CN113886912B - Multi-stage dam break intelligent optimization emergency scheduling method - Google Patents
Multi-stage dam break intelligent optimization emergency scheduling method Download PDFInfo
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Abstract
The invention discloses an intelligent optimization emergency scheduling method for multi-stage dam break, which belongs to the field of reservoir scheduling, and is characterized in that the lowest highest water level in front of a reservoir group dam in a drainage basin and the smallest sum of squares of ex-warehouse flow are selected as scheduling targets, and a cascade reservoir group emergency scheduling sub-model is established; coupling the emergency scheduling submodel with a breach flood calculation module and a dam break flood evolution module, and establishing a dynamic coupling calling model for seamless connection of emergency scheduling, breach calculation and flood evolution; aiming at the problem that the scheduling process is difficult to optimize and solve due to sudden condition change of the dam break reservoir group, a multi-stage dam break intelligent optimization emergency scheduling model is provided, and the overall intelligent optimization of the dam break emergency scheduling of the basin reservoir group is realized. The invention establishes the dam break emergency scheduling multi-stage intelligent optimization model, solves the problem that the optimization process is forced to be interrupted due to the change of the number of reservoir groups and the change of boundary conditions under the dam break situation, and provides a new thought and method for the dam break emergency scheduling of the watershed cascade reservoir groups.
Description
Technical Field
The invention belongs to the field of reservoir emergency scheduling, and particularly relates to a multi-stage dam break emergency scheduling method.
Background
Along with the deepening of the construction work of the reservoirs in each drainage basin, a cascade reservoir group system in the drainage basin is continuously improved, the reservoir group can realize comprehensive benefits of power generation, water supply, irrigation, shipping and the like, and the most important function of the cascade reservoir group system is flood control and disaster reduction. The flood control emergency scheduling of the watershed reservoir group aims at the optimal scheduling of over-standard flood, and although the probability of the reservoir breaking is very low, once the reservoir breaks, the flow rate of the flood of the break dam is large, the peak height is high, the destructive power is strong, and the destructive damage can be brought to the lives and properties of people in the downstream. Therefore, taking emergency scheduling measures for dam-break flood is the key point of flood control and disaster reduction research of reservoir groups in the watershed. The existing cascade reservoir group dam break emergency scheduling method generally performs cascade reservoir group scheduling under the dam break situation only through reservoir scheduling rules or by adopting the maximum reservoir discharge capacity. In the emergency scheduling process, once a dam is broken, the boundary condition of the reservoir is changed immediately, and the emergency scheduling with the dam breaking situation is difficult to solve through an optimization algorithm, so that the technical problem that the emergency optimal scheduling of the watershed reservoir group cannot be realized exists at present. In addition, the existing method is not tightly combined in the process of breach flood simulation, dam-break flood evolution and emergency dispatching of the step reservoir group.
Therefore, in the prior art, the combination of emergency scheduling, breach calculation and flood evolution is not close enough, and the dam break condition in the emergency scheduling process can cause reservoir boundary condition mutation, so that the solving process of the optimization algorithm is forced to be interrupted, and the technical defect that the global optimization scheduling of the watershed cascade reservoir group cannot be realized exists.
Disclosure of Invention
Aiming at the defects or improvement requirements in the prior art, the invention provides an intelligent optimization modeling method for multi-stage dam break emergency scheduling, and therefore the technical problems that the combination of dam break calculation and flood evolution is not close enough in the existing emergency scheduling, and the dam break condition occurs in the emergency scheduling process to cause sudden change of reservoir boundary conditions, so that the optimization algorithm solving process is forced to be interrupted are solved.
In order to achieve the purpose, the invention adopts the following technical scheme.
A multi-stage dam break intelligent optimization emergency scheduling method comprises the following steps:
step 2, coupling the emergency scheduling submodel with a dam break calculation module and a dam break flood evolution module to describe the dam break situation in the emergency scheduling of the cascade reservoir group so as to enable the dam break emergency scheduling result to be more accurate;
for the problem that reservoir boundary conditions are suddenly changed due to dam break in the cascade reservoir group emergency scheduling process and an algorithm is not easy to solve, a multi-stage dam break intelligent optimization emergency scheduling model is provided, and a cascade reservoir group dam break emergency optimization scheduling scheme is obtained by operating the model; the method comprises the following steps:
(1) Inputting the number of reservoirs participating in dispatching and corresponding constraints on the basis of the basin cascade reservoir group emergency dispatching submodel, and solving a dispatching model through a genetic algorithm;
(2) Judging whether a reservoir breaks in the optimized scheduling result, if so, storing the scheduling result of the upstream of the reservoir i, calling a break flood calculation module to calculate break flood, and calling a break flood evolution module to calculate the warehousing flow of the reservoir i + 1;
(3) Taking all the downstream reservoirs of the reservoir i, the corresponding constraint conditions and the warehousing flow rate of the reservoir i +1 as input conditions, and re-optimizing the downstream reservoir of the reservoir i;
(4) And (4) repeating the steps (1) and (3) until the reservoir-free break or the optimization of the final reservoir single reservoir is completed, and finally obtaining a step reservoir group break emergency optimization scheduling result.
Further, in the step reservoir group emergency dispatching submodel of step 1, firstly, in order to ensure the flood control safety of the reservoir itself, the upstream protection area and the reservoir area and to reduce the water level in the whole dispatching process as much as possible, the highest water level and the lowest water level in the dispatching period of the reservoir are used as main objective functions. Meanwhile, in order to avoid severe fluctuation of the discharge flow in the reservoir operation process as much as possible, the quadratic sum of the discharge flow is added in the scheduling process as a secondary optimization target. Therefore, the objective function form of the cascade reservoir group emergency dispatching is as follows:
in the formula, F obj Is a total objective function; f 1 And F 2 Respectively a water level target and an ex-warehouse flow target; alpha (alpha) ("alpha") 1 And alpha 2 Respectively two sub-target weight coefficients; n is the number of reservoirs; t is a scheduling time interval;
the highest water level of the reservoir i in the dispatching process is set;
the square of the outlet flow of the reservoir i in the j time period;
the emergency scheduling submodel needs to satisfy the following constraint conditions: water balance constraint, upstream and downstream hydraulic power connection constraint, reservoir discharge capacity constraint and reservoir water level constraint.
In the dam break flood simulation module in the step 2, the dam break flood peak flow calculation formula considering the instantaneous dam break is as follows:
b＝k(W 1/2 B 1/2 H 1/2 ) 1/2 (2.1)
in the formula, Q bmax The maximum peak flow is the maximum peak flow when the dam break flood occurs; avg { } is an average value; b is the length of the dam crest; g is gravity acceleration; b is the width of the breach; h 0 The water depth upstream of the dam; h' is the height of the residual dam; h is the ulceration depth; k is the soil property coefficient; w is the water storage capacity of the reservoir area above the break opening when the dam is broken; h is the water depth in front of the dam when the dam is broken.
For a dam break flood river course evolution calculation module, the specific formula is as follows:
in the formula, T all The total flood duration for upstream dam break; K. k g 、K 1 、K 2 Are all coefficients; w is the water storage capacity of the reservoir area above the break opening when the dam is broken; t is the t-th moment after dam break; t is t 1 The rise time for the downstream flood; t is t 2 The downstream peak emergence time; t is t 3 The end time of the downstream flood;
the dam break flood flow at the t-th moment;
the maximum peak flow when the dam break flood reaches a downstream reservoir; v is the water flow velocity in the upstream and downstream regions; l is an interval distance; h is M The river depth corresponding to the downstream maximum flow.
In step 2, aiming at the dam break condition possibly occurring in the scheduling process, a multi-stage dam break intelligent optimization emergency scheduling model is established, the reservoir level in the scheduling process is decided through an objective function, and the scheduling objective function has the following form:
in the formula
Respectively being the objective functions of the first, second and M stages; t is the t time period in the reservoir dispatching process; k is a radical of 1 In the first stage basin, reservoir k 1 Burst occurs and k 1 The upstream reservoirs are not burst; k is a radical of formula 2 Is a second stage reservoir k 1 All downstream of (2), reservoir k 2 A burst occurs, and k 2 The upstream reservoirs are not burst;
is a reservoir k 1 Water level at time period t;
is a reservoir k 1 The elevation of the dam crest;
is a reservoir k 2 Water level at time t;
is a reservoir k 2 The elevation of the dam crest;
and the constraint condition of each stage in the multi-stage dam break intelligent optimization emergency scheduling model is the corresponding constraint of the reservoir participating in scheduling of each stage. The warehousing flow process of the first stage is an actual inflow process, and the warehousing flow process of the subsequent stage is a warehousing flow process obtained by calling the breach calculation module and the flood evolution module.
In the step 2, the cascade reservoir group emergency dispatching model is solved through a genetic algorithm, and the method comprises the following steps:
firstly, selecting the reservoir dam front water level as a decision variable in the emergency dispatching process, and carrying out real number coding on the reservoir dam front water level by adopting a real number mode. The initialization algorithm parameters include a population size N 0 Evolution algebra N 1 Cross probability P c Mutation probability P m And the like. ByAnd determining the upper and lower boundaries of the water level change in each time interval by the initial and final water levels, the reservoir inflow process, the reservoir constraint conditions and the water quantity balance formula, and randomly generating an initial solution in a feasible boundary space. The initial population obtained in this way is all feasible solutions, various constraint conditions are met, and the problem that the randomly generated initial solutions do not meet the constraint conditions is solved.
Secondly, calculating the fitness of each individual in the current population by adopting a penalty function method, wherein the individual is
Is adapted to
Comprises the following steps:
in the formula, F obj Is an objective function in formula (1); i.e. i k Dam break occurs for the reservoir i; t is k Is the T th k Breaking of the dam occurs in a time period; alpha is alpha 3 And alpha 4 Respectively, a dam break penalty factor, if the reservoir always breaks down after optimization, the break is caused to occur in the downstream reservoir as far as possible, and the break is caused to occur at the same time as late as possible, so that alpha is introduced 3 And alpha 4 And punishing the fitness. If all reservoirs do not break the dam, alpha is obtained 3 And alpha 4 Are each 0.
And then, according to the result of fitness calculation, sequencing the individuals according to the fitness, and selecting a new generation of population by adopting an optimal individual storage method.
And finally, crossing and mutating the individuals in the new generation of population. However, the originally feasible solution after crossover and mutation is likely to become an infeasible solution. Therefore, the feasible boundary space of the water level in each time interval is calculated, the individuals in the new population are corrected, all the corrected individuals become feasible solutions, and the evolution efficiency of the algorithm is greatly improved. And repeating the steps until population evolution algebra is completed.
Compared with the prior art, the invention has the following advantages and effects:
(1) In the prior art, the emergency scheduling, the breach calculation and the flood routing are not tightly connected, and the emergency scheduling submodel is coupled with the breach calculation module and the breach flood routing module, so that the breach situation possibly occurring in the emergency scheduling process of the cascade reservoir group can be more accurately described.
(2) In the existing emergency scheduling process, once a dam is broken, reservoir boundary conditions are mutated, so that the algorithm solving is interrupted, and the global optimal scheduling of the watershed cascade reservoir group cannot be realized. The invention provides a multi-stage dam break intelligent optimization emergency scheduling model, which divides an emergency scheduling process with a possibility of dam break into a plurality of stages, and changes a target function, a constraint condition and an input condition for each stage to finally obtain a global optimal solution for the emergency scheduling of the dam break of a cascade reservoir group.
Drawings
Fig. 1 is a flowchart of a multi-stage dam break intelligent optimization emergency scheduling model according to an embodiment of the present invention;
fig. 2 is a water level emergency dispatching process of the step reservoir according to the embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention is further described in 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 do not 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.
Fig. 1 is a flowchart of a multi-stage dam break intelligent optimization emergency scheduling model provided in an embodiment of the present invention, which specifically includes the following steps:
in order to ensure flood control safety of the reservoir, an upstream protection area and a reservoir area and reduce the water level in the whole dispatching process as much as possible, the highest water level and the lowest water level in the dispatching period of the reservoir are used as main objective functions. Meanwhile, in order to avoid severe fluctuation of the discharge flow in the reservoir operation process as much as possible, the quadratic sum of the discharge flow is added in the scheduling process as a secondary optimization target. And in consideration of the problem of different dimensions among the targets, a normalization method is adopted to standardize the model target space so as to avoid the influence of different dimensions on the solution. Therefore, the objective function form of the cascade reservoir group emergency dispatching is as follows:
in the formula, F obj Is a total objective function; f 1 And F 2 Respectively a water level target and a delivery flow target; f 1 'and F' 2 Respectively is a water level target and an ex-warehouse flow target after normalization; alpha is alpha 1 And alpha 2 Respectively taking 10 and 5 as two sub-target weight coefficients; f k,min Is the minimum value of target k; f k,max Is the maximum value of target k; n is the number of reservoirs; t is a scheduling time interval;
the highest water level of the reservoir i in the dispatching process;
the square of the outlet flow of the reservoir i in the j time period is obtained;
the emergency scheduling submodel needs to satisfy the following constraint conditions:
and (3) water balance constraint:
in the formula (I), the compound is shown in the specification,
the storage capacity of the ith reservoir at the end of the jth dispatching time period;
the initial storage capacity of the ith reservoir in the jth scheduling period;
the storage flow of the ith reservoir in the jth scheduling time interval;
the flow of the ith reservoir out of the reservoir in the jth scheduling period; Δ t is the scheduling period.
Upstream and downstream hydraulic connection constraints:
in the formula (I), the compound is shown in the specification,
the flow rate of the upstream reservoir k reaching the reservoir i is the time interval j;
the water flow of the reservoir i in the upstream interval of the time period j; u shape i All reservoirs immediately upstream of reservoir i.
Reservoir discharge capacity constraint:
in the formula (I), the compound is shown in the specification,
and
let-down flow for reservoir i in time period jA lower limit and an upper limit;
the discharge quantity of the reservoir i in the time period j.
Reservoir water level constraint:
in the formula (I), the compound is shown in the specification,
and
the lower limit and the upper limit of the water level of the reservoir i in the time period j are set;
the water level of reservoir i at time period j.
In the formula (I), the compound is shown in the specification,
and
the water levels of the reservoir i at the initial and final periods of the dispatching process are obtained;
and
and (5) assigning initial and final water levels of the dispatching process for the reservoir i.
Step 2, coupling the emergency scheduling sub-model with a dam break calculation module and a dam break flood evolution module to describe a dam break situation in emergency scheduling of the cascade reservoir group;
the dam break flood peak flow calculation formula considering the dam instantaneous collapse is as follows:
b＝k(W 1/2 B 1/2 H 1/2 ) 1/2 (2.1)
in the formula, Q bmax The maximum peak flow when the dam break flood occurs; avg { } is an average value; b is the length of the dam crest; g is the acceleration of gravity; b is the width of the breach; h 0 The water depth upstream of the dam; h' is the height of the residual dam; h is the ulceration depth; k is the soil property coefficient; w is the water storage capacity of the reservoir area above the break opening when the dam is broken; h is the water depth before the dam is broken.
For a dam break flood river course evolution calculation module, the specific formula is as follows:
in the formula, T all The total flood duration for upstream dam break; K. k is g 、K 1 、K 2 Are all coefficients; w is the water storage capacity of the reservoir area above the break opening when the dam is broken; t is dam breakThe later t-th time; t is t 1 Rise time for downstream flood; t is t 2 The downstream peak emergence time; t is t 3 The end time of the downstream flood;
the dam break flood flow at the t-th moment;
the maximum peak flow of the dam-break flood reaching a downstream reservoir; v is the flow velocity of water flow in the upstream and downstream regions; l is an interval distance; h is a total of M The river depth corresponding to the downstream maximum flow.
And for the condition that reservoir boundary conditions are suddenly changed due to dam break in the emergency dispatching process of the cascade reservoir group and the algorithm is not easy to solve, a multi-stage dam break intelligent optimization emergency dispatching model is provided, and the model is operated to obtain a cascade reservoir group dam break emergency optimization dispatching scheme.
The modeling idea of the multi-stage dam break intelligent optimization emergency scheduling model is as follows:
(1) And inputting the number of reservoirs participating in scheduling and corresponding constraint conditions on the basis of the basin cascade reservoir group emergency scheduling submodel, and solving the scheduling model through a genetic algorithm.
(2) And judging whether a reservoir breaks in the optimized scheduling result, if so, storing the scheduling result of the upstream of the reservoir i, calling a break flood calculation module to calculate break flood, and calling a break flood evolution module to calculate the warehousing flow of the reservoir i + 1.
(3) And re-optimizing the downstream reservoir of the reservoir i by taking all the downstream reservoirs of the reservoir i, the corresponding constraint conditions and the warehousing flow rate of the reservoir i +1 as input conditions.
(4) And repeating the steps until no reservoir burst or the optimization of the final reservoir single bank is completed. And finally obtaining a step reservoir group dam break emergency optimized scheduling result.
In the established multi-stage dam break intelligent optimization emergency scheduling model, the reservoir level in the scheduling process is decided through an objective function, and the scheduling objective function has the following form:
in the formula
Respectively being the objective functions of the first, second and M stages; t is the t time period in the reservoir dispatching process; k is a radical of 1 In all reservoirs in the first stage basin, reservoir k 1 A burst occurs, and k 1 The upstream reservoirs are not burst; k is a radical of formula 2 Is a second stage reservoir k 1 All downstream of, reservoir k 2 A burst occurs, and k 2 The upstream reservoirs are not burst;
is a reservoir k 1 Water level at time t;
is a reservoir k 1 The elevation of the dam crest;
is a reservoir k 2 Water level at time t;
is a reservoir k 2 The elevation of the dam crest;
the constraint conditions of each stage in the multi-stage dam break intelligent optimization emergency scheduling model are the corresponding constraints of the reservoir participating in scheduling of each stage. For the model input conditions, the warehousing flow process in the first stage is an actual inflow process, and the warehousing flow process in the subsequent stage is a warehousing flow process obtained by calling the breach calculation module and the flood evolution module.
The emergency dispatching model of the cascade reservoir group is solved through a genetic algorithm and is divided into the following steps. If the water level reaches the dam crest elevation at a certain moment, the scheduling process is continuously solved according to overtopping treatment:
(1) And initializing algorithm parameters. Including population size N 0 Evolution algebra N 1 Cross probability P c Probability of mutation P m And the like.
(2) Initializing population individuals
Selecting the reservoir dam front water level as a decision variable of an emergency scheduling process, and performing real number coding on the reservoir dam front water level by adopting a real number mode, wherein the real number mode comprises the steps of
Wherein, the individual X i The system consists of T time interval initial and final water levels of N reservoirs in a drainage basin. And determining the upper and lower boundaries of the water level change at the end of each time period according to the initial and final water levels, the reservoir inflow process, the reservoir constraint conditions and the water balance formula, and randomly generating an initial solution in a feasible boundary space. The initial population obtained in this way is all feasible solutions, various constraint conditions are met, and the problem that the randomly generated initial solutions do not meet the constraint conditions is solved.
(3) And calculating the individual fitness. Calculating the fitness of each individual in the current population by adopting a penalty function method, wherein the individual is
Is adapted to
Comprises the following steps:
in the formula, F obj Is an objective function in formula (1); i.e. i k Dam break occurs for the reservoir i; t is k Is the T th k Breaking of the dam occurs in a time period; alpha is alpha 3 And alpha 4 Respectively, are dam break penalty factors. If the reservoir is always burst after optimization, the burst should be caused to occur as far as possible in the downstream reservoir, and the time when the burst occurs should be as late as possible, for which reason alpha is taken 3 And alpha 4 An individual who has developed a dam break is punished at 10000 and 100, respectively. If all reservoirs are in the reservoirWhen no dam break occurs, then alpha 3 And alpha 4 Are each 0.
(4) Selection, crossover, mutation. Firstly, according to the result of fitness calculation, the individuals are sorted according to the fitness size, and a new generation of population is selected by adopting an optimal individual storage method. Then, the individuals in the new generation population are crossed and mutated. However, the original feasible solution after crossover and mutation is likely to become an infeasible solution. Therefore, the feasible boundary space of the water level in each time interval is recalculated, the individuals in the new population are corrected, all the corrected individuals become feasible solutions, and the evolution efficiency of the algorithm is greatly improved.
(5) And (4) judging whether a termination condition is reached, outputting an optimal individual if the termination condition is reached, and returning to the step (3) to continue executing the algorithm operation until population evolution is completed.
In order to verify the effectiveness of the invention, a spring river basin is taken as an example, a terraced reservoir (first redrock, great gorges and white sand rivers) in the basin is taken as a research object, and super-huge flood is selected as a reservoir inflow process. Scheduling by respectively adopting a conventional scheduling method and a multi-stage dam break emergency scheduling intelligent optimization modeling research method, and comparing scheduling results of the conventional scheduling method and the multi-stage dam break emergency scheduling intelligent optimization modeling research method, wherein the related parameters of the genetic algorithm in the emergency scheduling are set as N 0 ＝300、N 1 ＝500、P c ＝0.9、P m =0.05. The water level results for each reservoir are shown in fig. 2;
it can be seen that the optimized scheduling process obtained by using the multi-stage dam break intelligent optimized emergency scheduling model has significant advantages compared with conventional scheduling. Under the condition of extra flood, after conventional scheduling, the cascade reservoirs are burst, and after optimized scheduling, the white sand river reservoir can be kept not to burst; from the aspect of dam break time, under the conventional scheduling and optimized scheduling method, the first red rock breaks in the 22 th time period, and the strait reservoir breaks in the 23 rd time period, but the dam break time of the first red rock and the dam break time of the strait reservoir are 891s later and 886s later than the conventional scheduling respectively after optimized scheduling. It can be seen that the optimized scheduling result is better than the conventional scheduling, thereby proving the effectiveness of the method.
It will be understood by those skilled in the art that the foregoing is only an exemplary embodiment of the present invention, and is not intended to limit the invention to the particular forms disclosed, since various modifications, substitutions and improvements within the spirit and scope of the invention are possible and within the scope of the appended claims.
Claims (6)
1. A multi-stage dam break intelligent optimization emergency scheduling method is characterized by comprising the following steps:
step 1, acquiring parameters and characteristic curves of reservoirs in a drainage basin, determining constraint conditions of an emergency dispatching process, and establishing a drainage basin cascade reservoir group emergency dispatching submodel by taking the lowest highest water level in front of a reservoir group main dam and the smallest sum of squares of ex-warehouse flow as dispatching targets;
step 2, seamlessly coupling the emergency scheduling submodel with a break flood calculation module and a dam break flood evolution module to describe a dam break situation in emergency scheduling of the cascade reservoir group;
for the problem that reservoir boundary conditions are suddenly changed due to dam break in the cascade reservoir group emergency scheduling process and an algorithm is not easy to solve, a multi-stage dam break intelligent optimization emergency scheduling model is provided, and a cascade reservoir group dam break emergency optimization scheduling scheme is obtained by operating the model; the method comprises the following steps:
(1) Inputting the number of reservoirs participating in dispatching and corresponding constraints on the basis of the basin cascade reservoir group emergency dispatching submodel, and solving a dispatching model through a genetic algorithm;
(2) Judging whether a reservoir breaks in the optimized scheduling results, if so, storing the scheduling results at the upstream of the reservoir i, calling a break flood calculation module to calculate break flood, and calling a break flood evolution module to calculate the warehousing flow of the reservoir i + 1;
(3) Taking all the downstream reservoirs of the reservoir i, the corresponding constraint conditions and the warehousing flow rate of the reservoir i +1 as input conditions, and re-optimizing the downstream reservoir of the reservoir i;
(4) Repeating the steps (1) and (3) until no reservoir burst or the optimization of the final reservoir single bank is completed; and finally obtaining a step reservoir group dam break emergency optimized scheduling result.
2. The multi-stage dam break intelligent optimization emergency scheduling method of claim 1, wherein in the cascade reservoir group emergency scheduling submodel, a reservoir level in a scheduling process is decided through an objective function, and the scheduling objective function has a form as follows:
in the formula, F obj Is a total objective function; f 1 And F 2 Respectively a water level target and an ex-warehouse flow target; alpha is alpha 1 And alpha 2 Respectively two sub-target weight coefficients; n is the number of reservoirs; t is a scheduling time interval;
the highest water level of the reservoir i in the dispatching process;
the square of the delivery flow of the reservoir i in the j-th time period.
3. The multi-stage dam break intelligent optimization emergency dispatching method of claim 1, wherein in the cascade reservoir group emergency dispatching submodel, the following constraint conditions need to be satisfied:
water quantity balance constraint, upstream and downstream hydraulic power connection constraint, reservoir discharge capacity constraint and reservoir water level constraint.
4. The multi-stage dam break intelligent optimization emergency scheduling method of claim 1, wherein in the dam break calculation module and the dam break flood evolution module, a dam break flood process calculation formula and a river course evolution formula are as follows:
considering the instant collapse situation of the dam, the calculation formula of the dam collapse flood peak flow is as follows:
in the formula, Q bmax The peak flow is the peak flow when dam break flood occurs; avg { } is an average value;
calculating the results of an empirical formula for the flood peak flows of three different dam breakages;
the calculation formula of the flow process when the dam-break flood reaches the downstream reservoir is as follows:
wherein K is a coefficient; w is the water storage capacity of the reservoir area above the break opening when the dam is broken; t is t 1 The rise time for the downstream flood; t is t 2 The downstream peak emergence time; t is t 3 The end time of the downstream flood;
the maximum peak flow when the dam break flood reaches a downstream reservoir; v is the flow velocity of water flow in the upstream and downstream regions; l is an interval distance; h is a total of M The river depth corresponding to the downstream maximum flow.
5. The multi-stage dam break intelligent optimization emergency dispatching method of claim 1, wherein the multi-stage dam break intelligent optimization emergency dispatching model is characterized in that the reservoir level of the dispatching process is decided by an objective function, and the dispatching objective function is in the form of:
in the formula
Respectively being the objective functions of the first, second and M stages; t is the t time period in the reservoir dispatching process; k is a radical of 1 In the first stage basin, reservoir k 1 Burst occurs and k 1 The upstream reservoirs are not burst; k is a radical of formula 2 As a second stage reservoir k 1 All downstream of (2), reservoir k 2 Burst occurs and k 2 The upstream reservoirs are not burst;
is a reservoir k 1 Water level at time period t;
is a reservoir k 1 The elevation of the dam crest;
is a reservoir k 2 Water level at time t;
is a reservoir k 2 The elevation of the dam crest.
6. The method of claim 5, wherein fitness of each individual in the current population is calculated by adopting a penalty function method in the step reservoir group emergency scheduling model solved by the GA genetic algorithm, and the individual is
Is adapted to
Comprises the following steps:
in the formula, F obj Is an objective function in formula (1); alpha (alpha) ("alpha") 3 And alpha 4 Respectively, a dam break penalty factor, if the reservoir always breaks down after optimization, the break is caused to occur in the downstream reservoir as far as possible, and the break is caused to occur at the same time as late as possible, so that alpha is introduced 3 And alpha 4 Punishment is carried out on individuals when the water level reaches the elevation of the dam crest. If all reservoirs do not break the dam, alpha is obtained 3 And alpha 4 Are each 0.
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| CN112749475A (en) * | 2020-11-10 | 2021-05-04 | 中国电力建设股份有限公司 | Analysis method for determining continuous dam break risk of cascade reservoir group |
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