped storage units, W t is the pumped storage reservoir capacity of pumped storage units; Calculating pumped hydro power , and according to , , the solution is x Intermediate state thermal power output, optimized thermal power target output ; The spike power redistribution algorithm f 1 includes, in particular, Computing the pumping demand during the low valley period of thermal power T 低 of the pumping demand , and then the pumping demand power , ; Computing peak thermal periods T 尖 of the water pumping capability , and then the water pumping power , ; Computing pumped hydro capacity , and according to , , the solution is x Intermediate state thermal power output, optimized thermal power target output .

2. The method of claim 1, wherein: According to D day T the operation basis data before the time, get T +4 to T +24 hours of new energy short-term prediction value, including, D day T , obtain running basic data in advance; wherein, the running basic data includes, T to T a new energy ultra-short-term prediction value of +4 hours D gc , T to T a new energy short-term prediction value of +24 hours D g , T to T a load short-term prediction value of +24 hours D a , T to T a nuclear power planned output value of +24 hours D b , T to T a cross-regional DC planned value of +24 hours D c , T to T a small thermal power planned output value of +24 hours D e , T to T a hydropower planned output value of +24 hours D d , T to T a system frequency modulation capacity value of +24 hours D f ; the sampling interval of the running basic data is 15 minutes; Based on the operation basis data, get T +4 to T +24 hours of new energy short-term prediction value, ， In the formula, t is a certain moment of the actual operation of the power grid on the day, and the time interval is 15 minutes; D gx is the corrected T +4 to T +24 hours of new energy short-term prediction value.

3. The method of claim 1, wherein: According to the above D day T operation base data before the time point, T +4 to T +24 hours of new energy short-term prediction value, the thermal power target output t at a certain time F ( t ) is obtained, including, The thermal power target output t at a certain time is calculated according to the following formula F ( t ), ， In the formula, D a ( t (for a certain moment) t Short-term load forecasts D b ( t (for a certain moment) t The planned output of nuclear power plants, D c ( t (for a certain moment) t The planned value of cross-regional DC transmission, D d ( t (for a certain moment) t The planned output value of hydropower. D e ( t (for a certain moment) t The planned output value of small thermal power plants, D f ( t (for a certain moment) t The system frequency regulation capacity value, D g ( t )for T to T At some point within +4 hours t Short-term forecasts for new energy sources D gx ( t )for T +4 to T At some point within 24 hours t Short-term forecasts for new energy sources.

4. The method of claim 1, wherein: According to a time t of a thermal power target output F ( t ) determines the peak period and the valley period, including, At a certain moment t thermal power target output F ( t (and the minimum generating capacity of thermal power) F 2( t )Compare; determining F ( t ) F 2( t ) times, t The time is the peak time of thermal power, and the period composed of continuous thermal power peak times is a peak period T 尖 ; determining F ( t )< F 2( t ) times, t The time is the time of the low valley of the thermal power, and the period composed of continuous low valley times of the thermal power is the low valley period T 低 .

5. The method of claim 1, wherein: When it is determined that the water level reaches the upper limit, the pumped storage unit is used instead of the hydroelectric unit to obtain the second pumped storage unit output , comprising, When the water level reaches the upper limit, the pumped storage unit replaces the hydroelectric unit to use the frequency modulation capacity, and the newly received new energy S 'for, ， wherein, D f ( t ) is the system frequency capacity value at a certain time t . Then the second pumped storage unit output is: ， In the formula, T 抽 is T 抽蓄 pumping period in the period, T 发 is T 抽蓄 power generation period in the period, T 抽 + T 发 = T 抽蓄 , T 抽蓄 is a period in which the upper limit of the pumped storage unit reservoir capacity is reached and the system peak shaving power curtailment is not lifted.

6. A two-stage pumped storage unit optimization adjustment system, characterized in that: Comprising, The new energy short-term prediction value acquisition module is configured to obtain the new energy short-term prediction value within 4 to 24 hours according to the operation basic data before the time point. D Day T The operation basic data before the time point. T +4 to T +24 hours of new energy short-term prediction value; wherein, D is the actual operation day of the power grid, T is a certain integer time point on the actual operation day of the power grid. The time period segmentation module is configured to, based on the above... D day T Basic operational data before the time point T +4 to T +24-hour short-term forecast of new energy sources, to obtain a certain moment t thermal power target output F ( t According to a certain moment t thermal power target output F ( t Determine peak and off-peak periods; The first optimization module is configured to define the adjacent first peak period and the first valley period as the first pumped storage conversion interval of the pumped storage unit M n , and construct the thermal power peak-valley interval set , t n for the nth pumped storage conversion interval period, n for the nth pumped storage conversion interval period, for the nth pumped storage conversion interval period, n for the nth peak period, S t for the nth peak period, n for the nth peak period, n for the nth valley period, L t for the nth valley period, n for the nth valley period, n for the nth valley period, S d for the nth valley period, n for the nth valley period, n for the nth valley period, L d for the nth valley period, n for the nth valley period, n for the nth valley period, n for the nth pumped storage conversion interval, F n for the nth pumped storage conversion interval, t for the nth pumped storage conversion interval, W w for the nth pumped storage conversion interval, t for the nth pumped storage conversion interval, and A second optimization module is configured to use the frequency modulation capacity of the pumped storage unit instead of the hydropower unit when the water level reaches the upper limit, to obtain a second pumped storage unit output ; wherein the dynamic programming optimization algorithm is, ， In the formula, M 1 is the first peak-valley interval set of thermal power, W t (0) is the initial state of the pumpable reservoir capacity, W d (0) is the initial state of the pumpable reservoir capacity; f 0 is the basic thermal power output allocation algorithm, f 1 is the peak thermal power redistribution algorithm; The base thermal power output distribution algorithm f 0 includes, according to the thermal power low valley period T 低 pumping demand power P n and the thermal power peak period T 尖 pumpable power P a , obtaining the pumping power , and further obtaining the optimized thermal power target output f 0; The peak fire power redistribution algorithm f 1 includes, according to the fire power low period T 低 The pumping demand power P n And the pumping power of the fire power peak period T 尖 P a , get pumping power , and then get the optimized fire power target output f 1;​ The base thermal power output distribution algorithm f The specific content of 0 includes, Computing the pumped storage demand during the low valley period of thermal power T 低 of pumped storage demand , and then the pumped storage demand power , wherein, W max is the maximum pumped power of the pumped storage unit, W is the total storage capacity of the pumped storage unit, g is the storage capacity-pumped power conversion function of the pumped storage unit; Computing peak period of thermal power T 尖 pumped hydro capacity , ; wherein, delta is the average energy conversion rate of pumped storage units, W t is the pumped storage reservoir capacity of pumped storage units; Calculating pumped hydro power , and according to , , the solution is x Intermediate state thermal power output, optimized thermal power target output ; The spike power redistribution algorithm f 1 includes, in particular, Computing the pumping demand during the low valley period of thermal power T 低 of the pumping demand , and then the pumping demand power , ; Computing peak hours of thermal power T 尖 of water , and then the water pumping power , ; Computing pumped hydro capacity , and according to , , the solution is x Intermediate state thermal power output, optimized thermal power target output .

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor; characterized in that: The processor implements the steps of the two-stage pumped storage unit optimization adjustment method of any one of claims 1 to 5 when executing the computer program.

8. A computer readable storage medium, the computer readable storage medium storing a computer program; characterized in that: The processor implements the steps of the two-stage pumped storage unit optimization adjustment method of any one of claims 1 to 5 when executing the computer program.

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