CN106873372B - Reservoir regulation for flood control optimization method based on the control of Flood Control Dispatch data adaptive - Google Patents
Reservoir regulation for flood control optimization method based on the control of Flood Control Dispatch data adaptive Download PDFInfo
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Abstract
The invention discloses a kind of reservoir regulation for flood control optimization method based on the control of Flood Control Dispatch data adaptive, it is related to reservoir regulation for flood control technical field.The method：Establish the general flood control chart of purpose reservoir；Establish Flood Control Dispatch model；Determine object function；Line flex point quantity is dispatched according to the scheduling line number amount of general flood control chart and each bar, obtains representing the sum of optimized variable needed for the general flood control chart；According to definite object function and optimized variable；Calculated using NSGA II algorithm optimizations, and Pareto non-domination solution analyses, the general flood control chart after being optimized are carried out to object function；Flood control business calculating is carried out with the general flood control chart after optimization.Flood Season of Reservoir scheduling present invention introduces flood control chart can make full use of the water of reservoir while downstream flood control safety is ensured, improve the utilization ratio of flood, at the same time, moreover it is possible to improve the solution efficiency of Optimized model.
Description
Technical Field
The invention relates to the technical field of reservoir flood control scheduling, in particular to a reservoir flood control scheduling optimization method based on flood control scheduling data self-adaptive control.
Background
The reservoir flood control dispatching refers to that human beings use the regulation and storage capacity of the reservoir, and according to the water inflow and storage conditions of the reservoir, storage and discharge are carried out on the runoff in a warehouse in a planned way on the premise of ensuring the reservoir and the downstream flood control safety, so that the purposes of interest promotion and harm removal are achieved, and the life and property safety of people and the smooth development of national economy are ensured. At present, the traditional reservoir flood control dispatching method is usually a method for limiting the reservoir capacity of the reservoir to the flood limit water level in the flood season, however, the flood control flow in the flood season is generally far larger than the flow corresponding to the expected output of a power station, so a large amount of water abandon can be generated, the reservoir action is greatly limited, and the reservoir cannot generate more contribution to the downstream flood control safety due to less stagnant flood water.
Although in recent years, on the premise of ensuring flood control safety, researchers have proposed various scheduling methods for fully utilizing flood resources in flood season, the following problems still exist:
1. the conventional reservoir flood limit water level dynamic control method is applied to a reservoir real-time dispatching stage, the dispatching rule is complex, and the operation is inconvenient in practical application.
2. The existing reservoir dispatching graph is visual and convenient to apply, and is widely applied to reservoir interest dispatching, but the existing reservoir dispatching graph cannot be applied to flood control dispatching.
3. The reservoir incoming water is introduced into the flood control dispatching graph, however, the flood control dispatching graph is generally designed by researchers, and the flood control dispatching graph has a uniform fixed shape, so that when a user uses the flood control dispatching graph introducing the reservoir incoming water, the user needs to study the flood control dispatching graph firstly and then arrange the flood control dispatching graph into a shape required by the user, and therefore the problem of inconvenient use exists.
Disclosure of Invention
The invention aims to provide a reservoir flood control scheduling optimization method based on flood control scheduling data self-adaptive control, so that the problems in the prior art are solved.
In order to achieve the above object, the present invention provides a reservoir flood control scheduling optimization method based on flood control scheduling data adaptive control, comprising:
s1, establishing a general flood control dispatching diagram of a target reservoir; the horizontal axis of the general flood control dispatch graph is the inflow water flow increment of an faced time interval, the vertical axis is the possible water level at the end of the faced time interval, the upper limit and the lower limit of the horizontal axis are calculated according to the historical flow or the simulated flow of the target reservoir during the flood season, and the upper limit and the lower limit of the vertical axis are respectively the historical highest water level and the historical lowest water level of the target reservoir;
a plurality of mutually-intersected scheduling lines which are in a descending trend are arranged in the general flood control scheduling graph, each scheduling line is formed by connecting piecewise straight lines formed by connecting any number of inflection points, and each scheduling line is set with a control flow and distributed in the general flood control scheduling graph;
according to the upper and lower position relations of the dispatching lines on the general flood control dispatching graph, the control flow of the dispatching lines above the general flood control dispatching graph is gradually increased to the control flow of the dispatching lines below the general flood control dispatching graph;
s2, establishing a flood control dispatching model, and when the water level of the target reservoir is higher than a flood limit water level in a flood season, starting to use the flood control dispatching model for flood control dispatching by the target reservoir; the method specifically comprises the following steps:
firstly, judging the flow increment of the reservoir, calculating the possible water level at the end of the period of time of the reservoir, inquiring a general flood control dispatching diagram, and obtaining the reservoir discharge at the current moment through interpolation calculation; secondly, under the condition of known reservoir discharge capacity, obtaining the relation between the possible water level of the reservoir at the end of the faced time interval of the target reservoir, the discharge capacity of the reservoir under the dam and the power generation output of the reservoir according to the formulas (1) to (7), then judging whether the results obtained by calculation according to the formulas (1) to (7) meet the preset constraint condition or not, and if so, entering S3; if not, recalculating the power generation flow of the target reservoir, performing water abandoning by redundant water conservancy, and then entering S3;
the flood control scheduling model comprises:
the water quantity balance relation is formula (1):
or
The relationship of the flow of the water level of the dam drainage is a formula (2):
Q＝f(H D ) (2)；
the library capacity curve is formula (3):
V＝V(H) (3)；
the water flow increment formula at the moment t is shown as a formula (4):
ΔI＝I t -I t-1 (4)；
the library capacity at time t is formula (5):
V t ＝I t-1 +I t ×Δt (5)；
possible water level formula (6) before the dam at time t:
H t ＝H(V t ) (6)；
the reservoir generated output calculation formula is as follows:
wherein I is warehouse entry flow and unit m 3 S; q is the flow out of the warehouse in m 3 S; v is the current water storage in the reservoir in m 3 (ii) a t is the time; v 1 、V 2 The water quantity of the reservoir at the beginning and the end of the time interval respectively, unit m 3 (ii) a Δ t is a scheduling time period, unit s; f (H) D ) The relationship of the flow of the drainage water level under the dam; v (H) represents a relational expression for reversely deducing the reservoir capacity from the reservoir water level; h is the dam front water level in m; delta I is the water flow increment of the reservoir at the moment t, and the unit m 3 /s；I t The water inflow of the reservoir at the time t in the unit of m 3 /s；I t-1 The water inflow of the reservoir at the time of t-1 in m 3 /s；V t Is the amount of water in the reservoir at time t in units of m 3 ；V t-1 Is the amount of water in the reservoir at time t-1, in m 3 ；H t Is at t timeThe possible water level before the reservoir dam is carved, unit m; h (V) t ) A relational expression representing the water level reversely deduced from the reservoir capacity of the reservoir; n is the power generation output of the reservoir, and the unit is kW; k is the output coefficient; h 1 、H 2 The water levels of the reservoir at the beginning and the end of the dispatching time period and the unit m are respectively; q E For generating flow of reservoir in m 3 /s；H D Is the reservoir dam water level, m; Δ V is the variation of the storage capacity of the reservoir in m 3 ；
S3, determining a target function;
s4, obtaining the total number of optimized variables required by the general flood control dispatching graph according to the quantity of dispatching lines of the general flood control dispatching graph and the quantity of inflection points of each dispatching line;
s5, solving an optimization problem by using an NSGA-II algorithm according to the determined objective function and the optimization variable;
s6, carrying out Pareto non-dominated solution analysis on the target function to obtain an optimized general flood control dispatching graph;
and S7, applying the optimized general flood control dispatching graph to calculate flood control services.
Preferably, the constraint condition includes:
water level constraint, equation (8):
H dl ≤H 1 ，H 2 ≤H nl (8)；
flow constraints, i.e., equation (9):
Q min ≤Q≤Q max (9)；
the power generation flow constraint condition, namely formula (10):
Q Emin ≤Q E ≤Q Emax (10)；
the generated output constraint, i.e., equation (11):
N min ≤N≤N max (11)；
wherein H dl Is the reservoir dead water level in m; h nl Is the normal water storage level of the reservoir, unit m; q min For larger value of ecological water demand and shipping water demand, unit m 3 /s；Q max Design maximum flood discharge for reservoir, unit m 3 /s；Q Emax Is the maximum flow rate of the engine, unit m 3 /s，Q Emmin Minimum generating flow for ensuring normal operation of reservoir in unit m 3 /s；
N max The maximum power generation output of the target reservoir is represented, namely the installed capacity of the reservoir, and the unit kW is obtained; n is a radical of min And (3) representing the minimum generated output, namely the reduced output in the power generation dispatching diagram of the reservoir, and when the target reservoir is a radial-flow reservoir, the reduced output is not generated, and the unit kW is obtained.
Preferably, in step S2, when the reservoir generated output N is greater than the reservoir generated output N max When, let N = N max Then, the generated current Q of the target reservoir is recalculated according to the formula (12) E ：
Preferably, in step S3, the objective function includes:
calculating the average power generation of a target reservoir for many years, wherein the larger the average power generation for many years is, the better the average power generation for many years is;
wherein EPow represents the average generation per year of the target reservoir in hundred million kWh; e h Generating capacity of a target reservoir in a time period h; y is the number of years covered by reservoir dispatching simulation; m is the total time interval;
ii, the flood season of the reservoir is dimensionless and has a value range of [0,1], and the closer to 1, the better the flood season of the reservoir is;
wherein Q is r For the flood season of the target reservoirThe ratio, I (t) is the warehousing flow of the target reservoir at the time t, Q (t) is the ex-warehousing flow of the target reservoir at the time t, and Q is the warehousing flow value when the target reservoir performs flood storage;
in the range from the dead water level to the normal water storage level, the lower the highest water level value before the dam is, the better the highest water level value before the dam is;
and iv, the larger the average generated energy in the flood season, the better the average generated energy in the flood season, and the unit is hundred million kWh.
Preferably, in step S4, a constraint method that adaptively modifies upper and lower limits of variables is set to sample the general flood control dispatch graph, which is specifically implemented according to the following steps:
s41, setting the number of inflection points of each dispatching line in the general flood control dispatching graph, wherein the abscissa and the ordinate of each inflection point both accord with value range constraints;
when sampling each scheduling line, the sampling sequence is as follows: extracting the dispatching lines from top to bottom according to the positions of the dispatching lines in the general flood control dispatching graph; for each extracted scheduling line, sequentially sampling from a left vertex, a left endpoint, a right vertex and a right endpoint of the scheduling line; then dividing the dispatching line into two parts to obtain a left half part and a right half part, and extracting inflection points on the left half part and the right half part from left to right;
s42, acquiring an upper limit and a lower limit of an abscissa of any inflection point P, specifically:
according to the adjacent inflection points of the inflection point P, the upper limit and the lower limit of the abscissa of the inflection point P are judged, and the method specifically comprises the following steps: the abscissa of the determined sampling inflection point, which is positioned on the left side of the inflection point P on the scheduling line where the inflection point P is positioned, is taken as the abscissa value lower limit of the inflection point P, and the abscissa value upper limit of the inflection point P is the maximum value taken by the abscissa of the inflection point P in the abscissa value range;
s42, calculating the upper limit and the lower limit of the ordinate of any inflection point P, specifically:
according to the non-intersection of each scheduling line and the descending trend of all the scheduling lines in the general flood control scheduling graph, sequentially performing global upper and lower limit determination, vertical control line determination and cross control determination to obtain an upper limit and a lower limit of a vertical coordinate of an inflection point P;
s421, determining the global upper limit and the global lower limit, wherein for any scheduling line L with the vertex at the normal water storage level or the flood limit water level of the target reservoir, the global upper limit of the scheduling line L is the normal water storage level or the flood limit water level of the reservoir, and the global lower limit of the scheduling line L is the dead water level of the target reservoir; for any one scheduling line J with the vertex not reaching the normal water storage level or the flood limit water level, the overall upper limit of the scheduling line J is the vertex water level of the scheduling line J, the overall lower limit of the scheduling line J is the dead water level of the target reservoir, and a first group of upper and lower water level limits is obtained;
s422, determining the vertical control lines, sequencing the scheduling lines from top to bottom according to the upper and lower positions of the scheduling lines in the general flood control scheduling graph for the scheduling lines, and sampling from the first scheduling line to the last scheduling line during sampling; the vertical upper limit of the first dispatching line is a normal water storage level or a flood limit water level; starting from the second dispatching line, determining the vertical coordinate of each inflection point in the dispatching line to be calculated according to the upper dispatching line of the following dispatching line by the vertical upper limit of each dispatching line, wherein the method specifically comprises the following steps:
any scheduling line with the serial number u, wherein u is larger than 1, the date T of any inflection point E in the scheduling line u is obtained, the water level value of the corresponding inflection point of the scheduling line u-1 at the date T is searched, and the obtained water level value is used as the upper limit of the water level of the inflection point E; according to the principle of increasing the left half part of a dispatching line in the general flood control dispatching graph, taking the water level value of the inflection point D closest to the inflection point E on the dispatching line u as the lower limit of the water level of the inflection point E to obtain a second group of upper and lower limits of the water level;
s423. The cross control determines
A1, acquiring a time period q of two adjacent inflection points E and D on a dispatching line u and a water level interval of the two adjacent inflection points, wherein the date of the inflection point D is less than that of the inflection point E, judging whether a water level value on the dispatching line u-1 is in the inflection point in the water level interval under the condition of the time period q, and if not, not crossing the dispatching line u and the dispatching line u-1 in the time period q; if yes, entering A2;
a2, judging whether the quantity of the inflection points of the water level value in the water level interval is equal to 1, if so, connecting the inflection point D with the inflection point A of the water level value in the water level interval and prolonging the time of the inflection point E to obtain an inflection point C, and taking the water level value of the inflection point C as the upper water level limit of the inflection point E; if the water level value is not equal to 1, selecting an inflection point A 'with the water level value at the leftmost side of the water level interval, connecting an inflection point D with the inflection point A' and prolonging the inflection point D to the time of the inflection point E to obtain an inflection point C ', and taking the water level value of the inflection point C' as the upper water level limit of the inflection point E to obtain the upper and lower water level limits of a third group;
and S424, taking the intersection of the upper and lower water level limits of the three groups to form the upper and lower water level limits of the point to be sampled, and sampling the point within the range of the upper and lower water level limits of the point to be sampled.
Preferably, the solving of the optimization problem by using the NSGA-II algorithm in step S5 includes the following steps:
s51, randomly generating an initial population, simulating each individual in the population, evaluating a target function value, and obtaining a first generation offspring population through three basic operations of selection, intersection and variation of a genetic algorithm after multi-target non-dominated sorting;
s52, from the second generation, merging the parent population and the offspring population, carrying out simulation solution one by one in the population, carrying out multi-target rapid non-dominated sorting to form a new parent population, carrying out crowding degree calculation on the individuals in each non-dominated layer, and selecting proper individuals according to the non-dominated relationship and the crowding degree of the individuals to form a new parent population;
s53, generating a new filial generation population through basic operation of a genetic algorithm; and circulating the calculation until the condition of ending the program is met.
Preferably, the Pareto non-dominated solution analysis is performed on the objective function in step S6, and the principle is as follows: two vectors u and v are set in a solution set, and f is satisfied for n smaller and better target functions i (u)≤f i (v),And wherein at least one strict inequality f i (u)＜f i (v) If it is true, the vector u dominates v, and similarly, if u can dominate all other solution vectors except itself or u is not dominated by other arbitrary solutions, u is called a Pareto non-branch of the multi-objective optimization problemAnd (5) matching and solving.
The invention has the beneficial effects that:
the method of the invention can adopt the flood control scheduling graph form in the flood season that the water level of the reservoir is higher than the flood limit water level, so as to reasonably use the flood control storage capacity of the reservoir, and can redistribute the water coming from the reservoir in the flood season, thereby providing a basis for reasonably utilizing flood resources to the maximum extent.
Compared with the prior art, the flood season scheduling method based on the reservoir flood control scheduling graph is used in the method, the flood control scheduling graph of the reservoir can set the water discharge rule of the reservoir in the current time period according to the current water level, the incoming water condition and the water forecast in a period of time, and compared with the flood control strategy in the traditional prosperity scheduling graph, the reservoir flood season scheduling introduced with the flood control scheduling graph can fully utilize the incoming water of the reservoir while ensuring the safety of downstream flood control, and the utilization efficiency of flood is improved. Meanwhile, a dispatching diagram constraint control method for adaptively adjusting the upper limit and the lower limit of the decision variable is established, when the reservoir dispatching diagram is optimized, the constraint control method for adaptively adjusting the upper limit and the lower limit of the decision variable is initiated according to the geometric constraint characteristic of the dispatching diagram, the feasibility of each solution in an optimization model can be ensured, the calculation efficiency of the optimization model in decision variable search is improved, and therefore the solution efficiency of the optimization model is improved.
Drawings
FIG. 1 is a schematic diagram of a reservoir flood control dispatch optimization method based on flood control dispatch data adaptive control;
FIG. 2 is a diagram of a generic flood control schedule;
FIG. 3 is a schematic view of a reservoir flood control scheduling calculation process;
FIG. 4 is a schematic diagram of dispatch line crossing control, and FIG. 4 includes (a) a schematic diagram of a dispatch line vertical level control line I, (b) a schematic diagram of a dispatch line vertical level control line II, and (c) a schematic diagram of dispatch line crossing control;
FIG. 5 is a flow chart of the NSGA-II algorithm;
FIG. 6 is a flood control schedule for a reservoir according to example 1;
fig. 7 is a comparison diagram of the discharge flow of a certain reservoir in 1998 flood season of the certain reservoir in example 1.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, several steps of the present application are explained in detail:
(one) the face schedule in step S1 is any one of upcoming times;
and (II) calculating the flood control dispatching of the reservoir related in the step 2, wherein the calculation process in the figure 3 shows that the interest dispatching is the main calculation, and the flood control dispatching calculation of the reservoir is carried out when the first judgment condition in the figure 3 is met. When the discharge capacity of the reservoir is known, the reservoir water level, the downstream tail water level and the actual output of the reservoir at the end of the faced time interval can be easily calculated according to the expressions (1) to (7), and the scheduling result of the reservoir also needs to follow the constraint conditions listed in the expressions (8) to (11). Because the water supply is large, the situation that the actual output exceeds the installed capacity of the reservoir is very likely to happen, at the moment, the power generation flow of the reservoir needs to be recalculated according to the formula (12), and the surplus water conservancy is abandoned.
The flood control dispatching graph designed by the application is less in use at present, is different from the flood control dispatching graph designed by the predecessor, and basically has no flood control dispatching graph which can be directly used in a reservoir. Therefore, when the flood control dispatch graph is applied, the flood control dispatch graph needs to be optimized in advance according to the general flood control dispatch graph formulation rule, and the water supply base can be used in the future flood control dispatch.
And (III) determining an objective function in the step S3, and ensuring the requirements of shipping, ecological water consumption and safety and stability of an electric power system on the premise of ensuring the safety of a reservoir and the downstream.
And (IV) in the step S4, a constraint method for adaptively modifying the upper limit and the lower limit of the variable is adopted to sample the general flood control dispatch diagram, the reservoir optimization problem is mainly to optimize the dispatch diagram, and in view of the particularity of the optimization problem, the invention designs a constraint control method for sampling the dispatch diagram by self, namely, the upper limit and the lower limit of the value of the horizontal coordinate and the vertical coordinate of each variable are calculated immediately before each variable is sampled, then uniform sampling is carried out within the upper limit and the lower limit, and the upper limit and the lower limit of each inflection point on each dispatch line are reasonably calculated, so that the sampled dispatch diagram population can be guaranteed to be feasible.
It is known from step S1 that the general flood control dispatch graph adopts a four-line control line manner, when the flood control dispatch graph is optimized, the number of inflection points of each dispatch line of the dispatch graph can be arbitrarily specified, but the abscissa and ordinate of each inflection point need to satisfy the geometric rules specified in step S1 in addition to time constraints, and according to the rules, when the abscissa and ordinate of each inflection point are extracted, the upper and lower limits of the abscissa and ordinate of each inflection point need to be determined together according to the adjacent inflection point and the adjacent inflection point of the adjacent dispatch line. And the extraction sequence when sampling each scheduling line is as follows: sampling the dispatch line from top to bottom; for each scheduling line, sampling a left vertex, a left endpoint, a right vertex and a right endpoint of the scheduling line; and then respectively extracting the inflection point coordinates of the left half part and the right half part of the dispatching line from left to right. Therefore, the inflection point is easy to obtain the upper and lower limits of the abscissa thereof during sampling, and the inflection point can be controlled directly according to the abscissa of the nearest sampled point. And in order to calculate the upper and lower limits of the ordinate of the inflection point, the principle of non-intersection of the dispatching lines and increasing and decreasing of the dispatching lines is required. The calculation of the upper and lower limits of the vertical coordinate of each point comprises the following steps:
(1) a global upper and lower bound. The ordinate of each point, the global upper limit of the water level, is the normal water storage level of the reservoir (the flood season is the flood limit water level), and the global lower limit is the dead water level of the reservoir. The top points of some dispatch lines will not reach the normal water level, and the global upper limit of the corresponding dispatch line is modified to the top point water level, and as mentioned above, the left and right top points are the first sampling batches of each dispatch line. Therefore, when the lower water level upper limit calculation is carried out at other points, the vertex water level coordinate is already known.
(2) And controlling the line vertically. As the dispatching lines are sampled from top to bottom, the vertical upper limits of the first dispatching line from top to bottom are all normal water storage levels (the flood season is the flood limit water level). But starting from the second line, the vertical coordinates of each point of each current dispatch line need to be controlled according to the sampled more than one line. As shown in fig. 4 (a), for example, to sample the water level value at point E in the second dispatch line in the graph (at this time, the time at point E has been determined), the water level value at point E in the previous dispatch line on the date (the water level at point C) needs to be searched, and this is used as the upper limit of the water level at point E, and meanwhile, according to the principle of increasing the left half of the dispatch line, the water level at point E takes the water level at point D as the lower limit.
(3) And (4) cross control. If the upper and lower limits of the inflection point are determined based on only the vertical control line, the sampled dispatch line will probably cross the previous line, and the situation shown in fig. 4 (b) occurs, and the sampled dispatch graph is not feasible. Therefore, to avoid this, it is necessary to perform scheduling line crossing control at the time of sampling, as shown in fig. 4 (c). In this process, first, it is determined whether there is an inflection point in the date of the previous scheduling line between the sample point D and the current sample point E (the abscissa date is known), such as inflection point a in the present example. And connecting the DA and prolonging the date to the E point to obtain the C point, and taking the water level of the C point as the upper limit of the water level of the E point, wherein the disjoint scheduling lines must be ensured at the moment. If there are several inflection points in the last dispatch line in the two DE dates, the calculation can be done with the leftmost point, and the other inflection points can be disregarded.
Under the three-layer control, three groups of upper and lower water level limits of the point to be sampled can be obtained, the intersection of the three groups of upper and lower water level limits can form the upper and lower water level limits of the point to be sampled, and the inflection point is extracted in the range, so that the feasibility of the dispatching graph can be ensured.
From the above, the calculation of the upper and lower limits of the water level of each point on the dispatching line is still complex, and the abscissa of the point to be calculated and the information of the nearby points of the same and the previous dispatching line are required. The upper and lower limits of each point can be updated in a self-adaptive mode according to the information of the related points nearby, and although the workload of the upper and lower limits of each point in the self-adaptive calculation is large, the feasibility of the sampled scheduling graph can be guaranteed, so that the workload of the optimized calculation is reduced to a great extent.
With reference to fig. 5, in step S5, the optimization problem is solved by using the NSGA-II algorithm. In fig. 5, the individual simulation in the population includes three processes of dispatch diagram reduction, reservoir dispatching model calculation, and dispatching target calculation. Decision variables in the optimization algorithm are a plurality of variables uniformly distributed in the [0,1] interval, during simulation, the sample values of the decision variables in each individual are firstly reduced into a dispatching graph according to a certain principle, and then long-series reservoir dispatching and target function evaluation can be carried out according to the dispatching graph.
In step S6, the Pareto non-dominated solution analysis is performed on the objective function, and the non-dominated solution has the least target conflicts compared with other solutions, so that a better selection space can be provided for a decision maker. The set of all Pareto non-dominant solutions is called a Pareto non-dominant solution set. Any objective function is improved on the basis of a non-dominant solution while at the same time at least one other objective function is necessarily attenuated. The principle is as follows:
two vectors u and v are set in a solution set, and f is satisfied for n smaller and better target functions i (u)≤f i (v),And wherein at least one strict inequality f i (u)<f i (v) If true, vector u dominates v. Similarly, if u can dominate all other solution vectors except itself or u is not dominated by any other solution, u is called a Pareto non-dominated solution of the multi-objective optimization problem.
In general, as shown in fig. 2, the general flood control dispatching diagram comprehensively considers information such as an incoming forecast of a target reservoir at an faced moment, hydrology at a possible time interval end and the like, and reasonably dispatches the target reservoir as much as possible. When the possible water level at the end of the time period is higher and the inflow of the target reservoir is larger, water is discharged as much as possible, so that the risk of the reservoir is reduced; when the possible water level at the end of the time period is lower and the inflow of the target reservoir is less, the reservoir discharge capacity is reduced, the flood control reservoir capacity of the target reservoir is used for storing the flood, the downstream flood control pressure is reduced, and the target reservoir water energy utilization efficiency is improved.
The upper limit value and the lower limit value of the water flow increment of the abscissa of the general flood control dispatching graph are obtained through the variation range of the historical measured flow or the forecast flow period in the flood season, the upper limit value and the lower limit value of the possible water level at the end of the ordinate period of the general flood control dispatching graph are obtained through the water level range under the normal condition of the water level of the target reservoir, the value of the dispatching line of the reservoir discharge is determined according to the flood control target at the downstream of the target reservoir, and the values of the maximum reservoir discharge and the minimum reservoir discharge are the discharge value of the highest water level and the discharge value of the lowest water level under the normal water level condition of the target reservoir respectively.
According to the calculation process, the prosperous scheduling is mainly used in the calculation, and the flood control scheduling calculation of the target reservoir is carried out when the flood season is entered and the water level of the target reservoir is higher than the flood limit water level. The flood control dispatching map designed by the invention is less in use at present, is different from the flood control dispatching map designed by the prior art, and basically has no flood control dispatching map which can be directly used for any reservoir. Therefore, when the flood control dispatching graph is applied, a flood control dispatching graph belonging to the reservoir needs to be optimized in advance according to the general flood control dispatching graph formulation rule in the step S1, and the reservoir can be used for future flood control dispatching.
Example 1
The horizontal axis of the general flood control dispatch graph is the inflow increment of the faced time interval, and the vertical axis is the possible water level at the end of the faced time interval. For a certain reservoir, analyzing the historical runoff rule of the dam site of the reservoir in the flood season, and replacing the forecast flow with the measured flow to obtain the inflow water flow increment of each time period of-20872 m 3 /s,20938m 3 /s]In 1961-2005, the flood limit water level of the reservoir is 145m, the normal water storage level is 175m, and the water level is 145m,175m under the normal condition]The range is changed, the upper limit and the lower limit of the value are properly widened, the amplitude of the water level is set to be [144.5m]And obtaining a general flood control dispatching chart of the reservoir as shown in figure 6.
General flood control dispatch diagramWith the four control line approach as shown in FIG. 6, the corresponding leakage flow rates (from top to bottom) are Q 4 ＝76000m 3 /s、Q 3 ＝54000m 3 /s、Q 2 ＝40000m 3 S and Q 1 ＝25000m 3 And/s, respectively controlling water levels of 45m, 44.5m, 43m and 40m of downstream flood control targets. In the general flood control dispatching chart, the control flow of 180m lines is the maximum discharge flow of a certain reservoir and is 200000m 3 The flow of the line 144.5m at the lowest end is determined according to the minimum water inflow amount in the flood season, and the minimum flow of a certain reservoir dam site is 6140m through analyzing historical runoff 3 And/s, in order to ensure the requirements of shipping, ecological water utilization and power system safety and stability, the research of the embodiment controls the minimum discharge rate to be 8000m 3 And s. When the general flood control dispatching graph is used, the flow interval is determined according to the water flow increment of a period of time and the possible water level at the end of the period of time, and then the final flow out of the reservoir is determined according to the control flow interpolation of the upper dispatching line and the lower dispatching line.
The goals of flood seasons obtained by performing long-series simulation on the design schedule chart in the implementation are listed in table 1.
TABLE 1 objective function with flood season as statistical time interval under normal operation of certain reservoir
As can be seen from the table 1, when the system operates according to a design scheduling chart, the flood control storage capacity utilization rate of a certain reservoir is quite low, and a large optimization space exists in the flood season. Therefore, in the flood control dispatch graph designed in this embodiment as shown in fig. 6, the value range of the horizontal and vertical coordinates of each dispatch line and the control flow rate are already determined. But the shape of the dispatching line needs to be optimized to obtain the best flood control and benefit comprehensive effect. The highest water level of the reservoir before the dam in the flood season is 147.15m, and the maximum water level exceeds the flood limit water level by 145m, so that the reservoir is quite safe, but the flood rate is very low, the flood effect is almost not great, the downstream flood control target is extremely unfavorable, the suitable navigation flow is also higher, and the navigation in the flood season is also unfavorable (Table 1). The following four objective functions are selected during optimization:
(1) The average power generation per year, i.e., hundreds of millions of kWh, the larger the power generation, the better
Wherein EPow represents the average generation per year of the target reservoir in hundred million kWh; e h Generating capacity of a target reservoir in a time period h; y is the number of years covered by reservoir dispatching simulation; m is the total number of time periods.
(2) The flood delay rate in the flood season is dimensionless, and the value range [0,1] is as large as possible;
in formula (14), Q r The flood period flood retardation rate of the target reservoir is shown, I (t) is the warehousing flow of the target reservoir at the time t, Q (t) is the ex-warehousing flow of the target reservoir at the time t, and Q is the warehousing flow value of the target reservoir when flood retaining is carried out;
(3) The dam front highest water level is in the range from the dead water level to the normal water storage level, and the smaller the dam front highest water level value is, the better the dam front highest water level value is;
(4) The larger the generated energy in flood season, i.e. hundred million kWh, the better. The method for calculating the average power generation amount in the flood season is the same as the method for calculating the average power generation amount of the target reservoir in many years, the statistical time period of the average power generation amount in the flood season is 5-10 months per year, and the larger the statistical time period is, the better the statistical time period is.
When the flood control dispatching chart is introduced to guide the dispatching of the reservoir in the flood season, the general flood control dispatching chart only plays a role when the reservoir enters the flood season and the water level is higher than the flood limit water level of the reservoir, and the reservoir prosperity dispatching chart is still adopted to guide the other situations. Therefore, when the general flood control dispatch graph is optimized, the target of the flood season is mainly selected as the optimized target function.
The abscissa of the flood control dispatch graph is the incoming water flow increment, the value is taken in a fixed range, different from the Xingli dispatch graph, the general flood control dispatch graph only needs to carry out geometric constraint when sampling the value, and each dispatch line in the general flood control dispatch graph is decreased progressively, so that an adaptive control variable upper and lower limit constraint control strategy is also adopted (fig. 4 (a-c)).
According to the four proposed objective functions of multi-objective optimization and the self-adaptive upper and lower limit constraint calculation method, long-series optimization is also carried out on the flood control dispatching graph of a certain reservoir. The optimization period is again 1/1962 to 12/31/2005. When a reservoir flood control dispatching diagram is optimized, 7 control points are arranged on the four flow control lines, and the coordinates of the end points of the four lines on the horizontal axis are fixed and do not need to be optimized. Therefore, 48 decision variables need to be optimized when a reservoir flood control dispatch graph is optimized in the embodiment. When the general flood control dispatching graph is optimized and calculated, the NSGA-II multi-target heuristic optimization algorithm is also adopted for solving, and the parameters are set as follows: the population scale is set as 200, the evolution generation number is 20, the cross probability is 0.9, the cross distribution index is 20, the mutation probability is 0.1, and the mutation distribution index is 20.
In the embodiment, the multi-target result of the four-dimensional space after the general flood control dispatch graph is optimized is projected on each plane to obtain a plurality of groups of two-target comparison graphs, and the four targets except the highest water level in front of the dam are all larger and better. Some targets are competitive, such as the highest water level before the dam and the reservoir flood rate, and the two targets are almost completely consistent and increase and decrease. This is consistent with the fact that higher head levels in front of the dam indicate more stagnant flood. In practice, these two goals are mutually contradictory, and therefore require a trade-off. Similarly, the highest water level before the dam and the annual power generation amount of the reservoir have obvious competitiveness, and the phenomenon that the annual power generation amount is larger when the highest water level before the dam is higher is obviously shown, because the annual water abandonment amount can be reduced when the flood storage water is used for power generation after flood in the flood season, so that the annual power generation amount is improved. Correspondingly, due to the accumulation effect of the flood, the power generation amount in the flood season is also influenced, but the relationship between the power generation amount in the flood season and the highest water level in front of the dam is not as clear as the relationship between the power generation amount in the flood season and the highest water level in front of the dam, so that the situation can be understood. Because when the reservoir is flooded in the flood season, the lower discharge capacity of the reservoir is bound to be reduced, but the difference between the upstream and downstream water heads is increased due to the fact that the water level of the reservoir is raised, and the relation between the generated energy and the water level of the reservoir is not simple and linear, so that the relation between the generated energy and the water level of the reservoir is difficult to measure.
In order to further analyze the optimization result of the reservoir flood control dispatching graph, the same optimal value analysis is carried out on all objective functions of the last population of the universal flood control dispatching graph in the optimization dispatching. The analysis results are shown in Table 3. As can be seen from table 3, after the general flood control dispatching diagram is introduced for optimization, the annual average power generation can be greatly improved under the condition of maintaining the prosperity dispatching diagram unchanged, the maximum power generation can be increased by 13%, but the maximum water level before the dam reaches the normal water storage level 175m in the flood season, which is quite unfavorable for flood control.
TABLE 3 Individual optimal solution in Multi-objective Joint optimization scheduling results
Actually, the most concerned targets in the flood season are the highest water level before the dam and the reservoir flood retardation rate, and the minimum scheme of the highest water level before the dam can still improve the annual average power generation of the reservoir, and the rate of increase reaches 10%; and when the flood retention rate is the maximum scheme, the flow rate of the opposite warehousing is higher than 40000m 3 In the case of the specific power generation quantity per second, the flood can be delayed by 27%, and the annual average power generation quantity can be increased by 12%. To further analyze the effect of the general flood control dispatch graph, in this example, the flood period flood process of 1998 (from 11 months to 30 months from 4 to 9), the process of discharging a certain reservoir under the effect of the minimum maximum water level scheme before the dam and the maximum flood rate scheme is analyzed as shown in fig. 7. It can be obviously seen that when a flood control dispatching diagram is not considered, the conventional dispatching of the reservoir has little flood stagnation effect, and the flow of the reservoir is almost equal to the flow of the reservoir. However, after the flood control dispatching graph is introduced, the reservoir starts to accumulate the flood, and the flood process has an obvious peak shifting phenomenon.
By adopting the technical scheme disclosed by the invention, the following beneficial effects are obtained:
the method of the invention can adopt the flood control scheduling graphic form in the flood season that the water level of the reservoir is higher than the flood limit water level, so as to reasonably use the flood control capacity of the reservoir, and can redistribute the water coming from the reservoir in the flood season, thereby providing a basis for reasonably utilizing the flood resources to the utmost extent.
Compared with the prior art, the flood season scheduling method based on the reservoir flood control scheduling graph is used in the method, the flood control scheduling graph of the reservoir can set the water discharge rule of the reservoir in the current time period according to the current water level, the incoming water condition and the water forecast in a period of time, and compared with the flood control strategy in the traditional prosperity scheduling graph, the reservoir flood season scheduling introduced with the flood control scheduling graph can fully utilize the incoming water of the reservoir while ensuring the safety of downstream flood control, and the utilization efficiency of flood is improved. Meanwhile, a dispatching diagram constraint control method for adaptively adjusting the upper limit and the lower limit of the decision variable is established, when the reservoir dispatching diagram is optimized, the constraint control method for adaptively adjusting the upper limit and the lower limit of the decision variable is initiated according to the geometric constraint characteristic of the dispatching diagram, the feasibility of each solution in an optimization model can be ensured, the calculation efficiency of the optimization model in decision variable search is improved, and therefore the solution efficiency of the optimization model is improved.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, many modifications and adaptations can be made without departing from the principle of the present invention, and such modifications and adaptations should also be considered to be within the scope of the present invention.
Claims (7)
1. A reservoir flood control dispatching optimization method based on flood control dispatching data self-adaptive control is characterized by comprising the following steps:
s1, establishing a general flood control dispatching diagram of a target reservoir; the horizontal axis of the general flood control scheduling graph is inflow flow increment of an confrontation time interval, the vertical axis of the general flood control scheduling graph is possible water level at the end of the confrontation time interval, the upper limit and the lower limit of the horizontal axis are calculated according to historical flow or simulated flow of a target reservoir during the flood season, and the upper limit and the lower limit of the vertical axis are respectively historical highest water level and historical lowest water level of the target reservoir;
a plurality of mutually-intersected scheduling lines which are in a descending trend are arranged in the general flood control scheduling graph, each scheduling line is formed by connecting piecewise straight lines formed by connecting any number of inflection points, and each scheduling line is set with a control flow and distributed in the general flood control scheduling graph;
according to the upper and lower position relations of the dispatching lines on the general flood control dispatching graph, the control flow of the dispatching lines above the general flood control dispatching graph is gradually increased to the control flow of the dispatching lines below the general flood control dispatching graph;
s2, establishing a flood control dispatching model, and when the water level of the target reservoir is higher than a flood limit water level in a flood season, starting to use the flood control dispatching model for flood control dispatching by the target reservoir; the method comprises the following specific steps:
firstly, judging the flow increment of the reservoir, calculating the possible water level at the end of the period of the reservoir, inquiring a general flood control dispatching graph, and obtaining the reservoir discharge at the current moment through interpolation calculation; secondly, under the condition of known reservoir discharge capacity, obtaining the relationship between the possible water level at the end of the faced time interval and the dam discharge water level flow of the target reservoir and the reservoir generated output according to the formulas (1) to (7), then judging whether the results obtained by calculation according to the formulas (1) to (7) meet the preset constraint condition, and if so, entering S3; if not, recalculating the power generation flow of the target reservoir, performing water abandoning by redundant water conservancy, and then entering S3;
the flood control scheduling model comprises:
the water balance relation is formula (1):
the flow relation of the dam drainage water level is a formula (2):
Q＝f(H D ) (2)；
the library capacity curve is formula (3):
V＝V(H) (3)；
the incremental formula of the water flow at the time t is shown as the formula (4):
ΔI＝I t -I t-1 (4)；
the library capacity at time t is formula (5):
V t ＝V t-1 +I t ×Δt (5)；
possible water level formula (6) before the dam at time t:
H t ＝H(V t ) (6)；
the reservoir generated output calculation formula is as follows:
wherein I is warehouse entry flow and unit m 3 S; q is the flow out of the warehouse in m 3 S; v is the current water storage in the reservoir in m 3 (ii) a t is the time; v 1 、V 2 The water quantity of the reservoir at the beginning and the end of the time interval respectively, unit m 3 (ii) a Δ t is a scheduling time period, unit s; f (H) D ) The relationship of the flow rate of the water level discharged under the dam; v (H) represents a relational expression for reversely deducing the reservoir capacity from the reservoir water level; h is the dam front water level in m; delta I is the water flow increment of the reservoir at the time t and the unit m 3 /s；I t The water inflow of the reservoir at the time t in the unit of m 3 /s；I t-1 The water inflow of the reservoir at the time of t-1 in m 3 /s；V t Is the amount of water in the reservoir at time t in units of m 3 ；V t-1 Is the amount of water in the reservoir at time t-1, in m 3 ；H t The possible water level in front of the reservoir dam at the moment t is unit m; h (V) t ) A relational expression representing the water level reversely deduced from the reservoir capacity of the reservoir; n is the power generation output of the reservoir in kW; k is the output coefficient; h 1 、H 2 The water levels of the reservoir at the beginning and the end of the dispatching time period and the unit m are respectively; q E For generating flow of reservoir in m 3 /s；H D Is the water level under the reservoir dam, unit m; Δ V is the amount of change in the storage capacity of the reservoir, in m 3 ；
S3, determining a target function;
s4, obtaining the total number of optimized variables required by the general flood control dispatch graph according to the number of the dispatch lines of the general flood control dispatch graph and the number of inflection points of each dispatch line;
s5, solving the optimization problem by using an NSGA-II algorithm according to the determined objective function and the optimization variable;
s6, carrying out Pareto non-dominated solution analysis on the target function to obtain an optimized general flood control dispatching graph;
and S7, applying the optimized general flood control dispatching graph to calculate flood control services.
2. The method of claim 1, wherein the constraint comprises:
water level constraint, equation (8):
H dl ≤H 1 ，H 2 ≤H nl (8)；
flow constraints, i.e., equation (9):
Q min ≤Q≤Q max (9)；
the power generation flow constraint condition, namely formula (10):
Q Emin ≤Q E ≤Q Emax (10)；
the generated output constraint, i.e., equation (11):
N min ≤N≤N max (11)；
wherein H dl Is the reservoir dead water level in m; h nl Is the normal water storage level of the reservoir, unit m; q min For larger value of ecological water demand and shipping water demand, unit m 3 /s；Q max Design of maximum flood discharge for reservoir in m 3 /s；Q Emax Is the maximum flow rate of the engine in m 3 /s，Q Emmin Minimum generating flow for ensuring normal operation of reservoir in unit m 3 /s；
N max The maximum power generation output of the target reservoir is represented, namely the installed capacity of the reservoir, and the unit kW is obtained; n is a radical of min And (3) representing the minimum generated output, namely the reduced output in the power generation dispatching diagram of the reservoir, and when the target reservoir is a radial-flow reservoir, the reduced output is not generated, and the unit kW is obtained.
3. The method of claim 2, wherein in step S2, the water is delivered as a reservoirThe electric output N is greater than the reservoir generated output N max When, let N = N max Then, the generated current Q of the target reservoir is recalculated according to the formula (12) E ：
4. The method of claim 1, wherein in step S3, the objective function comprises:
calculating the average power generation of a target reservoir for many years, wherein the larger the average power generation for many years is, the better the average power generation for many years is;
wherein EPow represents the average generation of the target reservoir for many years in hundreds of millions of kWh units; e h Generating capacity of a target reservoir in a time period h; y is the number of years covered by reservoir dispatching simulation; m is the total time interval;
ii, the flood season of the reservoir is dimensionless and has a value range of [0,1], and the closer the flood season of the reservoir is to 1, the better;
wherein Q is r The flood period flood retardation rate of the target reservoir is defined as I (t), the warehousing flow rate of the target reservoir at the time t is defined as I (t), the ex-warehousing flow rate of the target reservoir at the time t is defined as Q, and the warehousing flow rate value of the target reservoir during flood retardation storage is defined as Q;
in the range from the dead water level to the normal water storage level, the smaller the highest water level value before the dam is, the better the water level value is;
and iv, the larger the average generated energy in the flood season, the better the average generated energy in the flood season, and the unit is hundred million kWh.
5. The method according to claim 1, wherein in step S4, the general flood control dispatch graph is sampled by using a constraint method of adaptively modifying upper and lower limits of variables, and the method is implemented by the following steps:
s41, setting the number of inflection points of each dispatching line in the general flood control dispatching graph, wherein the abscissa and the ordinate of each inflection point both accord with value range constraints;
when sampling each scheduling line, the sampling sequence is as follows: extracting the dispatching lines from top to bottom according to the positions of the dispatching lines in the general flood control dispatching graph; for each extracted scheduling line, sequentially sampling from a left vertex, a left endpoint, a right vertex and a right endpoint of the scheduling line; then dividing the dispatching line into two parts to obtain a left half part and a right half part, and extracting inflection points on the left half part and the right half part from left to right respectively;
s42, acquiring an upper limit and a lower limit of an abscissa of any inflection point P, specifically:
according to the adjacent inflection points of the inflection point P, the upper limit and the lower limit of the abscissa of the inflection point P are judged, and the method specifically comprises the following steps: the abscissa of the determined sampling inflection point, which is located on the left side of the inflection point P on the scheduling line where the inflection point P is located, is taken as the abscissa value lower limit of the inflection point P, and the abscissa value upper limit of the inflection point P is the maximum value taken by the abscissa of the inflection point P in the abscissa value range;
s42, calculating the upper limit and the lower limit of the ordinate of any inflection point P, specifically:
according to the non-intersection of each scheduling line and the descending trend of all the scheduling lines in the general flood control scheduling graph, sequentially performing global upper and lower limit determination, vertical control line determination and cross control determination to obtain an upper limit and a lower limit of a vertical coordinate of an inflection point P;
s421, determining the global upper limit and the global lower limit, wherein for any scheduling line L with the vertex at the normal water storage level or the flood limit water level of the target reservoir, the global upper limit of the scheduling line L is the normal water storage level or the flood limit water level of the reservoir, and the global lower limit of the scheduling line L is the dead water level of the target reservoir; for any scheduling line J with the vertex not reaching the normal water storage level or the flood limit water level, the global upper limit of the scheduling line J is the vertex water level of the scheduling line J, and the global lower limit of the scheduling line J is the dead water level of the target reservoir, so that a first group of upper and lower water level limits is obtained;
s422, determining the vertical control lines, sequencing the scheduling lines from top to bottom according to the upper and lower positions of the scheduling lines in the general flood control scheduling graph for the scheduling lines, and sampling from the first scheduling line to the last scheduling line during sampling; the vertical upper limit of the first dispatching line is a normal water storage level or a flood limit water level; starting from the second dispatching line, determining the vertical coordinate of each inflection point in the dispatching line to be calculated according to the upper dispatching line of the following dispatching line by the vertical upper limit of each dispatching line, wherein the method specifically comprises the following steps:
any scheduling line with the serial number u, wherein u is larger than 1, the date T of any inflection point E in the scheduling line u is obtained, the water level value of the corresponding inflection point of the scheduling line u-1 at the date T is searched, and the obtained water level value is used as the upper limit of the water level of the inflection point E; according to the principle of increasing the left half part of a dispatching line in the general flood control dispatching graph, taking the water level value of the inflection point D closest to the inflection point E on the dispatching line u as the lower limit of the water level of the inflection point E to obtain a second group of upper and lower limits of the water level;
s423. The cross control determines
A1, acquiring a time period q of two adjacent inflection points E and D on a dispatching line u and a water level interval of the two adjacent inflection points, wherein the date of the inflection point D is less than that of the inflection point E, judging whether a water level value on the dispatching line u-1 is in the inflection point in the water level interval under the condition of the time period q, and if not, not crossing the time period q between the dispatching line u and the dispatching line u-1; if yes, entering A2;
a2, judging whether the quantity of the inflection points of the water level value in the water level interval is equal to 1, if so, connecting the inflection point D with the inflection point A of the water level value in the water level interval and prolonging the time of the inflection point E to obtain an inflection point C, and taking the water level value of the inflection point C as the upper water level limit of the inflection point E; if the water level value is not equal to 1, selecting an inflection point A 'with the water level value at the leftmost side of the water level interval, connecting an inflection point D with the inflection point A' and prolonging the time of the inflection point E to obtain an inflection point C ', and taking the water level value of the inflection point C' as the upper water level limit of the inflection point E to obtain a third group of upper and lower water level limits;
and S424, taking the intersection of the upper and lower water level limits of the three groups to form the upper and lower water level limits of the point to be sampled, and sampling the point within the range of the upper and lower water level limits of the point to be sampled.
6. The method of claim 1, wherein the step of solving the optimization problem using the NSGA-II algorithm in step S5 comprises the steps of:
s51, randomly generating an initial population, simulating each individual in the population, evaluating a target function value, and obtaining a first generation offspring population through three basic operations of selection, intersection and variation of a genetic algorithm after multi-target non-dominated sorting;
s52, from the second generation, merging the parent population and the offspring population, carrying out simulation solution one by one in the population, carrying out multi-target rapid non-dominated sorting to form a new parent population, carrying out crowding calculation on the individuals in each non-dominated layer, and selecting proper individuals according to the non-dominated relation and the crowding of the individuals to form a new parent population;
s53, generating a new filial generation population through basic operation of a genetic algorithm; and circulating the calculation until the condition of ending the program is met.
7. The method according to claim 1, wherein the Pareto non-dominated solution analysis of the objective function in step S6 is based on the following principle:
two vectors u and v are set in the solution set, and f is satisfied for the smaller n better target functions i (u)≤f i (v),And wherein at least one strict inequality f i (u)<f i (v) If it is true, the vector u dominates v, and similarly, if u can dominate all other solution vectors except itself or u is not dominated by other arbitrary solutions, u is called a Pareto non-dominated solution of the multi-objective optimization problem.
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