CN110348599B - Cross-basin hydropower station group peak shaving optimization scheduling method considering water abandoning risk - Google Patents

Cross-basin hydropower station group peak shaving optimization scheduling method considering water abandoning risk Download PDF

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CN110348599B
CN110348599B CN201910477359.0A CN201910477359A CN110348599B CN 110348599 B CN110348599 B CN 110348599B CN 201910477359 A CN201910477359 A CN 201910477359A CN 110348599 B CN110348599 B CN 110348599B
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周建中
柯生林
莫莉
覃晖
蒋志强
冯仲恺
刘光彪
何飞飞
杨钰琪
邹义博
秦洲
刘斌
胡斯曼
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Huazhong University of Science and Technology
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Abstract

The invention discloses a peak shaving optimization scheduling method for a cross-basin hydropower station group considering water abandoning risks, which comprises the following steps of: s1, constructing a hydropower station group peak regulation optimization scheduling model; s2, calculating the water abandoning risk of each cascade hydropower station; s3, coordinating and distributing the generated energy of each power station based on the water abandoning risk of each power station; and S4, calculating the optimal solution of the peak regulation optimal scheduling model of the hydropower station group based on the electric quantity distribution of each power station to obtain the output process line of each power station, and finishing the combined peak regulation scheduling of the hydropower station group. The risk of water abandonment of the hydropower station is quantitatively analyzed through runoff frequency, peak shaving electric quantity of different basin hydropower station groups is coordinately distributed based on the water abandonment risk value, the water abandonment risk of each power station can be fully considered, runoff compensation and electric power compensation benefits of the different basin hydropower station groups are brought into play, the risk of water abandonment of hydropower is greatly reduced when a power grid hydropower system peaks shaving, and the electric quantity of water abandonment of hydropower is reduced.

Description

Cross-basin hydropower station group peak shaving optimization scheduling method considering water abandoning risk
Technical Field
The invention belongs to the field of hydropower dispatching operation, and particularly relates to a peak shaving optimization dispatching method for a cross-basin hydropower station group with consideration of water abandoning risks.
Background
With the vigorous development of the national hydropower industry, a cross-basin hydropower station group with huge installed capacity appears in many regions. The hydropower station is a high-quality peak regulation power supply, peak regulation optimized scheduling is carried out on the water and power station group across the drainage basin, peak regulation benefits are fully played, and the method has important value on safe and economic operation of a power grid. Under the influence of factors such as uncertainty of reservoir warehousing runoff, relatively lagged construction of a power grid matched delivery channel due to over-concentrated development of water energy, intermittent new energy synchronization represented by wind power and solar energy and the like, a hydroelectric system faces huge peak load regulation pressure and continuous and prominent water abandonment, the water abandonment is an important assessment index for hydropower station operation management, and the research on hydropower station operation scheduling water abandonment risk control has important significance.
The existing common peak-shaving optimization scheduling method for the cross-basin hydropower station group does not consider the influence of water abandon risk factors when the hydropower station is operated and scheduled, and particularly, peak shaving electricity distribution among the hydropower station groups is simple according to the installed capacity of a power station, and the water conditions of different basin steps are not fully considered, so that the hydropower station operation faces higher water abandon risk, and a large amount of water resource waste is caused. The existing research about the water abandoning risk of the cascade hydropower station group is mainly used for carrying out water abandoning risk analysis based on runoff forecasting errors, and the quantitative analysis of the water abandoning risk of the cascade hydropower station is less.
Therefore, quantitative assessment can be performed on the water abandonment risk of the cascade hydropower station, and a peak regulation optimization scheduling method of the cross-basin hydropower station group considering the water abandonment risk is provided, which is a problem to be solved urgently.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a peak shaving optimization scheduling method of a cross-basin hydropower station group considering water abandoning risks, and aims to solve the problem that the existing peak shaving optimization scheduling method of the cross-basin hydropower station group does not consider the water abandoning risks.
In order to achieve the purpose, the invention provides a cross-basin hydropower station group peak shaving optimization scheduling method considering water abandoning risks, which comprises the following steps:
s1, constructing a hydropower station group peak regulation optimization scheduling model;
s2, calculating the water abandoning risk of each cascade hydropower station;
s3, coordinating and distributing the generated energy of each power station based on the obtained water abandoning risk of each power station;
and S4, calculating the optimal solution of the peak shaving optimization scheduling model of the hydropower station group based on the obtained electric quantity distribution of each power station to obtain the output process line of each power station, and finishing the combined peak shaving scheduling of the hydropower station group.
Preferably, the hydropower station group peak regulation optimization scheduling model in step S1 takes the minimum mean square error of the grid residual load as a peak regulation target, and an objective function thereof is as follows:
Figure BDA0002082708880000021
wherein F is the power grid residual load mean square error, namely the target value, T is the number of peak shaving dispatching time periods, RtIs the residual load value of the power grid at the time period t after peak regulation by the hydropower station group,
Figure BDA0002082708880000022
mean value of the remaining load of the grid, N, for the dispatching periodi,tThe output of the hydropower station i in the time period t, M is the number of the hydropower stations with the peak regulation of the power grid, and LtAnd the peak shaving power grid load value is the peak shaving power grid load value in the period t.
Furthermore, the constraint conditions of the peak shaving optimization scheduling model of the hydropower station group comprise:
(1) and (4) water abandoning risk constraint: thetai≤θmax
(2) Electric quantity controlBundling:
Figure BDA0002082708880000023
(3) and (3) water balance constraint: vi,t+1＝Vi,t+(Ri,t-Qi,t)Δt
(4) And (3) restricting the downward flow:
Figure BDA0002082708880000024
(5) water level restraint:
Figure BDA0002082708880000025
(6) force restraint:
Figure BDA0002082708880000026
(7) and (3) total-station vibration area constraint:
Figure BDA0002082708880000031
(8) minimum duration of force constraint: (N)i,t-τ+1-Ni,t-τ)(Ni,t-Ni,t-1)≥0
(9) Water level, flow and output amplitude variation restraint:
Figure BDA0002082708880000032
wherein, thetai、θmaxRespectively representing the water abandoning risk of the hydropower station i and the restriction value N for controlling the water abandoning riski,t、Qi,tAnd Zi,tRespectively representing the output, the downward discharge and the water level of the hydropower station i in the time period t,
Figure BDA0002082708880000033
Figure BDA0002082708880000034
and
Figure BDA0002082708880000035
respectively representing the output constraint value, the let-down flow and the upper and lower limit constraint values of the water level, delta N, of the hydropower station i in the t periodi、ΔQiAnd Δ ZiRespectively representing the maximum output, the downward leakage flow and the water level variation allowed by the hydropower station i in the adjacent time period, wherein delta t is the hours in the scheduling time period,
Figure BDA0002082708880000038
power generation amount, V, allocated for hydropower station ii,t、Vi,t+1、Ri,tRespectively representing the initial and final storage capacities and warehousing flow of the hydropower station i in the time period t,
Figure BDA0002082708880000039
and respectively representing the upper and lower boundary constraint values of the g group vibration region of the hydropower station i, wherein tau is the number of time periods during which the hydropower station i at least lasts at the output extreme point.
Preferably, in step S2, the water abandoning risk of the hydropower station is defined as a runoff frequency in a scheduling period corresponding to a maximum warehousing flow rate when the hydropower station satisfies water level control under a maximum power generation situation and does not abandon water, and the method specifically includes the following calculation steps:
s21, selecting long series of historical warehousing runoff data of each hydropower station interval of corresponding calculation time interval steps, fitting a runoff frequency-warehousing flow relation curve, and obtaining different runoff frequencies P of each hydropower stationiInterval warehousing traffic of
Figure BDA00020827088800000311
S22, numbering the cascade hydropower stations from downstream to upstream in sequence as 1, 2, …, N, N is a positive integer greater than or equal to 2, initializing the runoff frequency P of the hydropower station 1 to be 11At 0.5, a maximum number of iterations k _ max is initialized, where k _ max ranges from the interval [40,80 ]]A positive integer of (1);
s23, calculating the maximum ex-warehouse flow Q of the hydropower station i +1 under the condition of considering the water abandoning riski+1(ii) a Preferably, the maximum flow of the hydropower station i +1 in the scene of considering the water abandoning risk
Figure BDA00020827088800000310
Wherein Q isiFor the maximum ex-warehouse flow of the hydropower station i under the condition of considering the water abandoning risk,
Figure BDA0002082708880000041
is a frequency PiCorresponding interval warehousing traffic, Qi,ΔCorrespondingly calculating the ex-warehouse flow of the hydropower station i for the dispatching period reservoir capacity difference; preferably, the scheduling period library tolerance can be obtained by calculation according to the current water level of the power station and the control water level at the end of the scheduling period;
s24, if Qi+1Minimum out-of-warehouse flow constraint Q less than that of a power stationi+1,minThen Q is assertedi+1＝Qi+1,min(ii) a If Qi+1Maximum ex-warehouse flow constraint Q larger than that of power stationi+1,maxThen Q is assertedi+1＝Qi+1,maxUpdate
Figure BDA0002082708880000042
And corresponding runoff frequency Pi；
S25, order Pi+1＝PiAnd repeating the step S23 and the step S24 until the i is N-1, and obtaining the runoff frequency P corresponding to the maximum warehousing of the section of the hydropower station 1, 2, … and N-11,P2,…,PN-1And the maximum ex-warehouse flow Q of the hydropower station N under the condition of considering the water abandoning riskNCalculating the warehousing flow of the hydropower station N as QN,r＝QN+QN,ΔThen Q is obtained according to the relation curve of runoff frequency-warehousing flowN,rCorresponding frequency PN；
S26, if PN＜P1And QN≠QN,minThen P will be1Decrease of epsilonPIf P isN＞P1And QN≠QN,maxThen P will be1Increase of epsilonPThen, changing i to 1 again; preferably, epsilonPThe value is 0.05;
s27, repeating the steps S23-S26 to iterate until the convergence condition is met or the iteration number exceeds k _ max, stopping the iteration, and obtaining P1,P2…,PNNamely, each step of electricityThe risk of water abandoning of the station is large.
Preferably, the convergence condition in step S27 is the runoff frequency P adjusted twice in adjacentNAnd P1Change in magnitude relation or runoff frequency PNChange amount of (Δ P)NSatisfies Δ PN≤εP。
Preferably, for the case that only one hydropower station exists in the basin, the maximum warehousing flow Q of the hydropower station is directly calculatedr＝Q+QΔWherein Q is the maximum power generation flow of the power station, QΔThe maximum warehousing flow Q is obtained according to the relation curve of runoff frequency-warehousing flowrAnd the corresponding runoff frequency P is the water abandoning risk of the current power station.
Preferably, the method for coordinately distributing the power generation capacity of each power station based on the obtained water abandoning risk of each power station in the step S3 comprises the following steps:
s31, calculating the total power generation quantity E of the hydropower station grouptotalDistributing the electric quantity to each power station according to the installed capacity proportion to serve as an initial solution for electric quantity distribution of each hydropower station;
s32, for each cascade power station, calculating the difference between the maximum water abandoning risk values between the power stations as delta thetaiIf, if
Figure BDA0002082708880000051
Increasing the distributed electric quantity of the power station with the maximum water abandoning risk value by delta EiReducing the power distribution quantity of the power station with the minimum water abandoning risk value by delta EiCalculating the water abandoning risk value of each current power station according to the step S2; preferably, the first and second electrodes are formed of a metal,
Figure BDA0002082708880000052
the value is 0.05,. DELTA.EiThe minimum regulating output of the cascade power station is taken as the value or the value is 1 MW; preferably, when the electric quantity distributed by the power station changes, the corresponding end water level changes, so that the water abandoning risk also changes;
s33, repeating the step S32 to iterate until
Figure BDA0002082708880000053
Or Δ θiStopping current iteration when the current iteration is not reduced;
s34, for different basin cascade power stations, calculating the difference of the maximum water abandoning risks among different basin cascades to be delta theta, and if delta theta is larger than epsilonθIncreasing the total power generation of the basin step with the largest water abandoning risk by delta E, reducing the total power generation of the basin step with the smallest water abandoning risk by delta E, and then distributing the power generation adjustment quantity delta E of the basin to each power station according to the installed capacity proportion of the power station; preferably, the maximum water abandoning risk of the watershed steps is the maximum water abandoning risk of each power station in the watershed; preferably, the value of delta E is 1 percent and epsilon of the total power generation of the watershed cascadeθThe value is 0.1;
s35, repeating the steps S32-S34 to iterate, and repeating the electric quantity adjustment until the delta theta is less than or equal to the epsilonθOr delta theta is not reduced any more, and the electric quantity distributed by each power station in all the watersheds is output.
Preferably, in step S4, the optimal solution of the peak shaving optimization scheduling model of the hydropower station group is calculated based on the obtained electric quantity distribution of each power station to obtain the output process line of each power station, and the method for completing the combined peak shaving scheduling of the hydropower station group specifically includes the following steps:
s41, determining the adjustable output P of each power station according to the available generated water quantity and the reserve capacity of the power stationi,max；
S42, distributing electric quantity E according to each power station of the obtained cross-basin hydropower station groupiCalculating alphai＝Ei/Pi,maxAnd according to αiThe initial output process line N of the power station is obtained by sequentially cutting loads from small to largei,t；
S43, correcting the power station output process line N according to the relevant constraint conditions in the hydropower station group peak regulation optimization scheduling modeli,t(ii) a Preferably, relevant constraint conditions in the hydropower station group peak regulation optimization scheduling model comprise power station vibration region constraint, minimum output duration constraint and output amplitude variation constraint;
s44, repeating the step S42 and the step S43 until all the hydropower stations are calculated, and outputting output process lines of all the hydropower stations as initial feasible solutions of the peak regulation models;
and S45, iteratively adjusting the output process lines of different power stations in the model through a stepwise optimization algorithm until the target values of the two times of adjustment are not reduced or the iteration times preset by the algorithm are reached, considering that the mean square error of the residual load of the power grid is minimum, stopping iteration, and outputting the output process lines of each power station at the moment.
Preferably, the cross-basin hydropower station group peak shaving optimization scheduling method is applied to the field of hydropower scheduling operation.
Through the technical scheme, compared with the prior art, the invention can obtain the following beneficial effects:
1. the invention provides a peak shaving optimization scheduling method for cross-basin hydropower station groups considering water disposal risks, which quantificationally analyzes the water disposal risks of hydropower stations through runoff frequency, coordinates and distributes peak shaving electric quantity of hydropower station groups in different basins based on water disposal risk values, can fully consider the water disposal risks of each power station, utilizes the space-time distribution characteristics of warehousing runoff of the hydropower station groups in different basins, exerts the runoff compensation and electric power compensation benefits of the hydropower station groups in different basins, reduces the water disposal risks of hydropower when the peak shaving of a power grid hydropower system, and reduces the electric quantity of the water disposal of hydropower.
2. The invention provides a practical step hydropower station water abandoning risk assessment method, which can calculate and obtain the water abandoning risk value of each step hydropower station by taking the runoff frequency of a scheduling period corresponding to the maximum warehousing flow rate when the hydropower station meets water level control under the maximum power generation scene and does not abandon water as the standard of the water abandoning risk assessment, solves the problem that the existing water abandoning risk assessment method cannot carry out quantitative analysis on the water abandoning risk of the step hydropower station, and greatly improves the accuracy of assessing the water abandoning risk of the step hydropower station.
3. According to the cross-basin hydropower station group peak shaving optimization scheduling method considering the water abandon risk, when the generated energy of the hydropower stations is coordinately distributed, not only is the generated energy distribution of each hydropower station in a basin performed, but also the generated energy distribution of each basin is performed, the generated energy distribution and the generated energy distribution are performed alternately until the water abandon risk of the whole cross-basin hydropower station group is reduced to the minimum, the generated energy and the water abandon risk value of each hydropower station are well balanced, the generated energy is reasonably distributed by each hydropower station, and the waste of water resources is greatly reduced.
Drawings
FIG. 1 is a flow chart of a method for peak shaving optimal scheduling of a cross-basin hydropower station group with consideration of water abandonment risk provided by the invention;
FIG. 2 is a comparison graph of the actual water abandoning risk of a hydropower station group and the water abandoning risk obtained by adopting the scheduling method provided by the invention;
FIG. 3 is a graph comparing actual power allocation of a hydropower station group with power allocation obtained by the scheduling method provided by the invention;
FIG. 4 is a diagram of a hydropower station group joint peak regulation optimal scheduling result obtained by the method 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 embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In order to achieve the purpose, the invention provides a peak shaving optimization scheduling method of a cross-basin hydropower station group considering water abandoning risks.
Fig. 1 is a flowchart of a method for peak shaving optimal scheduling of a cross-basin hydropower station group considering water abandonment risk, specifically including the following steps:
s1, constructing a hydropower station group peak regulation optimization scheduling model, and taking the minimum mean square deviation of the residual load of the power grid as a peak regulation target, wherein the target function is as follows:
Figure BDA0002082708880000071
wherein F is the power grid residual load mean square error, namely the target value, T is the number of peak shaving dispatching time periods, RtIs the residual load value of the power grid at the time period t after peak regulation by the hydropower station group,
Figure BDA00020827088800000812
mean value of the remaining load of the grid, N, for the dispatching periodi,tThe output of the hydropower station i in the time period t, M is the number of the hydropower stations with the peak regulation of the power grid, and LtAnd the peak shaving power grid load value is the peak shaving power grid load value in the period t.
Furthermore, the constraint conditions of the peak shaving optimization scheduling model of the hydropower station group comprise:
(1) and (4) water abandoning risk constraint: thetai≤θmax
(2) Electric quantity constraint:
Figure BDA0002082708880000081
(3) and (3) water balance constraint: vi,t+1＝Vi,t+(Ri,t-Qi,t)Δt
(4) And (3) restricting the downward flow:
Figure BDA0002082708880000082
(5) water level restraint:
Figure BDA0002082708880000083
(6) force restraint:
Figure BDA0002082708880000084
(7) and (3) total-station vibration area constraint:
Figure BDA0002082708880000085
(8) minimum duration of force constraint: (N)i,t-τ+1-Ni,t-τ)(Ni,t-Ni,t-1)≥0
(9) Water level, flow and output amplitude variation restraint:
Figure BDA0002082708880000086
wherein, thetai、θmaxRespectively representing the risk of water abandonment of the hydropower station i andcontrolling the size of the risk of water abandonment, Ni,t、Qi,tAnd Zi,tRespectively representing the output, the downward discharge and the water level of the hydropower station i in the time period t,
Figure BDA0002082708880000087
Figure BDA0002082708880000088
and
Figure BDA0002082708880000089
respectively representing the output constraint value, the let-down flow and the upper and lower limit constraint values of the water level, delta N, of the hydropower station i in the t periodi、ΔQiAnd Δ ZiRespectively representing the maximum output, the downward leakage flow and the water level variation allowed by the hydropower station i in the adjacent time period, wherein delta t is the hours in the scheduling time period,
Figure BDA00020827088800000810
power generation amount, V, allocated for hydropower station ii,t、Vi,t+1、Ri,tRespectively representing the initial and final storage capacities and warehousing flow of the hydropower station i in the time period t,
Figure BDA00020827088800000811
respectively representing the upper and lower boundary constraint values of the g group of vibration regions of the hydropower station i, wherein tau is the number of at least continuous time periods of the hydropower station i at the output extreme point;
s2, calculating the water abandoning risk of each power station of the cascade; specifically, the water abandoning risk size of the hydropower station is defined as a runoff frequency of a scheduling period corresponding to the maximum warehousing flow rate when the hydropower station meets water level control and does not abandon water under the maximum power generation situation, and the method specifically comprises the following evaluation steps:
s21, selecting long series of historical warehousing runoff data of each hydropower station interval of corresponding calculation time interval steps, fitting a runoff frequency-warehousing flow relation curve, and obtaining different runoff frequencies P of each hydropower stationiInterval warehousing traffic of
Figure BDA0002082708880000092
S22, numbering the cascade hydropower stations from downstream to upstream in sequence as 1, 2, …, N, N is a positive integer greater than or equal to 2, initializing the runoff frequency P of the hydropower station 1 to be 11At 0.5, a maximum number of iterations k _ max is initialized, where k _ max ranges from the interval [40,80 ]]A positive integer of (1);
s23, calculating the maximum ex-warehouse flow of the hydropower station i +1 under the condition of considering the water abandoning risk; specifically, the maximum ex-warehouse flow of the hydropower station i +1 under the condition of considering the water abandoning risk
Figure BDA0002082708880000091
Wherein Q isiFor the maximum ex-warehouse flow of the hydropower station i under the condition of considering the water abandoning risk,
Figure BDA0002082708880000093
is a frequency PiCorresponding interval warehousing traffic, Qi,ΔCorrespondingly calculating the ex-warehouse flow of the hydropower station i for the dispatching period reservoir capacity difference; specifically, the scheduling period library tolerance can be obtained by calculation according to the current water level of the power station and the control water level at the end of the scheduling period;
s24, if Qi+1Less than minimum outbound flow constraint Qi+1,minThen Q is assertedi+1＝Qi+1,min(ii) a If Qi+1Constraint Q of greater than maximum ex-warehouse flowi+1,maxThen Q is assertedi+1＝Qi+1,maxUpdate
Figure BDA0002082708880000094
And corresponding runoff frequency Pi；
S25, order Pi+1＝PiAnd repeating the step S23 and the step S24 until the i is N-1, and obtaining the corresponding frequency P of the maximum warehousing runoff of the interval of the hydropower stations 1, 2, … and N-11,P2,…,PN-1And the maximum ex-warehouse flow Q of the hydropower station N under the condition of considering the water abandoning riskNCalculating Q of N of the hydropower stationN,rThe flow rate of warehousing is QN,r＝QN+QN,ΔThen, according to the relation curve of runoff frequency-warehousing flow, obtaining the corresponding frequency PN；
S26, if PN＜P1And QN≠QN,minThen P will be1Decrease of epsilonPIf P isN＞P1And QN≠QN,maxThen P will be1Increase of epsilonPThen, changing i to 1 again; in particular, epsilonPCan take the value of 0.05;
s27, repeating the steps S23-S26 to iterate until the convergence condition is met or the maximum iteration number k _ max is exceeded, stopping the iteration, and obtaining P1,P2…,PNNamely the water abandoning risk of each power station of the cascade; specifically, the convergence condition is the runoff frequency P adjusted twice adjacentlyNAnd P1Change in magnitude relation or runoff frequency PNChange amount of (Δ P)NSatisfies Δ PN≤εPIn particular, epsilonPA value of 0.05 can be taken.
Further, for the condition that only one hydropower station exists in the basin, the maximum warehousing flow Q of the hydropower station is directly calculatedr＝Q+QΔWherein Q is the maximum power generation flow of the power station, QΔThe maximum warehousing flow Q is obtained according to the relation curve of runoff frequency-warehousing flowrAnd the corresponding runoff frequency P is the water abandoning risk of the current power station.
S3, based on the obtained water abandoning risk of each power station, the generated energy of each power station is distributed in a coordinated manner, and the method specifically comprises the following steps:
s31, calculating the total power generation quantity E of the hydropower station grouptotalDistributing the electric quantity to each power station according to the installed capacity proportion to serve as an initial solution for electric quantity distribution of each hydropower station;
s32, for each cascade power station, calculating the difference between the maximum water abandoning risk values between the power stations as delta thetaiIf, if
Figure BDA0002082708880000101
Increasing the distributed electric quantity of the power station with the maximum water abandoning risk value by delta EiReducing the power distribution quantity of the power station with the minimum water abandoning risk value by delta EiCalculating the water abandoning risk value of each current power station according to the step S2; in particular, the method comprises the following steps of,
Figure BDA0002082708880000102
can be taken as 0.05, Delta EiThe value can be the minimum regulating output of the cascade power station or 1 MW; specifically, when the electric quantity distributed by the power station changes, the corresponding tail water level changes, so that the risk of water abandonment also changes;
s33 repeating step S32 for iteration until
Figure BDA0002082708880000103
Or Δ θiStopping current iteration when the current iteration is not reduced;
s34, for different basin cascade power stations, calculating the difference of the maximum water abandoning risks among different basin cascades to be delta theta, and if delta theta is larger than epsilonθIncreasing the total power generation of the basin step with the largest water abandoning risk by delta E, reducing the total power generation of the basin step with the smallest water abandoning risk by delta E, and then distributing the power generation adjustment quantity delta E of the basin to each power station according to the installed capacity proportion of the power station; specifically, the maximum water abandoning risk of the basin step is the maximum water abandoning risk of each power station in the basin, and the value of delta E can be 1 percent and epsilon of the total power generation amount of the basin stepθCan take the value of 0.1;
s35, repeating the steps S32-S34 to iterate, and repeating the electric quantity adjustment until the delta theta is less than or equal to the epsilonθOr delta theta is not reduced any more, and the electric quantity distributed by each power station in all the watersheds is output.
S4, calculating the optimal solution of the peak regulation optimal scheduling model of the hydropower station group based on the obtained electric quantity distribution of each power station to obtain the output process line of each power station, and finishing the combined peak regulation scheduling of the hydropower station group, wherein the method specifically comprises the following steps:
s41, determining the adjustable output P of each power station according to the available generated water quantity and the reserve capacity of the power stationi,max；
S42, distributing electric quantity E according to each power station of the obtained cross-basin hydropower station groupiCalculating alphai＝Ei/Pi,maxAnd according to αiThe initial output process line N of the power station is obtained by sequentially cutting loads from small to largei,t；
S43, according to waterCorrecting power station output process line N by power station vibration region constraint, minimum output duration constraint and output amplitude variation constraint in power station group peak regulation optimized scheduling modeli,t；
S44, repeating the step S42 and the step S43 until all the hydropower stations are calculated, and outputting output process lines of all the hydropower stations as initial feasible solutions of the peak regulation models;
and S45, iteratively adjusting the output process lines of different power stations in the model through a stepwise optimization algorithm until the target values of the two times of adjustment are not reduced or the iteration times preset by the algorithm are reached, considering that the mean square error of the residual load of the power grid is minimum, stopping iteration, and outputting the output process lines of each power station at the moment.
By taking the hydropower stations in Qingjiang basin and Hanjiang basin under the administrative jurisdiction of the Hubei power grid as examples, the hydropower station group peak shaving optimization scheduling method provided by the invention is adopted according to the steps, the electric quantity distribution among the hydropower station groups is coordinated based on the water abandoning risk of the hydropower station, and the combined peak shaving optimization scheduling is carried out. Wherein the Qingjiang river basin comprises a water buya hydropower station, a river rock separation hydropower station and a high dam continent hydropower station, the Hanjiang river basin comprises a Danjiang mouth hydropower station, and the water abandoning risk is controlled by the size theta from 5 months to 20 months in 5-to-6 months during the flood season before 2015maxIs 0.1; as shown in fig. 2, a comparison graph of the actual water abandoning risk of a hydropower station group and the water abandoning risk obtained by adopting the scheduling method provided by the invention is shown, a solid line is a change curve of the actual water abandoning risk along with time, a dotted line is a change curve of the water abandoning risk along with time obtained by adopting the scheduling method provided by the invention, the graph shows that the water abandoning risk value of a terraced hydropower station in the actual scheduling process is larger, so that the hydropower station needs to be enlarged and drained before a main flood season arrives, so that the water abandoning is generated in a cascade, and after the peak-shaving electric quantity of each hydropower station is coordinately distributed based on the water abandoning risk of the hydropower station provided by the invention, a comparison graph of the actual electric quantity distribution of the hydropower station group shown in fig. 3 and the electric quantity distribution obtained by adopting the scheduling method provided by the invention is obtained, as can be shown, the graph shows that the electric quantity adjustment between terraced stages before 6 months and 15 days reduces the electric quantity of the hydropower station distributed by water distribution, and increases the electric quantity of the terraced hydropower station, thereby reducing the water abandoning risk of the river separation rock, increasing the generating capacity of a hydropower station at the Dangjiang mouth by adjusting the cross-basin electric quantity after 6 months and 15 days, and simultaneously reducing the water buffetThe generated energy of the hydropower station is reduced, so that the water abandoning risk of the river-separated rock hydropower station is reduced; further, the water abandon risk value is changed, after the electric quantity distribution method provided by the invention is adopted, fig. 2 shows that the water abandon risk of the river-separated rock power station is controlled below 0.1 and corresponds to lg (100 x 0.1) in the diagram and is below 1, and compared with the actual operation scheduling process, the water abandon quantity is reduced by 0.86 hundred million m3And the effect of reducing the water discard is obvious. Meanwhile, aiming at the electric quantity distribution result obtained by adopting the electric quantity distribution method provided by the invention, the combined peak regulation optimization scheduling is carried out for 20 days in 6 months, and the result is shown in fig. 4, which is a hydropower station group combined peak regulation optimization scheduling result graph obtained by adopting the method provided by the invention, and the graph shows that the output process line of each power station can track the change of the peak valley of the power grid, so that the load mean square error of the power grid is reduced from 682126 to 3592, and the peak regulation effect is obvious.
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 (7)

1. A cross-basin hydropower station group peak shaving optimization scheduling method considering water abandoning risks is characterized by comprising the following steps:
s1, constructing a hydropower station group peak regulation optimization scheduling model;
s2, calculating the water abandoning risk of each cascade hydropower station;
s3, coordinating and distributing the generated energy of each power station based on the water abandoning risk of each power station;
s4, calculating the optimal solution of the peak regulation optimization scheduling model of the hydropower station group based on the electric quantity distribution of each power station to obtain an output process line of each power station, and finishing the combined peak regulation scheduling of the hydropower station group;
the method of step S3 includes the following steps:
s31, distributing the total generated energy of the hydropower station group to each power station according to the installed capacity proportion, and using the total generated energy as an initial solution for the electric quantity distribution of each hydropower station;
s32, for eachCalculating the difference between the maximum water abandoning risk values of the power stations to be delta thetaiIf, if
Figure FDA0003316295370000011
Increasing the distributed electric quantity of the power station with the maximum water abandoning risk value by delta EiReducing the power distribution quantity of the power station with the minimum water abandoning risk value by delta EiCalculating the water abandoning risk value of each current power station according to the step S2;
s33, repeating the step S32 to adjust the electric quantity until the electric quantity is adjusted
Figure FDA0003316295370000012
Or Δ θiStopping current iteration when the current iteration is not reduced;
s34, for different basin cascade power stations, calculating the difference of the maximum water abandoning risks among different basin cascades to be delta theta, and if delta theta is larger than epsilonθIncreasing the total power generation of the basin step with the largest water abandoning risk by delta E, reducing the total power generation of the basin step with the smallest water abandoning risk by delta E, and then distributing the power generation adjustment quantity delta E of the basin to each power station according to the installed capacity proportion of the power station;
s35, repeating the steps S32-S34 to iterate, and repeating the electric quantity adjustment until the delta theta is less than or equal to the epsilonθOr the delta theta is not reduced any more, the iteration is stopped, and the distributed electric quantity of each power station of the cross-basin water power station group is output.
2. The peak shaving optimal scheduling method for the cross-basin hydropower station group according to claim 1, wherein the method of the step S2 comprises the following steps:
s21, selecting long series of historical warehousing runoff data of each hydropower station interval of corresponding calculation time interval steps, fitting a runoff frequency-warehousing flow relation curve, and obtaining interval warehousing flow of different runoff frequencies of each hydropower station;
s22, numbering the cascade hydropower stations from downstream to upstream in sequence as 1, 2, …, N, N is a positive integer greater than or equal to 2, initializing the runoff frequency P of the hydropower station 1 to be 11At 0.5, a maximum number of iterations k _ max is initialized, where k _ max ranges from the interval [40,80 ]]A positive integer of (1);
s23, calculating the maximum ex-warehouse flow Q of the hydropower station i +1 under the condition of considering the water abandoning riski+1；
S24, if Qi+1Minimum export flow constraint Q less than hydropower station i +1i+1,minThen Q is assertedi+1＝Qi+1,min(ii) a If said Q isi+1Maximum export flow constraint Q greater than hydropower station i +1i+1,maxThen Q is assertedi+1＝Qi+1,maxUpdate QPi＝Qi+Qi,Δ-Qi+1And corresponding runoff frequency Pi；Qi,ΔCorrespondingly calculating the ex-warehouse flow of the hydropower station i for the dispatching period reservoir capacity difference;
s25, order Pi+1＝PiAnd repeating the step S23 and the step S24 until the i is N-1, and obtaining the corresponding frequency P of the maximum warehousing runoff of the interval of the hydropower stations 1, 2, … and N-11,P2,…,PN-1And the maximum ex-warehouse flow Q of the hydropower station N under the condition of considering the water abandoning riskNCalculating the warehousing flow of the hydropower station N as QN,r＝QN+QN,ΔThen Q is obtained according to the relation curve of runoff frequency-warehousing flowN,rCorresponding runoff frequency PN；QN,ΔCorrespondingly calculating the outlet flow of the hydropower station N for the reservoir capacity difference in the dispatching period;
s26, if PN＜P1And QN≠QN,minThen P will be1Decrease of epsilonPIf P isN＞P1And QN≠QN,maxThen P will be1Increase of epsilonPThen, changing i to 1 again;
s27, repeating the steps S23-S26 to iterate until the convergence condition is met or the iteration number exceeds k _ max, stopping the iteration, and obtaining P1,P2…,PNNamely the water abandoning risk of each power station of the cascade.
3. The peak shaving optimal scheduling method for the cross-basin hydropower station group according to claim 2, wherein the maximum warehousing flow Q of the hydropower station is directly calculated for the condition that only one hydropower station exists in the basinr＝Q+QΔThen obtaining the maximum warehousing flow Q according to the relation curve of runoff frequency-warehousing flowrCorresponding runoff frequency is the water abandoning risk of the current power station, wherein Q is the maximum power generation flow of the power station, and Q is the maximum power generation flow of the power stationΔThe flow rate of the warehouse-out is correspondingly converted according to the warehouse capacity difference in the dispatching period.
4. The peak shaving optimal scheduling method for the cross-basin hydropower station group according to claim 2, wherein the convergence condition is runoff frequency P adjusted twice adjacentlyNAnd P1Change in magnitude relation or runoff frequency PNChange amount of (Δ P)NSatisfies Δ PN≤εP。
5. The peak shaving optimal scheduling method for the cross-basin hydropower station group according to claim 1, wherein the method of the step S4 comprises the following steps:
s41, determining the adjustable output P of each power station according to the available generated water quantity and the reserve capacity of the power stationi,max；
S42, distributing electric quantity E according to each power station of the cross-basin hydropower station groupiCalculating alphai＝Ei/Pi,maxAnd according to αiThe initial output process line N of the power station is obtained by sequentially cutting loads from small to largei,t；
S43, correcting the power station output process line N according to the relevant constraint conditions in the hydropower station group peak regulation optimization scheduling modeli,t；
S44, repeating the step S42 and the step S43 until all the hydropower stations are calculated, and outputting output process lines of all the hydropower stations as initial feasible solutions of the peak regulation models;
and S45, iteratively adjusting the output process lines of different power stations in the model through a stepwise optimization algorithm until the target values of the two times of adjustment are not reduced or the iteration times preset by the algorithm are reached, considering that the mean square error of the residual load of the power grid is minimum, stopping iteration, and outputting the output process lines of the power stations at the moment.
6. The peak shaving optimal scheduling method for the cross-basin hydropower station group according to claim 5, wherein the relevant constraint conditions comprise power station vibration area constraint, minimum output duration constraint and output amplitude constraint.
7. The cross-basin hydropower station group peak-shaving optimization scheduling method according to claim 1, wherein the cross-basin hydropower station group peak-shaving optimization scheduling method is applied to the field of hydropower scheduling operation.
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