CN111445061B - Determination method for year-end fluctuating level of regulated reservoir by considering incoming flow frequency difference - Google Patents

Determination method for year-end fluctuating level of regulated reservoir by considering incoming flow frequency difference Download PDF

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CN111445061B
CN111445061B CN202010153894.3A CN202010153894A CN111445061B CN 111445061 B CN111445061 B CN 111445061B CN 202010153894 A CN202010153894 A CN 202010153894A CN 111445061 B CN111445061 B CN 111445061B
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蒋志强
胡德超
覃晖
刘懿
冯仲恺
陈璐
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Huazhong University of Science and Technology
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Abstract

The invention discloses a method for determining year-end fluctuating level of a year-end regulated reservoir by considering incoming flow frequency difference, and belongs to the field of water resource management. The method comprises the following steps: dispersing the range of regulating the dead water level of the reservoir to the normal water storage level for many years in the cascade system; taking each discrete water level value as the constraint of year-end fluctuating water level of a multi-year regulating reservoir, and establishing a cascade system combined optimization scheduling model with the maximum total power generation amount as a target; taking the flow frequency in the years as model input, and solving the model by a multi-dimensional dynamic programming algorithm; taking the discrete water level corresponding to the maximum generated energy as the optimal falling water level of each incoming flow frequency; and fitting a scatter diagram of the incoming flow frequency and the optimal falling water level based on the least square principle to obtain the optimal falling water level under different incoming flow frequencies. The invention can give full play to the regulation performance of the multi-year regulation reservoir, improves the water energy conversion efficiency and the total cascade power generation capacity of the cascade system, and has important significance for guiding the actual dispatching operation of the cascade reservoir group containing the multi-year regulation reservoir.

Description

Determination method for year-end fluctuating level of regulated reservoir by considering incoming flow frequency difference
Technical Field
The invention belongs to the field of water resource management, and particularly relates to a method for determining year-end fluctuating level of a regulation reservoir by considering incoming flow frequency difference.
Background
The hydroelectric energy is a high-quality and high-efficiency energy which is vigorously developed all over the world at present, and has the characteristics of cleanness, no pollution, renewability, low operation cost, quick output response and the like. Particularly, the quick response characteristic of the high-voltage power supply to the power load plays an extremely important role in the safe and stable operation of the power system, and plays an extremely important role. At present, the development and utilization mode of hydroelectric energy is mainly that a dam is built in a river channel, dispersed river channel hydraulic energy resources are concentrated and a water head is raised, and then hydraulic energy is efficiently converted into electric energy through a hydraulic power station-water turbine generator set. The types of reservoirs can be classified into daily regulation, seasonal regulation, annual regulation and perennial regulation according to the strength of the regulation performance of the reservoirs.
Generally speaking, the water coming from rivers has the characteristics of rich and withered change rule in the year and different water quantities between the years. Considering the periodicity of hydrologic years, the actual scheduling generally takes one hydrologic year as a scheduling period, and the water unevenness in the coming year can be well adjusted by adjusting the reservoir year by year. However, in the actual hydrologic process, the water quantity difference between the years also exists, so that the water quantity distribution and adjustment between the years are needed, and the water quantity distribution between the years can be realized by adjusting the reservoir. Therefore, how to determine the operation mode of the perennial regulating reservoir in a dispatching cycle has a great influence on the final power generation benefit of the perennial regulating reservoir.
Many scholars have also made relevant studies in this regard, with some success, but most of the previous studies have focused on regulating the conditions under which reservoirs operate individually for many years. With the construction and operation of a plurality of reservoirs, a cascade reservoir group with upstream and downstream water quantity and water head relation is gradually formed. After the cascade reservoir is formed, the original single-reservoir scheduling method cannot meet the demand of reservoir group combined scheduling, and the method needs to be used for researching a multi-year regulation reservoir scheduling mode in a cascade reservoir system in a targeted mode, namely determining the optimal year-end fluctuating level of the multi-year regulation reservoir in the cascade system. In addition, the research aiming at regulating the operation mode of the reservoir for many years only considers the size of the water level of the water falling at the end of the year from the average view of many years, does not consider the water difference between years, namely neglecting the influence of the water frequency difference between different years, and has certain defects and places to be improved.
Disclosure of Invention
In view of the above defects or improvement requirements of the prior art, the invention provides a method for determining year-end fluctuating level of a multi-year regulation reservoir in consideration of incoming flow frequency difference, and aims to determine optimal year-end fluctuating level of the multi-year regulation reservoir in a cascade reservoir system in consideration of incoming flow frequency difference of different years.
In order to achieve the purpose, the invention provides a method for determining the year-end fluctuating level of a multi-year-regulated reservoir by considering incoming flow frequency difference, which comprises the following steps:
s1, dispersing the range from the dead water level of a multi-year regulating reservoir in a cascade system to a normal water storage level into a series of discrete water level values according to set water level dispersion precision;
s2, taking each discrete water level value as the constraint of year-end water level of the multi-year regulating reservoir, and establishing a cascade system combined optimization scheduling model with the maximum total power generation amount as a target;
s3, taking the frequency of the incoming flow as input data of the joint optimization scheduling model, and solving the model by adopting a multi-dimensional dynamic programming algorithm to obtain the total power generation amount of the downstep system corresponding to different discrete water levels and different incoming flow years;
s4, traversing all the discrete water level values for each incoming flow frequency, and finding out the discrete water level value corresponding to the maximum generated energy as the optimal falling water level under the current incoming flow frequency;
and S5, point-drawing each incoming flow frequency and the corresponding optimal falling water level scatter diagram by taking the incoming flow frequency as an abscissa and the optimal falling water level as an ordinate, and fitting the optimal trend line of the scatter points by a polynomial on the basis of the least square principle to finally obtain the optimal falling water level under different incoming flow frequencies.
Further, the water level dispersion accuracy in step S1 is set according to the calculation accuracy requirement.
Further, the objective function of the cascade system joint optimization scheduling model is as follows:
Figure GDA0003665113510000031
wherein E is the total power generation amount of the cascade system in the whole dispatching period, T is the number of dispatching time segments of the whole dispatching period, and cascade reservoirs are numbered as 1,2,sfor the output coefficient of the s-th station，
Figure GDA0003665113510000032
For the electricity generation quote flow of the s-th reservoir in the t-th time period,
Figure GDA0003665113510000033
the average water head of the s-th reservoir in the t-th time interval is shown, and delta t is the length of a scheduling time interval.
Further, the constraint conditions of the initial and final water levels of the scheduling of the cascade system joint optimization scheduling model are as follows:
Figure GDA0003665113510000034
Figure GDA0003665113510000035
wherein Z0 sIs the water level of the s-th reservoir at the beginning of the 1 st period, Zb sThe water level of the s-th reservoir at the beginning of the entire dispatch period,
Figure GDA0003665113510000036
water level of the s-th reservoir at the end of the last period, Ze sAnd the water level of the S-th reservoir at the end of the whole dispatching period is the discrete water level value obtained in the step S1.
Furthermore, the constraint conditions of the joint optimization scheduling model further comprise a water quantity balance constraint, a reservoir capacity constraint, a lower discharge quantity constraint and an output constraint.
Further, step S4 includes:
s4.1. for the 1 st incoming flow frequency P1Go through all discrete water level values (Z)1,Z2,…,Zn) Finding out the maximum value E of the generated energyi,1The discrete water level value Z corresponding to the discrete water level value Z is calculatediAs the current incoming stream frequency P1Lower optimal falling water level Z1 *；
S4.2. for the 2 nd incoming stream frequencyRate P2Traverse all discrete water level values (Z)1,Z2,…,Zn) Finding out the maximum value E of the generated energyi,2The discrete water level value Z corresponding to the water level value is calculatediAs the current incoming water frequency P2Lower optimal falling water level Z2 *。
S4.3, repeating the process until all incoming flow frequencies P are foundj(j 1,2, …, m) the optimum falling water level Z corresponding to the maximum power generationj *。
Further, step S5 includes:
s5.1, generating the number of terms and times of a series of polynomials in a feasible range in equal step length;
s5.2, determining a polynomial structure according to the number of terms and the degree of each polynomial, and finding out the optimal polynomial coefficient and the correlation coefficient R thereof under the current structure according to scatter data and a least square principle2；
S5.3. with the correlation coefficient R2Traversing all polynomial structures to determine the optimal polynomial structure and the corresponding coefficient at the maximum target;
and S5.4, obtaining the optimal water level value of the falling water under different incoming flow frequencies according to the obtained optimal polynomial structure.
In general, the above technical solutions contemplated by the present invention can achieve the following advantageous effects compared to the prior art.
(1) The invention extracts the annual-end fluctuating level determining rule of the multi-year regulation reservoir considering the incoming flow frequency by the least square principle based on the optimal calculation result of multi-dimensional dynamic planning, compared with a fluctuating mode of a multi-year fixed water level, the extracted fluctuating rule considers the annual difference of the incoming water, can fully exert the regulation performance of the multi-year regulation reservoir, improves the water energy resource conversion efficiency and the gradient power generation amount of the cascade system, and has important significance for guiding the actual dispatching operation of the cascade reservoir group containing the multi-year regulation reservoir.
(2) The elimination rule which is obtained by extraction and considers different incoming flow frequencies determines the elimination water level at the end of the year directly through the incoming flow frequencies without other additional information, and the operability is strong. The incoming flow frequency directly reflects the size of the incoming water volume, the settlement of the falling elimination rule takes the incoming flow frequency as a decision index, the coupling relation between the incoming flow frequency (water volume) of the reservoir and the falling elimination water level (water head) can be well coordinated for many years, the overall benefit of the cascade reservoir is fully exerted, and the total generated energy of the cascade system is very close to the total generated energy under the optimal condition.
Drawings
FIG. 1 is a flow chart of a method for determining year-end fluctuating level of a multi-year-regulated reservoir in consideration of incoming flow frequency difference, provided by the invention;
FIG. 2 is a diagram of the optimal falling water map for different incoming flow frequencies provided by the present invention;
fig. 3 is an optimal falling water bitmap of different incoming flow frequencies in a dry water situation provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the respective embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Referring to fig. 1, an embodiment of the present invention provides a method for determining a year-end fluctuating level of a multi-year-adjusted reservoir in consideration of incoming flow frequency differences, including:
s1, dispersing the range from the dead water level of a multi-year regulating reservoir in a cascade system to a normal water storage level into a series of discrete water level values according to set water level dispersion precision;
specifically, the embodiment of the present invention takes a downstream step reservoir group in yamo river basin as an example to describe the method of the present invention in detail. A middle and lower river reach of the Yashujiang river is a key river reach for dry running water and power development of the Yashujiang river at present, and seven power stations including two river mouths, a Yangchan ditch, a Jinpingyi stage, an official land, a second beach and a Tongzhilin are built, wherein the two river mouth reservoir has the regulation performance for many years. The runoff data utilized in this embodiment is the runoff series data in 62 days from 6 months in 1957 to 5 months in 2019 in the drainage basin.
In order to analyze the power generation amount change condition of the cascade system under different water falling levels of the two estuary reservoirs, the embodiment of the invention takes 5m as the discrete precision (the water level discrete precision is set according to the calculation precision requirement during specific implementation), and takes the dead water level 2785m to the normal water storage level 2845m as the discrete range to obtain different discrete water level values: 2785m,2790m,2795m,2800m,2805m,2810m,2815m,2820m,2825m,2830m,2835m,2840m, and 2845 m.
S2, taking each discrete water level value as the constraint of year-end water level of the multi-year regulating reservoir, and establishing a cascade system combined optimization scheduling model by taking the maximum total power generation amount as a target;
specifically, the objective function of the cascade system joint optimization scheduling model is as follows:
Figure GDA0003665113510000051
wherein E is the total power generation amount of the cascade system in the whole dispatching period, T is the dispatching time period number of the whole dispatching period, and cascade reservoirs are numbered as 1,2,sas the output coefficient of the s-th power station,
Figure GDA0003665113510000061
for the electricity generation quote flow of the s-th reservoir in the t-th period,
Figure GDA0003665113510000062
the average water head of the s-th reservoir in the t-th time period is shown, delta t is the length of a scheduling time period, and the value of the embodiment of the invention is 1 month.
The constraints of the model include:
1) water balance constraint
Figure GDA0003665113510000063
Wherein Vs tThe storage capacity of the s-th reservoir in the t-th time period,
Figure GDA0003665113510000064
for the flow of the s-th reservoir in the t-th period, Qs tFor the discharge of the s-th reservoir during the t-th period,
Figure GDA0003665113510000065
the reject flow rate of the s-th reservoir in the t-th period,
Figure GDA0003665113510000066
the evaporation flow rate of the s-th reservoir in the t-th period.
2) Reservoir capacity constraint
Figure GDA0003665113510000067
Wherein Vs t,minIs Vs tLower limit value of (V)s t,maxIs Vs tThe upper limit value of (3).
3) Let-down flow restriction
Figure GDA0003665113510000068
Wherein Qs t,minIs Qs tLower limit value of, Qs t,maxIs Qs tThe upper limit value of (3).
4) Restraint of output
Figure GDA0003665113510000069
Wherein O iss tFor the s-th reservoir at the t-th time interval, Os t,minIs Os tThe lower limit of (C) is generally determined by the minimum allowable output, Os t,maxIs Os tThe upper limit of (d) is generally determined by the installed capacity of the power plant and the expected output.
5) Early and late scheduling period water level constraints
Figure GDA00036651135100000610
Figure GDA00036651135100000611
Wherein Z0 sIs the water level of the s-th reservoir at the beginning of the 1 st period, Zb sThe water level of the s-th reservoir at the beginning of the whole scheduling period,
Figure GDA0003665113510000071
water level of the s-th reservoir at the end of the last period, Ze sThe water level for the s-th reservoir at the end of the entire dispatch period. Z at this timee sCorresponding to the discrete water level values 2785m,2790m,2795m,2800m,2805m,2810m,2815m,2820m,2825m,2830m,2835m,2840m,2845m in step S1.
S3, taking the frequency of the incoming flow as input data of the combined optimization scheduling model, and solving the model by adopting a multi-dimensional dynamic programming algorithm to obtain the total power generation amount of the downstep system corresponding to different discrete water levels and different incoming flow years;
specifically, in order to make the joint optimization result obtained by the model have global convergence, the established joint optimization model is solved by a multidimensional dynamic programming algorithm, and the inverse equation of the algorithm core is as follows:
Figure GDA0003665113510000072
wherein, Ft *(Vt-1) Indicating that the t-th period corresponds to the state Vt-1Total reserve period benefit of time cascade power station, NtRepresenting the total step plant output, V, over the t-th time periodt-1＝(Vt-1 1,Vt-1 2,…,Vt-1 n) Is a state variable directionAmount, Qt＝(Qt 1,Qt 2,…,Qt n) 'for decision variable vector, superscript' ″ denotes vector transposition, in calculation
Figure GDA0003665113510000073
Figure GDA0003665113510000074
Are respectively dispersed into M discrete points, i.e. (V)t 1,1,Vt 1,2,…,Vt 1,M)，
Figure GDA0003665113510000075
Figure GDA0003665113510000076
S4, traversing all discrete water level values for each incoming flow frequency, and finding out the discrete water level value corresponding to the maximum generated energy as the optimal falling water level under the current incoming flow frequency;
specifically, step S4 includes
S4.1. for the 1 st incoming flow frequency P1Traversing all discrete falling water level values (Z)1,Z2,…,Zn) Finding out the maximum value E of the generated poweri,1The discrete falling water level value Z corresponding to the discrete falling water level value is calculatediAs the current incoming stream frequency P1Lower optimal falling water level Z1 *；
S4.2. for the 2 nd incoming flow frequency P2Traversing all discrete falling water level values (Z)1,Z2,…,Zn) Finding out the maximum value E of the generated energyi,2The discrete falling water level value Z corresponding to the water level value is calculatediAs the current incoming water frequency P2Lower optimal falling water level Z2 *。
S4.3, analogizing to find out all incoming flow frequencies Pj(j 1,2, …, m) the optimum falling water level Z corresponding to the maximum power generationj *Thereby obtaining a series of point data (P)j,Zj *)，(j＝1,2,…,m)。
In order to analyze the optimal water level of the maximum total cascade power generation under different incoming flow frequencies and refine a general rule to guide actual operation, the embodiment of the invention respectively calculates the 62-year runoff data, and arranges the obtained results according to the sequence from rich to poor, the optimal water level of the water and the power generation thereof under each incoming water year are shown in table 1, and the average power generation over the years is 1010.2 hundred million kWh.
TABLE 1
Figure GDA0003665113510000081
Figure GDA0003665113510000091
S5, point-drawing each incoming flow frequency and an optimal falling water level scatter diagram corresponding to the incoming flow frequency by taking the incoming flow frequency as a horizontal coordinate and the optimal falling water level as a vertical coordinate, fitting an optimal trend line of the scatter points by a polynomial on the basis of a least square principle, and finally obtaining the optimal falling water level under different incoming flow frequencies.
S5.1, generating the number and times of terms of a series of polynomials in a feasible range in an equal step length manner;
s5.2, determining a polynomial structure according to the number and the times of each polynomial, and finding out the optimal polynomial coefficient and the correlation coefficient R under the current structure according to scatter data and a least square principle2；
S5.3. with the correlation coefficient R2Traversing all polynomial structures to determine the optimal polynomial structure (number of terms and times) and corresponding coefficients at the maximum target;
and S5.4, obtaining the optimal water level value of the water falling under different incoming flow frequencies according to the obtained optimal polynomial structure.
According to the results in table 1, the embodiment of the present invention draws a scatter diagram with the incoming flow frequency as the abscissa and the optimal falling water level as the ordinate, as shown in fig. 2, it can be seen that in the relatively rich years (48.7% and below), the optimal falling water level is 2875m of the dead water level; in the relatively dry year of the incoming flow, the optimal falling water level fluctuates greatly in different years, the regularity is not strong, but the overall trend is ascending, namely, in the dry year, the optimal falling water level increases along with the increase of the frequency of the incoming flow.
Considering the practicability of the calculation result, the overall regularity of the dry year needs to be extracted to guide the scheduling operation of the actual dry year. Therefore, based on the data that the incoming flow frequency is greater than 48.7%, a scatter diagram is drawn again, and based on the principle of least squares, an optimal trend line is fitted by a polynomial, the final result is shown as a dotted line in fig. 3, and the optimal functional relationship between the incoming flow frequency of the dry year and the water drop level obtained corresponding to the result of fig. 3 is as follows:
Z＝1301.3P3-2896.7P2+2171.9P+2275.2
wherein Z represents the late year falling water level and P represents the incoming flow frequency. Correlation index R corresponding to the above formula2Is 0.73.
Therefore, under different incoming flow frequencies, the determination rule of the year-end fluctuating level of the two estuary reservoirs is as follows:
Figure GDA0003665113510000101
at this time, the falling water level of the two estuary reservoirs under different incoming flow frequencies can be determined according to the above formula. By performing a simulation calculation in this way, the annual power generation amount can be obtained as shown in table 2 (sorted by incoming flow frequency), and the annual average power generation amount is 1009.84 billion kWh.
TABLE 2
Figure GDA0003665113510000102
Figure GDA0003665113510000111
Comparing table 1 with table 2, the average power generation amount for many years in table 1 is 1010.2 hundred million kWh, and the average power generation amount for many years in table 2 is 1009.84 hundred million kWh, although the power generation amount after simulation scheduling according to the water level of the obtained settlement rules is reduced, the amplitude is not large, the absolute value is 0.36 hundred million kWh, the relative reduction amplitude is only 0.036%, and the reservoir scheduling according to the extracted settlement rules has the advantages of easy operability, practical feasibility and the like.
Furthermore, compared to the results of the multi-year fixed water-level-fluctuating mode (table 3), the multi-year average power generation in table 2 was 1009.84 billion kWh, which was 4.04 billion kWh greater than the maximum 1005.8 billion kWh in the multi-year fixed water-level-fluctuating mode, and the increase was 0.4%.
TABLE 3
End of year falling water level/m 2785 2790 2795 2800 2805 2810 2815
Step total power generation/hundred million kWh 1005.8 1005.5 1004.9 1004.3 1003.0 1001.6 999.5
End of year falling water level/m 2820 2825 2830 2835 2840 2845 ---
Cascaded Total Power Generation/hundred million kWh 997.2 994.3 990.8 986.4 981.0 973.7 ---
Therefore, the extracted falling elimination rules under different incoming flow frequencies have strong operability, and can well coordinate the coupling relation between the incoming water frequency (water quantity) and the falling elimination water level (water head) of the two estuary reservoirs, so that the overall benefit of the cascade reservoir is fully exerted, and the total generated energy of the cascade system is very close to the total generated energy under the optimal condition.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (5)

1. A method for determining year-end fluctuating level of a multi-year regulation reservoir in consideration of incoming flow frequency difference is characterized by comprising the following steps:
s1, dispersing the range from the dead water level of a multi-year regulating reservoir in a cascade system to a normal water storage level into a series of discrete water level values according to set water level dispersion precision;
s2, taking each discrete water level value as the constraint of year-end water level of the multi-year regulating reservoir, and establishing a cascade system combined optimization scheduling model with the maximum total power generation amount as a target;
s3, taking the frequency of the incoming flow as input data of the joint optimization scheduling model, and solving the model by adopting a multi-dimensional dynamic programming algorithm to obtain the total power generation amount of the downstep system corresponding to different discrete water levels and different incoming flow years;
s4, traversing all the discrete water level values for each incoming flow frequency, and finding out the discrete water level value corresponding to the maximum generated energy as the optimal falling water level under the current incoming flow frequency; step S4 includes:
s4.1. for the 1 st incoming flow frequency P1Traversing all discrete water level values Z1,Z2,…,ZnFinding out the maximum value E of the generated energyi,1The discrete water level value Z corresponding to the water level value is calculatediAs the current incoming stream frequency P1Lower optimal falling water level Z1 *；
S4.2. for the 2 nd incoming flow frequency P2Traverse all discrete water level values Z1,Z2,…,ZnFinding out the maximum value E of the generated energyi,2The discrete water level value Z corresponding to the discrete water level value Z is calculatediAs the current incoming water frequency P2Lower optimal falling water level Z2 *；
S4.3, repeating the process until all incoming flow frequencies P are foundjOptimal falling water level Z corresponding to maximum generated energyj *(ii) a Wherein, i is 1,2, n, j is 1,2, …, m, m represents the incoming flow frequency discrete number, n represents the water level discrete number;
s5, point-drawing each incoming flow frequency and an optimal falling water level scatter diagram corresponding to the incoming flow frequency by taking the incoming flow frequency as a horizontal coordinate and the optimal falling water level as a vertical coordinate, and fitting an optimal trend line of the scatter points by a polynomial on the basis of a least square principle to finally obtain the optimal falling water level under different incoming flow frequencies; step S5 includes:
s5.1, generating the number and times of terms of a series of polynomials in a feasible range in an equal step length manner;
s5.2, determining a polynomial structure according to the number and the times of each polynomial, and finding out the optimal polynomial coefficient and the correlation coefficient R under the current structure according to scatter data and a least square principle2；
S5.3. with a correlation coefficient R2Traversing all polynomial structures to determine the optimal polynomial structure and the corresponding coefficient at the maximum target;
and S5.4, obtaining the optimal water level value of the water falling under different incoming flow frequencies according to the obtained optimal polynomial structure.
2. The method for determining the year-end fluctuating level of a multi-year regulated reservoir in consideration of incoming flow frequency difference as claimed in claim 1, wherein the water level dispersion accuracy in step S1 is set according to the calculation accuracy requirement.
3. The method for determining the year-end fluctuating level of the multi-year regulated reservoir in consideration of incoming flow frequency difference according to claim 1 or 2, wherein the objective function of the cascade system joint optimization scheduling model is as follows:
Figure FDA0003665113500000021
wherein E is the total power generation amount of the cascade system in the whole dispatching period, T is the number of dispatching time segments of the whole dispatching period, and cascade reservoirs are numbered as 1,2,sis the output coefficient of the s-th station, qt sFor the electricity generation reference flow of the s-th reservoir in the t-th period, Ht sThe average water head of the s-th reservoir in the t-th time interval is shown, and delta t is the length of a scheduling time interval.
4. The method for determining the year-end fluctuating level of the multi-year regulated reservoir in consideration of incoming flow frequency difference as claimed in claim 3, wherein the constraint conditions of the initial and end water levels of the scheduling of the cascade system joint optimization scheduling model are as follows:
Figure FDA0003665113500000022
Figure FDA0003665113500000023
wherein Z0 sIs the water level of the s-th reservoir at the beginning of the 1 st period, Zb sThe water level of the s-th reservoir at the beginning of the entire dispatch period,
Figure FDA0003665113500000024
water level of the s-th reservoir at the end of the last period, Ze sThe water level of the S-th reservoir at the end of the whole dispatching period is the discrete water level value obtained in the step S1.
5. The method for determining the year-end fluctuating level of a multi-year regulation reservoir in consideration of incoming flow frequency difference as claimed in claim 4, wherein the combined optimization scheduling model constraint conditions further comprise a water balance constraint, a reservoir capacity constraint, a let-down flow constraint and an output constraint.
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