Hydropower simulation method, device, equipment and medium for integrated energy base

Abstract

The application discloses a hydropower simulation method, device, equipment and medium of a comprehensive energy base, relates to the technical field of comprehensive energy base planning and design and operation scheduling, in the method, a second time length is taken as a statistical dimension, output fluctuation coefficients and abandoned electricity coefficients of wind and light power stations are counted, output weights of hydropower stations are determined based on the output fluctuation coefficients and the abandoned electricity coefficients, and the power generation of the hydropower stations is corrected based on the output weights, so that the power generation of the hydropower stations can be reduced when the output fluctuation coefficients and the abandoned electricity coefficients of the wind and light power stations are large, and the power generation of the hydropower stations can be increased when the output fluctuation coefficients and the abandoned electricity coefficients of the wind and light power stations are small. Since the output fluctuation coefficients and the abandoned electricity coefficients of the wind and light power stations are considered when the power generation of the hydropower stations is determined, the power generation of the hydropower stations obtained finally can be relatively accurate, and thus the problem that the scheduling of the hydropower stations is not accurate enough can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of comprehensive energy base planning and operation scheduling technology, and particularly relates to a hydropower simulation method, device, equipment and medium for a comprehensive energy base. BACKGROUND

[0002] In a water-wind-solar multi-energy complementary comprehensive energy base, 8760-hour continuous time sequence simulation is a key link for verifying the joint scheduling performance of a hydropower station and a wind-solar power station. When performing continuous time sequence simulation, in order to reduce the difficulty of solving, a multi-time scale hierarchical nested simulation is usually adopted. The so-called multi-time scale hierarchical nested simulation is a calculation method of decomposing a complex long-period optimization problem into multiple time scales (such as year, month, decade, day, and hour), and refining layer by layer through hierarchical coupling (upper layer results constrain lower layer input).

[0003] At present, in some technologies, when performing multi-time scale hierarchical nested simulation, the wind-solar power generation of a long time scale (such as year-decade) is a mean value, and its volatility and intermittency are flattened, which leads to inaccurate scheduling of the hydropower station on the long time scale, and further leads to the problems of insufficient or excessive scheduling capacity of the hydropower station in short time scale (such as decade-hour) simulation. SUMMARY

[0004] The present application provides a hydropower simulation method, device, electronic equipment, computer readable storage medium and computer program product for a comprehensive energy base, to at least solve the problem of inaccurate scheduling of a hydropower station in related technologies.

[0005] The present application provides a hydropower simulation method for a comprehensive energy base, the method comprising:

[0006] obtaining simulation reference information, the simulation reference information comprising an operation parameter of a hydropower station, a wind-solar power generation sequence obtained by taking a first time length as a statistical dimension, and a maximum power transmission capacity supported by a power transmission channel;

[0007] statistically processing the wind-solar power generation sequence by taking a second time length as a statistical dimension, to obtain an output fluctuation coefficient of a wind-solar power station, the second time length being greater than or equal to the first time length;

[0008] statistically processing the wind-solar power generation sequence by taking the second time length as a statistical dimension and taking the maximum power transmission capacity supported by the power transmission channel as a constraint condition, to obtain an abandoned power coefficient of the wind-solar power station;

[0009] determining an output weight of the hydropower station based on the output fluctuation coefficient and the abandoned power coefficient of the wind-solar power station;

[0010] The simulation module is configured to: take the operation parameters of the hydropower station and the maximum power transmission capacity supported by the power transmission channel as constraints, take the maximum on-grid power of the integrated energy base as a target, correct the power generation of the hydropower station based on the output weight, obtain a target power generation of the hydropower station, and simulate the operation of the hydropower station based on the target power generation.

[0011] The application further provides a hydropower simulation device of an integrated energy base, which comprises:

[0012] The information acquisition module is configured to acquire simulation reference information, wherein the simulation reference information comprises operation parameters of a hydropower station, a wind-solar power generation sequence obtained by taking a first time length as a statistical dimension, and a maximum power transmission capacity supported by a power transmission channel.

[0013] The first coefficient determination module is configured to take the second time length as a statistical dimension to statistically process the wind-solar power generation sequence, and obtain an output fluctuation coefficient of a wind-solar power station, wherein the second time length is greater than or equal to the first time length.

[0014] The second coefficient determination module is configured to take the second time length as a statistical dimension, take the maximum power transmission capacity supported by the power transmission channel as a constraint condition, and statistically process the wind-solar power generation sequence to obtain an abandoned power coefficient of the wind-solar power station.

[0015] The third coefficient determination module is configured to determine an output weight of the hydropower station based on the output fluctuation coefficient and the abandoned power coefficient of the wind-solar power station.

[0016] The simulation module is configured to: take the operation parameters of the hydropower station and the maximum power transmission capacity supported by the power transmission channel as constraints, take the maximum on-grid power of the integrated energy base as a target, correct the power generation of the hydropower station based on the output weight, obtain a target power generation of the hydropower station, and simulate the operation of the hydropower station based on the target power generation.

[0017] The application further provides an electronic device, which comprises a memory configured to store a computer program and a processor configured to execute the computer program to implement the steps of the hydropower simulation method of the integrated energy base.

[0018] The application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the hydropower simulation method of the integrated energy base.

[0019] In the technical solutions of some embodiments of the present application, the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are counted based on the second time length as the counting dimension, the output weight of the hydropower station is determined based on the output fluctuation coefficient and the power abandonment coefficient, and the power generation of the hydropower station is corrected based on the output weight, so that when the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are large, the power generation of the hydropower station can be reduced, and when the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are small, the power generation of the hydropower station can be increased. Since the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are considered when determining the power generation of the hydropower station, the power generation of the hydropower station obtained finally can be more accurate, thereby solving the problem of inaccurate scheduling of the hydropower station in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application, the drawings required in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0021] Figure 1 A flowchart of a hydropower simulation method provided by some embodiments of the present application is shown in the figure.

[0022] Figure 2 A flowchart of a multi-time scale hierarchical nested simulation provided by an embodiment of the present application is shown in the figure.

[0023] Figure 3 A module diagram of a hydropower simulation device provided by some embodiments of the present application is shown in the figure.

[0024] Figure 4 A module diagram of an electronic device provided by some embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0026] It should be noted that in the description of the present application, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. The terms "first", "second" and the like in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence.

[0027] In order to enable those skilled in the art to better understand the present application, the present application will be further described in detail below in combination with the drawings and specific embodiments.

[0028] The output of the power station refers to the instantaneous power generation capacity of the power station at a certain moment. In a water-wind-solar multi-energy complementary integrated energy base, at least a wind-solar power station and a hydroelectric power station are included, and the wind-solar power station further includes a wind power station and a photovoltaic power station. The power generation capacity of the wind power station is affected by the wind strength, the power generation capacity of the photovoltaic power station is affected by the day and night light, and the power generation capacity of the hydroelectric power station is relatively stable and flexible. By reasonably scheduling the water-wind-solar power station, the maximum utilization of energy can be realized, the waste of wind-solar energy can be reduced, and at the same time, the power supply stability of the power grid can be improved. For example, when the wind is strong or the light is sufficient, the water in the hydroelectric power station can be stored to reduce the power generation capacity of the hydroelectric power station. In this way, the wind-solar power generation capacity can be fully utilized, thereby reducing the wind-solar curtailment. Conversely, when the wind is weak or the light is insufficient, the power generation capacity of the hydroelectric power station can be increased. In this way, the deficiency of the wind-solar power generation capacity can be supplemented, and the power supply capacity of the power grid can be ensured.

[0029] In the design or operation process of the integrated energy base, by simulating the operation state of the integrated energy base in 8760 hours of the whole year, the scheduling strategy for the wind-solar-hydro power station can be determined or verified. However, the operation simulation of the hydroelectric power station has nonlinear constraints such as water level-storage capacity curve, discharge flow-tail water level curve, and head-expected output curve, and the head flow calculation output is a quadratic function, which is a typical mixed integer nonlinear programming problem. If 8760 hours of continuous simulation is performed, there are at least 8760 variables, which is extremely difficult to solve. In order to reduce the difficulty of solving, multi-time scale hierarchical nested simulation is usually used. For example, in the long time scale, the power generation capacity of the hydroelectric power station in each decade can be calculated based on the wind-solar power generation capacity in each decade in a year, and then in the short time scale, the power generation capacity of the hydroelectric power station in each hour in each decade can be calculated based on the calculation results of each decade, and the hydroelectric power station is controlled based on the calculated power generation capacity. In this way, in the long time scale, the number of variables to be solved can be reduced to 36, and in the short time scale, the number of variables to be solved can be reduced to 240, so that the difficulty of solving can be greatly reduced.

[0030] Currently, in some technologies, when performing multi-time scale nested simulation, the wind and light power generation at a long time scale (such as year-decade) is an average value, and the fluctuation and intermittence thereof are averaged, which leads to inaccurate scheduling of the hydropower station at the long time scale, and further leads to problems such as insufficient or excessive scheduling capacity of the hydropower station at a short time scale (such as decade-hour). For example, assuming that the average power generation of the wind power station in each decade at the long time scale is 50 kW, 55 kW, …, 40 kW, and the average power generation of the photovoltaic power station in each decade is 20 kW, 30 kW, …, 15 kW, the power generation of the hydropower station in each decade can be calculated based on the average power generation of the wind and light power stations. This scheduling strategy based on the average value is not accurate enough. For example, the power generation of the photovoltaic power station during the day can reach 60 kW, but the power generation at night can be close to 0 kW. After averaging the power generation, the average power generation of the photovoltaic power station in the decade can be 30 kW. When the hydropower station is scheduled according to 30 kW, the power generation of the comprehensive energy base in the daytime can be excessive, but the power generation at night can be insufficient.

[0031] In view of this, the present application provides a hydropower simulation method of a comprehensive energy base, which can solve the problem of inaccurate scheduling of the hydropower station in the related art. The hydropower simulation method can be applied to an electronic device. The electronic device can include but is not limited to a tablet computer, a desktop computer, a notebook computer, a server, a control circuit board, etc. For better understanding Figure 1 The flowchart of the hydropower simulation method provided for some embodiments of the present application is shown in FIG. 1. Figure 1 The hydropower simulation method can include the following steps:

[0032] In step S101, simulation reference information is obtained, and the simulation reference information includes the operating parameters of the hydropower station, the wind and light power generation sequence obtained by taking the first time length as the statistical dimension, and the maximum power transmission capacity supported by the power transmission channel.

[0033] Specifically, the operating parameters of the hydropower station can include the following information:

[0034] 1) The characteristic parameters of the hydropower station, such as installed capacity, characteristic water level, minimum discharge, and comprehensive output coefficient. The characteristic water level can include the storage water level, dead water level, flood limit water level, ecological water level, and design flood water level of the hydropower station.

[0035] 2) The characteristic curves of the hydropower station, such as water level-storage capacity relationship curve, discharge-tail water level curve, water head-expected output curve, and water level-maximum discharge curve.

[0036] 3) The operating parameters of the power transmission channel, such as the maximum power transmission capacity, the minimum power transmission capacity, the power transmission efficiency, and the power transmission loss.3) water balance of the hydropower station and constraints of water level, flow rate, output and the like in each period.

[0037] Based on the operating parameters of the hydropower station, the hydropower station can be simulated. Based on the simulated hydropower station, the operation state of the integrated energy base in 8760 hours of a year can be simulated.

[0038] In this embodiment, the first duration is 1 hour. The wind and light power generation sequence includes a wind power generation sequence and a photovoltaic power generation sequence of the integrated energy base in a typical year. The wind power generation sequence includes 8760 wind power generations counted in hours, and the photovoltaic power generation sequence includes 8760 photovoltaic power generations counted in hours. It can be understood that in actual application, the first duration can be determined according to actual needs. For example, the first duration can also be 1 day. The wind power generation sequence includes 365 wind power generations counted in days, and the photovoltaic power generation sequence includes 365 photovoltaic power generations counted in days. The specific value of the first duration is not limited in the present application.

[0039] In step S102, the wind and light power generation sequence is counted with the second duration as the statistical dimension to obtain the output fluctuation coefficient of the wind and light power station, and the second duration is greater than or equal to the first duration.

[0040] Specifically, the output fluctuation coefficient represents the fluctuation size of the wind and light power generation. For any second duration, the standard deviation and the mean of the wind and light power generation in the second duration can be determined, and based on the standard deviation and the mean, the output fluctuation coefficient of the wind and light power station in the second duration can be determined.

[0041] In this embodiment, the second duration is 1 decade. Based on the wind power generation sequence and the photovoltaic power generation sequence obtained in step S101, the wind power generation and the photovoltaic power generation at the corresponding time point can be added to obtain the wind and light power generation at the corresponding time point. For example, the wind power generation and the photovoltaic power generation at the first hour are added to obtain the wind and light power generation at the first hour; the wind power generation and the photovoltaic power generation at the second hour are added to obtain the wind and light power generation at the second hour.

[0042] Based on the wind and light power generation of each hour, the standard deviation and the mean of the wind and light power generation in the tth decade can be counted. Based on the standard deviation and the mean of the wind and light power generation in the tth decade, the output fluctuation coefficient of the wind and light power station in the tth decade can be determined. Wherein, the value of t is an integer between 1 and 36 (including 1 and 36). Specifically, the output fluctuation coefficient of the wind and light power station in the tth decade can be calculated based on expression (1).

[0043] (1)

[0044] Wherein, a coefficient of output fluctuation of the wind-solar power station in the tth decade, a standard deviation of the wind-solar power generation in the tth decade, a mean value of the wind-solar power generation in the tth decade, an nth wind-solar power generation in the tth decade, a number of the wind-solar power generations in the tth decade, n is an integer between 1 and T3 (inclusive).

[0045] After the coefficients of output fluctuation of the decades are normalized, a sequence of the coefficients of output fluctuation in a typical year can be obtained .

[0046] It can be understood that in actual applications, the second time length can be determined according to actual needs. For example, the second time length can also be 1 month. The specific value of the second time length is not limited in the application.

[0047] In step S103, the wind-solar power generation sequence is counted with the second time length as a statistical dimension and the maximum power transmission capacity supported by the power transmission channel as a constraint condition, to obtain a curtailment coefficient of the wind-solar power station.

[0048] Specifically, the curtailment coefficient includes a curtailment amount of the wind-solar power station. For any second time length, the sum of the wind-solar power generations in the second time length can be determined, and based on the sum of the wind-solar power generations and the maximum power transmission capacity supported by the power transmission channel, the curtailment coefficient of the wind-solar power station in the second time length can be determined.

[0049] In this embodiment, the curtailment coefficient of the wind-solar power station in the tth decade can be calculated based on expression (2).

[0050] (2)

[0051] wherein, a curtailment coefficient of the wind-solar power station in the tth decade, a curtailment amount of the wind-solar power station in the tth decade, a wind-solar power generation of the wind-solar power station in the tth decade.

[0052] After the curtailment coefficients of the decades are normalized, a sequence of the curtailment coefficients of the wind-solar power station in a typical year can be obtained .

[0053] In step S104, an output weight of the hydroelectric power station is determined based on the coefficient of output fluctuation and the curtailment coefficient of the wind-solar power station.

[0054] Specifically, the output weight is used to correct the power generation of the hydropower station. The corrected power generation is less than the uncorrected power generation. The greater the output weight, the greater the correction degree of the power generation. That is, the greater the output weight, the smaller the corrected power generation.

[0055] The output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station can be proportional to the output weight of the hydropower station. The reasons for the proportionality are described below.

[0056] 1) When the output fluctuation coefficient is relatively large, it indicates that the power generation of the wind-solar power station has a relatively large value. At this time, the power generation of the hydropower station can be further reduced (i.e., the output weight needs to be larger). In this way, when the power generation of the wind-solar power station is high, the power generation of the hydropower station is also high, thereby causing excessive power abandonment and waste of natural resources. Of course, it can be understood that when the output fluctuation coefficient is relatively large, the power generation of the wind-solar power station also has a relatively small value. When the power generation of the wind-solar power station is small, in order to ensure normal power supply, other power stations (such as thermal power stations) in the power system can be controlled to generate power. In this way, on the one hand, the power grid can be ensured to supply power normally, and on the other hand, the natural energy such as wind, light, and water can be fully utilized to avoid waste of natural energy.

[0057] 2) When the power abandonment coefficient is relatively large, it indicates that the power generation of the wind-solar power station is already excessive. At this time, the power generation of the hydropower station can also be further reduced (i.e., the output weight needs to be larger). In this way, when the power generation of the wind-solar power station is excessive, the power generation of the hydropower station is also high, thereby causing excessive power abandonment and waste of natural resources.

[0058] In the present embodiment, for any second time length, the output weight of the wind-solar power station in the second time length can be determined based on the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station in the second time length. That is, based on the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station in the t th decade, the output weight of the wind-solar power station in the t th decade can be determined. In this way, the output weight sequence of the hydropower station in the typical year can be obtained .

[0059] Based on the output weight in the t th decade, the power generation of the hydropower station in the t th decade can be corrected.

[0060] Further, the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station can have respective corresponding weights. The weights are used to represent the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station, and the influence size of the output weight of the hydropower station. When the output weight of the hydropower station is determined based on the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station, a first weight of the output fluctuation coefficient and a second weight of the power abandonment coefficient can be obtained. Based on the first weight and the second weight, the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station can be weighted and fused to obtain the output weight.

[0061] Specifically, the output weight of the hydropower station in the t th decade can be determined based on expression (3) .

[0062] (3)

[0063] wherein, the first weight is represented by w 1, the second weight is represented by w 2, .

[0064] In step S105, the generation amount of the hydropower station is corrected based on the output weight, to obtain a target generation amount of the hydropower station, and the operation of the hydropower station is simulated based on the target generation amount, with the operation parameters of the hydropower station and the maximum transmission capacity supported by the transmission channel as constraints, and the maximum on-grid power of the integrated energy base as a target.

[0065] In the embodiment, the target generation amount of the hydropower station in each first time length (i.e., each hour) can be determined through multi-time scale hierarchical nested simulation. For reference, see Figure 2 The flowchart of the multi-time scale hierarchical nested simulation provided by one embodiment of the present application is shown in FIG. 2. Figure 2 The multi-time scale hierarchical nested simulation includes the following steps:

[0066] In step S201, the target water level of the hydropower station at the beginning and end of each first dispatching period is obtained based on the output weight, with the third time length as a first dispatching cycle, the second time length as a first dispatching period, the maximum on-grid power of the integrated energy base as a target, and the operation parameters of the hydropower station and the maximum transmission capacity supported by the transmission channel as constraints. The third time length is greater than or equal to the second time length.

[0067] Specifically, the third time length is 1 year. Based on the output weight, a first target function as shown in expression (4) can be constructed:

[0068] (4)

[0069] wherein, represents the online power of the wind power station in the tth first dispatching period, represents the output weight of the hydropower station in the tth first dispatching period, represents the online power of the hydropower station in the tth first dispatching period, represents the online power of the wind power station in the tth first dispatching period, represents the online power of the photovoltaic power station in the tth first dispatching period, represents the curtailment rate of the wind and light power station in the tth first dispatching period, represents the time length of the tth first dispatching period.

[0070] The operation parameters of the hydropower station are taken as constraints to solve the first objective function, and the target water level of the hydropower station at the beginning and end of each first dispatching period can be obtained. The constraint conditions can include the following expressions (5)~(18).

[0071] (5)

[0072] (6)

[0073] (7)

[0074] (8)

[0075] (9)

[0076] (10)

[0077] (11)

[0078] (12)

[0079] (13)

[0080] (14)

[0081] (15)

[0082] (16)

[0083] (17)

[0084] (18)

[0085] In the above expressions (5) to (9), k represents a comprehensive output coefficient of the hydropower station, represents a power generation reference flow rate of the hydropower station in the tth first dispatching period, represents a power generation head of the hydropower station in the tth first dispatching period, represents an upstream water level of the hydropower station at the beginning of the tth first dispatching period, represents an upstream water level of the hydropower station at the end of the tth first dispatching period, represents an average downstream water level of the hydropower station in the tth first dispatching period, represents a discharge flow rate-tailwater level relationship curve of the hydropower station; represents a water level-storage capacity relationship curve of the hydropower station, represents a discharge flow rate of the hydropower station in the tth first dispatching period, represents a spill flow rate of the hydropower station in the tth first dispatching period.

[0086] In the above expressions (10) to (11), represents a minimum power supported by the power transmission channel, represents a maximum power supported by the power transmission channel.

[0087] In the above expression (12), represents a storage capacity of the hydropower station in the tth first dispatching period, represents a storage capacity of the hydropower station in the (t-1)th first dispatching period, represents a discharge flow rate of the reservoir of the hydropower station in the tth first dispatching period.

[0088] In the above expressions (13) to (14), represents an initial water level of the hydropower station at the beginning of the first dispatching period, represents an end water level of the hydropower station at the end of the first dispatching period.

[0089] In the above expression (15), represents a lower limit of a dam front water level of the hydropower station in the tth first dispatching period, represents an upper limit of a dam front water level of the hydropower station in the tth first dispatching period.

[0090] In the above expression (16), represents a lower limit of a discharge flow rate of the hydropower station in the tth first dispatching period, represents an upper limit of a discharge flow rate of the hydropower station in the tth first dispatching period.

[0091] In the above expression (17), represents the allowable variation range of the reservoir water level of the hydropower station in a single first dispatching period.

[0092] In the above expression (18), represents the minimum power generation amount of the hydropower station in the tth first dispatching period, represents the maximum power generation amount of the hydropower station in the tth first dispatching period.

[0093] In step S202, the target power generation amount of the hydropower station in each second dispatching period is determined with the second time length as the second dispatching period, the first time length as the second dispatching period, and the target water level of the hydropower station at the beginning and end of each first dispatching period as the constraint.

[0094] Specifically, the second objective function shown in expression (19) can be constructed with the target water level of the hydropower station at the beginning and end of each first dispatching period as the constraint.

[0095] (19)

[0096] wherein, represents the on-grid power of the integrated energy base in one of the second dispatching periods, T2 represents the number of second dispatching periods in one of the second dispatching periods, represents the output weight of the hydropower station in the mth second dispatching period, represents the on-grid power of the hydropower station in the mth second dispatching period, represents the on-grid power of the wind power station in the mth second dispatching period, represents the on-grid power of the photovoltaic power station in the mth second dispatching period, represents the curtailment rate of the wind-solar power station in the mth second dispatching period, represents the time length of the mth second dispatching period.

[0097] The second objective function can be solved in combination with the constraint conditions shown in expressions (20)-(33) to obtain the target power generation amount of the hydropower station in each second dispatching period and the curtailment amount of the wind-solar power station in each second dispatching period.

[0098] (20)

[0099] (21)

[0100] (22)

[0101] (23)

[0102] (24)

[0103] (25)

[0104] (26)

[0105] (27)

[0106] (28)

[0107] (29)

[0108] (30)

[0109] (31)

[0110] (32)

[0111] (33)

[0112] In the above expressions (20) to (24), k represents a comprehensive output coefficient of the hydroelectric power plant, represents a power generation reference flow of the hydroelectric power plant in the mth second dispatch period, represents a power generation head of the hydroelectric power plant in the mth second dispatch period, represents an upstream water level at the beginning of the mth second dispatch period of the hydroelectric power plant, represents an upstream water level at the end of the mth second dispatch period of the hydroelectric power plant, represents an average downstream water level of the mth second dispatch period of the hydroelectric power plant, represents a discharge flow-tail water level relationship curve of the hydroelectric power plant; represents a water level-storage capacity relationship curve of the hydroelectric power plant, represents a discharge flow of the hydroelectric power plant in the mth second dispatch period, represents a water abandonment flow of the hydroelectric power plant in the mth second dispatch period.

[0113] In the above expressions (25) to (26), is the lowest power supported by the power transmission channel, is the highest power supported by the power transmission channel.

[0114] In the above expression (27), represents a storage capacity of the hydroelectric power plant in the mth second dispatch period, represents a storage capacity of the hydroelectric power plant in the (m-1)th second dispatch period, represents the outflow of the reservoir of the hydropower station at the mth second dispatch period.

[0115] In the above expressions (28) to (29), represents the initial water level of the hydropower station at the beginning of the second dispatch period, represents the end water level of the hydropower station at the end of the second dispatch period.

[0116] In the above expression (30), represents the lower limit of the water level before the dam of the hydropower station at the mth second dispatch period, represents the upper limit of the water level before the dam of the hydropower station at the mth second dispatch period.

[0117] In the above expression (31), represents the lower limit of the outflow of the hydropower station at the mth second dispatch period, represents the upper limit of the outflow of the hydropower station at the mth second dispatch period.

[0118] In the above expression (32), represents the allowable variation range of the water level of the reservoir of the hydropower station within a single second dispatch period.

[0119] In the above expression (33), represents the minimum power generation of the hydropower station at the mth second dispatch period, represents the maximum power generation of the hydropower station at the mth second dispatch period.

[0120] In summary, in the technical solutions of some embodiments of the present application, the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are counted with the second time length as the counting dimension, the output weight of the hydropower station is determined based on the output fluctuation coefficient and the power abandonment coefficient, and the power generation of the hydropower station is corrected based on the output weight. When the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are large, the power generation of the hydropower station can be reduced, and when the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are small, the power generation of the hydropower station can be increased. Since the output fluctuation coefficient and the power abandonment coefficient of the wind-solar power station are considered when determining the power generation of the hydropower station, the final power generation of the hydropower station can be more accurate, thereby solving the problem of inaccurate scheduling of the hydropower station in the related art.

[0121] Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be realized by means of software and a necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment.

[0122] Corresponding to the method, the application further provides a hydropower simulation device of a comprehensive energy base. Figure 3 A module schematic diagram of the hydropower simulation device provided for some embodiments of the application is shown. Figure 3 In some embodiments, the hydropower simulation device comprises:

[0123] The information acquisition module 301 is configured to acquire simulation reference information, wherein the simulation reference information comprises operation parameters of the hydropower station, a wind-solar power generation sequence obtained by taking a first time length as a statistical dimension, and a maximum transmission capacity supported by the transmission channel.

[0124] The first coefficient determination module 302 is configured to perform statistics on the wind-solar power generation sequence by taking a second time length as the statistical dimension, to obtain an output fluctuation coefficient of the wind-solar power station, wherein the second time length is greater than or equal to the first time length.

[0125] The second coefficient determination module 303 is configured to perform statistics on the wind-solar power generation sequence by taking the second time length as the statistical dimension and taking the maximum transmission capacity supported by the transmission channel as a constraint condition, to obtain an abandoned power coefficient of the wind-solar power station.

[0126] The third coefficient determination module 304 is configured to determine an output weight of the hydropower station based on the output fluctuation coefficient and the abandoned power coefficient of the wind-solar power station.

[0127] The simulation module 305 is configured to correct the power generation of the hydropower station based on the output weight, to obtain a target power generation of the hydropower station, by taking the operation parameters of the hydropower station and the maximum transmission capacity supported by the transmission channel as constraints and taking the maximum on-grid power of the comprehensive energy base as a target, and simulate the operation of the hydropower station based on the target power generation.

[0128] In some embodiments, the hydropower simulation device comprises: Figure 4 In some embodiments, the application further provides an electronic device, which comprises a memory 10 and a processor 20, wherein the memory 10 stores a computer program, and the processor 20 is configured to run the computer program to perform the steps in any one of the above hydropower simulation method embodiments of the comprehensive energy base.

[0129] In some embodiments, the application further provides a computer readable storage medium, which stores a computer program, wherein the computer program is configured to perform the steps in any one of the above hydropower simulation method embodiments of the comprehensive energy base when running.

[0130] In an example embodiment, the computer readable storage medium described above can include, but is not limited to, a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store computer programs.

[0131] Embodiments of the present application also provide a computer program product, which comprises a computer program, and the computer program, when executed by a processor, implements the steps in any of the above-mentioned embodiments of the method for simulating hydropower generation of a comprehensive energy base.

[0132] Embodiments of the present application also provide another computer program product, which comprises a non-volatile computer readable storage medium, and the non-volatile computer readable storage medium stores a computer program, and the computer program, when executed by a processor, implements the steps in any of the above-mentioned embodiments of the method for simulating hydropower generation of a comprehensive energy base.

[0133] The skilled in the art can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in the above description in general terms. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0134] The above describes in detail a method, device, equipment and medium for simulating hydropower generation of a comprehensive energy base provided by the present application. The principles and implementation modes of the present application are described by applying specific examples in this paper, and the above description of the examples is only used to help understand the method of the present application and its core idea. It should be pointed out that, for those skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

Claims

1. A method of simulating hydroelectric power generation of an integrated energy base, characterized by, The method comprises: acquiring analog reference information, the analog reference information comprising operation parameters of a hydropower station, a wind-solar power generation sequence obtained by taking a first time length as a statistical dimension, and a maximum transmission capacity supported by a transmission channel; statistically processing the wind-solar power generation sequence by taking a second time length as a statistical dimension to obtain an output fluctuation coefficient of the wind-solar power station, the second time length being greater than or equal to the first time length; statistically processing the wind-solar power generation sequence by taking the second time length as a statistical dimension and the maximum transmission capacity supported by the transmission channel as a constraint condition to obtain an abandoned power coefficient of the wind-solar power station; determining an output weight of the hydropower station based on the output fluctuation coefficient and the abandoned power coefficient of the wind-solar power station; correcting the power generation of the hydropower station based on the output weight, taking the operation parameters of the hydropower station and the maximum transmission capacity supported by the transmission channel as constraints, and taking the maximum on-grid power of the integrated energy base as a target to obtain a target power generation of the hydropower station, and simulating the operation of the hydropower station based on the target power generation.

2. The method of claim 1, wherein, The method for obtaining the target power generation of the hydropower station comprises: correcting the power generation of the hydropower station based on the output weight, taking the operation parameters of the hydropower station and the maximum transmission capacity supported by the transmission channel as constraints, and taking the maximum on-grid power of the integrated energy base as a target to obtain a target water level of the hydropower station at the beginning and end of each first scheduling period, the third time length being greater than or equal to the second time length; determining the target power generation of the hydropower station in each second scheduling period by taking the target water level of the hydropower station at the beginning and end of each first scheduling period as a constraint, the second time length being taken as a second scheduling cycle and the first time length being taken as a second scheduling period.

3. The method of claim 2, wherein, The wind-solar power station comprises a wind power station and a photovoltaic power station; the method for obtaining the target water level of the hydropower station at the beginning and end of each first scheduling period comprises: a first target function shown in the following formula is constructed based on the output weight, and the first target function is solved by taking the operation parameters of the hydropower station as constraints to obtain the target water level of the hydropower station at the beginning and end of each first scheduling period: wherein, , , , , , represents the grid-connected power of the integrated energy base in the first dispatching period, T1 represents the number of first dispatching periods in the first dispatching period, represents the output weight of the hydropower station in the tth first dispatching period, represents the grid-connected power of the hydropower station in the tth first dispatching period, represents the grid-connected power of the wind power station in the tth first dispatching period, represents the grid-connected power of the photovoltaic power station in the tth first dispatching period, represents the curtailment rate of the wind-solar power station in the tth first dispatching period, represents the duration of the tth first dispatching period, k represents the integrated output coefficient of the hydropower station, represents the power generation reference flow of the hydropower station in the tth first dispatching period, represents the power generation water head of the hydropower station in the tth first dispatching period, represents the upstream water level of the hydropower station at the beginning of the tth first dispatching period, represents the upstream water level of the hydropower station at the end of the tth first dispatching period, represents the average downstream water level of the hydropower station in the tth first dispatching period, represents the discharge-tailwater relationship curve of the hydropower station, represents the reservoir capacity of the hydropower station in the tth first dispatching period; represents the water level-reservoir capacity relationship curve of the hydropower station, represents the discharge of the hydropower station at the end of the tth first dispatching period, represents the flow of the hydropower station at the end of the tth first dispatching period.

4. The method of claim 2, wherein, The wind-solar power station comprises a wind power station and a photovoltaic power station; the method for determining the target power generation of the hydropower station in each second scheduling period comprises: a second target function shown in the following formula is constructed by taking the target water level of the hydropower station at the beginning and end of each first scheduling period as a constraint, and the second target function is solved to obtain the target power generation of the hydropower station in each second scheduling period: wherein, , , , , , represents the online power of the wind-solar power station in the mth second dispatch period, represents the online power of the hydropower station in the mth second dispatch period, represents the online power of the wind-solar power station in the mth second dispatch period, represents the online power of the wind-solar power station in the mth second dispatch period, represents the curtailment rate of the wind-solar power station in the mth second dispatch period, represents the duration of the mth second dispatch period, k represents the comprehensive output coefficient of the hydropower station, represents the power generation reference flow of the hydropower station in the mth second dispatch period, represents the power generation water head of the hydropower station in the mth second dispatch period, represents the upstream water level of the hydropower station at the beginning of the mth second dispatch period, represents the upstream water level of the hydropower station at the end of the mth second dispatch period, represents the average downstream water level of the hydropower station in the mth second dispatch period, represents the discharge-flow tailwater relationship curve of the hydropower station; represents the water level-storage relationship curve of the hydropower station, represents the storage of the hydropower station in the mth second dispatch period, represents the discharge flow of the hydropower station at the end of the mth second dispatch period, represents the flow of the hydropower station at the end of the mth second dispatch period.

5. The method according to any one of claims 1 to 4, characterized in that, The method for statistically processing the wind-solar power generation sequence by taking a second time length as a statistical dimension to obtain an output fluctuation coefficient of the wind-solar power station comprises: For any second time length, determine the standard deviation and mean of the wind and light power generation in the second time length, and based on the standard deviation and the mean, determine the output fluctuation coefficient of the wind and light power station in the corresponding second time length.

6. The method according to any one of claims 1 to 4, characterized in that, The statistics of the wind and light power generation sequence based on the second time length as the statistical dimension and the maximum power transmission capacity supported by the power transmission channel as the constraint condition, obtains the curtailment coefficient of the wind and light power station, including: For any second time length, determine the sum of the wind and light power generation in the second time length, and based on the sum of the wind and light power generation and the maximum power transmission capacity supported by the power transmission channel, determine the curtailment coefficient of the wind and light power station in the corresponding second time length.

7. The method according to any one of claims 1 to 4, characterized in that, The output weight of the hydropower station is determined based on the output fluctuation coefficient and the curtailment coefficient of the wind and light power station, including: Obtain the first weight of the output fluctuation coefficient and the second weight of the curtailment coefficient; Based on the first weight and the second weight, the output fluctuation coefficient and the curtailment coefficient of the wind and light power station are weighted and fused to obtain the output weight.

8. A hydroelectric power generation simulation device of an integrated energy base, characterized by, The device comprises: An information acquisition module is configured to acquire simulation reference information, the simulation reference information including operation parameters of a hydropower station, a wind and light power generation sequence obtained by taking a first time length as a statistical dimension, and a maximum power transmission capacity supported by a power transmission channel; A first coefficient determination module is configured to take a second time length as a statistical dimension to statistically process the wind and light power generation sequence, thereby obtaining an output fluctuation coefficient of a wind and light power station, the second time length being greater than or equal to the first time length; A second coefficient determination module is configured to take the second time length as a statistical dimension and take the maximum power transmission capacity supported by the power transmission channel as a constraint condition to statistically process the wind and light power generation sequence, thereby obtaining a curtailment coefficient of the wind and light power station; A third coefficient determination module is configured to determine an output weight of the hydropower station based on the output fluctuation coefficient and the curtailment coefficient of the wind and light power station; A simulation module is configured to take the operation parameters of the hydropower station and the maximum power transmission capacity supported by the power transmission channel as constraints, take the maximum on-grid power of the integrated energy base as a target, correct the power generation of the hydropower station based on the output weight, obtain a target power generation of the hydropower station, and simulate the operation of the hydropower station based on the target power generation.

9. An electronic device, comprising: including: A memory is configured to store a computer program; A processor is configured to execute the computer program to implement the hydropower simulation method of the integrated energy base according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, wherein the computer program is executed by the processor to implement the hydropower simulation method of the integrated energy base according to any one of claims 1 to 7.

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