CN103088784A - Cascade reservoir flood control water level real-time dynamic control method - Google Patents

Cascade reservoir flood control water level real-time dynamic control method Download PDF

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CN103088784A
CN103088784A CN2013100222229A CN201310022222A CN103088784A CN 103088784 A CN103088784 A CN 103088784A CN 2013100222229 A CN2013100222229 A CN 2013100222229A CN 201310022222 A CN201310022222 A CN 201310022222A CN 103088784 A CN103088784 A CN 103088784A
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reservoir
polymerization
flood
long
period
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CN103088784B (en
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郭生练
周研来
刘攀
陈华
汪芸
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Wuhan University WHU
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Abstract

The invention discloses a cascade reservoir flood control water level real-time dynamic control method. The cascade reservoir flood control water level real-time dynamic control method comprises the following steps: (1) building a numerical meteorological hydrological forecast model of the flood season of a river basin, forecasting the flood process of the river basin of the future 1- 7 days in a rolling mode, (2) building a 'large scale system polymerization idea'-based random long-term optimization scheduling graph model, using a self-adaptive genetic algorithm to make a long-term optimization scheduling graph, (3) building a 'large scale system polymerization decomposition idea'-based cascade reservoir flood control water level real-time dynamic control model according to the coupling principle of long-term and short-term scheduling, and using a sequential optimization method to optimize and obtain a cascade reservoir flood control level real-time dynamic control scheme. The cascade reservoir flood control water level real-time dynamic control method can conduct unified schedule to all reservoirs in the upstream and the downstream of a cascade reservoir group, improve the power benefit of the cascade reservoir to the maximum under the premise that flood control safety of the cascade reservoir is guaranteed, is suitable for cascade reservoirs or reservoir groups flood resource scheduling, and can be widely applied to river basin cascade reservoir flood control water level real-time dynamic control.

Description

A kind of step reservoir flood real-time dynamic control method of restricting water supply
Technical field
The invention belongs to step reservoir scheduling field, particularly a kind of step reservoir flood real-time dynamic control method of restricting water supply.
Background technology
Enter 21 century, building up and coming into operation along with the large quantities of hydro plant with reservoirs of China, the Chinese Water Conservancy hydroelectric project entered into by the crucial transitional period of building to management operating, carrying out the hydropower station group combined dispatching is the major action of complying with " energy-saving power generation " and " based on utilization of flood resources " Times ' Demand, has important theory value and realistic meaning.Dynamic control of limitation level in flood season is one of important non-engineering measure that realizes " based on utilization of flood resources ".Along with the significantly lifting of the medium-term and long-term numerical value weather forecast of increase and the basin technology of reservoir quantity (dimension) in water reservoir system, need the information considered more and more, the restrict water supply dynamic control of position of flood also will become more complicated.
At present both at home and abroad few to the restrict water supply method of position research of step reservoir flood, existing research method majority is the flood of single reservoir to be restricted water supply a research method is nested simply advances step reservoir, does not consider the restrict water supply mutual coordination problem of position of flood between storage capacity compensation problem between the upstream and downstream reservoir and reservoir.The Guo Sheng of Wuhan University practices the teach problem group the restrict water supply dynamic control problem of position of step reservoir flood has been carried out systematic research, has successively proposed based on the multi-reservoir flood control compensation combined dispatching of forecast and storage capacity compensation progressive Coordination Model successively [1], based on the step reservoir dynamic control of limitation level in flood season of forecast and storage capacity compensation progressive compensation scheduling model successively [2]With a co-design and the utilization scheduling model of restricting water supply based on the step reservoir flood of " polymerization reservoir " [3,4]Consider that actual reservoir operation is the rolling process forward of " forecast, decision-making, enforcement, forecast again, decision-making again, implement again " [5], existing step reservoir dynamic control of limitation level in flood season model is only paid attention to current regimen situation of change as can be known, does not take the long term variations of warehouse-in runoff into account.
The list of references that relates in literary composition is as follows:
[1] Li Wei, Guo Shenglian, Guo Fuqiang, etc. Hydropower Plant Reservoir group controls flood and compensates combined dispatching scale-model investigation and application [J]. Journal of Hydraulic Engineering, 2007,38 (7): 826-831.
[2] Li Wei, Guo Shenglian, Liu Pan, etc. the scale-model investigation of step reservoir dynamic control of limitation level in flood season and utilization [J]. hydroelectric generation journal, 2008,27 (2): 22-28.
[3] Guo Shenglian, Chen Jionghong, Liu Pan. a kind of step reservoir flood limit water level combined application dispatching method: China, CN201110067570.9[P] .2011-9-14.
[4] Guo Shenglian, Chen Jionghong, Li Fei is etc. Qingjian River step reservoir flood restrict water supply a co-design and utilization [J]. hydroelectric generation journal, 2012,31 (4): 6-11.
[5] Qiu Lin, Chen Shouyu. Hydropower Plant Reservoir Real time optimal dispatch model and application thereof [J]. Journal of Hydraulic Engineering, 1997,57 (3): 74-77
Summary of the invention
For the deficiencies in the prior art, the present invention is based on the meteorological hydrological forecast of basin numerical value, a kind of compensation of the storage capacity between the upstream and downstream reservoir, step reservoir flood long-term and that short term scheduling is coupled real-time dynamic control method of restricting water supply of considering has been proposed.
For solving the problems of the technologies described above, the present invention adopts following technical scheme:
A kind of step reservoir flood real-time dynamic control method of restricting water supply comprises the following steps:
Step 1 is set up the step reservoir basin meteorological hydrologic forecast model of numerical value in flood season, and the forecast basin peb process in 1~7 day future that rolls; The meteorological hydrologic forecast model of described numerical value is comprised of numerical value Meteorological Forecast Model and hydrologic forecast model;
Step 2, build the randomness Long-term Optimal Dispatch graph model of step reservoir based on " large system polymerization thought ", and adopt self-adapted genetic algorithm to obtain the Long-term Optimal Dispatch figure of step reservoir, obtain the Long-term Optimal Dispatch strategy of polymerization reservoir based on Long-term Optimal Dispatch figure; Described Long-term Optimal Dispatch graph model is based on the randomness Optimized model that " large system polymerization thought " builds;
Step 3, according to the Long-term Optimal Dispatch of polymerization reservoir and principles in coupling and the meteorological hydrologic forecast model of numerical value of short term scheduling, structure is based on the step reservoir flood of " large system polymerization Idea of Classification " Real-time dynamic control model of restricting water supply, and obtains a step reservoir flood real-time dynamic control case of restricting water supply according to a step reservoir flood Real-time dynamic control model of restricting water supply.
The meteorological hydrologic forecast model of numerical value in step 1 is based on the numerical value weather forecast and distributedly oozes the ability hydrological model under variable and set up, and valid time can reach 1~7 day, and the numerical value weather forecast is used for the Meteorological Characteristics such as forecast rainfall, temperature.
The randomness Long-term Optimal Dispatch graph model based on " large system polymerization thought " structure step reservoir in step 2 further comprises substep:
2-1a obtains virtual polymerization reservoir based on " large system polymerization thought " polymerization step reservoir;
2-2a with the period at the beginning of accumulation of energy and be carved into when facing and can represent polymerization reservoir running status, take period Mo accumulation of energy as decision variable, build relate to polymerization reservoir adjacent time interval enter can correlation randomness Long-term Optimal Dispatch model, and definite constraints.
The Long-term Optimal Dispatch figure that employing self-adapted genetic algorithm in step 2 obtains step reservoir further comprises substep:
2-1b adopts genetic algorithm to generate at random the initial schedule line of polymerization reservoir;
2-2b initial schedule line produces new scheduling line through individual variation, intersection and selection, calculates the fitness of polymerization reservoir initial schedule line and new scheduling line; Described fitness is the target function value of randomness Long-term Optimal Dispatch graph model, and described object function is the annual average power generation of step reservoir.
Whether 2-3b restrains based on the new scheduling of the fitness judgement line of scheduling line, if convergence, described new scheduling line is the Long-term Optimal Dispatch figure of polymerization reservoir, otherwise repeating step 2-2b.
In step 2, the Long-term Optimal Dispatch strategy of gained polymerization reservoir is:
s *(t+1)=Opt(u(t),s(t),t)
In formula,
s *(t+1) for the Long-term Optimal Dispatch strategy of polymerization reservoir t+1 period;
(u (t), s (t) t) dispatches t period optimal policy for the polymerization reservoir to Opt for a long time.
Long-term Optimal Dispatch in step 3 and the principles in coupling of Short-term Optimal Operation are expressed as:
s ( T + 1 ) = τ t T y Opt ( u ( t ) , s ( t ) , t ) + T y - τ t T y Opt ( u ( t + 1 ) , s ( t + 1 ) , t + 1 )
Wherein,
T is last period of short term scheduling;
S (T+1) is the period Mo accumulation of energy of " polymerization reservoir ";
T yBe valid time, its value is 1~7 day;
τ tFor at leading time T yIn belong to time span in the Long-term Optimal Dispatch t period.
S (t), s (t+1) are polymerization reservoir t, accumulation of energy at the beginning of the t+1 period;
Opt (u (t), s (t), t), (u (t+1), s (t+1) t+1) are respectively the polymerization reservoir and dispatch for a long time t, t+1 period optimal policy Opt;
U (t), u (t+1) enter polymerization reservoir t, t+1 period energy, u ( t + 1 ) = 1 T y - τ t Σ j = 1 L I j y ( t ) Σ i = 1 L ( c j , i K i H 2 i ( t ) ) Δt , Be j reservoir and the interval prediction process that becomes a mandarin, L is the number of reservoir in step reservoir, c J, iBe waterpower incidence matrix value, K iBe the power factor of i reservoir, H 2i(t) be the average productive head of i reservoir t period, Δ t is that calculation interval is long, and i, j are the numbering of each reservoir in step reservoir.
Compared with prior art, the present invention has the following advantages and effect:
1, the present invention can carry out United Dispatching to each reservoir of step reservoir upstream and downstream, under the prerequisite that guarantees the step reservoir flood control safety, with long-term generation schedule and short-term Real-Time Scheduling efficient coupling, can improve to greatest extent the emerging sharp benefit of step reservoir, suitablely use in the scheduling of step reservoir or multi-reservoir based on utilization of flood resources, can be widely used in the cascaded reservoirs flood position of restricting water supply and dynamically control in real time;
2, prior art all turns to optimization aim with the multi annual average benefit maximum, and the present invention emphasizes cascaded reservoirs to be put in storage the valid time T of runoff based on the basin meteorological hydrological forecast of numerical value in flood season yExtend to 7 days, the flood of seeking the benefit value maximum of step reservoir within 7 a days valid times real-time dynamic control case of restricting water supply has more practicality in practice.
Description of drawings
Fig. 1 is the step reservoir flood of the present invention in real time dynamically control flow chart of position of restricting water supply;
Fig. 2 is the polymerization Long-term Optimal Regulation for Reservoir figure in this concrete enforcement.
The specific embodiment
The present invention is based on the meteorological hydrological forecast of numerical value, principles in coupling according to long-term and short term scheduling, set up a step reservoir flood Real-time dynamic control model of restricting water supply, and based on a step reservoir flood Real-time dynamic control model of restricting water supply, each reservoir of step reservoir upstream and downstream is carried out United Dispatching, under the prerequisite that guarantees the step reservoir flood control safety, the step reservoir flood of seeking a comprehensive utilization benefit maximum real-time dynamic control case of restricting water supply, its idiographic flow sees Fig. 1 for details.
Below by embodiment, and by reference to the accompanying drawings, the present invention will be further described.
A kind of step reservoir flood real-time dynamic control method of restricting water supply comprises the following steps:
Step 1, set up the step reservoir basin meteorological hydrologic forecast model of numerical value in flood season based on numerical value weather forecast and hydrological model, the meteorological hydrologic forecast model of numerical value can roll and forecast the peb process that the basin leading time is interior, and the valid time of the meteorological hydrologic forecast model of numerical value can reach 1~7.
At present, generally take " throughfall " as the forecast basis, leading time is limited in the flood forecasting prediction; And the numerical value Meteorological Models can obtain the weather informations such as following contingent rainfall in advance, by coupling weather forecast result and hydrological distribution model, can extend the leading time of flood forecasting, for flood decision tries to gain time precious to one, provide scientific basis for correctly making the Flood Control Dispatch decision-making, can reduce or remit flood loss, increase generating retaining etc., obtain huge economic benefit and social benefit.
Reliable numerical value weather forecast precision is for the coupling that realizes weather forecast and hydrological forecast, effectively extend the flood forecasting leading time scientific basis is provided.The present embodiment has been set up Japan, Germany and artificial multiple numerical value Meteorological Models and has been oozed the coupling mechanism of ability (VIC) hydrological model with distributed under variable, thereby obtains the step reservoir basin numerical value meteorology hydrologic forecast model in flood season.Utilize the various weather forecasts output of numerical value Meteorological Models, as, the time segment length be rainfall, the temperature process of 1h, drive distributed VIC hydrological model, continuous analog and the real-time prediction of realization to step reservoir river basin flood process.
In the situation that leading time is 7 days, the tradition flood forecasting has almost been lost the prediction ability to flood peak, but the meteorological hydrologic forecast model of numerical value still can forecast the Flood Information that the basin may occur future, therefore, the meteorological hydrologic forecast model of numerical value just can be predicted flood generation event before 7 days, can realize the meteorological real-time hydrological forecasting in basin, thereby effectively extend the leading time of flood forecasting, play positive effect for carrying out the work such as Analysis on flood control situation, reservoir operation.
Step 2, build the randomness Long-term Optimal Dispatch graph model of step reservoir based on " large system polymerization thought ", and adopt self-adapted genetic algorithm to obtain the Long-term Optimal Dispatch figure of step reservoir, based on Long-term Optimal Dispatch figure, the polymerization reservoir is carried out operation simulation and obtain the Long-term Optimal Dispatch strategy.
This step is further comprising the steps:
1) build the randomness Long-term Optimal Dispatch graph model of step reservoir
At first this step obtains virtual polymerization reservoir based on " large system polymerization thought " polymerization step reservoir, and inquires into the Optimized Operation figure of polymerization reservoir, thereby provides long-term schedule information for the Real-Time Scheduling of step reservoir.
Polymerization reservoir running status by the period at the beginning of accumulation of energy and be carved into the vector representation that can form when facing, take period Mo accumulation of energy as decision variable, foundation considers that polymerization reservoir adjacent time interval enters the randomness Long-term Optimal Dispatch model of energy correlation (take 5~October of flood season as schedule periods, week is scheduling slot t) the contrary recurrence equation, as follows:
F t ( u ( t ) , s ( t ) ) = max { R t ( u ( t ) , s ( t ) , s ( t + 1 ) ) + Σ k = 1 M p k ( t + 1 ) F t + 1 * ( u ( t + 1 ) , s ( t + 1 ) ) } F t * ( s ( t ) ) = Σ k = 1 M p k ( t ) F t * ( u ( t ) , s ( t ) ) - - - ( 1 )
In formula,
At the beginning of s (t), s (t+1) are respectively the polymerization reservoir t period, last accumulation of energy;
U (t), u (t+1) enter polymerization reservoir t, t+1 period energy;
R t(u (t), s (t), s (t+1)) is polymerization reservoir t stage period benefit;
M is the dispersed number that enters energy the t period;
K is the discrete sequence number that enters energy the period;
p k(t), p k(t+1) being respectively that polymerization reservoir t, the k equal portions of t+1 period enter can transition probability, wherein, and p k(t)=P (u (t) u (t-1)), p k(t+1)=P (u (t+1)/u (t)), P (x) is probability-distribution function, u (t-1) enters energy for the polymerization reservoir t-1 period;
Be respectively polymerization reservoir t, t+1 period to the optimum remaining benefits of dispatching the end of term;
F t(u (t), s (t)) is that the t period is to the remaining benefits of dispatching the end of term;
For the t period enters optimum remaining benefits in energy to the M that dispatches the end of term is discrete.
The below will describe the polymerization process of step reservoir in detail:
In step reservoir, because the water of upper pond can be able to be reused by lower storage basin, when calculating each reservoir and contain electric weight, should multiply by the conversion coefficient sum of the whole step reservoirs of this reservoir and downstream thereof so, can be by accumulation of energy s (t) at the beginning of formula (2) the calculating polymerization reservoir t period:
s ( t ) = Σ j = 1 L ( V j ( t ) - V j ( 0 ) ) Σ i = 1 L ( c j , i K i H 1 i ( t ) ) - - - ( 2 )
In formula,
V j(t) be water retention capacity at the beginning of j reservoir t period;
V j(0) be j reservoir minimum capacity of a reservoir;
L is the number of reservoir in step reservoir;
I, j are reservoir numbering in step reservoir;
H 1i(t) be i the reservoir average water head that the retaining state has at the beginning of the t period, Wherein, φ iBe the water level storage-capacity curve of i reservoir, H 1i(0) be the downstream head of i reservoir; V i(t), V i(0) be respectively water retention capacity and minimum capacity of a reservoir at the beginning of i reservoir t period;
K iIt is the power factor of i reservoir;
c J, iBe the concrete value of waterpower incidence matrix, its value rule is seen formula (3)~(5):
c j,i=λ(X j,i,Y j,i)i,j∈[1,L](3)
X j , i = 1 0 , Y j , i = 1 0 - - - ( 4 )
In formula (3)~(5),
As reservoir j during in reservoir i downstream, X j,iValue is 0, otherwise is 1;
As reservoir i, when j has hydraulic connection, Y j,iValue is 1, otherwise is 0;
Work as X J, i=Y j,i=1 o'clock, c J, iBe 1, otherwise, c J, iBe 0.
Can calculate equally that the polymerization reservoir t period enters can u (t):
u ( t ) = Σ j = 1 L I j ( t ) Σ i = 1 L ( c j , i K i H 2 i ( t ) ) Δt - - - ( 6 )
In formula,
L is the number of reservoir in step reservoir;
I, j are reservoir numbering in step reservoir;
K iIt is the power factor of i reservoir;
c J, iBe the concrete value of waterpower incidence matrix, its value rule is seen formula (3)~(5);
I j(t) be the average reservoir inflow of j reservoir t period, I j(t)=Q j-1(t)+QJ j(t), Q j-1(t) be the generating flow of j-1 reservoir t period, QJ j(t) be local inflow between j-1 reservoir and j reservoir, j-1 reservoir and j reservoir are adjacent reservoir;
H 2i(t) be the average productive head of i reservoir t period, φ iBe the water level storage-capacity curve of i reservoir, V i(t), V i(t+1) be respectively i reservoir t, water retention capacity at the beginning of the t+1 period, Be i reservoir level of tail water flow curve, Q i(t) be the generating flow of i reservoir t period, H 2i(0) be the head loss of i reservoir;
Δ t is that calculation interval is long.
It is as follows that the polymerization reservoir goes out energy r (t) in the t period:
r ( t ) = Σ j = 1 L Q j ( t ) Σ i = 1 L ( c j , i K i H 2 i ( t ) ) Δt - - - ( 7 )
In formula,
Q j(t) be the generating flow of j reservoir t period;
L is the number of reservoir in step reservoir;
I, j are reservoir numbering in step reservoir;
H 2i(t) be the average productive head of i reservoir t period, φ iBe the water level storage-capacity curve of i reservoir, V i(t), V i(t+1) be respectively i reservoir t, water retention capacity at the beginning of the t+1 period, Be i reservoir level of tail water flow curve, Q i(t) be the generating flow of i reservoir t period, H 2i(0) be the head loss of i reservoir;
c J, iBe the concrete value of waterpower incidence matrix, its value rule is seen formula (3)~(5);
K iIt is the power factor of i reservoir;
Δ t is that calculation interval is long.
It is as follows that polymerization reservoir period t abandons energy w (t):
w ( t ) = Σ j = 1 L W j ( t ) Σ i = 1 L ( c j , i K i H 2 i ( t ) ) Δt - - - ( 8 )
In formula,
W j(t) be the discharge of abandoning of j reservoir period t;
H 2i(t) be the average productive head of i reservoir t period, Wherein, φ iBe the water level storage-capacity curve of i reservoir, V i(t), V i(t+1) be respectively i reservoir t, water retention capacity at the beginning of the t+1 period, Be i reservoir level of tail water flow curve, Q i(t) be the generating flow of i reservoir t period, H 2i(0) be the head loss of i reservoir;
c J, iBe the concrete value of waterpower incidence matrix, its value rule is seen formula (3)~(5);
K iIt is the power factor of i reservoir;
L is the number of reservoir in step reservoir;
I, j are reservoir numbering in step reservoir;
Δ t is that calculation interval is long.
Step reservoir converts virtual polymerization reservoir to and depends on to a great extent net water head, and the variation of net water head is usually very large, therefore need the actual power flow function of structure polymerization reservoir in the t period.If the scheduling rule of polymerization reservoir is piecewise linear function figure, as shown in Figure 2, in this figure, abscissa represents polymerization reservoir t period utilizable energy power s (t)+u (t), and ordinate represents the actual power generation d (t) of polymerization reservoir t period, for dropping on a B (x B, y B) and C (x C, y C) between point, can adopt formula (9) to calculate the actual power generation of polymerization reservoir t period:
d ( t ) = y B + y C - y B x C - x B ( ( s ( t ) + u ( t ) ) - x B ) - - - ( 9 )
In formula,
D (t) is the actual power generation of polymerization reservoir t period, d (t)=D (t) Δ t, and D (t) exerted oneself for the step reservoir t period, and Δ t is that calculation interval is long;
S (t)+u (t) can be regarded as t period available energy for accumulation of energy at the beginning of the polymerization reservoir t period and t period enter the energy sum.
So far, step reservoir has been polymerized to 1 virtual polymerization reservoir, polymerization reservoir key element comprises s (t), s (t+1), u (t), r (t), w (t) and d (t)).
Determine the constraints of the randomness Long-term Optimal Dispatch model of polymerization reservoir, as follows:
(1) polymerization reservoir energy balance constraint can be represented by following formula:
s(t+1)=s(t)+u(t)-r(t)-w(t)(10)
In formula,
At the beginning of s (t), s (t+1) are respectively the polymerization reservoir t period, last accumulation of energy;
U (t) enters energy for the polymerization reservoir t period;
W (t) abandons energy for the polymerization reservoir t period;
R (t) goes out energy for the polymerization reservoir in the t period.
(2) polymerization reservoir fraction constraint can be represented by following formula:
D'(t)=D(t)-σA(NF-D(t))(11)
In formula,
D ' is exerting oneself for step reservoir t period of taking into account fraction constraint (t);
NF is that step reservoir guarantees to exert oneself;
D (t) exerted oneself for the step reservoir t period;
A is the penalty coefficient greater than 0, and the order of magnitude is 10 3~10 6
σ is 0 or 1 variable, and its value rule is: during D (t) 〉=NF, σ is 0, otherwise is 1.
(3) polymerization reservoir accumulation of energy constraint can be represented by following formula:
0≤s(t)≤su(t)(12)
In formula,
S (t) is accumulation of energy at the beginning of the polymerization reservoir t period;
Su (t) is for the maximum accumulation of energy of polymerization reservoir t period, and in flood season, su (t) is the flood of each reservoir in the polymerization reservoir accumulation of energy summation that position corresponding storage capacity emptying to minimum capacity of a reservoir has of restricting water supply.
(4) the polymerization reservoir goes out and can retrain, and can be represented by following formula:
rl(t)≤r(t)≤ru(t)(13)
In formula,
R (t) goes out energy for the polymerization reservoir t period;
Rl (t) goes out energy for the minimum of polymerization reservoir t period, by irrigation, water supply, shipping or the ecological requirement decision of each reservoir;
Ru (t) goes out energy for the maximum of polymerization reservoir t period, by downstream flood control requirement, the discharge capacity decision of each reservoir.
(5) polywater library partition condition can be represented by following formula:
s(0)=s 0(14)
s(T+1)=s T+1(15)
In formula,
s 0Be the just accumulation of energy of polymerization reservoir schedule periods, the accumulation of energy summation that has for initial given storage capacity emptying to the minimum capacity of a reservoir of each reservoir operation in the polymerization reservoir;
s T+1For the polymerization reservoir in scheduling end of term accumulation of energy, the accumulation of energy summation that has to minimum capacity of a reservoir for given storage capacity emptying of each reservoir operation end of term in the polymerization reservoir.
(6) reservoir variable nonnegativity restrictions.
2) obtain the Long-term Optimal Dispatch figure of step reservoir based on the randomness Long-term Optimal Dispatch graph model of step reservoir.
Can adopt self-adapted genetic algorithm to obtain the Long-term Optimal Dispatch figure of step reservoir.Can at first preset the shape of initial schedule line, as shown in Figure 2, then adopt genetic algorithm that horizontal stroke, the ordinate of key point are encoded.To the scheduling line of day part, as take week as scheduling slot, only need 4 control point A, B, the horizontal stroke of C, D, ordinate are arranged the coding variable, namely 8 floating-point encoding variablees.Utilize genetic coding to provide at random the feasible solution of scheduling line, the polymerization reservoir moves according to scheduling graph, and the statistics operation result is selected optimum scheduling graph, obtains new improvement scheduling line by genetic operators such as intersection, variations, iterates, until convergence.
Adopt the step of self-adapted genetic algorithm formulation polymerization optimizing scheduling of reservoir figure as follows:
1. adopt genetic algorithm to generate at random the initial schedule line of polymerization reservoir;
2. the initial schedule line produces new scheduling line through individual variation, intersection and selection; Calculate the fitness of initial schedule line and new scheduling line; The object function of the present invention take the annual average power generation of step reservoir as randomness Long-term Optimal Dispatch graph model, the fitness of polymerization reservoir operation line is the target function value of randomness Long-term Optimal Dispatch graph model;
3. judge whether new scheduling line satisfies the condition of convergence of genetic algorithm, the condition of convergence is that the object function difference of adjacent twice iteration is less than or equal to setting accuracy, restrains output scheduling line if satisfy, thereby obtains Long-term Optimal Dispatch figure; Otherwise repeating step 2..
3) by Long-term Optimal Dispatch figure, the polymerization reservoir is carried out operation simulation, just can obtain the Long-term Optimal Dispatch strategy:
s *(t+1)=Opt(u(t),s(t),t)(16)
In formula,
s *(t+1) for the Long-term Optimal Dispatch strategy of polymerization reservoir t+1 period;
(u (t), s (t) t) dispatches t period optimal policy for the polymerization reservoir to Opt for a long time.
Step 3 according to long-term and principles in coupling short term scheduling, is set up based on the step reservoir flood of " large system polymerization decomposition thought " Real-time dynamic control model of restricting water supply.
Step reservoir flood in the present embodiment is restricted water supply a Real-time dynamic control model with " valid time T yThe power benefit of interior step reservoir is maximum " as optimization aim, and satisfy following constraints: the constraint of (1) water balance; (2) constraint of the hydraulic connection between the upstream and downstream reservoir; (3) reservoir level constraint; (4) outbound flow restriction; (5) output of power station constraint.In addition, also need satisfy reservoir border constraint
Z i ( 0 ) = Z i 0 Z i ( T + 1 ) = Z i T + 1 - - - ( 17 )
In formula,
Z i(0), Z i(T+1) be respectively schedule periods just and last water level;
Be respectively schedule periods just and last given water level.
According to formula (2), the scheduling end of term water level in the constraint formula of each reservoir border is polymerized to period Mo accumulation of energy s (T+1):
s ( T + 1 ) = Σ j = 1 L ( V j ( T + 1 ) - V j ( 0 ) ) Σ i = 1 L ( c j , i K i H 1 i ( T + 1 ) ) - - - ( 18 )
In formula,
V j(T+1) be j the corresponding storage capacity of reservoir operation end of term water level;
V j(0) be the corresponding storage capacity of a j water dead water level;
L is the number of reservoir in step reservoir;
I, j are reservoir numbering in step reservoir;
H 1i(T+1) be the average water head of i reservoir operation end of term retaining state, Wherein, φ iBe the water level storage-capacity curve of i reservoir, H 1i(0) be the downstream head of i reservoir; V i(T+1), V i(0) be respectively i water scheduling end of term water retention capacity and minimum capacity of a reservoir;
K iIt is the power factor of i reservoir;
c J, iBe the concrete value of waterpower incidence matrix, its value rule is seen formula (3)~(5).
Set up the Real time optimal dispatch model that " polymerization reservoir " combines with Short-term Optimal Operation for a long time, key is how to utilize randomness Long-term Optimal Dispatch strategy formula (16), determine the period Mo accumulation of energy s (T+1) in Model of Short-term Optimal Dispatch, long and short phase Optimized Operation is connected, take into account the long-term benefit of step reservoir scheduling to be reflected in statistics variations rule how to consider runoff in short term scheduling.
If cascaded reservoirs is put runoff leading time T flood season in storage y=7 days can be discrete simple Markov Chain take flood season as dispatching cycle of period by week with runoff process, sets up the optimisation strategy formula (16) of the randomness Long-term Optimal Dispatch model of " polymerization reservoir ".Be located at the t in the t period cConstantly forecast, each reservoir and the interval prediction process of becoming a mandarin are Leading time is T y, The meteorological hydrologic forecast model of numerical value that can be constructed according to step 1 obtains.The period Mo accumulation of energy s (T+1) in the Model of Short-term Optimal Dispatch of " polymerization reservoir " determines by following rule:
s ( T + 1 ) = τ t T y Opt ( u ( t ) , s ( t ) , t ) + T y - τ t T y Opt ( u ( t + 1 ) , s ( t + 1 ) , t + 1 ) - - - ( 19 )
In formula,
u ( t ) = 1 τ t Σ j = 1 L I j y ( t ) Σ i = 1 L c j , i K i H 2 i ( t ) Δt ;
u ( t + 1 ) = 1 T y - τ t Σ j = 1 L I j y ( t ) Σ i = 1 L c j , i K i H 2 i ( t ) Δt ;
τ tFor at leading time T yIn belong to time span in Long-term Optimal Dispatch period t.
Due to the Z in r (t) and formula (17) i(0) be known, just can let out principle according to Flood Control Dispatch rules and reservoir classification control, the optimal Decomposition strategy of the power benefit maximum of the step reservoir of seeking to send as an envoy to.Based on " large system polymerization decompose thought ", at first set up the storage capacity upper limit relation of holding in advance of upstream and downstream step reservoir according to the hydraulic connection between the upstream and downstream reservoir and each flood control control point flood control standard, until each reservoir is at valid time T yThe storage capacity upper limit of holding in advance satisfy equation (19).Each initial period according to weather report information obtain one group of optimal policy, and along with forecast information roll to be constantly updated strategy, the power benefit of step reservoir is maximized.Step reservoir flood in the present embodiment restrict water supply the position in real time dynamically control problem belong to multidimensional multistage Optimal Decision-making problem, useful nonlinear optimization method is found the solution, and adopts successively optimization optimization comparatively ripe in dynamic programming problems to obtain a step reservoir flood real-time dynamic control case of restricting water supply.

Claims (8)

1. step reservoir flood real-time dynamic control method of restricting water supply, is characterized in that, comprises the following steps:
Step 1 is set up the step reservoir basin meteorological hydrologic forecast model of numerical value in flood season, and the forecast basin peb process in 1~7 day future that rolls;
Step 2, build the randomness Long-term Optimal Dispatch graph model of step reservoir based on " large system polymerization thought ", and adopt self-adapted genetic algorithm to obtain the Long-term Optimal Dispatch figure of step reservoir, obtain the Long-term Optimal Dispatch strategy of polymerization reservoir based on Long-term Optimal Dispatch figure;
Step 3, according to the Long-term Optimal Dispatch of polymerization reservoir and principles in coupling and the meteorological hydrologic forecast model of numerical value of short term scheduling, structure is based on the step reservoir flood of " large system polymerization Idea of Classification " Real-time dynamic control model of restricting water supply, and obtains a step reservoir flood real-time dynamic control case of restricting water supply according to a step reservoir flood Real-time dynamic control model of restricting water supply.
2. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
The meteorological hydrologic forecast model in step reservoir basin flood season of described step 1 is based on the numerical value weather forecast and distributedly oozes the ability hydrological model under variable and build.
3. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
Described randomness Long-term Optimal Dispatch graph model based on " large system polymerization thought " structure step reservoir further comprises substep:
2-1a obtains virtual polymerization reservoir based on " large system polymerization thought " polymerization step reservoir;
2-2a with the period at the beginning of accumulation of energy and be carved into when facing and can represent polymerization reservoir running status, take period Mo accumulation of energy as decision variable, build relate to polymerization reservoir adjacent time interval enter can correlation randomness Long-term Optimal Dispatch model, and definite constraints.
4. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
The Long-term Optimal Dispatch figure that described employing self-adapted genetic algorithm obtains step reservoir further comprises substep:
2-1b adopts genetic algorithm to generate at random the initial schedule line of polymerization reservoir;
2-2b initial schedule line produces new scheduling line through individual variation, intersection and selection, calculates the fitness of polymerization reservoir initial schedule line and new scheduling line;
Whether 2-3b restrains based on the new scheduling of the fitness judgement line of scheduling line, if convergence, described new scheduling line is the Long-term Optimal Dispatch figure of polymerization reservoir, otherwise repeating step 2-2b.
5. a step reservoir flood according to claim 4 real-time dynamic control method of restricting water supply is characterized in that:
The fitness of described polymerization reservoir operation line is the target function value of randomness Long-term Optimal Dispatch graph model, and described object function is the annual average power generation of step reservoir.
6. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
The Long-term Optimal Dispatch strategy of described polymerization reservoir is:
s *(t+1)=Opt(u(t),s(t),t)
In formula,
s *(t+1) for the Long-term Optimal Dispatch strategy of polymerization reservoir t+1 period;
(u (t), s (t) t) dispatches t period optimal policy for the polymerization reservoir to Opt for a long time.
7. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
The principles in coupling of described Long-term Optimal Dispatch and Short-term Optimal Operation is:
s ( T + 1 ) = τ t T y Opt ( u ( t ) , s ( t ) , t ) + T y - τ t T y Opt ( u ( t + 1 ) , s ( t + 1 ) , t + 1 )
Wherein,
S (T+1) is the period Mo accumulation of energy of " polymerization reservoir ";
T is last period of short term scheduling;
T yBe valid time, its value is 1~7 day;
τ tFor at leading time T yIn belong to time span in the Long-term Optimal Dispatch t period.
S (t), s (t+1) are polymerization reservoir t, accumulation of energy at the beginning of the t+1 period;
Opt (u (t), s (t), t), (u (t+1), s (t+1) t+1) are respectively the polymerization reservoir and dispatch for a long time t, t+1 period optimal policy Opt;
U (t), u (t+1) enter polymerization reservoir t, t+1 period energy, u ( t + 1 ) = 1 T y - τ t Σ j = 1 L I j y ( t ) Σ i = 1 L ( c j , i K i H 2 i ( t ) ) Δt , Be j reservoir and interval t period to forecast the process that becomes a mandarin, L is the number of reservoir in step reservoir, c J, iBe waterpower incidence matrix value, K iBe the power factor of i reservoir, H 2i(t) be the average productive head of i reservoir t period, Δ t is that calculation interval is long, and i, j are the numbering of each reservoir in step reservoir.
8. a step reservoir flood according to claim 1 real-time dynamic control method of restricting water supply is characterized in that:
A described step reservoir flood optimization aim of real-time dynamic control case of restricting water supply is valid time T yThe power benefit of interior step reservoir is maximum.
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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104091240A (en) * 2014-07-18 2014-10-08 河海大学 Hydropower station hierarchical scheduling method and system with combination of medium and long term forecasts
CN105676890A (en) * 2016-01-22 2016-06-15 长江水利委员会长江科学院 Dynamic operation water level control method for 3D or higher cascaded reservoirs in flood season
CN105760703A (en) * 2016-05-03 2016-07-13 大连理工大学 Flood forecasting method based on simulation of water storage and release of aggregated reservoir
CN106127348A (en) * 2016-07-04 2016-11-16 大连理工大学 A kind of multi-reservoir joint optimal operation feasible decision space discrimination method
CN106845712A (en) * 2017-01-20 2017-06-13 中国水利水电科学研究院 The extracting method of scheduling rule is decomposed in polymerization towards big system multi-reservoir
CN107059761A (en) * 2017-06-19 2017-08-18 武汉大学 Multi-reservoir storage capacity space-time distribution design method
CN107288096A (en) * 2017-08-16 2017-10-24 国网湖南省电力公司 Reservoir Restricted Water Level demarcation method and system based on secondary high intermediate-term movement
CN107341567A (en) * 2017-06-19 2017-11-10 武汉大学 The storage capacity displacement computational methods of Cascade Reservoirs
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CN113177189A (en) * 2021-05-20 2021-07-27 中国水利水电科学研究院 Calculation method for grading and staging drought limit storage capacity of cascade reservoir

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03290520A (en) * 1990-04-05 1991-12-20 Hitachi Ltd River system operation method and device therefor
CN101149822A (en) * 2007-10-15 2008-03-26 马志鹏 Reservoir forecast dispatch grey dynamic programming method
CN102182159A (en) * 2011-03-21 2011-09-14 武汉大学 Step reservoir flood limit water level combined application dispatching method
CN102296562A (en) * 2010-06-25 2011-12-28 华东电网有限公司 Step reservoir joint flood scheduling optimization method coupling flood protection with power generation
CN102433855A (en) * 2011-10-13 2012-05-02 贵州东方世纪科技有限责任公司 Flood scheduling system

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH03290520A (en) * 1990-04-05 1991-12-20 Hitachi Ltd River system operation method and device therefor
CN101149822A (en) * 2007-10-15 2008-03-26 马志鹏 Reservoir forecast dispatch grey dynamic programming method
CN102296562A (en) * 2010-06-25 2011-12-28 华东电网有限公司 Step reservoir joint flood scheduling optimization method coupling flood protection with power generation
CN102182159A (en) * 2011-03-21 2011-09-14 武汉大学 Step reservoir flood limit water level combined application dispatching method
CN102433855A (en) * 2011-10-13 2012-05-02 贵州东方世纪科技有限责任公司 Flood scheduling system

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* Cited by examiner, † Cited by third party
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CN105676890B (en) * 2016-01-22 2018-06-26 长江水利委员会长江科学院 Three-dimensional and Yi Shang step reservoir operating level during flood season dynamic control method
CN105760703B (en) * 2016-05-03 2018-04-10 大连理工大学 A kind of Flood Forecasting Method that the simulation that discharges water is stored based on polymerization reservoir
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CN107341567A (en) * 2017-06-19 2017-11-10 武汉大学 The storage capacity displacement computational methods of Cascade Reservoirs
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