CN107341570A - Reservoir filling phase runoff grading control power generation dispatching method under the conditions of a kind of random water - Google Patents
Reservoir filling phase runoff grading control power generation dispatching method under the conditions of a kind of random water Download PDFInfo
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Abstract
The invention belongs to optimizing scheduling of reservoir field, discloses the reservoir filling phase runoff grading control power generation dispatching method in the case of a kind of random water.First, water storage phase two Phase flow is divided into two stages of period and remaining phase long duration that face, history two Phase flow data, statistics obtain the transition probability matrix between the current runoff of water storage phase day part and the average runoff of remaining phase long duration to analysis reservoir for many years.Then discrete water storage phase day part reservoir operating level and reservoir inflow, obtain the combination of day part reservoir level and reservoir inflow.For each combination, the remaining various stochastic averaginas of phase long duration are obtained according to transition probability matrix and enter flow valuve probability, being calculated makes the decision-making flow value of present period and remaining phase long duration generated energy desired value maximum, and combining establishment after calculating water storage phase all periods obtains runoff level control table (LCT).The inventive method can improve reservoir filling phase water provenance and generated energy in the case of the period water randomness that looks to the future.
Description
Technical field
The invention belongs to optimizing scheduling of reservoir field, the reservoir filling phase runoff classification being related in the case of a kind of random water
Control power generation dispatching method.
Background technology
Existing reservoir filling phase power generation dispatching theoretical research is more dispatched with deterministic optimization based on, following water as
Know, and because Runoff Forecast precision problem, deterministic optimization scheduling achievement are difficult to be applied.
Reservoir capacity adjustment figure independent of Runoff Forecast, turn into current reservoir filling phase actual motion scheduling it is main according to
According to.The routine dispactching figure drawn out according to typical low water annual discharge series are chosen, main purpose are to ensure that reservoir can smoothly store
It is full.There is the reservoir of flood control task for flood season, the reservoir refill phase is shorter, preferable by scheduling graph operating effect.And for flood season without
Flood control task reservoir, the water storage phase is especially long, is easily stored too early completely in most of time by traditional scheduler figure output division operation, after
The later stage can be made to produce the more generated energy and water provenance abandoned water, reduce all the period of time if phase water is larger.
Therefore, a kind of more practical and general reservoir filling phase progress control method is formulated to realizing that the reservoir filling phase is sent out
Electrically optimized scheduling is significant.
The content of the invention
For the disadvantages described above or Improvement requirement of prior art, the invention provides the reservoir in the case of a kind of random water
Water storage phase runoff grading control power generation dispatching method, it is intended that formulating a kind of more practical and general reservoir filling phase
Progress control method, realize that reservoir filling phase generation optimization is dispatched, farthest improve the generated energy and water profit of all the period of time
With rate.
To achieve the above object, according to one aspect of the present invention, there is provided reservoir filling under the conditions of a kind of random water
Phase runoff grading control power generation dispatching method, comprises the following steps：
Step 1：Water storage phase two Phase flow is divided into two stages of period and remaining phase long duration that face, analysis reservoir is gone through
History two Phase flow data, statistics obtain the transition probability between the current runoff of water storage phase day part and the average runoff of remaining phase long duration
Matrix,
Step 2：To each period in the reservoir filling phase, the discretization period operating water level and reservoir inflow, water is obtained
Whole combinations of the discrete operating water level of storehouse day part and reservoir inflow,
Step 3：Combined for each of water storage phase day part water level value and two Phase flow value, using turning in step 1
Move probability matrix and obtain remaining various stochastic averaginas of phase long duration and enter flow valuve probability, the initial last water level of fixed schedule, to it is current when
Section decision-making flow value is traveled through, and optimization obtains the decision-making stream for making present period and remaining phase long duration generated energy desired value maximum
Value,
Step 4：Optimization calculates the decision-making stream under water storage phase all periods, all water level sections and reservoir inflow interval combinations
Value, combination establishment obtain runoff level control table (LCT), for controlling power station water storage phase generator operation.
Further, the transition probability matrix for acquisition being counted in step 1 is：
In formula, pij(QIt is remaining=qj|Qt=qi) represent t period footpaths flow valuve QtFor qiAnd remaining phase long duration average diameter flow valuve
QIt is remainingFor qjProbability.
Further, in step 2, to water storage phase all scheduling slots, by reservoir level it is discrete in range of operation be more
Individual section [Hn,Hn+1], n=1,2 ..., N,
Wherein, n represents n-th of discrete operating water level, and N represents discrete operating water level number,
Similarly for reservoir inflow, multiple section [Q are also separated into the range of actual capabilitiesm,Qm+1], m=1,2 ...,
M；M represents m-th of discrete reservoir inflow, and M represents discrete reservoir inflow number,
Step 3：Median is taken to discrete water level section and the section that becomes a mandarin, for water storage phase day part water level value and storage
Each combination of footpath flow valuve, the randomness for the water that looks to the future,
The remaining various stochastic averaginas of phase long duration are obtained according to the transition probability matrix in step 1 and enter flow valuve probability, it is fixed
Last water level at the beginning of schedule periods, present period decision-making flow value is traveled through, optimization obtains different water level sections and reservoir inflow level
Under other, make present period and each decision-making flow value of remaining phase long duration generated energy desired value maximum,
Step 4：Using the method in step 3, optimization calculates water storage phase all period, all water level sections and reservoir inflows
Decision-making flow value under interval combinations, combination establishment obtain runoff level control table (LCT), and the runoff level control table (LCT) is as follows,
Wherein, [Hn,Hn+1] n-th of discrete operating water level section is represented, N represents discrete operating water level number, [Qm,Qm+1]
M-th of discrete reservoir inflow section is represented, M represents discrete reservoir inflow number, and t represents t-th of period, and T represents total period
Number, QTt,n,mRepresent that t-th of period water level is in n-th of section, aerial drainage under decision-making when reservoir inflow is in m-th of section
Value.
Further, the remaining phase long duration refers to the cumulative duration from second period to the water storage end of term.
In general, by the contemplated above technical scheme of the present invention compared with prior art, it can obtain down and show
Beneficial effect：
The inventive method estimates following various possible water scenes according to water storage phase present period two Phase flow size, if
The Rational Decision flow and reservoir storage of present period are counted, by obtaining different decision-making streams for present period difference runoff size
Value carries out runoff grading control scheduling to the water storage phase, can efficiently reduce the water storage phase and abandon water, improve water provenance, increase
Generated energy.The runoff hierarchical control method proposed considers the randomness of following water, with more practicality.
Brief description of the drawings
Fig. 1 is central diameter stream grading control power generation dispatching method implementing procedure figure of the embodiment of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the present invention, not
For limiting the present invention.As long as in addition, technical characteristic involved in each embodiment of invention described below that
Conflict can is not formed between this to be mutually combined.
In the inventive method, water storage phase two Phase flow is divided into faces two ranks of period and remaining phase long duration first
Section, reservoir history two Phase flow data for many years are analyzed, statistics obtains the current runoff of water storage phase day part and remaining phase long duration is put down
Transition probability matrix between equal runoff.Then reservoir level and reservoir inflow are separated into multiple areas in the range of actual capabilities
Between, combine for each of all water level sections of water storage phase day part and reservoir inflow section, obtained according to transition probability matrix
Obtain the following remaining various stochastic averaginas of phase long duration and enter flow valuve probability, optimization, which is calculated, makes present period and remaining phase long duration
The maximum decision-making flow value of generated energy desired value, combination establishment obtain runoff level control table (LCT), and the table can be used as the reservoir filling phase
The foundation of power generation dispatching.
Fig. 1 is central diameter stream grading control power generation dispatching method implementing procedure figure of the embodiment of the present invention, as seen from the figure, the present invention
Method specifically comprises the following steps：
Step 1：Water storage phase two Phase flow is divided into two stages of period and remaining phase long duration that face, analysis reservoir is more
Year history two Phase flow data, statistics obtain the transfer between the current runoff of water storage phase day part and the average runoff of remaining phase long duration
Probability matrix, matrix P are as follows：
In formula, pij(QIt is remaining=qj|Qt=qi) represent t period footpaths flow valuve QtFor qiAnd remaining phase long duration average diameter flow valuve
QIt is remainingFor qjProbability.The time for referring to have hydrology historical records for many years, the remaining phase long duration refer to from second when
Section arrives all periods in the water storage end of term, for example, it is assumed that the water storage phase is 10 days, 1 day period, facing the period refers to the 1st day, is left
9 days are the remaining phase.
Step 2：To water storage phase all scheduling slots, by reservoir level it is discrete in range of operation be multiple section [Hn,
Hn+1], n=1,2 ..., N；N represents n-th of discrete operating water level, and N represents discrete operating water level number.Flowed similarly for storage
Amount, is also separated into multiple section [Q in the range of actual capabilitiesm,Qm+1], m=1,2 ..., M；M represents m-th of discrete storage stream
Amount, M represent discrete reservoir inflow number.
Step 3：Median is taken to discrete water level section and the section that becomes a mandarin, for water storage phase day part water level value and storage
Each combination of footpath flow valuve, the randomness for the water that looks to the future, remaining phase length is obtained according to the transition probability matrix in step 1
Period various stochastic averaginas enter flow valuve probability, the initial last water level of fixed schedule, present period decision-making flow value are traveled through, excellent
Change is obtained under different water level sections and reservoir inflow rank, makes present period and remaining phase long duration generated energy desired value maximum
Each decision-making flow value.
Step 4：Using the method in step 3, optimization calculates water storage phase all period, all water level sections and reservoir inflows
Decision-making flow value under interval combinations, combination establishment obtain runoff level control table (LCT) and transported to control the power station water storage phase to generate electricity
OK.
Runoff level control table (LCT) is as shown in table 1, in table 1, [Hn,Hn+1] n-th of discrete operating water level section is represented, N is represented
Discrete operating water level number, [Qm,Qm+1] m-th of discrete reservoir inflow section is represented, M represents discrete reservoir inflow number, t tables
Show t-th of period, T represents total period number, QTt,n,mRepresent that t-th of period water level is in n-th of section, at reservoir inflow
Decision-making letdown flow value when m-th of section.
Table 1 is runoff level control table (LCT)
The inventive method is described as follows with a specific embodiment below：
Step 1：By taking certain power station as an example, the water storage phase is 10 days, and using day as the minimum period, flow is from 3900m3/ s is extremely
17400m3/ s discrete is 9 sections.Current is first period, and the remaining phase is 9 days, analyzes reservoir history two Phase flow data,
Counting the transition probability matrix obtained between water storage phase current runoff and average runoff of remaining phase is：
Step 2：Current level be 560 meters, scheduling the end of term water level be 580 meters, by reservoir level between 560 to 580 meters from
It is 0.1 meter to dissipate for 200 sections, discrete precision.Similarly for reservoir inflow, in 3900m3/ s to 17400m3Discrete between/s is 9
Individual section, discrete precision are 1500m3/s。
Step 3：To first water level section and flow rate zone, water level is in section [560,560.1] rice, current reservoir inflow
In section [3900,5400] m3/ s, remaining phase long duration mean inflow is obtained in section [3900,5400] m3/ s probability is
0.48, in section [5400,6900] m3/ s probability is 0.39, in section [6900,8400] m3/ s probability is 0.1, in section
[8400,9900]m3/ s probability is 0.03.In this way, median is taken to simplify meter to reservoir inflow section and water level section
Calculate, travel through present period decision-making flow value, optimization obtains making present period and remaining phase long duration generated energy desired value maximum
Decision-making flow value is 2000m3/s。
By that analogy, combined for each of water storage phase day part water level value and two Phase flow value, being all calculated makes
Each decision-making flow value of present period and remaining phase long duration generated energy desired value maximum.
Step 4：Using the method in step 3, optimization calculates water storage phase all period, all water level sections and reservoir inflows
Decision-making flow value under interval combinations, combination establishment obtain runoff level control table (LCT) and transported to control the power station water storage phase to generate electricity
OK.The runoff level control table (LCT) actually obtained is as shown in table 2.
Table 2 is runoff level control table (LCT) example
In above chart, some decision-making flow values have been dispensed.Embodiment above is designed solely for the purpose of illustration the present invention
The core idea of method, and specific runoff level control table (LCT) need not be provided comprehensively.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, all any modification, equivalent and improvement made within the spirit and principles of the invention etc., all should be included
Within protection scope of the present invention.
Claims (4)
1. reservoir filling phase runoff grading control power generation dispatching method under the conditions of a kind of random water, it is characterised in that including such as
Lower step：
Step 1：Water storage phase two Phase flow is divided into two stages of period and remaining phase long duration that face, analysis reservoir history enters
Storehouse footpath flow data, statistics obtain the transition probability square between the current runoff of water storage phase day part and the average runoff of remaining phase long duration
Battle array,
Step 2：To each period in the reservoir filling phase, the discretization period operating water level and reservoir inflow, it is each to obtain reservoir
Whole combinations of period discrete operating water level and reservoir inflow,
Step 3：Combined for each of water storage phase day part water level value and two Phase flow value, it is general using the transfer in step 1
Rate matrix obtains the remaining various stochastic averaginas of phase long duration and enters flow valuve probability, the initial last water level of fixed schedule, present period is determined
Plan flow value is traveled through, and optimization obtains the decision-making flow for making present period and remaining phase long duration generated energy desired value maximum
Value,
Step 4：Optimization calculates the decision-making flow under water storage phase all periods, all water level sections and reservoir inflow interval combinations
Value, combination establishment obtain runoff level control table (LCT), for controlling power station water storage phase generator operation.
2. method as claimed in claim 2, it is characterised in that the transition probability matrix that acquisition is counted in step 1 is：
In formula, pij(QIt is remaining=qj|Qt=qi) represent t period footpaths flow valuve QtFor qiAnd remaining phase long duration average diameter flow valuve QIt is remainingFor
qjProbability.
3. method as claimed in claim 2, it is characterised in that in step 2, to water storage phase all scheduling slots, by reservoir water
Position discrete in range of operation is multiple section [Hn,Hn+1], n=1,2 ..., N,
Wherein, n represents n-th of discrete operating water level, and N represents discrete operating water level number,
Similarly for reservoir inflow, multiple section [Q are also separated into the range of actual capabilitiesm,Qm+1], m=1,2 ..., M；M generations
M-th of discrete reservoir inflow of table, M represent discrete reservoir inflow number,
Step 3：Median is taken to discrete water level section and the section that becomes a mandarin, for water storage phase day part water level value and two Phase flow
Each combination of value, the randomness for the water that looks to the future,
The remaining various stochastic averaginas of phase long duration are obtained according to the transition probability matrix in step 1 and enter flow valuve probability, fixed schedule
Initial last water level, is traveled through to present period decision-making flow value, and optimization is obtained under different water level and reservoir inflow ranks, makes to work as
Preceding period and each decision-making flow value of remaining phase long duration generated energy desired value maximum,
Step 4：Using the method in step 3, optimization calculates water storage phase all period, all water level sections and reservoir inflow sections
Decision-making flow value under combination, combination establishment obtain runoff level control table (LCT), and the runoff level control table (LCT) is as follows：
Wherein, [Hn,Hn+1] n-th of discrete operating water level section is represented, N represents discrete operating water level number, [Qm,Qm+1] represent
M-th of discrete reservoir inflow section, M represent discrete reservoir inflow number, and t represents t-th of period, and T represents total period number,
QTt,n,mRepresent that t-th of period water level is in n-th of section, reservoir inflow is in decision-making letdown flow value during m-th of section.
4. the method as described in claim 1, it is characterised in that the remaining phase long duration referred to from second period to water storage
All periods in the end of term.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107894784A (en) * | 2017-11-13 | 2018-04-10 | 山信软件股份有限公司 | A kind of Dynamic water balance control method and device |
| CN108154268A (en) * | 2017-12-25 | 2018-06-12 | 国网福建省电力有限公司 | The method of quick estimation Small Hydropower Stations generated energy |
| CN113077167A (en) * | 2021-04-16 | 2021-07-06 | 中山大学 | Hydrological situation change analysis method for runoff in and out of warehouse |
| CN113468739A (en) * | 2021-06-28 | 2021-10-01 | 南昌大学 | Hydropower station medium-and-long-term power generation optimal scheduling method considering relaxation strategy |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105243505A (en) * | 2015-10-20 | 2016-01-13 | 华中科技大学 | Method for making combined power-generation dispatching output control table of cascade hydropower station |
-
2017
- 2017-06-26 CN CN201710493290.1A patent/CN107341570B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105243505A (en) * | 2015-10-20 | 2016-01-13 | 华中科技大学 | Method for making combined power-generation dispatching output control table of cascade hydropower station |
Non-Patent Citations (2)
| Title |
|---|
| OMID ALIZADEH-MOUSAVI等: "Stochastic Security Constrained Unit Commitment with variable-speed pumped-storage Hydropower Plants", 《2016 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC)》 * |
| 周瑜等: "基于最小水耗的梯级水电站联合发电模型研究", 《广西水利水电》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107894784A (en) * | 2017-11-13 | 2018-04-10 | 山信软件股份有限公司 | A kind of Dynamic water balance control method and device |
| CN107894784B (en) * | 2017-11-13 | 2021-03-09 | 山信软件股份有限公司 | Dynamic water balance control method and device |
| CN108154268A (en) * | 2017-12-25 | 2018-06-12 | 国网福建省电力有限公司 | The method of quick estimation Small Hydropower Stations generated energy |
| CN113077167A (en) * | 2021-04-16 | 2021-07-06 | 中山大学 | Hydrological situation change analysis method for runoff in and out of warehouse |
| CN113468739A (en) * | 2021-06-28 | 2021-10-01 | 南昌大学 | Hydropower station medium-and-long-term power generation optimal scheduling method considering relaxation strategy |
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