A rapid generation method for medium- and long-term power generation scheduling decisions of a reservoir for flood control and water storage

Abstract

The present invention provides a method for quickly generating medium- and long-term power generation scheduling decisions for flood control and water storage of a reservoir, belonging to the field of medium- and long-term reservoir scheduling decisions. According to the power generation amount, power generation water consumption, and reservoir storage capacity curve data of the long-term actual operation of the reservoir after commissioning, the power generation water consumption rate of the reservoir is deduced, and a data set of power generation water consumption rates is constructed; based on the long-term medium- and long-term inflow data of the reservoir and the reservoir outflow flow demand data, according to the time requirements for reserving the flood control storage capacity of the reservoir, the time spans of the flood control scheduling period and the water storage scheduling period of the reservoir are clarified, and reservoir scheduling decision information such as the medium- and long-term scheduling drawdown timing, drawdown level, and available water storage capacity of the reservoir is determined.

Description

Technical Field

[0001] The present invention relates to the field of medium- and long-term reservoir operation decision-making, and particularly to a rapid generation method for medium- and long-term power generation operation decision-making of a reservoir for flood control and water storage. Background Art

[0002] Combined with the inflow and water level change laws of the reservoir, the whole-cycle operation process of the reservoir can be divided into the drawdown operation period, the flood control operation period, and the water storage operation period. During the drawdown operation period, the reservoir operation mainly focuses on power generation and water supply to the downstream. With less inflow, the reservoir reduces its storage capacity and increases the discharge flow. During the flood control operation period, with more inflow, the reservoir operation mainly focuses on flood control, taking power generation into account, and operates according to the flood limit water level. During the water storage operation period, the inflow of the reservoir shows a decreasing trend. On the premise of meeting the downstream water use demand, the reservoir operation mainly focuses on water storage to raise the reservoir water level and strive to fill the reservoir to its full capacity at the end of the operation period. Thus, it can be seen that the whole-cycle operation of the reservoir needs to balance the requirements of power generation, flood control, water storage, etc. For the controlling reservoir in the upper reaches of the basin, with a large storage capacity and strong regulation ability, if it fails to combine the medium- and long-term inflow of the reservoir and handle the key information of reservoir operation such as the drawdown timing, drawdown water level, and water storage process, it may affect the benefits of the reservoir itself and the downstream reservoirs.

[0003] To balance the benefits of reservoir power generation, flood control, water storage, etc., at present, most methods adopt the way of constructing a multi-objective operation model and applying a multi-objective intelligent optimization algorithm for solution to obtain the reservoir operation strategy and guide the reservoir operation. However, this method has several deficiencies: First, the construction of the multi-objective operation model is complex, and the solution results are presented in the form of a non-dominated solution set, and it is impossible to directly screen out the power generation operation decision of the reservoir that takes both flood control and water storage into account; Second, the model calculation and solution time is relatively long, and there are random factors in the multi-objective intelligent optimization algorithm, and the obtained operation decision is not stable. In view of this, a rapid generation method for medium- and long-term power generation operation decision-making of a reservoir for flood control and water storage is proposed. Combining the medium- and long-term inflow data of the reservoir and comprehensively considering the whole-cycle operation process such as the drawdown operation period, the flood control operation period, and the water storage operation period of the reservoir, it can rapidly generate the reservoir operation decision and give full play to the comprehensive benefits of the reservoir. Summary of the Invention

[0004] The purpose of the present invention is to provide a rapid generation method for medium- and long-term power generation operation decision-making of a reservoir for flood control and water storage in view of the above deficiencies of the prior art, so as to provide technical support for guiding reservoir operation.

[0005] To achieve the above purpose, the present invention adopts the following technical solutions:

[0006] The present invention provides a rapid generation method for medium- and long-term power generation operation decision-making of a reservoir for flood control and water storage, including:

[0007] S1. Collect the data of the annual power generation, water consumption for power generation, and the reservoir storage curve during the long-term actual operation of the reservoir, calculate the annual water consumption rate for power generation of the reservoir, and construct a data set of water consumption rates for power generation;

[0008] S2. Collect the long-term medium- and long-term inflow data at the dam site of the reservoir and the data of the reservoir outflow demand, and clarify the time spans of the flood control scheduling period and the water storage scheduling period of the reservoir according to the time requirements for reserving the flood control storage capacity of the reservoir;

[0009] S3. Adopt the dynamic time warping algorithm to calculate the similarity between the annual runoff data at the dam site before the reservoir operation and the inflow runoff series after the reservoir operation, select the water consumption rate for power generation corresponding to the inflow runoff series with the highest similarity after the reservoir operation, construct a matching matrix of inflow runoff and water consumption rate for power generation, and set the number of iterative calculations ;

[0010] S4. Assume the reservoir drawdown time node for the -th iterative calculation, combine the reservoir outflow demand from the reservoir drawdown time node to the end of the water storage scheduling period, and calculate the maximum water storage volume and water consumption for power generation from the reservoir drawdown time node to the end of the water storage scheduling period according to the water balance formula;

[0011] S5. According to the maximum water storage volume from the reservoir drawdown time node assumed in the -th iterative calculation in S4 to the end of the water storage scheduling period, determine the water level at the reservoir drawdown time node, and calculate the power generation during the reservoir drawdown scheduling period based on the water consumption rate for power generation of the reservoir;

[0012] S6. According to the water consumption for power generation from the reservoir drawdown time node assumed in the -th iterative calculation in S4 to the end of the water storage scheduling period, calculate the power generation during the flood control scheduling period and the water storage scheduling period of the reservoir based on the water consumption rate for power generation of the reservoir;

[0013] S7. Calculate the total power generation during the reservoir drawdown scheduling period, flood control scheduling period, and water storage scheduling period for the -th iterative calculation, set , return to S4, re-assume the reservoir drawdown time node, and determine the reservoir scheduling decision information on the drawdown timing, drawdown water level, and water storage volume for the medium- and long-term reservoir scheduling.

[0014] Furthermore, in S1, the annual power generation , water consumption for power generation , and the reservoir storage curve during the long-term actual operation of the reservoir are specifically:

[0015] PG = [ pg 1 ( 1 ) , pg 1 ( 2 ) , ⋯ , pg 1 ( t ) , ⋯ , pg 1 ( T ) pg 2 ( 1 ) , pg 2 ( 2 ) , ⋯ , pg 2 ( t ) , ⋯ , pg 2 ( T ) ... pg y ( 1 ) , pg y ( 2 ) , ⋯ , pg y ( t ) , ⋯ , pg y ( T ) ... pg Y * ( 1 ) , pg Y * ( 2 ) , ⋯ , pg Y * ( t ) , ⋯ , pg Y * ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y * ] ;

[0016] WG = [ wg 1 ( 1 ) , wg 1 ( 2 ) , ⋯ , wg 1 ( t ) , ⋯ , wg 1 ( T ) wg 2 ( 1 ) , wg 2 ( 2 ) , ⋯ , wg 2 ( t ) , ⋯ , wg 2 ( T ) ... wg y ( 1 ) , wg y ( 2 ) , ⋯ , wg y ( t ) , ⋯ , wg y ( T ) ... wg Y * ( 1 ) , wg Y * ( 2 ) , ⋯ , wg Y * ( t ) , ⋯ , wg Y * ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y * ] ;

[0017] VZ = [ v 1 , v 2 ⋯ , v m , ⋯ , v M z 1 , z 2 ⋯ , z m , ⋯ , z M ] ⊤ , m ∈ [ 1 , M ] ;

[0018] Among them, represents the power generation of the reservoir in the th year and the th time period; represents the total number of time periods; represents the total number of years since the reservoir was put into operation; represents the th year and the th time period of the reservoir's water consumption for power generation; and respectively represent the th water level and storage capacity data in the reservoir storage capacity curve; represents the number of data of water level and storage capacity in the reservoir storage capacity curve;

[0019] In the above S1, the annual power generation water consumption rate of the reservoir is derived, and a data set of power generation water consumption rates is constructed, specifically:

[0020] η = [ η 1 , η 2 , ⋯ , η y , ⋯ , η Y * ] ;

[0021] ;

[0022] Among them, represents the data set of the reservoir's power generation water consumption rate; represents the th year's power generation water consumption rate of the reservoir.

[0023] Furthermore, in the above S2, long-term inflow data and reservoir outflow demand data at the reservoir dam site are collected, specifically:

[0024] Q = [ Q 1 in ( 1 ) , Q 1 in ( 2 ) , ⋯ , Q 1 in ( t ) , ⋯ , Q 1 in ( T ) Q 2 in ( 1 ) , Q 2 in ( 2 ) , ⋯ , Q 2 in ( t ) , ⋯ , Q 2 in ( T ) .... Q y in ( 1 ) , Q y in ( 2 ) , ⋯ , Q y in ( t ) , ⋯ , Q y in ( T ) .... Q Y in ( 1 ) , Q Y in ( 2 ) , ⋯ , Q Y in ( t ) , ⋯ , Q Y in ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y ] ;

[0025] q = [ q 1 out ( 1 ) , q 1 out ( 2 ) , ⋯ , q 1 out ( t ) , ⋯ , q 1 out ( T ) q 2 out ( 1 ) , q 2 out ( 2 ) , ⋯ , q 2 out ( t ) , ⋯ , q 2 out ( T ) ... q y out ( 1 ) , q y out ( 2 ) , ⋯ , q y out ( t ) , ⋯ , q y out ( T ) ... q Y out ( 1 ) , q Y out ( 2 ) , ⋯ , q Y out ( t ) , ⋯ , q Y out ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y ] ;

[0026] Among them, and respectively represent the inflow and outflow demand in the th year and the th time period of the reservoir; represents the total number of years of long-term inflow at the reservoir;

[0027] In the above S2, according to the time requirements for the reserved flood control storage capacity of the reservoir, the time spans of the reservoir flood control operation period and the water storage operation period are as follows:

[0028] duT fc = T im − T fc + 1 , t ∈ [ 1 , T ] ;

[0029] duT im = T − T im t ∈ [ 1 , T ] ;

[0030] Among them, and represent the time spans of the flood control operation period and the impoundment operation period of the reservoir respectively; and represent the start time and the end time of the flood control operation period of the reservoir respectively.

[0031] Furthermore, in the step S3, the dynamic time warping algorithm is adopted to calculate the similarity between the annual runoff data at the dam site before the reservoir is put into operation and the inflow runoff series after the reservoir is put into operation. Specifically:

[0032] dist j , i = dtw { [ Q j in ( 1 ) , Q j in ( 2 ) , ⋯ , Q j in ( T ) ] , [ Q i in ( 1 ) , Q i in ( 2 ) , ⋯ , Q i in ( T ) ] } j ∈ [ 1 , Y Before investment ] , i ∈ [ Y Before investment + 1 , Y After investment ] ;

[0033] Among them, represents the dynamic time warping distance between the runoff at the dam site in the th year before the reservoir is put into operation and the runoff in the th year after the reservoir is put into operation; represents the dynamic time warping algorithm; and represent the total number of years before and after the reservoir is put into operation respectively;

[0034] In the step S3, the power generation water consumption rate corresponding to the inflow runoff series with the highest similarity after the reservoir is put into operation is selected to construct a matching matrix of the inflow runoff and the power generation water consumption rate. Specifically:

[0035] M = [ Q 1 in ( 1 ) , Q 1 in ( 2 ) , ⋯ , Q 1 in ( t ) , ⋯ , Q 1 in ( T ) , η 1 i * Q 2 in ( 1 ) , Q 2 in ( 2 ) , ⋯ , Q 2 in ( t ) , ⋯ , Q 2 in ( T ) , η 2 i * .... Q j in ( 1 ) , Q j in ( 2 ) , ⋯ , Q j in ( t ) , ⋯ , Q j in ( T ) , η j i * .... Q Y Before investment in ( 1 ) , Q Y Before investment in ( 2 ) , ⋯ , Q Y Before investment in ( t ) , ⋯ , Q Y Before investment in ( T ) , η Y Before investment i * Q Y Before investment + 1 in ( 1 ) , Q Y Before investment + 1 in ( 2 ) , ⋯ , Q Y Before investment + 1 in ( t ) , ⋯ , Q Y Before investment + 1 in ( T ) , η 1 .... Q Y Before investment + Y * in ( 1 ) , Q Y Before investment + Y * in ( 2 ) , ⋯ , Q Y Before investment + Y * in ( t ) , ⋯ , Q Y Before investment + Y * in ( T ) , η Y * ] ;

[0036] Among them, represents the matching matrix of the inflow runoff and the power generation water consumption rate after the reservoir is put into operation; represents the power generation water consumption rate corresponding to the inflow runoff in the th year after the reservoir is put into operation, which has the highest similarity with the runoff at the dam site in the th year before the reservoir is put into operation.

[0037] Furthermore, in the step S4, according to the water balance formula, the maximum water storage volume from the reservoir drawdown time node to the end of the impoundment operation period is calculated. Specifically:

[0038] { ∑ t = T k , y d + 1 T im [ Q y in ( t ) − q y out ( t ) ] × Δ t ≥ V k , y fc ∑ t = T im + 1 T [ Q y in ( t ) − q y out ( t ) ] × Δ t ≥ V k , y im V k , y im ≥ V r fc V k , y fc + V k , y im ≤ V N , y ∈ [ 1 , Y ] ;

[0039] ;

[0040] Among them, and respectively represent the flood control reserved storage capacity and regulation storage capacity of the reservoir; represents the th iteration calculation assumed drawdown time node of the reservoir; and respectively represent the th iteration calculation assumed drawdown time node of the reservoir, the available water storage volume during the flood control operation period and the water storage operation period; represents the calculation time period length; represents the th iteration calculation assumed drawdown time node of the reservoir to the maximum available water storage volume at the end of the water storage operation period;

[0041] In the above S4, the power generation water consumption is specifically:

[0042] ;

[0043] ;

[0044] Among them, represents the th iteration calculation assumed drawdown time node of the reservoir to the power generation water consumption at the end of the water storage operation period; represents the th time period power generation flow rate of the reservoir; represents the rated flow rate of the reservoir unit.

[0045] Furthermore, in the above S5, to determine the water level of the reservoir drawdown time node, specifically:

[0046] ;

[0047] Among them, represents the th iteration calculation assumed drawdown time node water level of the reservoir; represents the reservoir normal storage level corresponding storage capacity; represents the storage capacity curve interpolation function. When the reservoir storage capacity is known, the corresponding water level is inversely deduced through the reservoir storage capacity curve interpolation;

[0048] In the above S5, to calculate the power generation amount during the reservoir drawdown operation period, specifically:

[0049] P k , y d = [ ∑ t = 1 T k , y d Q y in ( t ) × Δ t + V k , y max ] × η y * ;

[0050] Among them, represents the The electricity generation during the drawdown scheduling period of the reservoir in the th year is calculated in the th iteration; represents the power generation water consumption rate corresponding to the runoff sequence after the commissioning of the reservoir with the highest similarity to the annual inflow runoff in the

[0051] Furthermore, in the said S6, the electricity generation during the flood control scheduling period and the water storage scheduling period of the reservoir is calculated as follows:

[0052] ;

[0053] wherein, represents the electricity generation from the drawdown time node of the reservoir in the th iteration to the end of the water storage scheduling period in the th year.

[0054] Furthermore, in the said S7, the total electricity generation during the drawdown scheduling period, the flood control scheduling period and the water storage scheduling period of the reservoir calculated in the th iteration is calculated as follows:

[0055] ;

[0056] wherein, represents the total electricity generation of the reservoir calculated in the th iteration;

[0057] Let , return to step S4, re-assume the drawdown time node of the reservoir, and after multiple iterations of calculation, obtain the total electricity generation vector of the reservoir, specifically:

[0058] P y = [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] k ∈ [ 1 , K ] ;

[0059] wherein, represents the total electricity generation vector of the reservoir in the th year; represents the total number of iterations;

[0060] In the said S7, the reservoir operation decision-making information such as the drawdown timing, drawdown water level and available water storage volume for the medium- and long-term reservoir operation is determined as follows:

[0061] { k y * = argmax [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] Z k y * d = f ( V N max − V k y * max , VZ ) W k y * fd = ∑ t = T k y * d + 1 T q y fd ( t ) × Δ t ;

[0062] wherein, represents the number of iterations corresponding to the maximum total electricity generation of the reservoir in the th year; represents the drawdown water level corresponding to the drawdown time with the maximum total electricity generation of the reservoir in the th year; represents the th year of the reservoir in the The maximum water storage volume from the iterative drawdown time node to the end of the water storage operation period.

[0063] The beneficial effects of the present invention are as follows: A rapid generation method for medium- and long-term power generation scheduling decisions of a reservoir that takes into account flood control and water storage is proposed for the first time. Considering the flood control and water storage requirements of reservoir operation, it can quickly generate reservoir power generation scheduling decision information, including drawdown levels, drawdown timings, water storage volumes, etc., providing a reference basis for the full-cycle operation of the reservoir.

[0064] The rapid generation method for medium- and long-term power generation scheduling decisions of a reservoir that takes into account flood control and water storage proposed by the present invention has stable solutions, a simple calculation process, and a relatively fast calculation speed compared with the multi-objective scheduling calculation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flowchart of a rapid generation method for medium- and long-term power generation scheduling decisions of a reservoir for flood control and water storage;

[0066] Figure 2 is a schematic diagram of an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0068] Embodiment:

[0069] Please refer to Figure 1 A rapid generation method for medium- and long-term power generation scheduling decisions of a reservoir for flood control and water storage, characterized by comprising:

[0070] S1. Collect data on the power generation and water consumption for power generation during the long-term actual operation of the reservoir after it is put into operation, as well as data on the reservoir storage capacity curve, and calculate the annual power generation water consumption rate of the reservoir to construct a data set of power generation water consumption rates;

[0071] S2. Collect long-term medium- and long-term inflow data at the reservoir dam site and data on the required outflow of the reservoir, and clarify the time spans of the flood control operation period and the water storage operation period of the reservoir according to the time requirements for reserving the flood control storage capacity of the reservoir;

[0072] S3. Use the dynamic time warping algorithm to calculate the similarity between the annual runoff data at the reservoir dam site before the reservoir is put into operation and the inflow runoff series after the reservoir is put into operation, select the power generation water consumption rate corresponding to the inflow runoff series with the highest similarity after the reservoir is put into operation, construct a matching matrix of inflow runoff and power generation water consumption rate, and set the number of iterative calculations ;

[0073] S4. Assume the The reservoir drawdown time node of the secondary iterative calculation, combined with the reservoir discharge flow demand from the reservoir drawdown time node to the end of the water storage operation period, calculates the maximum water storage volume and power generation water consumption from the reservoir drawdown time node to the end of the water storage operation period according to the water balance formula;

[0074] S5. According to the maximum water storage volume from the assumed reservoir drawdown time node to the end of the water storage operation period in the S4 iteration calculation, determine the water level of the reservoir drawdown time node, and calculate the power generation amount during the reservoir drawdown operation period based on the reservoir power generation water consumption rate;

[0075] S6. According to the power generation water consumption from the assumed reservoir drawdown time node to the end of the water storage operation period in the S4 iteration calculation, calculate the power generation amount during the reservoir flood control operation period and the water storage operation period based on the reservoir power generation water consumption rate;

[0076] S7. Calculate the total power generation amount during the reservoir drawdown operation period, the flood control operation period, and the water storage operation period in the iteration calculation, let , return to the S4, re-assume the reservoir drawdown time node, and determine the reservoir operation decision information on the drawdown timing, drawdown water level, and water storage volume for the medium- and long-term reservoir operation.

[0077] In the S1, the power generation amount , the power generation water consumption during the long-term actual operation after the reservoir is put into operation, and the reservoir storage capacity curve are specifically:

[0078] PG = [ pg 1 ( 1 ) , pg 1 ( 2 ) , ⋯ , pg 1 ( t ) , ⋯ , pg 1 ( T ) pg 2 ( 1 ) , pg 2 ( 2 ) , ⋯ , pg 2 ( t ) , ⋯ , pg 2 ( T ) ... pg y ( 1 ) , pg y ( 2 ) , ⋯ , pg y ( t ) , ⋯ , pg y ( T ) ... pg Y * ( 1 ) , pg Y * ( 2 ) , ⋯ , pg Y * ( t ) , ⋯ , pg Y * ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y * ] ;

[0079] WG = [ wg 1 ( 1 ) , wg 1 ( 2 ) , ⋯ , wg 1 ( t ) , ⋯ , wg 1 ( T ) wg 2 ( 1 ) , wg 2 ( 2 ) , ⋯ , wg 2 ( t ) , ⋯ , wg 2 ( T ) ... wg y ( 1 ) , wg y ( 2 ) , ⋯ , wg y ( t ) , ⋯ , wg y ( T ) ... wg Y * ( 1 ) , wg Y * ( 2 ) , ⋯ , wg Y * ( t ) , ⋯ , wg Y * ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y * ] ;

[0080] VZ = [ v 1 , v 2 ⋯ , v m , ⋯ , v M z 1 , z 2 ⋯ , z m , ⋯ , z M ] ⊤ , m ∈ [ 1 , M ] ;

[0081] Among them, represents the reservoir power generation amount in the th year and the th time period; represents the total number of time periods; represents the total number of years since the reservoir was put into operation; represents the reservoir power generation water consumption in the th year and the th time period; and respectively represent the th water level and storage capacity data in the reservoir storage capacity curve; represents the total number of years since the reservoir was put into operation; Indicates the total number of time periods; Indicates the number of data points of water level and reservoir capacity in the reservoir capacity curve;

[0082] In step S1, calculate the annual power generation water consumption rate of the reservoir and construct a data set of power generation water consumption rates, specifically:

[0083] η = [ η 1 , η 2 , ⋯ , η y , ⋯ , η Y * ] ;

[0084] ;

[0085] Among them, Indicates the data set of the reservoir's power generation water consumption rate; Indicates the annual power generation water consumption rate of the reservoir.

[0086] In step S2, collect long-term inflow data at the reservoir dam site and reservoir outflow demand data, specifically:

[0087] Q = [ Q 1 in ( 1 ) , Q 1 in ( 2 ) , ⋯ , Q 1 in ( t ) , ⋯ , Q 1 in ( T ) Q 2 in ( 1 ) , Q 2 in ( 2 ) , ⋯ , Q 2 in ( t ) , ⋯ , Q 2 in ( T ) .... Q y in ( 1 ) , Q y in ( 2 ) , ⋯ , Q y in ( t ) , ⋯ , Q y in ( T ) .... Q Y in ( 1 ) , Q Y in ( 2 ) , ⋯ , Q Y in ( t ) , ⋯ , Q Y in ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y ] ;

[0088] q = [ q 1 out ( 1 ) , q 1 out ( 2 ) , ⋯ , q 1 out ( t ) , ⋯ , q 1 out ( T ) q 2 out ( 1 ) , q 2 out ( 2 ) , ⋯ , q 2 out ( t ) , ⋯ , q 2 out ( T ) ... q y out ( 1 ) , q y out ( 2 ) , ⋯ , q y out ( t ) , ⋯ , q y out ( T ) ... q Y out ( 1 ) , q Y out ( 2 ) , ⋯ , q Y out ( t ) , ⋯ , q Y out ( T ) ] , t ∈ [ 1 , T ], y ∈ [ 1 , Y ] ;

[0089] Among them, and respectively indicate the inflow and outflow demand of the reservoir in the th year and the th time period; Indicates the total number of years of long-term inflow at the reservoir;

[0090] In step S2, according to the time requirements for the flood control reserve capacity of the reservoir, the time spans of the reservoir flood control period and the water storage period are as follows:

[0091] duT fc = T im − T fc + 1 , t ∈ [ 1 , T ] ;

[0092] duT im = T − T im t ∈ [ 1 , T ] ;

[0093] Among them, and respectively indicate the time spans of the reservoir flood control period and the water storage period; and respectively indicate the start and end times of the reservoir flood control period;

[0094] In step S3, use the dynamic time warping algorithm to calculate the similarity between the annual runoff data at the reservoir dam site before the reservoir is put into operation and the inflow runoff series after the reservoir is put into operation, specifically:

[0095] dist j , i = dtw { [ Q j in ( 1 ) , Q j in ( 2 ) , ⋯ , Q j in ( T ) ] , [ Q i in ( 1 ) , Q i in ( 2 ) , ⋯ , Q i in ( T ) ] } j ∈ [ 1 , Y Before investment ] , i ∈ [ Y Before investment + 1 , Y After investment ] ;

[0096] Among them, represents the dynamic time warping distance between the runoff at the dam site in the th year before the reservoir is put into operation and the runoff in the th year after the reservoir is put into operation; represents the dynamic time warping algorithm; and respectively represent the total number of years before and after the reservoir is put into operation;

[0097] In the step S3, select the power generation water consumption rate corresponding to the runoff series with the highest similarity after the reservoir is put into operation, and construct a matching matrix of the incoming runoff and the power generation water consumption rate, specifically:

[0098] M = [ Q 1 in ( 1 ) , Q 1 in ( 2 ) , ⋯ , Q 1 in ( t ) , ⋯ , Q 1 in ( T ) , η 1 i * Q 2 in ( 1 ) , Q 2 in ( 2 ) , ⋯ , Q 2 in ( t ) , ⋯ , Q 2 in ( T ) , η 2 i * .... Q j in ( 1 ) , Q j in ( 2 ) , ⋯ , Q j in ( t ) , ⋯ , Q j in ( T ) , η j i * .... Q Y Before investment in ( 1 ) , Q Y Before investment in ( 2 ) , ⋯ , Q Y Before investment in ( t ) , ⋯ , Q Y Before investment in ( T ) , η Y Before investment i * Q Y Before investment + 1 in ( 1 ) , Q Y Before investment + 1 in ( 2 ) , ⋯ , Q Y Before investment + 1 in ( t ) , ⋯ , Q Y Before investment + 1 in ( T ) , η 1 .... Q Y Before investment + Y * in ( 1 ) , Q Y Before investment + Y * in ( 2 ) , ⋯ , Q Y Before investment + Y * in ( t ) , ⋯ , Q Y Before investment + Y * in ( T ) , η Y * ] ;

[0099] Among them, represents the matching matrix of the incoming runoff and the power generation water consumption rate after the reservoir is put into operation; represents the power generation water consumption rate corresponding to the incoming runoff in the th year after the reservoir is put into operation, which has the highest similarity with the runoff at the dam site in the th year before the reservoir is put into operation.

[0100] In the step S4, according to the water balance formula, calculate the maximum water storage volume from the reservoir drawdown time node to the end of the water storage operation period, specifically:

[0101] { ∑ t = T k , y d + 1 T im [ Q y in ( t ) − q y out ( t ) ] × Δ t ≥ V k , y fc ∑ t = T im + 1 T [ Q y in ( t ) − q y out ( t ) ] × Δ t ≥ V k , y im V k , y im ≥ V r fc V k , y fc + V k , y im ≤ V N , y ∈ [ 1 , Y ] ;

[0102] ;

[0103] Among them, and respectively represent the flood control storage capacity and the regulating storage capacity reserved by the reservoir; represents the drawdown time node assumed in the th year and the th iteration calculation of the reservoir; and respectively represent the water storage volumes that can be stored during the flood control operation period and the water storage operation period under the drawdown time node assumed in the th year and the th iteration calculation of the reservoir; represents the length of the calculation time period; represents the maximum water storage volume that can be stored from the drawdown time node assumed in the th year and the th iteration calculation of the reservoir to the end of the water storage operation period;

[0104] In the step S4, the power generation water consumption is specifically:

[0105] ;

[0106] ;

[0107] Among them, represents the power generation water consumption from the assumed water level drawdown time node to the end of the water storage operation period in the th year of the reservoir's th iterative calculation; represents the power generation flow rate during the th period in the th year of the reservoir; represents the rated flow rate of the reservoir's generating units.

[0108] In the above S5, to determine the water level at the reservoir's water level drawdown time node, specifically:

[0109] ;

[0110] Among them, represents the water level at the assumed water level drawdown time node in the th year of the reservoir's th iterative calculation; represents the storage capacity corresponding to the normal storage water level of the reservoir; represents the interpolation function of the storage capacity curve. When the reservoir's storage capacity is known, the corresponding water level is inversely deduced through interpolation of the reservoir's storage capacity curve;

[0111] In the above S5, to calculate the power generation during the reservoir's water level drawdown operation period, specifically:

[0112] P k , y d = [ ∑ t = 1 T k , y d Q y in ( t ) × Δ t + V k , y max ] × η y * ;

[0113] Among them, represents the power generation during the water level drawdown operation period of the reservoir in the th year in the th iterative calculation; represents the power generation water consumption rate corresponding to the runoff sequence after the operation of the reservoir with the highest similarity to the annual inflow runoff in the th year.

[0114] In the above S6, to calculate the power generation during the reservoir's flood control operation period and water storage operation period, specifically:

[0115] ;

[0116] Among them, represents the power generation from the water level drawdown time node to the end of the water storage operation period of the reservoir in the th year in the th iterative calculation.

[0117] In the above S7, to calculate the The total power generation during the reservoir water level drawdown scheduling period, flood control scheduling period, and water storage scheduling period is calculated in the

[0118] ;

[0119] Among them, represents the total power generation of the reservoir calculated in the th iteration;

[0120] Let , return to step S4, re-assume the reservoir water level drawdown time node, and after multiple iterations of calculation, obtain the total power generation vector of the reservoir, specifically:

[0121] P y = [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] k ∈ [ 1 , K ] ;

[0122] Among them, represents the total power generation vector of the reservoir in the th year; represents the total number of iterations;

[0123] In the above S7, determine the reservoir scheduling decision information such as the medium- and long-term scheduling water level drawdown timing, water level drawdown, and available water storage capacity of the reservoir, specifically:

[0124] { k y * = argmax [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] Z k y * d = f ( V N max − V k y * max , VZ ) W k y * fd = ∑ t = T k y * d + 1 T q y fd ( t ) × Δ t ;

[0125] Among them, represents the number of iterations corresponding to the maximum total power generation of the reservoir in the th year; represents the water level drawdown corresponding to the water level drawdown time with the maximum total power generation of the reservoir in the th year; represents the maximum water storage capacity from the th iteration water level drawdown time node of the reservoir in the th year to the end of the water storage scheduling period.

[0126] Through the calculation of the multi-year runoff data of the reservoir, the average water level drawdown of the reservoir over the years is 1821m, and the average water level drawdown timing with the maximum total power generation is in the middle of June. The scheduling process is as Figure 2 shown.

[0127] The above embodiments only represent the implementation manners of the present invention, and the description is relatively specific and detailed, but it cannot be understood as a limitation to the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several deformations and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be based on the appended claims.

Claims

1. A method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs, characterized in that: include: S1. Collect the data of actual power generation, power generation water consumption, and reservoir capacity curve of the long-term operation of the reservoir, deduce the annual power generation water consumption rate of the reservoir, and construct the power generation water consumption rate data set; S2. Collect the long-term inflow data and outflow demand data of the reservoir dam site, and clarify the time span of the reservoir flood control scheduling period and water storage scheduling period according to the time requirements of the reservoir reserved flood control storage capacity; S3. Use the dynamic time normalization algorithm to calculate the similarity between the runoff data of the dam site each year before the reservoir is put into operation and the runoff series after the reservoir is put into operation. Select the runoff series after the reservoir is put into operation with the highest similarity and the corresponding power generation water consumption rate. Construct a matching matrix between the runoff and the power generation water consumption rate. Set the number of iterative calculations to ; S4. Assume The maximum water storage capacity and water consumption for power generation from the reservoir drawdown time node to the end of the water storage scheduling period are calculated based on the reservoir drawdown time node calculated in the first iteration, combined with the reservoir outflow demand from the reservoir drawdown time node to the end of the water storage scheduling period, according to the water balance formula; S5. According to S4, The maximum water storage capacity from the assumed reservoir drawdown time node to the end of the water storage scheduling period is calculated in the first iteration, the water level at the reservoir drawdown time node is determined, and the power generation during the reservoir drawdown scheduling period is calculated based on the reservoir power generation water consumption rate; S6. According to S4, The first iteration calculates the water consumption for power generation from the assumed reservoir drawdown time node to the end of the water storage scheduling period, and calculates the power generation during the reservoir flood control scheduling period and the water storage scheduling period based on the reservoir power generation water consumption rate; S7. Calculate the The total power generation during the reservoir drawdown operation period, flood control operation period and water storage operation period is calculated by the iteration. , return to S4, re-assume the reservoir drawdown time node, and determine the reservoir scheduling decision information of the reservoir drawdown timing, drawdown water level, and water storage capacity in the medium and long term.

2. The method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 1 is characterized in that: In S1, the actual power generation of the reservoir during the long operation period , Water consumption for power generation , and the reservoir capacity curve , specifically: ； ； ； in, Reservoir Year Reservoir power generation during the period; Indicates the total number of time periods; It indicates the total number of years the reservoir has been in operation; Reservoir Year Water consumption of reservoir for power generation during the period; and Respectively represent the first Water level and reservoir capacity data; Represents the number of data points of water level and storage capacity in the reservoir storage capacity curve; In S1, the annual power generation water consumption rate of the reservoir is calculated to construct a power generation water consumption rate data set, which is specifically: ； ； in, Represents the reservoir power generation water consumption rate data set; Indicates Annual water consumption rate of reservoir power generation.

3. The method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 2 is characterized by: In S2, the medium- and long-term inflow data of the reservoir dam site and the outflow demand data of the reservoir are collected, specifically: ； ； in, and Respectively represent the reservoir Year Inbound and outbound traffic demand during the time period; It represents the total number of years of medium- and long-term inflow into the reservoir in the long series; In S2, according to the time requirement for the reservoir to reserve flood control storage capacity, the time span of the reservoir flood control scheduling period and the water storage scheduling period is specifically: ； ； in, and They represent the time span of the reservoir flood control operation period and water storage operation period respectively; and They respectively represent the beginning and end time of the reservoir flood control operation period.

4. The method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 3 is characterized by: In S3, a dynamic time warping algorithm is used to calculate the similarity between the annual dam site runoff data before the reservoir is put into operation and the inflow runoff series after the reservoir is put into operation, specifically: ； in, It means that before the reservoir is put into operation The dam site runoff and the reservoir runoff after commissioning Dynamic time warping distance of years; represents the dynamic time warping algorithm; and They represent the total number of years before and after the reservoir is put into operation; In S3, the runoff series corresponding to the power generation water consumption rate after the reservoir is put into operation with the highest similarity is selected to construct a matching matrix between the reservoir runoff and the power generation water consumption rate, which is specifically: ； in, It represents the matching matrix between the inflow and the water consumption rate of power generation after the reservoir is put into operation; It means that the reservoir is The reservoir with the highest dam site runoff similarity in 2017 was put into operation Water consumption rate for power generation corresponding to annual runoff into the reservoir.

5. The method for rapidly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 4 is characterized by: In S4, the maximum water storage capacity from the reservoir drawdown time node to the end of the water storage scheduling period is calculated according to the water balance formula, which is specifically: ； ； in, and They represent the reserved flood control storage capacity and regulation storage capacity of the reservoir respectively; Reservoir Year The iteration calculates the assumed extinction time node; and Respectively represent the reservoir Year The first iteration calculates the storable water volume during the flood control operation period and the water storage operation period under the assumed drawdown time node; Indicates that the calculation period is long; Reservoir Year The iteration calculates the maximum water storage capacity from the assumed drawdown time node to the end of the water storage scheduling period; In S4, the amount of water used for power generation is specifically: ； ； in, Reservoir Year The iteration calculates the water consumption for power generation from the assumed drawdown time node to the end of the water storage scheduling period; Reservoir Year Power generation flow during the period; Indicates the rated flow of the reservoir unit.

6. The method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 5 is characterized by: In S5, the water level of the reservoir drawdown time node is determined, specifically: ； in, Reservoir Year The water level at the assumed drawdown time node is calculated in the first iteration; Indicates the storage capacity corresponding to the normal water level of the reservoir; It represents the interpolation function of the reservoir capacity curve. When the reservoir capacity is known, the corresponding water level can be inferred by interpolating the reservoir capacity curve. In S5, the power generation during the reservoir drawdown scheduling period is calculated, specifically: ； in, Indicates The first iteration calculates the reservoir Power generation during annual decline and flooding dispatch; Indicates The water consumption rate for power generation corresponding to the runoff sequence after the operation of the reservoir with the highest annual inflow runoff similarity.

7. The method for rapidly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 6 is characterized by: In S6, the power generation during the reservoir flood control scheduling period and the water storage scheduling period is calculated, specifically: ； in, Indicates The first iteration calculates the reservoir The power generation from the annual drawdown time node to the end of the water storage scheduling period.

8. The method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs according to claim 7 is characterized by: In S7, the calculation The total power generation during the reservoir drawdown scheduling period, flood control scheduling period and water storage scheduling period is calculated in the iteration, specifically: ； in, Indicates The total power generation of the reservoir is calculated in the iteration; make , return to step S4, re-assume the reservoir drawdown time node, and after multiple iterative calculations, obtain the total reservoir power generation vector, specifically: ； in, Indicates Annual total reservoir power generation vector; Indicates the total number of iterations; In S7, the reservoir scheduling decision information such as the timing of medium- and long-term scheduling of the reservoir, the water level, and the amount of water that can be stored is determined, specifically: ； in, Indicates The number of iterations corresponding to the maximum total annual reservoir power generation; Indicates The drawdown water level corresponding to the drawdown time of maximum total annual reservoir power generation; Indicates Reservoir The maximum water storage capacity from the iterative drawdown time node to the end of the water storage scheduling period.

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