CN110533236A - A kind of power station refines peak regulation dispatching method in short term - Google Patents
A kind of power station refines peak regulation dispatching method in short term Download PDFInfo
- Publication number
- CN110533236A CN110533236A CN201910772757.5A CN201910772757A CN110533236A CN 110533236 A CN110533236 A CN 110533236A CN 201910772757 A CN201910772757 A CN 201910772757A CN 110533236 A CN110533236 A CN 110533236A
- Authority
- CN
- China
- Prior art keywords
- power station
- power
- period
- unit
- jth platform
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 71
- 230000033228 biological regulation Effects 0.000 title claims description 25
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 136
- 238000003860 storage Methods 0.000 claims abstract description 50
- 230000008569 process Effects 0.000 claims abstract description 29
- 238000010248 power generation Methods 0.000 claims abstract description 24
- 238000000926 separation method Methods 0.000 claims description 13
- 230000005611 electricity Effects 0.000 claims description 11
- 230000005540 biological transmission Effects 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 7
- 238000005086 pumping Methods 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 5
- 238000010606 normalization Methods 0.000 claims description 2
- 230000008859 change Effects 0.000 abstract description 5
- 230000007423 decrease Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012886 linear function Methods 0.000 description 2
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 1
- 240000002853 Nelumbo nucifera Species 0.000 description 1
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 1
- XCWPUUGSGHNIDZ-UHFFFAOYSA-N Oxypertine Chemical compound C1=2C=C(OC)C(OC)=CC=2NC(C)=C1CCN(CC1)CCN1C1=CC=CC=C1 XCWPUUGSGHNIDZ-UHFFFAOYSA-N 0.000 description 1
- 230000001154 acute effect Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000009194 climbing Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 230000005619 thermoelectricity Effects 0.000 description 1
- 238000010977 unit operation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- Mathematical Physics (AREA)
- Tourism & Hospitality (AREA)
- Mathematical Analysis (AREA)
- Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- Computational Mathematics (AREA)
- Marketing (AREA)
- Pure & Applied Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Operations Research (AREA)
- Mathematical Optimization (AREA)
- Software Systems (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Algebra (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Databases & Information Systems (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Control Of Water Turbines (AREA)
Abstract
The present invention relates to a kind of power stations to refine dispatching method in short term, belongs to hydrothermal generation scheduling technical field.This method has comprehensively considered reservoir operation constraint, the constraint of unit run-limiting, electric power and change of water level to the power generation of water-storage Hydropower Unit and the influence for characteristic of drawing water, it is intended to which the fining for improving scheduling is horizontal with the minimum target of power grid residue load peak-valley difference.It is constrained for Nonlinear Multiobjective function, the unit generation water power in scheduling model, the constraint of turbine power characteristic, water pump power characteristic constrains and the non-linear factors such as operating states of the units constraint, propose corresponding linearization process strategy, master mould is converted into standard mixed integer linear programming model, then model is solved.The present invention has given full play to pumped-storage power station Peak Load Adjustment in power grid, while the fining for improving dispatching of power netwoks is horizontal, ensure that the safe and stable operation in power station.
Description
Technical field
The invention belongs to hydrothermal generation scheduling technical fields, and in particular to a kind of power station refines peak regulation tune in short term
Degree method is that a kind of pumped-storage power station of consideration Unit Combination refines Optimization Scheduling in short term.
Background technique
In recent years, what China's provincial power network was different degrees of is faced with the peak regulation common problem that the situation is tense.With with wind
Electricity is the renewable energy large-scale grid connection of representative, and randomness, intermittence and anti-tune peak character will lead to the net load of power grid
Fluctuation is more violent, and the peak regulation pressure of power grid has been further aggravated.Huge peak regulation pressure is to power grid security, stabilization, economic fortune
Row brings great challenge, also constrains the further consumption of renewable energy.Water-storage Hydropower Unit start and stop are rapid, load
Tracking ability is strong, exactly because these advantages, pumped-storage power station has very important effect in dispatching of power netwoks, can be fast
The peak regulation requirement of fast responsive electricity grid.
The present invention pays close attention to the On Peak Modulation Modes Of Short-term Scheduling of pumped-storage power station in regional power grid, in control daily electricity
In the case where, to stabilize the load fluctuation of power grid as far as possible, meet the peak regulation demand of each provincial power network.High scheduling controlling
It is required that and the constraint of complicated waterpower, electric power brought greatly so that the operation plan in power station makes to dispatching of power netwoks personnel
Challenge.It at present both at home and abroad about the research of this respect, but is mainly minimum scheduling unit with power station, it is contemplated that with for the moment
Different units are likely to be at different operating statuses in the power station Duan Tongyi, and it is inadequate for participating in calculating with a fixed power coefficient
Accurately, the influence for different productive heads to the operational efficiency of unit considers insufficient, so that the generation schedule worked out
It can and plan a degree of deviation occur when being handed down to power station and executing, also limit pumped-storage power station peak regulation potentiality
It gives full play to.Therefore, one kind is established it can be considered that Unit Combination mode, the short-term optimal operation of hydropower method more refined
Seem particularly necessary.
Summary of the invention
It is an object of the present invention to solve the deficiency of the existing technology and provide a kind of more finings for considering Unit Combination
The short-term peak regulation Optimization Scheduling in power station, emphasis be by the non-linear factor in scheduling problem before meeting required precision
Carry out linearization process is put, so that former mixed integer nonlinear programming problem is just converted to the mixed integer linear programming of standard
Then problem is solved；The fining that this method is able to ascend dispatching of power netwoks is horizontal, ensure that the safety and stability fortune in power station
Row.
To achieve the above object, The technical solution adopted by the invention is as follows:
A kind of power station refines peak regulation dispatching method in short term, which comprises the steps of:
Step (1), is arranged condition, including each power station or more library initial water level and the lower library scheduling end of term controls water level, unit
Power limit, unit generation flow restriction and the load curve for saving net out；
Step (2), using the minimum target of network load peak-valley difference Fk, then objective function is expressed as follows:
In formula: k is power grid number；T, t is respectively dispatching cycle and scheduling slot, h；CK, t、C′K, tRespectively indicate power grid k
In the system loading and remaining load of t period, MW；M is power station sum；For the power transmission between power station i and power grid k,
MW；
Two auxiliary variables are introduced later, and two auxiliary variables are the maximum residual load of power grid kWith power grid k
Least residue loadC′k , and meet
It converts objective function toObjective function after conversion includes that the peak regulation of K power grid optimizes mesh
Mark introduces the method for weighting and is converted into single-objective problem, while returning in target conversion process to each power grid residue load
One change processing, then the final goal function after converting are as follows:
Wherein, K is provincial power network sum；wkFor the weight coefficient of power grid k；F′kIt is the load peak after power grid k normalization
Paddy is poor,For the maximum original loads of power grid k；
Step (3), power generationNet water headConstraint such as following formula:
In formula: HI, j, tFor power stationiPower generation net water head of the jth platform unit in the t period, m；Respectively power stationi
In the Shang Ku and lower reservoir level of t period Mo, m；Respectively power stationiIn tAt the beginning of periodShang Ku and lower reservoir level, m；
hlI, j, tFor power stationiJth platform unit the t period productive head lose, m；Respectively power stationiIn t period Mo
Shang Ku and lower Kuku hold, m3；Respectively power stationiShang Ku and the water level in lower library-storage capacity relation function；
Water level-storage capacity relation function of Shang Ku and lower library are carried out at linearisation respectively using piecewise linear interpolation method later
Reason；
Step (4), operating states of the units constraint such as following formula:
In formula:For power stationiGenerating state variable of the jth platform unit in the t period, if unit j is in generating stateOtherwiseFor power stationiDraw water state variable of the jth platform unit in the t period, draw water if unit j is in
State is thenOtherwise Ji For power stationiThe total number of units of unit；
Later, 0-1 integer variable pair is introducedCarry out linearization process；
Step (5), turbine power characteristic constraint such as following formula:
In formula:For power stationiJth platform unit the t period generated output；HI, j, tFor power stationiJth platform unit in t
The power generation net water head of period；For stationiJth platform unit the t period generating flow；For power stationiJth platform machine
Binary crelation function between the generated output and generating flow, productive head of group；
Turbine power characteristic is constrained later and carries out linearization process；
Step (6), water pump power characteristic constraint such as following formula:
In formula:For power stationiJth platform unit flow and head relation function；
Water pump power characteristic is constrained using piecewise linear interpolation method and carries out linearization process；
Step (7), according to step (1) be arranged condition, and by step (2)-(6) linearisation after objective function and constraint
It is built into the mixed-integer programming model of standard together with remaining linear restriction, is then solved, day part reservoir water is obtained
Position, set state and unit output；Finally power station is scheduled according to the content that solution obtains；
Remaining described linear restriction include the constraint of upper and lower library water balance, storage capacity constraint,Reservoir is just lastWater level limitation, machine
Group units limits, unit traffic constraints and the constraint of the unit duration of operation.
It is further preferred that carrying out the step of linearization process to the water level-storage capacity relation function in upper library in step (3)
It is rapid as follows:
1. upper Kuku is held sectionIt is divided into N number of subinterval, each separation is defined as:
In formula:Respectively power stationiUpper Kuku hold maximum and minimum value；For power stationiUpper library
Storage capacityTheThe separation in n subinterval and (n+1)th subinterval；ForCorresponding upper reservoir level；For power stationi
The water level in upper library-storage capacity relation function；
2. introducing 0-1 integer variable rI, t, n, and meet constraintWherein rI, t, nBecome for instruction
Amount, works as power stationiWhen the upper Kuku of t period holds and is located at n-th of subinterval, rI, t, n=1；For auxiliary variable, without actual
Physical significance；
3. 2. uniquely determining the Kuku on the t period by step holds be located at storage capacity subinterval, the Shang Kushui of t period Mo
Position is expressed as follows:
In formula:Respectively storage capacity separationWithCorresponding water level, m；For power stationiIn the t period
The upper reservoir level at end, m；
Identical water level-storage capacity relationship the letter with to upper library of linearization process is carried out to the water level-storage capacity relation function in lower library
It is identical that number carries out Linearization Method.
It is further preferred that introducing 0-1 integer variable pair in step (4)Carry out linearization process
Method particularly includes:
Introduce 0-1 integer variableWithAnd meetOperating states of the units is constrainedBe converted to linear restriction combination:
For power stationiJth platform unit the t period generating state variable；For power stationiJth platform unit in t
The state variable of drawing water of period；JiFor power stationiThe total number of units of unit；WithIt is 0-1 integer variable, is auxiliary variable,
Without actual physics meaning.
It is further preferred that constraining turbine power characteristic the specific side for carrying out linearization process in step (5)
Method are as follows:
In unit maximum, minimum productive head section, three dynamic characteristic curves, respectively highest head are selected
Average water headAnd the lowest water headEvery dynamic characteristic curves are divided into 2 sections, entire turbine power characteristic curve
9 triangle subareas are divided into, turbine power characteristic constraint representation is as follows:
In formula: l is the index of triangle subarea, l=1,2 ..., 9；U is the rope on each vertex of triangle subarea
Draw, u=1,2,3；Respectively indicate power stationiJth platform unit dynamic characteristic curves in lIt is aTriangle
The u of shapeIt is aHead corresponding to vertex, generating flow and generated output；zI, j, t, lFor indicator variable, zI, j, t, lWhen=1 expression t
Section power stationiThe combination of the generated output of jth platform unit, head and generating flow be located in lIt is aIn triangle subarea；
It indicates in the period power station tiJth platform unit dynamic characteristic curves in triangle l uIt is aWeight shared by vertex；
Hi, j, tFor power stationiPower generation net water head of the jth platform unit in the t period, m.
It is further preferred that being constrained using piecewise linear interpolation method water pump power characteristic in step (6) and carrying out line
Propertyization processing method particularly includes:
1. by head section [HI, j, min, HI, j, max] it is divided into M subinterval, each separation is defined as:
In formula: HI, j, max、HI, j, minThe maximum and minimum value of the head of the jth platform unit of respectively power station i；HI, j, 1For
The jth platform unit of power station iHeadThe separation in m subinterval and the m+1 subinterval；For HI, j, mCorresponding
Unit draws water flow；
2. introducing 0-1 integer variable vI, j, t, m, and meet constraintWherein
vI, j, t, mFor indicator variable, work as power stationiUnit j when the head of t period is located at m-th of subinterval, vI, j, t, m=1；HI, j, t, m
To assist decision variable, no actual physics meaning；
3. 2. can be uniquely determined by step in the subinterval that t period unit head is located at, the flow that draws water of t period
It is expressed as follows:
It is further preferred that remaining described linear restriction specifically includes following constraint in step (7):
(1) library water balance constrains up and down
In formula:Respectively power stationiHold in the Shang Ku of t period Mo and lower Kuku, m3；Respectively
Power stationiIn the Shang Ku and lower Kuku appearance at the beginning of the t period, m3；ΔtFor period step-length, h；QI, tFor power stationiThe total storage outflow in upper library,
m3/ s, QI, tIndicate that power station is drawn water from lower library to upper library when < 0；
In formula:Respectively power stationiPower generation and draw water flow of the jth platform unit in the t period, m3/s；J iFor electricity
It standsiThe total number of units of unit；
(2) storage capacity constrains
In formula:Respectively power stationiHold upper and lower limit, m in the upper Kuku of t period Mo3； Respectively
Hold upper and lower limit, m in the lower Kuku of t period Mo for power station i3；
(3)Reservoir is just lastWater level limitation
In formula:Respectively power stationiShang Ku and lower library starting storage capacity, by the operation plan of the previous day
It determines, m3；For power stationiIn the control storage capacity in the scheduling end of term, set by dispatcher, m3；
(4) unit output constrains
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generated output, MW；For electricity
It standsiThe maximum of jth platform unit draw water power, MW；For power stationiGenerating state variable of the jth platform unit in the t period, if
Unit j is in generating state thenOtherwiseFor power stationiJth platform unit the t period operating status become
Amount, if unit j is in state of drawing waterOtherwiseRespectively power stationiJth platform unit t when
The generated output of section and the power that draws water, MW；
(5) unit traffic constraints
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generating flow, m3/s；Maximum, the minimum of the jth platform unit of respectively power station i are drawn water flow, m3/s；Respectively unit j
Power generation in the t period and the flow that draws water, m3/s；
(6) the unit duration of operation constrains
In formula: αI, j、βI, jRespectively power stationiMinimum of jth platform unit when serving as the hydraulic turbine open, downtime duration,
h；xI, j, t、The respectively period power station tiJth platform unit opening when serving as the hydraulic turbine, shutdown operation variable, xI, j, t=1 table
Show in the period power station tiJth platform unit begin to act as hydraulic turbine power generation, otherwise xI, j, t=0,It indicates in the period power station tiJth platform unit start stop power generation, otherwiseψI, j、φI, jRespectively power stationiJth platform unit when serving as water pump
Minimum opens, downtime duration, h；yI, j, t、The respectively period power station tiJth platform unit opening, stopping when serving as the hydraulic turbine
Machine performance variable, yI, j, t=1 indicates in the period power station tiJth platform unit begin to act as pumping for water pump, otherwise yI, j, t=0,It indicates in the period power station tiJth platform unit start to stop pumping, otherwise
(7) each power grid by electricity and send Constraint
In formula: RI, kFor power stationiPower energy allocation to power grid k ratio；Respectively power stationiJth platform machine
The generated output of the t period of group and the power that draws water, MW；Indicate t period power stationiTo the transmission power of power grid k, MW；
Indicate t period power stationiThe power consumed from power grid k, MW.
Compared with prior art, the present invention has the advantages that:
The dispatching method of the currently used pumped-storage power station by equal proportion distribution day part electric power is difficult to simultaneouslySignificant responseThe load variations demand of each province's net differentiation, limits giving full play to for the Peak Load Adjustment in power station.The present invention mentions
Out it is a kind of with unit be basic scheduling unit pumped-storage power station Short-term Optimal Operation method, this method comprehensively considered water
Library runs the influence of constraint, the constraint of unit run-limiting, electric power and change of water level to unit operation characteristic, has given full play to and has drawn water
Storage station Peak Load Adjustment, after peak regulation, the load process of each power grid is more steady, and load peak-valley difference is different degrees of
It decreases, while the method for the present invention improves the fining level of dispatching of power netwoks, ensure that the safe and stable operation in power station.
Detailed description of the invention
Fig. 1 is turbine power characteristic curve linearisation schematic diagram；
Fig. 2 is water pump power characteristic curve；
Fig. 3 is the balancing the load result of each power grid；
Fig. 4 is each output of power station and transmission process；
Fig. 5 is the upper and lower reservoir level process in each power station.
Specific embodiment
Below with reference to embodiment, the present invention is described in further detail.
It will be understood to those of skill in the art that the following example is merely to illustrate the present invention, and it should not be regarded as limiting this hair
Bright range.In the examples where no specific technique or condition is specified, described technology or conditions according to the literature in the art
Or it is carried out according to product description.Production firm person is not specified in material therefor or equipment etc., is that can be obtained by purchase
Conventional products.
The main task in power station first is that peak regulation, by the adjusting to provincial power network load, to reduce thermoelectricity in system
Unit goes out fluctuation and startup-shutdown number, realizes electricity net safety stable economical operation.More common peak regulation target is at present
Maximum Entropy coherency function value minimum and power grid residue load mean square deviation are minimum, but are both difficult to linearize, so the present invention adopts
With network load peak-valley differenceFk Minimum target, is expressed as follows:
In formula: k is power grid number；T, t is respectively dispatching cycle and scheduling slot, h；CK, t、C′K, tRespectively indicate power grid k
In the system loading and remaining load of t period, MW；M is power station sum；M is the number in power station；For power station i and power grid k it
Between power transmission, MW indicates with following formula:
In formula:Indicate power stationiTo the transmission power of power grid k, MW；Indicate power stationiThe power consumed from power grid k,
MW。
Solving power station head relation problem needs the constraint condition met to be expressed as follows:
(1) library water balance constrains up and down
In the present invention, the water balance constraint in upper and lower library may be expressed as:
In formula:Respectively power stationiHold in the Shang Ku of t period Mo and lower Kuku, m3；Respectively
Power stationiIn the Shang Ku and lower Kuku appearance at the beginning of the t period, m3；ΔtFor period step-length, h；QI, tFor power stationiThe total storage outflow in upper library,
m3/ s, QI, tIndicate that power station is drawn water from lower library to upper library when < 0.
In formula:Respectively power generation and draw water flow of the j unit in the t period, m3/s；Ji For power stationiUnit
Total number of units.
(2) storage capacity constrains
In formula:Respectively power stationiHold upper and lower limit, m in the upper Kuku of t period Mo3； Respectively
For power stationiHold upper and lower limit, m in the lower Kuku of t period Mo3。
(3)Reservoir is just lastWater level limitation
In formula:Respectively power stationiShang Ku and lower library starting storage capacity, by the operation plan of the previous day
It determines, m3；For power stationiIn the control storage capacity in the scheduling end of term, set by dispatcher, m3。
(4) unit output constrains
In generating state, power output can arbitrarily be adjusted unit in feasible traffic coverage, not consider climbing/landslide speed generally
Degree limitation.And when drawing water state, power cannot be adjusted arbitrarily, and it is attached generally to only run in maximum (specified) power points that draws water
Closely.
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generated output, MW；For
Power stationiThe maximum (specified) of jth platform unit draw water power, MW；For power stationiJth platform unit the t period power generation shape
State variable, if unit j is in generating stateOtherwise For power stationiJth platform unit the t period pumping
Watery state variable, if unit j is in state of drawing waterOtherwiseRespectively power stationiJth platform
The generated output of the t period of unit and the power that draws water, MW.
(5) unit generation/traffic constraints of drawing water
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generating flow, m3/s；Respectively power stationiMaximum, the minimum of jth platform unit draw water flow, m3/s；Respectively unit j
Power generation in the t period and the flow that draws water, m3/s；
(6) it generates electricityNet water headConstraint
In formula: HI, j, tFor power stationiPower generation net water head of the jth platform unit in the t period, m；Respectively power stationi
In the Shang Ku and lower reservoir level of t period Mo, m；Respectively power stationiIn tAt the beginning of periodShang Ku and lower reservoir level, m；
hL, i, j, tFor power stationiJth platform unit the t period productive head lose, m；Respectively power stationiIn t period Mo
Shang Ku and lower Kuku hold, m3；Respectively power stationiShang Ku and the water level in lower library-storage capacity relation function；
(7) turbine power characteristic constrains
In formula:For power stationiJth platform unit the t period generated output；HI, j, tFor power stationiJth platform unit exist
The power generation net water head of t period；For stationiJth platform unit the t period generating flow；For power stationiJth platform
Binary crelation function between the generated output and generating flow, productive head of unit；
For participating in the power station of peak load regulation network, library and lower water level fluctuation of reservoir are violent thereon, and then will lead to its head
The acute variation in schedule periods, therefore influence of the head for unit output generally be can not ignore.
(8) water pump power characteristic constrains
The unit power that draws water is also binary function about draw water flow and head, but as described in constraint (4), unit exists
When state of drawing water, the water pump power characteristic with rated power operation, therefore unit is actually drawing water under power fixation of drawing water
Relationship between flow and head, is expressed as follows:
In formula:For power stationiJth platform unit flow and head relation function.
(9) operating states of the units constrains
Same unit is in officeTwoPeriod can be only in a kind of working condition；In order to guarantee power station operation stability, for
The different units in same power station,When extremelyWhen a rare unit is in generating state, remaining all unit cannot draw water；It is on the contrary
.It is expressed as follows:
In formula:For power stationiGenerating state variable of the jth platform unit in the t period, if unit j is in generating stateOtherwiseFor power stationiDraw water state variable of the jth platform unit in the t period, draw water if unit j is in
State is thenOtherwise Ji For power stationiThe total number of units of unit；
(10) the unit duration of operation constrains
In formula: αI, j、βI, jRespectively power stationiMinimum of jth platform unit when serving as the hydraulic turbine open, downtime duration,
h；xI, j, t、The respectively period power station tiJth platform unit opening when serving as the hydraulic turbine, shutdown operation variable, xI, j, t=1 table
Show in the period power station tiJth platform unit begin to act as hydraulic turbine power generation, otherwise xI, j, t=0,It indicates in the period power station tiJth platform unit start stop power generation, otherwiseψI, j、φI, jRespectively power stationiJth platform unit when serving as water pump
Minimum open, downtime duration, h；yI, j, t、The respectively period power station tiJth platform unit opening when serving as the hydraulic turbine,
Shutdown operation variable, yI, j, t=1 indicates in the period power station tiJth platform unit begin to act as pumping for water pump, otherwise yI, j, t=0,It indicates in the period power station tiJth platform unit start to stop pumping, otherwise
(11) power grid is by (sending) Constraint
In formula: RI, kFor power stationiPower energy allocation to power grid k ratio；Respectively power stationiJth platform machine
The generated output of the t period of group and the power that draws water, MW；Indicate t period power stationiTo the transmission power of power grid k, MW；Table
Show the period power station tiThe power consumed from power grid k, MW.
There are 5 non-linear factors (objective function and constraint (6), (7), (8), (9)) in above-mentioned model, therefore, this hair
It is bright to carry out linearization process to above-mentioned non-linear factor, so that former mixed-integer nonlinear programming model is converted to and meets precision
Required standard mixed integer linear programming model, then using mature, efficient business solver to MIXED INTEGER linear gauge
Model is drawn to be solved.Specific implementation steps are as follows:
(1) design conditions, including each power station or more library initial water level are set and lower library scheduling end of term control water level, unit go out
Power limit, unit generation flow restriction, the load curve for saving net；
(2) target function typeIt is to contain the function of a maximum minimal form,
It is nonlinear, it is difficult to directly be solved by business optimization software.Therefore, invention introducesWithC′k Two auxiliary
Variable, and meetSo objective function can be converted intoLinearisation shape
Formula.
Target function type after conversion contains KIt is aThe peak regulation optimization aim of power grid is a typical multiple-objection optimization
Problem, the present invention are converted into single-objective problem using the multiple target method of weighting, while to avoid each network load magnitude difference
The caused adverse effect to solving result has carried out normalized to each power grid residue load in target conversion process,
Objective function after conversion is expressed as follows:
In formula: wkFor kthIt is aThe weight coefficient of target, the present invention use equal weight, i.e. wk=1/K；F′kIt is power grid k normalizing
Load peak-valley difference after change, MW；For the maximum original loads of power grid k, MW.
(3) unit head is the linear function of Shang Ku and lower reservoir level, and water level-storage capacity relation function is usually non-linear
Function, it is therefore desirable to linearization process be carried out to water level-storage-capacity curve of formula Shang Ku and lower library respectively.The water in the above library below
The step of position-storage capacity relationship linearly turns to example, describes its linearisation.
1. upper Kuku is held sectionIt is divided into N number of subinterval, each separation is defined as
In formula:The maximum and minimum value that the upper Kuku of respectively power station i holds；For the upper library of power station i
The separation in storage capacity n-th of subinterval and (n+1)th subinterval；ForCorresponding upper reservoir level；For on the i of power station
The water level in library-storage capacity relation function；
2. introducing 0-1 integer variable rI, t, n, and meet constraintWherein rI, t, nBecome for instruction
Amount, works as power stationiWhen the upper Kuku of t period holds and is located at n-th of subinterval, rI, t, n=1；For auxiliary variable, without actual
Physical significance；
3. 2. by stepIt can be uniqueDetermine that Kuku holds be located at storage capacity subinterval, the upper library of t period Mo on the t period
Water level can be expressed as follows:
In formula:Respectively storage capacity separationWithCorresponding water level, m；It is power station i in the t period
The upper reservoir level at end, m；
(4) 0-1 integer variable is introducedWithAnd meetOperating states of the units is constrainedBe converted to following constraint combination:
In formula:WithIt is aid decision variable, andFor power stationiJth platform unit
In the generating state variable of t period；For power station i jth platform unit the t period state variable of drawing water；Ji For power stationi's
The total number of units of unit.
WhenWhen, i.e., when unit j the t period be in draw water state when, due toIt is necessary for 0, that
ForIt is similar, whenWhen,Wherein j=1,2 ..., Ji.Therefore, above-mentioned constraint
Combination can ensure that be not in operating condition that existing unit draws water and has unit generation in same power station.
(5) turbine power characteristic curve is power output-generating flow set of curves under multiple groups difference productive head, is characterized
Unit output, generating flow, the non-linear relation between productive head three.Previous linearization technique will lead to unit generation
Head it is discontinuous, influence to calculate the efficiency solved, and be represented in entire head subinterval with a certain dynamic characteristic curves
The corresponding dynamic characteristic curves of all heads can also reduce the accuracy of model, therefore, the invention proposes a kind of new water
Turbine dynamic characteristic curves linearization technique is to improve the accuracy of scheduling decision.
As shown in Figure 1, three dynamic characteristic curves are selected in possible maximum, the minimum productive head section of unit, point
Highest head is not corresponded toAverage water headAnd the lowest water headMaximum output and maximum generation flow are considered simultaneously
(dotted line indicates in Fig. 1), every dynamic characteristic curves are divided into 2 sections, in this way, entire turbine power characteristic curve is divided
For 9 triangle subareas.The dynamic characteristics of the hydraulic turbine can be expressed as follows: in possible maximum, the minimum electrical generation water Head Section of unit
In, three dynamic characteristic curves are selected, highest head is respectively correspondedAverage water headAnd the lowest water headTogether
When consider that maximum output and maximum generation flow, every dynamic characteristic curves are divided into 2 sections, in this way, entire turbine power
Characteristic curve is divided into 9 triangle subareas, and the dynamic characteristics of the hydraulic turbine can be expressed as follows:
In formula: l is the index of triangle subarea, l=1,2 ..., 9；U is the rope on each vertex of triangle subarea
Draw, u=1,2,3；Respectively indicate power stationiJth platform unit dynamic characteristic curves in lIt is aTriangle
The u of shapeIt is aHead corresponding to vertex, generating flow and generated output；zI, j, t, lFor indicator variable, zI, j, t, lWhen=1 expression t
Section power stationiThe combination of the generated output of jth platform unit, head and generating flow be located in lIt is aIn triangle subarea；It indicates in the period power station tiJth platform unit dynamic characteristic curves in triangle l uIt is aPower shared by vertex
Weight；HI, j, tFor power generation net water head of the jth platform unit in the t period of power station i, m.
(6) as shown in Fig. 2, what the dynamic characteristic curves of water pump actually indicated is that the one-dimensional nonlinear of flow and head is closed
System carries out linear process to water pump power characteristic curve using subsection linearity inser value method described in step (3) is similar to.
(7) by after step (1)-(6) described linearisation objective function and constraint with remaining linear restriction integrate, constructed
At the mixed-integer programming model of standard, then using business optimization software packet LINGO and the branch-and-bound built in it is called to calculate
Method is solved, output day part reservoir level, set state, unit output etc..
East China Power Grid is one of big regional power grid in China six, has Shanghai, Zhejiang, Jiangsu, Anhui, 5, Fujian province (city) under its command
Grade power grid.Now apply the inventive method to day famine level ground, Tongbai, the Mt. Langya, Xiangshui County of East China Power GridRavine4 large-scale pumped storage powers
The short term scheduling planning in power station, to verify the validity of the proposed method of the present invention.Fig. 3 gives summer typical day each electricity
The balancing the load of net is as a result, can intuitively find out, after each power station peak regulation, the load process of each power grid is more steady, bear
Lotus peak-valley difference is different degrees of to decrease.Anhui, Shanghai, Zhejiang and Jiangsu Power Grid load peak-valley difference respectively by 10930,
6363,13632 and 12868MW is reduced to 6168,4572,10341 and 11895MW, the range of decrease respectively reached 28.1%,
43.6%, 24.1% and 7.6%.Fig. 4 is the power output process in each power station and the transmission process to each power grid, and Fig. 5 is each water power
It stands the water level process in upper and lower library, is all satisfied each item constraint, ensure that the safe and stable operation in power station.
The basic principles, main features and advantages of the present invention have been shown and described above.The technology of the industry
Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the above embodiments and description only describe this
The principle of invention, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes
Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its
Equivalent thereof.
Claims (6)
1. a kind of power station refines peak regulation dispatching method in short term, which comprises the steps of:
Step (1), is arranged condition, including each power station or more library initial water level and the lower library scheduling end of term controls water level, unit output
Limitation, unit generation flow restriction and the load curve for saving net；
Step (2), using network load peak-valley differenceFk Minimum target, then objective function is expressed as follows:
In formula: k is power grid number；T, t is respectively dispatching cycle and scheduling slot, h；CK, t、C′K, tPower grid k is respectively indicated in t
The system loading of section and remaining load, MW；M is power station sum；For power stationiPower transmission between power grid k, MW；
Two auxiliary variables are introduced later, and two auxiliary variables are the maximum residual load of power grid kMost with power grid k
Small residue loadC′k , and meet
It converts objective function toObjective function after conversion includes KIt is aThe peak regulation optimization aim of power grid, draws
Enter the method for weighting and be converted into single-objective problem, while place is normalized to each power grid residue load in target conversion process
Reason, then the final goal function after converting are as follows:
Wherein, K is provincial power network sum；wkFor the weight coefficient of power grid k；F′kIt is the load peak-valley difference after power grid k normalization,For the maximum original loads of power grid k；
Step (3), power generationNet water headConstraint such as following formula:
In formula: HI, j, tFor power stationiPower generation net water head of the jth platform unit in the t period, m；Respectively power stationiIn t
The Shang Ku and lower reservoir level at section end, m；Respectively power stationiIn tAt the beginning of periodShang Ku and lower reservoir level, m；hlI, j, t
For power station i jth platform unit the t period productive head lose, m；Respectively power stationiIn the upper library of t period Mo
Hold with lower Kuku, m3；Respectively power stationiShang Ku and the water level in lower library-storage capacity relation function；
Linearization process is carried out to water level-storage capacity relation function of Shang Ku and lower library respectively using piecewise linear interpolation method later；
Step (4), operating states of the units constraint such as following formula:
In formula:For power stationiGenerating state variable of the jth platform unit in the t period, if unit j is in generating stateOtherwise For power stationiDraw water state variable of the jth platform unit in the t period, if unit j is in the shape that draws water
State is thenOtherwise Ji For power stationiThe total number of units of unit；
Later, 0-1 integer variable pair is introducedCarry out linearization process；
Step (5), turbine power characteristic constraint such as following formula:
In formula:For power stationiJth platform unit the t period generated output；HI, j, tFor power stationiJth platform unit in the t period
Power generation net water head；For stationiJth platform unit the t period generating flow；For the jth platform unit of power station i
Binary crelation function between generated output and generating flow, productive head；
Turbine power characteristic is constrained later and carries out linearization process；
Step (6), water pump power characteristic constraint such as following formula:
In formula:For power stationiJth platform unit flow and head relation function；
Water pump power characteristic is constrained using piecewise linear interpolation method and carries out linearization process；
Step (7), according to step (1) be arranged condition, and by step (2)-(6) linearisation after objective function and constrain and its
Remaining linear restriction is built into the mixed-integer programming model of standard together, is then solved, and day part reservoir level, machine are obtained
Group state and unit output；Finally power station is scheduled according to the content that solution obtains；
Remaining described linear restriction include the constraint of upper and lower library water balance, storage capacity constraint,Reservoir is just lastWater level limitation, unit go out
Force constraint, unit traffic constraints and the constraint of the unit duration of operation.
2. power station according to claim 1 refines peak regulation dispatching method in short term, which is characterized in that right in step (3)
It is as follows that the water level in upper library-storage capacity relation function carries out the step of linearization process:
1. upper Kuku is held sectionIt is divided into N number of subinterval, each separation is defined as:
In formula:Respectively power stationiUpper Kuku hold maximum and minimum value；For power stationiUpper libraryStorage capacity TheThe separation in n subinterval and (n+1)th subinterval；ForCorresponding upper reservoir level；For power stationiUpper library
Water level-storage capacity relation function；
2. introducing 0-1 integer variable rI, t, n, and meet constraintWherein rI, t, nFor indicator variable, when
Power stationiWhen the upper Kuku of t period holds and is located at n-th of subinterval, rI, t, n=1；For auxiliary variable, no actual physics meaning
Justice；
3. 2. uniquely determining the Kuku on the t period by step holds be located at storage capacity subinterval, the upper reservoir level table of t period Mo
Show as follows:
In formula:Respectively storage capacity separationWithCorresponding water level, m；For power stationiIt is upper in t period Mo
Reservoir level, m；
To the water level in lower library-storage capacity relation function carry out the identical water level-storage capacity relation function with to upper library of linearization process into
Row Linearization Method is identical.
3. power station according to claim 1 refines peak regulation dispatching method in short term, which is characterized in that in step (4), draw
Enter 0-1 integer variable pairCarry out linearization process method particularly includes:
Introduce 0-1 integer variableWithAnd meetOperating states of the units is constrainedTurn
It is changed to linear restriction combination:
For power stationiJth platform unit the t period generating state variable；For power stationiJth platform unit in the t period
It draws water state variable；Ji For power stationiThe total number of units of unit；WithIt is 0-1 integer variable, is auxiliary variable, no reality
Physical meaning.
4. power station according to claim 1 refines peak regulation dispatching method in short term, which is characterized in that right in step (5)
The constraint of turbine power characteristic carries out linearization process method particularly includes:
In unit maximum, minimum productive head section, three dynamic characteristic curves, respectively highest head are selectedIt is average
HeadAnd the lowest water headEvery dynamic characteristic curves are divided into 2 sections, and entire turbine power characteristic curve is drawn
It is divided into 9 triangle subareas, turbine power characteristic constraint representation is as follows:
In formula: l is the index of triangle subarea, l=1,2 ..., 9；U is the index on each vertex of triangle subarea, u
=1,2,3；Respectively indicate the l in the dynamic characteristic curves of the jth platform unit of power station iIt is aTriangle
UIt is aHead corresponding to vertex, generating flow and generated output；zI, j, t, lFor indicator variable, zI, j, t, l=1 indicates t period electricity
It standsiThe combination of the generated output of jth platform unit, head and generating flow be located in lIt is aIn triangle subarea；It indicates
In the period power station tiJth platform unit dynamic characteristic curves in triangle l uIt is aWeight shared by vertex；HI, j, tFor
Power generation net water head of the jth platform unit of power station i in the t period, m.
5. power station according to claim 1 refines peak regulation dispatching method in short term, which is characterized in that in step (6), adopt
Linearization process is carried out to the constraint of water pump power characteristic with piecewise linear interpolation method method particularly includes:
1. by head section [HI, j, min, HI, j, max] it is divided into M subinterval, each separation is defined as:
In formula: HI, j, max、HI, j, minThe maximum and minimum value of the head of the jth platform unit of respectively power station i；HI, j, 1For water power
It standsiJth platform unitHeadThe separation in m subinterval and the m+1 subinterval；For HI, j, mCorresponding unit
Draw water flow；
2. introducing 0-1 integer variable vI, j, t, m, and meet constraintWherein vI, j, t, mTo refer to
Show variable, when the unit j of power station i is when the head of t period is located at m-th of subinterval, vI, j, t, m=1；HI, j, t, mFor aid decision
Variable, no actual physics meaning；
3. 2. can be uniquely determined by step in the subinterval that t period unit head is located at, the flow expression of drawing water of t period
It is as follows:
6. power station according to claim 1 refines peak regulation dispatching method in short term, which is characterized in that in step (7), institute
Remaining linear restriction stated specifically includes following constraint:
(1) library water balance constrains up and down
In formula:Respectively power stationiHold in the Shang Ku of t period Mo and lower Kuku, m3；Respectively power stationi
In tAt the beginning of periodShang Ku and lower Kuku hold, m3；ΔtFor period step-length, h；QI, tFor power stationiThe total storage outflow in upper library, m3/ s,
QI, tIndicate that power station is drawn water from lower library to upper library when < 0；
In formula:Respectively power stationiPower generation and draw water flow of the jth platform unit in the t period, m3/s；Ji For power stationi's
The total number of units of unit；
(2) storage capacity constrains
In formula:Respectively power stationiHold upper and lower limit, m in the upper Kuku of t period Mo3； It is respectively electric
I stand in the lower Kuku of t period Mo appearance upper and lower limit, m3；
(3) reservoir just last water level limitation
In formula:Respectively power stationiShang Ku and lower library starting storage capacity, determined by the operation plan of the previous day,
m3；For power stationiIn the control storage capacity in the scheduling end of term, set by dispatcher, m3；
(4) unit output constrains
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generated output, MW；For power stationi
The maximum of jth platform unit draw water power, MW；For power stationiGenerating state variable of the jth platform unit in the t period, if machine
Group j is in generating state thenOtherwise For operating status variable of the jth platform unit in the t period of power station i,
If unit j is in state of drawing waterOtherwise Respectively power stationiJth platform unit the t period
Generated output and the power that draws water, MW；
(5) unit traffic constraints
In formula:Respectively power stationiThe maximum of jth platform unit, minimum generating flow, m3/s；
Respectively power stationiMaximum, the minimum of jth platform unit draw water flow, m3/s；Respectively hair of the unit j in the t period
Electricity and the flow that draws water, m3/s；
(6) the unit duration of operation constrains
In formula: αI, j、βI, jRespectively power stationiMinimum of jth platform unit when serving as the hydraulic turbine open, downtime duration, h；
xI, j, t、The respectively period power station tiJth platform unit opening when serving as the hydraulic turbine, shutdown operation variable, xI, j, t=1 indicates
In the period power station tiJth platform unit begin to act as hydraulic turbine power generation, otherwise xI, j, t=0,It indicates in the period power station ti
Jth platform unit start stop power generation, otherwiseψI, j、φI, jWhen the jth platform unit of respectively power station i serves as water pump
Minimum opens, downtime duration, h；yI, j, t、The respectively period power station tiJth platform unit opening, stopping when serving as the hydraulic turbine
Machine performance variable, yI, j, t=1 indicates in the period power station tiJth platform unit begin to act as pumping for water pump, otherwise yI, j, t=0,It indicates to start to stop pumping in the jth platform unit of the period power station t i, otherwise
(7) each power grid by electricity and send Constraint
In formula: RI, kFor power station i power energy allocation to power grid k ratio；Respectively power stationiJth platform unit t
The generated output of period and the power that draws water, MW；Indicate t period power stationiTo the transmission power of power grid k, MW；When indicating t
Section power stationiThe power consumed from power grid k, MW.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910772757.5A CN110533236A (en) | 2019-08-21 | 2019-08-21 | A kind of power station refines peak regulation dispatching method in short term |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910772757.5A CN110533236A (en) | 2019-08-21 | 2019-08-21 | A kind of power station refines peak regulation dispatching method in short term |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110533236A true CN110533236A (en) | 2019-12-03 |
Family
ID=68662309
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910772757.5A Pending CN110533236A (en) | 2019-08-21 | 2019-08-21 | A kind of power station refines peak regulation dispatching method in short term |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110533236A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
| CN111431213A (en) * | 2020-03-13 | 2020-07-17 | 郑州大学 | Plant network coordination method for exciting combined operation of wind power plant and pumped storage power station and combined scheduling method thereof |
| CN111934362A (en) * | 2020-07-29 | 2020-11-13 | 国网甘肃省电力公司电力科学研究院 | Multi-power-supply coordinated optimization peak regulation method for fluctuation characteristics of renewable energy |
| CN112580872A (en) * | 2020-12-18 | 2021-03-30 | 郑州大学 | Opportunity constraint planning-based short-term optimization scheduling method for water-light combined system |
| CN113824152A (en) * | 2021-10-26 | 2021-12-21 | 国网新源控股有限公司 | Variable-speed pumped storage and wind-solar power generation peak regulation scheduling method considering water head sensitivity |
| CN114050611A (en) * | 2022-01-12 | 2022-02-15 | 清华四川能源互联网研究院 | Operation scheduling linearization modeling method suitable for pumped storage power station with multiple units |
| CN114243710A (en) * | 2021-12-21 | 2022-03-25 | 国网湖北省电力有限公司经济技术研究院 | Short-term interval optimal scheduling method for water-fire-wind-solar multi-energy system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104063808A (en) * | 2014-06-27 | 2014-09-24 | 大连理工大学 | Trans-provincial power transmission cascade hydropower station group peak-shaving dispatching two-phase search method |
| CN106130079A (en) * | 2016-07-08 | 2016-11-16 | 华北电力大学 | A kind of edema due to wind pathogen fire short-term joint optimal operation method |
| CN106655280A (en) * | 2016-11-26 | 2017-05-10 | 大连理工大学 | Electric quantity control-based stair-step hydropower short-term peak-regulating model and solving method |
| CN109447405A (en) * | 2018-09-20 | 2019-03-08 | 中国南方电网有限责任公司 | A kind of library multi-stag step library group's short-term plan formulating method undertaking peak regulation task |
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
-
2019
- 2019-08-21 CN CN201910772757.5A patent/CN110533236A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104063808A (en) * | 2014-06-27 | 2014-09-24 | 大连理工大学 | Trans-provincial power transmission cascade hydropower station group peak-shaving dispatching two-phase search method |
| CN106130079A (en) * | 2016-07-08 | 2016-11-16 | 华北电力大学 | A kind of edema due to wind pathogen fire short-term joint optimal operation method |
| CN106655280A (en) * | 2016-11-26 | 2017-05-10 | 大连理工大学 | Electric quantity control-based stair-step hydropower short-term peak-regulating model and solving method |
| CN109447405A (en) * | 2018-09-20 | 2019-03-08 | 中国南方电网有限责任公司 | A kind of library multi-stag step library group's short-term plan formulating method undertaking peak regulation task |
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
Non-Patent Citations (8)
| Title |
|---|
| CHENG CHUNTIAN 等: "AN MILP-based model for short-term peak shaving operation of pumped-storage hydropower plants serving multiple power grids", 《ENERGY》 * |
| GE X 等: "Multi-objective hydro optimal scheduling with flow time", 《EEE INTERNATIONAL CONFERENCE ON POWER SYSTEM》 * |
| 张政 等: "复杂约束下梯级水电站短期厂网协调多目标MILP模型", 《电力系统自动化》 * |
| 张政: "水电站群短期调峰优化模型目标函数比较研究", 《电网技术》 * |
| 武新宇 等: "大规模水电站群短期优化调度方法Ⅲ:多电网调峰问题", 《水利学报》 * |
| 王嘉阳: "西南干流梯级水电站群短期与实时精细化调度研究", 《中国优秀博硕士学位论文全文数据库(博士)工程科技Ⅱ辑》 * |
| 王金文: "大规模水电系统短期调峰电量最大模型及其求解", 《电力系统自动化》 * |
| 苏承国 等: "考虑机组组合的梯级水电站短期调峰MILP模型", 《电网技术》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111353654A (en) * | 2020-03-13 | 2020-06-30 | 郑州大学 | Direct-current transmitting-end hydropower station optimal scheduling method compatible with peak regulation requirements of receiving-end power grid |
| CN111431213A (en) * | 2020-03-13 | 2020-07-17 | 郑州大学 | Plant network coordination method for exciting combined operation of wind power plant and pumped storage power station and combined scheduling method thereof |
| CN111934362A (en) * | 2020-07-29 | 2020-11-13 | 国网甘肃省电力公司电力科学研究院 | Multi-power-supply coordinated optimization peak regulation method for fluctuation characteristics of renewable energy |
| CN112580872A (en) * | 2020-12-18 | 2021-03-30 | 郑州大学 | Opportunity constraint planning-based short-term optimization scheduling method for water-light combined system |
| CN112580872B (en) * | 2020-12-18 | 2023-09-26 | 郑州大学 | Short-term optimization scheduling method of water-light combined system based on opportunity constraint planning |
| CN113824152A (en) * | 2021-10-26 | 2021-12-21 | 国网新源控股有限公司 | Variable-speed pumped storage and wind-solar power generation peak regulation scheduling method considering water head sensitivity |
| CN113824152B (en) * | 2021-10-26 | 2023-06-23 | 国网新源控股有限公司 | Variable speed pumping and accumulating cooperative wind-light power generation peak regulation scheduling method considering water head sensitivity |
| CN114243710A (en) * | 2021-12-21 | 2022-03-25 | 国网湖北省电力有限公司经济技术研究院 | Short-term interval optimal scheduling method for water-fire-wind-solar multi-energy system |
| CN114243710B (en) * | 2021-12-21 | 2024-02-27 | 国网湖北省电力有限公司经济技术研究院 | Short-term interval optimal scheduling method for water-fire wind-light multi-energy system |
| CN114050611A (en) * | 2022-01-12 | 2022-02-15 | 清华四川能源互联网研究院 | Operation scheduling linearization modeling method suitable for pumped storage power station with multiple units |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110533236A (en) | A kind of power station refines peak regulation dispatching method in short term | |
| CN103699941B (en) | A kind of formulating method of electric power system dispatching operation year scheme | |
| CN105006846B (en) | A kind of wind energy turbine set station level active power optimization method | |
| CN107276127B (en) | Consider the wind electricity digestion optimization method of the multi-area Interconnected Power System of interconnection electricity transaction plan | |
| CN103580063B (en) | A kind of method of large-scale grid connection wind-powered electricity generation of dissolving based on demanding party's response | |
| CN107153885A (en) | Consider the real-time generation schedule optimization method of fired power generating unit depth peak regulation | |
| EP3255750A1 (en) | High-efficiency and energy-saving method for operating power network | |
| CN104917204B (en) | A kind of active power of wind power field optimal control method | |
| CN103296682A (en) | Multiple spatial and temporal scale gradually-advancing load dispatching mode designing method | |
| CN101777764B (en) | Area control deviation and unit generation deviation-based scheduling feedback control system | |
| CN107590579A (en) | A kind of heat and power system Joint economics dispatching method using heat supply network energy storage characteristic | |
| CN107154644B (en) | A kind of new energy consumption method adjusted based on generation frequency limit value | |
| CN103226735B (en) | A kind of power system optimal dispatch method based on wind-powered electricity generation segmentation | |
| CN106385044B (en) | Composite energy storage control system and its control method for the tracking of wind power plant generation schedule | |
| CN102751724B (en) | Prediction-based three-phase load scheduling method and device responding to demand side | |
| CN114722709B (en) | Cascade reservoir group optimal scheduling method and system considering generated energy and minimum output | |
| CN108365637B (en) | Power transmission plan and water pumping energy storage power generation plan optimization method and system | |
| CN110046780B (en) | Islanding micro-grid demand response economic dispatching method and system based on time-of-use electricity price | |
| CN107196320B (en) | A kind of steel mill's load management method based on timing optimization | |
| CN108667077A (en) | A kind of wind storage association system Optimization Scheduling | |
| CN105069533B (en) | A kind of iron and steel enterprise's multiple-energy-source Optimization Scheduling based on stochastic prediction model | |
| CN109386429A (en) | A kind of wind-powered electricity generation and photo-thermal power generation complementary system coordinated operation control method and device | |
| CN104794576B (en) | Unit has distribution of work coordination approach in a kind of wind power plant | |
| CN104659818B (en) | A kind of optimum allocation method of positive and negative spinning reserve capacity in containing wind power system | |
| CN108062606A (en) | A kind of virtual plant method for optimizing scheduling based on Riemann integral |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191203 |