CN107341567A - The storage capacity displacement computational methods of Cascade Reservoirs - Google Patents
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Abstract
The present invention provides a kind of storage capacity displacement computational methods of Cascade Reservoirs, and this method can quantify the storage capacity displacement relational expression between storehouse above and below step, it is characterised in that comprise the following steps：Step 1, the big system of Cascade Reservoirs is divided into subsystem；Step 2, the Model for Multi-Objective Optimization of upper and lower multi-reservoir is established；Step 3, multiple target is normalized, and solution is optimized to multi-objective Model, the Pareto forward positions of reservoir storage allocation between upper and lower multi-reservoir are calculated；Step 4, the storage capacity displacement relation between upper and lower subsystem is inquired intoStep 5, storage capacity permutation matrix between each subsystem is inquired into the big system of Cascade Reservoirs.
Description
Technical field
The present invention relates to reservoir operation technical field, the storage capacity displacement computational methods of more particularly to a kind of Cascade Reservoirs.
Background technology
Flood damage is one of natural calamity of China's most serious, and reservoir is main engineering measure, and it can pass through flood retention
Water storage adjusts water flow process, cuts down the crest discharge into downstream river course, so as to reach the purpose of deduction and exemption big flood.Carried in China
On the premise of advocating flood-water resources utilization, the foundation of flood control by reservoir regulation and Xing Li Model for Multi-Objective Optimization starts progressively to develop, and
Limited Water Level of Reservoir in Flood Season but the crucial water level characteristic parameter for coordinating flood control by reservoir regulation and emerging sharp contradiction, it substantially embodies storage capacity
Flood resource distribution between multiple target.At present, the technology such as the flood season limit level design in single storehouse, operating level during flood season dynamic control has been
Through relative maturity, and form a set of more perfect theoretical system.But compared to the theoretical research progress in single storehouse, step reservoir
The problems such as dynamic control of the conjunctive use of group and flood season limit level, is then increasingly complex, and lays particular emphasis on analysis of project example more, lacks
The theoretical system of system.For the big system of Cascade Reservoirs, due to certain hydraulic connection between step reservoir be present,
Storage capacity compensation between upper and lower storehouse be present, if improving the flood season limit level of a certain reservoir or the scheduling rule of a certain reservoir of optimization merely
It might not can improve the overall flood water resources utilization rate of Cascade Reservoirs system.Moreover, with Cascade Reservoirs system reclaimed water
, it is necessary to which the information considered is more and more, the control of Limited Water Level of Reservoir in Flood Season will also become more and more multiple for the increase of storehouse quantity (dimension)
It is miscellaneous.At present, for the research of Cascade Reservoirs combined dispatching problem, lay particular emphasis on more and Optimized model is integrally established to reservoir group system
And how with optimized algorithm progress dimensionality reduction solution, due to the complexity of multi-reservoir compensative dispatching mechanism, accordingly, with respect to multi-reservoir
System aspects do not further investigate the mechanism of its storage capacity displacement.
There are the following problems in existing technology：Stress currently for multi-reservoir conjunctive use and reservoir storage allocation problem more
In terms of establishing global optimization model and studying the optimized algorithm solution of multidimensional model, storage capacity between step reservoir is not furtherd investigate
Displacement relation.
The content of the invention
The present invention is, and it is an object of the present invention to provide a kind of storage capacity displacement of Cascade Reservoirs in order to solving the above problems and carry out
Computational methods, this method can quantify the storage capacity displacement relational expression between storehouse above and below step, inquire into Cascade Reservoirs system neutron
Storage capacity permutation matrix between system.
The invention provides a kind of storage capacity of Cascade Reservoirs to replace computational methods, it is characterised in that comprises the following steps：
Step 1, Cascade Reservoirs are considered as big system, each reservoir in Cascade Reservoirs is considered as subsystem, and to ladder
Each reservoir is numbered according to the order from upstream to downstream in level multi-reservoir, and is labeled as 1,2 successively ..., N, by big system
In any upper and lower series connection two reservoirs as a subsystem, according to being 1 from the order number consecutively in upstream to downstream,
2 ..., N-1, subsystem i and subsystem i+1 form subsystem i, i=1,2 ..., N-1；It will be connected up and down in each subsystem
Two reservoirs be considered as upper and lower subsystem；
Step 2, establish Model for Multi-Objective Optimization for subsystem i, then the object function of Optimized model be generated energy most
Big and storage capacity is maximum, and objectives function includes：
Object function 1
Object function 2
In formula：For subsystem i power generation in the flood seasons amount,For the power generation in the flood seasons amount of subsystem k in subsystem i,For subsystem i storage capacity,For the storage capacity of subsystem k in subsystem i；I=1,2 ..., N-1, k=1,
2；
The solution of subsystem Model for Multi-Objective Optimization will using routine flood control standard and gross generation as constraints：
In formula：For the storage capacity value under subsystem i routine dispactching,For subsystem i routine dispactching
Under power generation in the flood seasons value；
Step 3, the Model for Multi-Objective Optimization for being directed to subsystem i foundation in step 2 is carried out into target using the method for weighting to return
One changes, and object function is：
In formula：α is weight coefficient, and span is 0~1；
Weight factor alpha is converted, gradually optimization obtains the multiple target Noninferior Solution Set of subsystem, that is, obtains in subsystem i
A series of reservoir storage allocation Pareto forward positions between upper and lower subsystem；
Step 4, inquire into the storage capacity displacement relation between the upper and lower subsystems of subsystem i, be implemented as follows：
Step 4-1, statistic procedure 3 calculate the scheme solution of upper and lower subsystem storage capacity in gained Noninferior Solution Set, and arrangement obtains
The scheme disaggregation G of upper and lower subsystem storage capacity, the disaggregation expression formula are：
In formula：WithThe jth group solution of upper and lower subsystem in respectively subsystem i disaggregation G, m are to be solved in disaggregation G
Number, U=i represents that subsystem i, D=i+1 represent subsystem i+1；
Step 4-2, according to the scheme disaggregation G of upper and lower subsystem storage capacity, it is fitted the functional relation of upper and lower subsystem storage capacity
Formula VU=f (VD), and inquire into the displacement relation of upper and lower subsystem storage capacityAndG in formula
(VD)=f-1(VD)；
Step 5, inquire into the big system of Cascade Reservoirs storage capacity permutation matrix between each subsystem, be implemented as follows：
Repeat step 2,3,4, multiple-objection optimization is carried out to N-1 subsystem successively and solved, it is big to inquire into Cascade Reservoirs
Storage capacity permutation matrix between each subsystem, permutation matrix expression formula are in system：
According to storage capacity permutation matrix between each subsystem in the big system of Cascade Reservoirs, you can inquire into the big system of Cascade Reservoirs
In each subsystem storage capacity Equivalence expressions：
Expression formula implication is subsystem i'sIt can replace subsystem i+1'sStorage capacity value, and can be with
Replace subsystem i+2'sStorage capacity value.
Compared with prior art, the beneficial effects of the present invention are：
(1) present invention proposes a kind of storage capacity displacement computational methods of Cascade Reservoirs, this method can quantify on step,
Storage capacity permutation function relational expression between lower storehouse
(2) the Cascade Reservoirs storage capacity in a kind of storage capacity displacement computational methods of Cascade Reservoirs proposed by the invention is put
Change the storage capacity displacement relation that matrix can be used between recursion each subsystem, such as subsystem iSubsystem i+1 can be replaced
'sStorage capacity value, and can replace subsystem i+2'sStorage capacity value, so as to not borrow
In the case of helping optimized algorithm solution, simplify storage capacity assembled scheme between derivation subsystem.
Brief description of the drawings
Fig. 1 is that a kind of storage capacity of Cascade Reservoirs of the embodiment of the present invention one replaces the flow chart of computational methods；
Fig. 2 is the noninferior solution schematic diagram of the subsystem Model for Multi-Objective Optimization of the embodiment of the present invention one；
Fig. 3 be the embodiment of the present invention one subsystem in upper and lower subsystem storage capacity relation schematic diagram.
Embodiment
The specific implementation of computational methods is replaced to a kind of storage capacity of Cascade Reservoirs of the present invention below in conjunction with accompanying drawing
Scheme is described in detail.
<Embodiment one>
As shown in figure 1, a kind of storage capacity displacement computational methods for Cascade Reservoirs that the present embodiment one is provided are including following
Step：
Cascade Reservoirs are considered as big system by step 1., and each reservoir in Cascade Reservoirs is considered as into subsystem, and to ladder
Each reservoir is numbered according to the order from upstream to downstream in level multi-reservoir, and is labeled as 1,2 successively ..., N, by big system
In any upper and lower series connection two reservoirs as a subsystem, according to being 1 from the order number consecutively in upstream to downstream,
2 ..., N-1, subsystem i and subsystem i+1 form subsystem i, i=1,2 ..., N-1；It will be connected up and down in each subsystem
Two reservoirs be considered as upper and lower subsystem；
Step 2. establishes Model for Multi-Objective Optimization for subsystem i, then the object function of Optimized model be generated energy most
Big and storage capacity is maximum, and objectives function includes：
Object function 1
Object function 2
In formula：For subsystem i power generation in the flood seasons amount,For the power generation in the flood seasons amount of subsystem k in subsystem i,For subsystem i storage capacity,For the storage capacity of subsystem k in subsystem i；I=1,2 ..., N-1, k=
1,2；
The solution of subsystem Model for Multi-Objective Optimization will using routine flood control standard and gross generation as constraints：
In formula：For the storage capacity value under subsystem i routine dispactching,For subsystem i routine dispactching
Under power generation in the flood seasons value；
Other conventional constraint conditions repeat no more；
The Model for Multi-Objective Optimization that subsystem i foundation is directed in step 2 is carried out target using the method for weighting and returned by step 3.
One changes, and object function is：
In formula：α is weight coefficient, and span is 0~1；
Weight factor alpha is converted, gradually optimization obtains the multiple target Noninferior Solution Set of subsystem, that is, obtains in subsystem i
A series of reservoir storage allocation Pareto forward positions (such as Fig. 2) between upper and lower subsystem；
Step 4. inquires into the storage capacity displacement relation between the upper and lower subsystems of subsystem i, is implemented as follows：
Step 4-1. statistic procedures 3 calculate the scheme solution of upper and lower subsystem storage capacity in gained Noninferior Solution Set, and arrangement obtains
The scheme disaggregation G of upper and lower subsystem storage capacity, the disaggregation expression formula are：
In formula：WithThe jth group solution of upper and lower subsystem in respectively subsystem i disaggregation G, m are to be solved in disaggregation G
Number, U=i represents that subsystem i, D=i+1 represent subsystem i+1；
Step 4-2. is fitted the functional relation of upper and lower subsystem storage capacity according to the scheme disaggregation G of upper and lower subsystem storage capacity
Formula VU=f (VD) (such as Fig. 3), and inquire into the displacement relation of upper and lower subsystem storage capacityAndFormula
Middle g (VD)=f-1(VD)；
Step 5. inquires into the big system of Cascade Reservoirs storage capacity permutation matrix between each subsystem, is implemented as follows：
Repeat step 2,3,4, multiple-objection optimization is carried out to N-1 subsystem successively and solved, it is big to inquire into Cascade Reservoirs
Storage capacity permutation matrix between each subsystem, permutation matrix expression formula are in system：
According to storage capacity permutation matrix between each subsystem in the big system of Cascade Reservoirs, you can inquire into the big system of Cascade Reservoirs
In each subsystem storage capacity Equivalence expressions：
Expression formula implication is subsystem i'sIt can replace subsystem i+1'sStorage capacity value, and can be with
Replace subsystem i+2'sStorage capacity value.
It should be appreciated that the part that this specification does not elaborate belongs to prior art.Tool described herein
Body embodiment is only to spirit explanation for example of the invention.Those skilled in the art can be to described
Specific embodiment make it is various modification supplement or using similar mode substitute, but without departing from the present invention essence
God surmounts scope defined in appended claims.
Claims (1)
1. the storage capacity displacement computational methods of a kind of Cascade Reservoirs, it is characterised in that comprise the following steps：
Step 1, Cascade Reservoirs are considered as big system, each reservoir in Cascade Reservoirs are considered as subsystem, and give step water
Each reservoir is numbered according to the order from upstream to downstream in the group of storehouse, and is labeled as 1,2 successively ..., N, will appoint in big system
Anticipate upper and lower series connection two reservoirs as a subsystem, be 1,2 according to from the order number consecutively in upstream to downstream ...,
N-1, subsystem i and subsystem i+1 form subsystem i, i=1,2 ..., N-1；Two will to be connected up and down in each subsystem
Individual reservoir is considered as upper and lower subsystem；
Step 2, establish Model for Multi-Objective Optimization for subsystem i, then the object function of Optimized model be generated energy it is maximum and
Storage capacity is maximum, and objectives function includes：
Object function 1
Object function 2
In formula：For subsystem i power generation in the flood seasons amount,For the power generation in the flood seasons amount of subsystem k in subsystem i,To be secondary
Level system i storage capacity,For the storage capacity of subsystem k in subsystem i；I=1,2 ..., N-1, k=1,2；
The solution of subsystem Model for Multi-Objective Optimization will using routine flood control standard and gross generation as constraints：
In formula：For the storage capacity value under subsystem i routine dispactching,For the flood under subsystem i routine dispactching
Phase generating value；
Step 3, the Model for Multi-Objective Optimization that subsystem i foundation is directed in step 2 is subjected to target normalization using the method for weighting,
Object function is：
In formula：α is weight coefficient, and span is 0~1；
Weight factor alpha is converted, gradually optimization obtains the multiple target Noninferior Solution Set of subsystem, that is, obtains upper and lower in subsystem i
A series of reservoir storage allocation Pareto forward positions between subsystem；
Step 4, inquire into the storage capacity displacement relation between the upper and lower subsystems of subsystem i, be implemented as follows：
Step 4-1, statistic procedure 3 calculate the scheme solution of upper and lower subsystem storage capacity in gained Noninferior Solution Set, and arrangement obtains upper and lower
The scheme disaggregation G of subsystem storage capacity, the disaggregation expression formula are：
In formula：WithThe jth group solution of upper and lower subsystem in respectively subsystem i disaggregation G, m are solved in disaggregation G
Number, U=i represent that subsystem i, D=i+1 represent subsystem i+1；
Step 4-2, according to the scheme disaggregation G of upper and lower subsystem storage capacity, it is fitted the functional relation Formula V of upper and lower subsystem storage capacityU=
f(VD), and inquire into the displacement relation of upper and lower subsystem storage capacityAndG (V in formulaD)=f-1
(VD)；
Step 5, inquire into the big system of Cascade Reservoirs storage capacity permutation matrix between each subsystem, be implemented as follows：
Repeat step 2,3,4, multiple-objection optimization is carried out to N-1 subsystem successively and solved, inquires into the big system of Cascade Reservoirs
In storage capacity permutation matrix between each subsystem, permutation matrix expression formula is：
According to storage capacity permutation matrix between each subsystem in the big system of Cascade Reservoirs, you can inquire into each in the big system of Cascade Reservoirs
The Equivalence expressions of subsystem storage capacity：
Expression formula implication is subsystem i'sIt can replace subsystem i+1'sStorage capacity value, and can replace
Subsystem i+2'sStorage capacity value.
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| CN109829611A (en) * | 2018-12-24 | 2019-05-31 | 长江勘测规划设计研究有限责任公司 | The step Optimization Scheduling dynamically distributed based on storage capacity |
| CN111005346A (en) * | 2019-12-06 | 2020-04-14 | 河海大学 | Reservoir group multi-objective action mechanism and optimization scheduling scheme analysis method |
| CN111079066A (en) * | 2019-11-21 | 2020-04-28 | 河海大学 | Reservoir group power generation ecological two-target competition relationship analysis method |
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| CN111005346A (en) * | 2019-12-06 | 2020-04-14 | 河海大学 | Reservoir group multi-objective action mechanism and optimization scheduling scheme analysis method |
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