CN109190902A - Consider the uncertain water resource optimal allocation Emulation of Newsboy Model of supply and demand - Google Patents
Consider the uncertain water resource optimal allocation Emulation of Newsboy Model of supply and demand Download PDFInfo
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Abstract
The present invention relates to a kind of uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand.Including: S1. seeks streamflow change rule using actual measurement analysis of hydrological data, obtains the probability distribution of runoff by statistical analysis;S2. these three type water requirements are assumed to be and are uniformly distributed, carry out needing water rail vehicle roller test-rig using the data of the first three years as historical data analysis according to agricultural, industry, domestic water feature according to classical Newsboy problem;S3. using water, need the probability-distribution function of water, introduce economics Emulation of Newsboy Model, building considers the probabilistic water resource optimal allocation Emulation of Newsboy Model of supply and demand water, and solution obtains preliminary allocation plan;Judge that preliminary allocation plan always configures whether water is more than maximum available water, if not having, preliminary allocation plan is exactly optimal case, if being more than, re-starts solution using two-phase heuristic algorithm, obtains optimal case.Method provided by the invention can obtain the closer Water Resources Allocation scheme to need water actual conditions.
Description
Technical field
The present invention relates to water resources management fields, more particularly, to a kind of uncertain water resource optimization of consideration supply and demand
Configure Emulation of Newsboy Model.
Background technique
Traditional Optimal Allocation Model and method considers mostly by uncertainty optimization problem reduction at certainty planning problem
Information content it is few, cannot reflect completely the water process of Water Resources Allocation system physical presence with need water process it is uncertain because
Element causes optimum results to have irrationality.Although there is minority to consider the probabilistic water resource of water using stochastic simulation
Allocation models needs water still not account for uncertainty due to being limited by modelling, without concentrated expression water simultaneously and
Need the uncertainty of water.For the uncertainty for fully considering water in Water Resources Allocation Model He needing water, exist herein
On the basis of analysis water and the uncertainty for needing water, it is excellent that newsboy's mode thought of Science of Economics is introduced to water resource system
Change configuration, and traditional Emulation of Newsboy Model improved, while to Water Resources Allocation demand end --- need water process to consider not true
Feed end qualitative, to Water Resources Allocation --- water process considers uncertainty, and building considers water and needs water uncertain
Water resource optimal allocation Emulation of Newsboy Model, coordinate the Optimized Matching between the erratic demand of water resource and uncertain water process
Relationship.
Summary of the invention
The present invention in order to overcome at least one of the drawbacks of the prior art described above, provides a kind of consideration supply and demand uncertain water
Science of Economics newsboy's mode thought is introduced to water resource optimal allocation, to traditional report by most optimum distribution of resources Emulation of Newsboy Model
Virgin model improves, while considering uncertainty to Water Resources Allocation demand end, feed end, thus the closer water of acquisition,
Need the Water Resources Allocation scheme of water actual conditions.
In order to solve the above technical problems, the technical solution adopted by the present invention is that: a kind of uncertain water resource of consideration supply and demand
Distribute Emulation of Newsboy Model rationally, comprising the following steps:
S1. water analysis of uncertainty: seek streamflow change rule using actual measurement analysis of hydrological data, pass through statistical analysis
Obtain the probability-distribution function of runoff;
S2. water analysis of uncertainty is needed: according to classical Newsboy problem, according to agricultural, industry, domestic water feature, agriculture
Three industry, industry, life type water requirements are assumed to be and are uniformly distributed, to predict the data of time the first three years as historical data
Analysis carries out needing water rail vehicle roller test-rig;
S3. the water analyzed using S1, S2 step, the probability-distribution function for needing water introduce economics Emulation of Newsboy Model,
Building, which considers to supply water, needs the probabilistic water resource optimal allocation Emulation of Newsboy Model of water, and solution obtains preliminary allocation plan;Judgement is just
Step allocation plan always configures whether water is more than maximum available water, and preliminary allocation plan is exactly optimal case if without being more than,
Solution is re-started using two-phase heuristic algorithm if being more than, obtains optimal case.
Further, as described in step 2, need water process analysis procedure analysis, it is contemplated that regional agriculture, industry fast development and
Population increases, according to classical Newsboy problem, according to agricultural, industry, domestic water feature, three agricultural, industry, life types
Water requirement, which is assumed to be, to be uniformly distributed, to predict that the data of time the first three years carry out rail vehicle roller test-rig, example as historical data analysis
Water requirement in 2019 is such as forecast with 2016~2018 years water data, maximum value is used as the upper limit in the first three years, the smallest
Value is used as lower limit, that is, has:
As x >=Dmax
In formula,It is for water requirement x cumulative distribution function,For water requirement x density function;
DmaxIt is herein the maximum value of water requirement in the first three years for water requirement maximum value;
DminIt is herein the smallest value of water requirement in the first three years for water requirement minimum value.
Further, the uncertain water resource optimal allocation Emulation of Newsboy Model of the consideration supply and demand considers water, needs water
Uncertainty, the water of objective function and to need water variable be all stochastic variable, the probability distribution letter for considering water, needing water
Number:
Somewhere type water distribution cost function is
Expected cost is as follows:
In formula,It is stochastic variable for i unit, j department, t period water requirement;It is for cumulative distribution function;For density function,For minimum water dosage,For maximum water requirement;RtFor t period runoff rate, for
Machine variable;G(Rt) it for cumulative distribution function is g (Rt) it is density function,For maximum diameter flow,For minimum runoff
Amount;For i unit, j department, t period water distribution quantity;cI, jFor i unit, j department water price;hI, jFor i unit, dilutional hyponatremia is matched by j department
Unit fine;vI, jFor i unit, hydropenic opportunity loss is matched by j department;CoFor t period water distribution excessive cost;CuFor the t period
Water distribution deficiency cost;CpTo purchase water cost;rt=t period, actual flow.
Further, in the S3 step, according to water balance and characteristic water level of reservoir constraint can obtain it is maximum for
Water:
Characteristic level of water constraint:
According to Design of Reservoirs water level storage-capacity curve, storage capacity limitation can be obtained:
Vmin≤Vt≤Vmax
Water balance constraint:
Vt=Vt-1+rt-Qt
Total amount constraint:
Distribution water total amount is less than outflow from reservoir, i.e.,
Nonnegativity restrictions:
Reservoir storage outflow can be obtained according to water balance and characteristic level of water constraint:
It is obtained by constraints above:
Vt-1+rt-Vmax≤Qt≤Vt-1+rt-Vmin
I.e. reservoir maximum storage outflow is
If total water distribution quantity has been more than maximum available water, xI, j *It is not optimal water distribution quantity, needs to be adjusted.Herein
It is solved using two-phase heuristic algorithm.This method be by LaGrange parameter by target cost function with it is available
Water quantity restraint connects, and constitutes a completely new Lagrangian, then solving this by solving this function can
Utilize the Water Resources Allocation Emulation of Newsboy Model under water quantity restraint
Further, described to be solved using two-phase heuristic algorithm, it is by LaGrange parameter by target
Cost function is connected with utilized water resources constraint, constitutes a completely new Lagrangian, function are as follows:
In formula, t is the moment,To let out maximum stream flow under t moment reservoir, λ is the Lagrange ginseng for indicating constraint condition
Number.
Further, using P-III type frequency curve, Weibull distribution, generalized Pareto distribution in the S1 step
The probability distribution for statistical analysis for obtaining runoff.
Compared with prior art, beneficial effect is: a kind of uncertain water resource optimization of consideration supply and demand provided by the invention
Emulation of Newsboy Model is configured, newsboy's mode thought is introduced to water resource optimal allocation, and improve to traditional Emulation of Newsboy Model, together
Water process that when --- needs water process consideration uncertainty, to the feed end of Water Resources Allocation --- to Water Resources Allocation demand end
Consider uncertainty, the water for having comprehensively considered Water Resources Allocation needs water process uncertain, more closer than conventional method practical
Situation is more accurate.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart.
Fig. 2 is to distribute result in the embodiment of the present invention rationally.
Fig. 3 is to distribute result and actual disposition result water supply fraction comparison diagram in the embodiment of the present invention rationally.
Fig. 4 is to distribute cost and actual disposition Cost comparisons figure in the embodiment of the present invention rationally.
Specific embodiment
Attached drawing only for illustration, is not considered as limiting the invention;In order to better illustrate this embodiment, attached
Scheme certain components to have omission, zoom in or out, does not represent the size of actual product;To those skilled in the art,
The omitting of some known structures and their instructions in the attached drawings are understandable.Being given for example only property of positional relationship is described in attached drawing
Illustrate, is not considered as limiting the invention.
As shown in Figure 1, a kind of uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand, includes the following steps:
The analysis of step 1 water is sought streamflow change rule using actual measurement analysis of hydrological data, is obtained by frequency analysis
The probability distribution of runoff, it is generally for statistical analysis using P-III type frequency curve, Weibull distribution, generalized Pareto distribution
Obtain the probability distribution of runoff;
Step 2 water requirement analysis obtains the probability-distribution function of prediction water requirement by history water data, according to classics
Newsboy problem is assumed to be agricultural, industry, three, cities and towns type water requirement and is uniformly distributed;
Step 3 building considers the uncertain water resource optimal allocation Emulation of Newsboy Model of supply and demand, is analyzed using front
Water, the probability-distribution function for needing water carry out considering the uncertain water resource optimal allocation of supply and demand, obtain preliminary allocation plan, sentence
The preliminary allocation plan that breaks always configure water whether be more than maximum can storage outflow, if without be more than if preliminary allocation plan be exactly optimal
Scheme re-starts solution using two-phase heuristic algorithm if being more than, obtains optimal case.Concrete model building process is such as
Under:
Similar newsboy sells report (corresponding to water distribution), in newspaper buyer cost c (corresponding to water resource purchase cost), purchase
The loss h (fine for corresponding to over water requirement) that does not sell into excess part, the loss v for buying insufficient section (correspond to not
Meet the opportunity loss of water requirement) in the case that (to correspond to water requirement) it is known that exact demand unknown, solving newsboy will purchase daily
It can just make cost (water distribution cost) minimum into how many parts of newspapers (correspond to and solve the problems, such as with how many water).The one of Emulation of Newsboy Model
A basic assumption be the demand of newspaper be it is uncertain, it is how excellent when can be very good to solve to need water uncertain in Water Resources Allocation
The problem of changing configuration.Difference with traditional Emulation of Newsboy Model also resides in, and there is no limit and days for the size of order of traditional Emulation of Newsboy Model
Right water is limited, and unknown, while also suffering from the limitation of process capability, therefore, for supplying, need under changing environment
Optimization allocation of water resources under condition of uncertainty is improved on the basis of original Emulation of Newsboy Model, be desirably to obtain consider water,
The uncertain water resource optimal allocation Emulation of Newsboy Model of water is needed, and draws corresponding Water Resources Allocation side by solving the model
Case.
Water resource optimal allocation is reasonably to be divided the limited usable water resources in region between each water-using sector
Match, the final efficient utilization for realizing water resource.Without loss of generality, if some region can be divided into i computing unit, i=1,2,
3…I;Each computing unit has j water-using sector, j=1,2,3 ... J.To computing unit i, the t period water requirement of j department is matched
Water is used respectivelyIt indicates, with the minimum target of water distribution totle drilling cost, determines objective function.
According to newsboy's mode, model parameter is provided that
For i unit, j department, t period water requirement, stochastic variable, cumulative distribution function isDensity functionIt is minimumIt is up to
For i unit, j department, t period water distribution quantity;
cI, jFor i unit, j department water price;
hI, jFor i unit, j department imposes a fine with the unit of dilutional hyponatremia;
vI, jFor i unit, hydropenic opportunity loss is matched by j department;
CoFor t period water distribution excessive cost;
CuFor t period water distribution deficiency cost;
CpTo purchase water cost;
VtFor t period reservoir capacity;
VminFor minimum capacity of a reservoir;
rtFor t period, actual flow
RtFor t period runoff rate, stochastic variable, cumulative distribution function is G (Rt), density function g (Rt), it is up toIt is minimum
Then had according to Emulation of Newsboy Model:
Somewhere type water distribution cost function is
Expected cost is as follows:
Then E [C (x)] single order is led:
Second order is led are as follows:
SoIt is concave function, to seek optimal water distribution quantity, only needs so that cost function is minimum, even if cost letter
Number single order is led equal to 0
Runoff and the bound for needing water:
Divide situation that the cost function between runoff maximum value and water requirement maximum value under different relationships is discussed:
When
Have
ByIt can obtain:
Wherein middle xI, j *For the best water distribution quantity of somewhere type.
When
ByCocoa obtains:
WhereinFor certain period best water distribution quantity of somewhere type.
Difference with traditional Emulation of Newsboy Model is, there is no limit and water resource can for the size of order of traditional Emulation of Newsboy Model
Water with distribution is limited by reservoir, i.e., is limited by reservoir storage outflow with water inventory, at the same reservoir discharge water also by
To the constraint of Design of Reservoirs water level, it may be assumed that
Constraint condition:
Characteristic level of water constraint:
According to Design of Reservoirs water level storage-capacity curve, storage capacity limitation can be obtained:
Vmin≤Vt≤Vmax
Water balance constraint:
Vt=Vt-1+rt-Qt
Total amount constraint:
Distribution water total amount is less than outflow from reservoir, i.e.,
Nonnegativity restrictions:
Reservoir storage outflow can be obtained according to water balance and characteristic level of water constraint:
It is obtained by constraints above:
Vt-1+rt-Vmax≤Qt≤Vt-1+rt-Vmin
I.e. reservoir maximum storage outflow is
The all types of water distribution quantities in each region solved for the Water Resources Allocation Emulation of Newsboy Model of unfettered condition limitationEach all types of optimal water distribution quantities in region are still if meeting each constraint condition
But if if being unsatisfactory for constraint condition, and having: V by calculatingt> Vmax,
It is then more than the water whole outbound of flood season limit level (normal pool level), each all types of optimal water distribution quantities in region are still
If Vt< Vmin, then:
I.e. total water distribution quantity has been more than maximum storage outflow, then xI, j *It is not optimal water distribution quantity, needs to be adjusted.Herein
It is solved using two-phase heuristic algorithm.This method be by LaGrange parameter by target cost function with it is available
Water quantity restraint connects, and constitutes a completely new Lagrangian, then solving this by solving this function can
Utilize the Water Resources Allocation Emulation of Newsboy Model under water quantity restraint.
Steps are as follows for calculating:
Stage one:
By no water condition limit Water Resources Allocation Emulation of Newsboy Model solve to obtain all types of optimal water distribution quantities in each region beIt calculatesIt obtains:
Stage two: it establishes with drag:
It enables λ indicate the LaGrange parameter of constraint condition, then constructs Lagrangian numberAre as follows:
If
According to the Rule for derivation of function sum:
Work as Rmax< DI, jmax, byIt can obtain:
WhereinFor certain period best water distribution quantity of somewhere type.
Work as Rmax> DI, jmax:
ByIt can obtain:
Wherein xI, j *For the best water distribution quantity of somewhere type.
It is indicated with λIt is substituted intoIn, an optimal value of λ is calculated, so that it is every to obtain each region
The optimal water distribution quantity of a type
Embodiment 1
It selects Huizhou western Zhijiang basin basin as case study region, verifies allocative effect.
Step 1: water is analyzed, seeks streamflow change rule using actual measurement analysis of hydrological data, obtained by frequency analysis
The probability distribution of runoff generally uses P-III type frequency curve:
The reservoir inflow that goes out for -2011 years 1986 after water historical data uses Baipenzhu reservoir to build library does analysis of cases,
Due to the randomness of runoff, the specific flow of two Phase flow can not be learnt, can only seek them using actual measurement analysis of hydrological data and become
Law can obtain the distribution of runoff by frequency analysis, generally use P-III type frequency curve, which is this
The prior art well known to skilled artisan, is not described in detail herein.
Frequency analysis is done to Baipenzhu reservoir 1985-2011 1-12 month two Phase flow, the Baipenzhu reservoir 1-12 month can be obtained
Part frequency curve, fitting effect is as shown in table 1, and P-III type frequency curve degree of fitting is high, and least correlativing coefficient is all up to 0.9,
Therefore the distribution of available P-III type frequency curve fitting Baipenzhu reservoir moon two Phase flow.
1 Baipenzhu reservoir of table is put in storage moon runoff P-III type frequency analysis correlation coefficient charts
Step 2: water requirement analysis, obtains the probability-distribution function of prediction water requirement by history water data, according to classics
Newsboy problem, we, which are assumed to be agricultural, industry, three, cities and towns type water requirement, is uniformly distributed:
In view of the fast development of agro-industry and population increase, to predict the data of time the first three years as historical data
Analysis carries out rail vehicle roller test-rig, such as water requirement in 2019 is forecast with 2016~2018 years water data, maximum in the first three years
Value as the upper limit, the smallest value is used as lower limit, that is, have:
As x >=Dmax
It is analyzed with 2002~2011 years ten annual datas, predicts that see Table 2 for details for year water consumption bound and practical year water consumption, respectively
With being distributed in water year as shown in table 3, industrial and domestic water was assumed to be in year to be uniformly distributed industry, and water distribution root is used in agriculture year
It obtains according to the mean value of 2002~2011 years 10 years water data, can be seen that by table, since agricultural development is just stable, thus agriculture
Industry prediction needs water and use water mean error smaller, and agricultural needs water mean error to be up to 8.01%, minimum 2.07%, and due to
The fast development and the rapid growth of population of industrial economy, industrial water demand and life water demand forecast error are larger, wherein industry needs
Water mean error is up to 34.52%, and life needs water mean error to be up to 17.38%, but over time, error
It gradually decreases, industrial water demand mean error minimum reaches -1.07%, and life needs water error minimum up to -0.94%, it can thus be assumed that will
Water requirement be assumed to be uniformly distributed it is relatively reasonable, can be obtained by history water data prediction water requirement probability distribution letter
Number.
Table 2 predicts year water consumption bound and practical year water consumption table (ten thousand m3)
3 each department of table distribution table in water year
Step 3: building considers the uncertain water resource optimal allocation Emulation of Newsboy Model of supply and demand, analyzed using front
Water, the probability-distribution function for needing water carry out considering the uncertain water resource optimal allocation of supply and demand, optimal case are obtained, such as 4 institute of table
Show, configuration result and the multiple-objection optimization configuration result of actual disposition and certainty allocation models compared:
Table 4 distributes result (ten thousand m rationally3)
As shown in Fig. 2, in actual disposition, (2006,2008), the configuration water of actual disposition scheme when water is more
Amount generates much larger than water is distributed rationally and largely abandons water, the time for causing later period water less (2009~2011 years), in reservoir
Available water is insufficient for actual used water, and water supply fraction compares visible Fig. 3.During practical water distribution, when water is more,
Such as 2005~2008 years, water supply fraction was higher, had all reached 100%, but when water is less within 2009~2011 years, supplied water
Fraction is relatively low, if between 2005~2011 years, actual disposition score 653 is divided in terms of being divided by every 1% water supply fraction 1, lower than optimization
685 points of configuration.As shown in Table 5, between 2005~2008 years, although water supply fraction all reaches during practical water distribution
100%, but abandoning water electrode is more, and between 2005~2008 years, 1,526,250,000 m of water is abandoned during practical water distribution3, during distributing rationally
Abandon water only 95,790,000 m3, 2009~2011 years, in the less situation of water, actual disposition abandoned dilutional hyponatremia, reservoir filling due to early period
Deficiency, cause this between 3 years water shortage it is more.
The comparison of 5 water supply fraction of table
Actual disposition is calculated according to price, remission parameter and distributes totle drilling cost rationally, as shown in figure 4, distributing rationally total
Only 4,810,080,000 yuan of cost, far below 71,456,660,000 yuan of actual disposition.
From the point of view of whether considering uncertainty, water resource optimal allocation is divided into certainty configuration and configures with uncertain.By
In the uncertainty for considering water He needing water, it is clear that the Water Resources Allocation Model of this chapter building belongs to uncertain configuration
Model, this chapter will be compared point with the middle water resource optimal allocation achievement of " Guangdong Province's Dongjiang basin water resource assignment scheme "
Analysis, the latter belong to certainty allocation models using multiobjective analysis method (MOA).Due to " Guangdong Province's Dongjiang basin water money
Source allocation plan " for water data using the water sequence and water demand forecast data of history, long sequence water data length is 1956
~2005 years, therefore compared with Water Resources Allocation scheme in 2005.
6 2005 years Emulation of Newsboy Model of table and MOA model Water Resources Allocation Comparative result
As seen from Table 6, it is compared with actual used water, water deficit all occurs in the allocation plan of Emulation of Newsboy Model and MOA model
(Emulation of Newsboy Model agricultural matches dilutional hyponatremia, generates and abandons water), but MOA model allocation plan water deficit is much larger than the configuration of Emulation of Newsboy Model
Scheme, especially agriculture water distribution, reason are to use water supply design dependability when MOA model optimizes configuration decisions
This parameter, in MOA Optimal Allocation Model, the water supply fraction of agricultural water is minimum, therefore agricultural water water shortage occurs
At most this is as a result, likewise, the industrial water allocation scheme water deficit of MOA is lower than the industry of Emulation of Newsboy Model in industrial water allocation scheme
Water allocation scheme, this is because in MOA model, caused by this factor of indusqtrial water supply fraction with higher.But from total
From the point of view of body allocation plan, 32643.64 ten thousand m of MOA model totality water shortage3, water deficit 3152.70 ten thousand is configured much higher than Emulation of Newsboy Model
m3.The cost that two allocation plans are calculated using identical price parameter can be seen that the deployment cost of MOA much higher than report by table
The deployment cost of virgin model, therefore relatively know to consider the uncertain water resource optimal allocation Emulation of Newsboy Model of supply and demand from this result
Obtained configuration scheme compared to traditional certainty MOA allocation models obtain under configuration scheme abandon water it is less, at
This is lower.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (4)
1. a kind of uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand, which comprises the following steps:
S1. water analysis of uncertainty: seek streamflow change rule using actual measurement analysis of hydrological data, obtained by statistical analysis
The probability-distribution function of runoff;
S2. water analysis of uncertainty is needed: according to classical Newsboy problem, according to agricultural, industry, domestic water feature, agricultural, work
Three industry, life type water requirements are assumed to be and are uniformly distributed, to predict the data of time the first three years as historical data analysis
It carries out needing water rail vehicle roller test-rig;
S3. the water analyzed using S1, S2 step, the probability-distribution function for needing water introduce economics Emulation of Newsboy Model, building
Consider to supply water and need the probabilistic water resource optimal allocation Emulation of Newsboy Model of water, solution obtains preliminary allocation plan;Judgement is tentatively matched
It sets scheme and always configures whether water is more than maximum available water, preliminary allocation plan is exactly optimal case if without being more than, if super
It crosses, solution is re-started using two-phase heuristic algorithm, obtains optimal case.
2. the uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand according to claim 1, which is characterized in that institute
The uncertainty that the uncertain water resource optimal allocation Emulation of Newsboy Model of the considerations of stating supply and demand considers water, needs water, target letter
Several water and to need water variable be all stochastic variable, the probability-distribution function for considering water, needing water:
Somewhere type water distribution cost function is
Expected cost is as follows:
In formula,It is stochastic variable for i unit, j department, t period water requirement;It is for cumulative distribution function;
It is minimum for density functionIt is up toRtIt is stochastic variable for t period runoff rate;G(Rt) it is iterated integral
Cloth function is g (Rt) it is density function, it is up toIt is minimum For i unit, j department, t period water distribution quantity;
cI, jFor i unit, j department water price;hI, jFor i unit, j department imposes a fine with the unit of dilutional hyponatremia;vI, jFor i unit, the water distribution of j department
Insufficient opportunity loss;CoFor t period water distribution excessive cost;CuFor t period water distribution deficiency cost;CpTo purchase water cost;rt=t
Period, actual flow.
3. the uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand according to claim 2, which is characterized in that institute
That states is solved using two-phase heuristic algorithm, is by LaGrange parameter by target cost function and utilized water resources
Constraint connects, and constitutes a completely new Lagrangian, function are as follows:
In formula, t is the moment,To let out maximum stream flow under t moment reservoir, λ is the LaGrange parameter for indicating constraint condition.
4. the uncertain water resource optimal allocation Emulation of Newsboy Model of consideration supply and demand according to claim 1, which is characterized in that institute
In the S1 step stated using P-III type frequency curve, Weibull distribution, generalized Pareto distribution is for statistical analysis obtains diameter
The probability distribution of stream.
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109784582A (en) * | 2019-02-15 | 2019-05-21 | 黄河勘测规划设计研究院有限公司 | A kind of regional economy department water distribution equalization methods and system |
CN112365128A (en) * | 2020-10-21 | 2021-02-12 | 西安理工大学 | Reservoir group scheduling risk quantification method based on child reporting principle |
CN113012353A (en) * | 2021-02-22 | 2021-06-22 | 广州好友数码科技有限公司 | Water quantity real-time monitoring method and system suitable for Internet of things water meter |
CN113688542A (en) * | 2021-10-26 | 2021-11-23 | 长江水利委员会长江科学院 | Intelligent optimization water resource configuration method and device, computer equipment and storage medium |
CN116307936A (en) * | 2023-05-17 | 2023-06-23 | 长江水利委员会长江科学院 | Method, system, electronic device and storage medium for decomposing total amount of water |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104636834A (en) * | 2015-03-20 | 2015-05-20 | 华北电力大学 | Improved optimization method for joint probability programming model system |
CN107944603A (en) * | 2017-11-09 | 2018-04-20 | 中山大学 | Water resource optimal allocation newsboy's method based on water total amount control |
-
2018
- 2018-08-03 CN CN201810876681.6A patent/CN109190902B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104636834A (en) * | 2015-03-20 | 2015-05-20 | 华北电力大学 | Improved optimization method for joint probability programming model system |
CN107944603A (en) * | 2017-11-09 | 2018-04-20 | 中山大学 | Water resource optimal allocation newsboy's method based on water total amount control |
Non-Patent Citations (1)
Title |
---|
何艳虎 陈晓宏等: "东江流域水资源优化配置报童模式研究", 《水力发电学报》 * |
Cited By (8)
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CN109784582B (en) * | 2019-02-15 | 2020-08-25 | 黄河勘测规划设计研究院有限公司 | Water distribution balancing method and system for regional economic department |
CN112365128A (en) * | 2020-10-21 | 2021-02-12 | 西安理工大学 | Reservoir group scheduling risk quantification method based on child reporting principle |
CN112365128B (en) * | 2020-10-21 | 2023-06-09 | 西安理工大学 | Reservoir group scheduling risk quantification method based on primordial principle |
CN113012353A (en) * | 2021-02-22 | 2021-06-22 | 广州好友数码科技有限公司 | Water quantity real-time monitoring method and system suitable for Internet of things water meter |
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CN116307936B (en) * | 2023-05-17 | 2023-08-18 | 长江水利委员会长江科学院 | Method, system, electronic device and storage medium for decomposing total amount of water |
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