Method for quickly generating medium-and-long-term power generation dispatching decision in flood-control water-storage reservoir

Abstract

The invention provides a flood control water storage reservoir medium and long term power generation scheduling decision rapid generation method, and belongs to the reservoir medium and long term scheduling decision field, and the method comprises the steps: deducing the reservoir power generation water consumption rate according to the power generation amount, power generation water consumption amount, reservoir storage capacity curve and other data of long series actual operation of reservoir commissioning, and constructing a power generation water consumption rate data set; on the basis of long-series medium-and-long-term reservoir inflow data and reservoir outflow demand data of the reservoir, according to the time requirement of the reserved flood control capacity of the reservoir, the time span of the flood control scheduling period and the water storage scheduling period of the reservoir is determined, and the medium-and-long-term scheduling hydro-fluctuation opportunity, the water level, the water storage capacity and other reservoir scheduling decision information of the reservoir are determined.

Description

Technical Field

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

[0002] Combined with the change rules of reservoir inflow and water level, the full-cycle dispatching process of the reservoir can be divided into the drawdown dispatching period, flood control dispatching period and water storage dispatching period. During the drawdown dispatching period, the reservoir dispatching is mainly for power generation and water replenishment to the downstream. The inflow is relatively small, the reservoir reduces the storage capacity and increases the downstream flow; during the flood control dispatching period, the inflow of the reservoir is relatively large, the reservoir dispatching is mainly for flood control, taking into account power generation, and operating according to the flood limit water level control; during the water storage dispatching period, the inflow of the reservoir shows a decreasing trend. On the premise of meeting the water demand of the downstream, the reservoir dispatching is mainly for water storage, raising the reservoir water level, and striving to store the full storage capacity at the end of the dispatching period. It can be seen that the full-cycle dispatching of the reservoir needs to balance the needs of power generation, flood control, water storage and other aspects. For the upstream control reservoir of the basin, the storage capacity is large and the regulation capacity is strong. If the key information of reservoir dispatching such as the timing of reservoir drawdown, drawdown level, and water storage process cannot be handled in combination with the medium- and long-term water inflow of the reservoir, it may affect the benefits of the reservoir itself and the downstream reservoirs.

[0003] In order to balance the benefits of reservoir power generation, flood control, water storage and other aspects, at present, most of them adopt the method of constructing a multi-objective scheduling model and applying a multi-objective intelligent optimization algorithm to solve the problem to obtain the reservoir scheduling strategy and guide the operation of the reservoir. However, this method has several shortcomings: first, the construction of the multi-objective scheduling model is complex, and the solution results are presented in the form of a non-inferior solution set, which cannot directly screen out the reservoir power generation scheduling decision that takes into account flood control and water storage; second, the model calculation and solution time is relatively long, and there are random factors in the multi-objective intelligent optimization algorithm, and the solved scheduling decision is not stable. In view of this, a method for quickly generating medium- and long-term reservoir power generation scheduling decisions that take into account flood control and water storage is proposed. Combined with the medium- and long-term water inflow data of the reservoir, the full-cycle scheduling process such as the reservoir drawdown scheduling period, flood control scheduling period and water storage scheduling period is comprehensively considered to quickly generate reservoir scheduling decisions and give full play to the comprehensive benefits of the reservoir. Summary of the invention

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and provide a method for quickly generating medium- and long-term power generation scheduling decisions for flood control and water storage reservoirs, thereby providing technical support for guiding reservoir scheduling.

[0005] To achieve the above object, the present invention adopts the following technical solutions: The present invention provides a method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs, comprising: 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.

[0006] Furthermore, in S1, the actual power generation of the reservoir during the long-term operation , Water consumption for power generation , and the reservoir capacity curve , specifically: 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 * ] ; 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 * ] ; VZ = [ v 1 , v 2 ⋯ , v m , ⋯ , v M z 1 , z 2 ⋯ , z m , ⋯ , z M ] ⊤ , m ∈ [ 1 , M ] ; 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 reservoir capacity curve 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: η = [ η 1 , η 2 , ⋯ , η y , ⋯ , η Y * ] ; ; in, Represents the reservoir power generation water consumption rate data set; Indicates Annual water consumption rate of reservoir power generation.

[0007] Furthermore, 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: 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 ] ; 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 ] ; 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: duT fc = T im − T fc + 1 , t ∈ [ 1 , T ] ; duT im = T − T im t ∈ [ 1 , T ] ; 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.

[0008] Furthermore, 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: 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 ] ; 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: 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 * ] ; 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.

[0009] Furthermore, 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: { ∑ 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 ] ; ; 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.

[0010] Further, in S5, the water level at 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: P k , y d = [ ∑ t = 1 T k , y d Q y in ( t ) × Δ t + V k , y max ] × η y * ; 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.

[0011] Furthermore, 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.

[0012] Further, 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 by the iteration calculation, 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: P y = [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] k ∈ [ 1 , K ] ; 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: { 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 ; 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.

[0013] The beneficial effects of the present invention are as follows: for the first time, a method for rapidly generating medium- and long-term reservoir power generation scheduling decisions that takes into account both flood control and water storage is proposed, which takes into account the flood control and water storage requirements of reservoir scheduling, and rapidly generates reservoir power generation scheduling decision information, including: drawdown water level, drawdown timing, water storage volume, etc., to provide a reference basis for the full-cycle scheduling of the reservoir; The method for rapidly generating medium- and long-term reservoir power generation dispatching decisions taking into account flood control and water storage proposed in the present invention has a stable solution, a simple calculation process and a fast calculation speed compared to multi-objective dispatching calculation models. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A flowchart of a method for quickly generating mid- and long-term power generation dispatching decisions for a flood control and water storage reservoir; Figure 2 A schematic diagram of an embodiment. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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.

[0016] Example: See also Figure 1 A method for quickly generating medium- and long-term power generation dispatching decisions for flood control and water storage reservoirs, characterized by comprising: 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.

[0017] 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: 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 * ] ; 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 * ] ; VZ = [ v 1 , v 2 ⋯ , v m , ⋯ , v M z 1 , z 2 ⋯ , z m , ⋯ , z M ] ⊤ , m ∈ [ 1 , M ] ; 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 reservoir capacity curve Water level and reservoir capacity data; It indicates the total number of years the reservoir has been in operation; Indicates the total number of time periods; 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: η = [ η 1 , η 2 , ⋯ , η y , ⋯ , η Y * ] ; ; in, Represents the reservoir power generation water consumption rate data set; Indicates Annual water consumption rate of reservoir power generation.

[0018] 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: 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 ] ; 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 ] ; 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: duT fc = T im − T fc + 1 , t ∈ [ 1 , T ] ; duT im = T − T im t ∈ [ 1 , T ] ; in, and They represent the time span of the reservoir flood control operation period and water storage operation period respectively; and They represent the beginning and end time of the reservoir flood control operation period respectively; 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: 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 ] ; 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: 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 * ] ; 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.

[0019] 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: { ∑ 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 ] ; ; 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.

[0020] 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: P k , y d = [ ∑ t = 1 T k , y d Q y in ( t ) × Δ t + V k , y max ] × η y * ; 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.

[0021] 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.

[0022] 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: P y = [ P 1 , y total , P 2 , y total , ⋯ , P k , y total , ⋯ , P K , y total ] k ∈ [ 1 , K ] ; 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: { 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 ; 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.

[0023] Through the calculation of the reservoir runoff data over the years, the average water level of the reservoir is 1821m, and the average water level drawdown time with the maximum total power generation is mid-June. The dispatching process is as follows Figure 2 shown.

[0024] The above-mentioned embodiments only express the implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, 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 attached 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 reservoir capacity curve 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 was 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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