CN106505635A - Abandon the minimum active power dispatch model of wind and scheduling system - Google Patents
Abandon the minimum active power dispatch model of wind and scheduling system Download PDFInfo
- Publication number
- CN106505635A CN106505635A CN201610835721.3A CN201610835721A CN106505635A CN 106505635 A CN106505635 A CN 106505635A CN 201610835721 A CN201610835721 A CN 201610835721A CN 106505635 A CN106505635 A CN 106505635A
- Authority
- CN
- China
- Prior art keywords
- unit
- wind
- real
- power
- plan
- 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.)
- Granted
Links
- 238000005096 rolling process Methods 0.000 claims abstract description 96
- 230000005611 electricity Effects 0.000 claims abstract description 59
- 238000013439 planning Methods 0.000 claims description 60
- 238000005457 optimization Methods 0.000 claims description 40
- 230000008859 change Effects 0.000 claims description 19
- 230000005540 biological transmission Effects 0.000 claims description 18
- 238000012937 correction Methods 0.000 claims description 14
- 238000009826 distribution Methods 0.000 claims description 11
- 230000035945 sensitivity Effects 0.000 claims description 11
- 238000009987 spinning Methods 0.000 claims description 9
- 230000000694 effects Effects 0.000 claims description 6
- 239000013598 vector Substances 0.000 claims description 4
- 240000002853 Nelumbo nucifera Species 0.000 claims description 3
- 235000006508 Nelumbo nucifera Nutrition 0.000 claims description 3
- 235000006510 Nelumbo pentapetala Nutrition 0.000 claims description 3
- 101150004094 PRO2 gene Proteins 0.000 claims description 3
- 238000013459 approach Methods 0.000 claims description 3
- 238000005192 partition Methods 0.000 claims description 3
- 230000001550 time effect Effects 0.000 claims description 3
- 101100084404 Mus musculus Prodh gene Proteins 0.000 claims 1
- 238000010248 power generation Methods 0.000 abstract description 14
- 230000008901 benefit Effects 0.000 abstract description 6
- 230000006870 function Effects 0.000 description 32
- 238000004458 analytical method Methods 0.000 description 29
- 238000007726 management method Methods 0.000 description 23
- 238000000034 method Methods 0.000 description 21
- 230000003068 static effect Effects 0.000 description 15
- 238000004422 calculation algorithm Methods 0.000 description 8
- 230000009194 climbing Effects 0.000 description 8
- 239000003245 coal Substances 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 6
- 238000010206 sensitivity analysis Methods 0.000 description 6
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 6
- 230000005283 ground state Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 4
- 238000011217 control strategy Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000012423 maintenance Methods 0.000 description 4
- 230000009897 systematic effect Effects 0.000 description 4
- 230000005619 thermoelectricity Effects 0.000 description 4
- 241001269238 Data Species 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 3
- 230000005684 electric field Effects 0.000 description 3
- 230000006872 improvement Effects 0.000 description 3
- 238000009434 installation Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 241000196324 Embryophyta Species 0.000 description 2
- 101100409308 Neurospora crassa (strain ATCC 24698 / 74-OR23-1A / CBS 708.71 / DSM 1257 / FGSC 987) adv-1 gene Proteins 0.000 description 2
- 238000010835 comparative analysis Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 230000008676 import Effects 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000007115 recruitment Effects 0.000 description 2
- 230000008439 repair process Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 238000003786 synthesis reaction Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- MWPLVEDNUUSJAV-UHFFFAOYSA-N anthracene Chemical compound C1=CC=CC2=CC3=CC=CC=C3C=C21 MWPLVEDNUUSJAV-UHFFFAOYSA-N 0.000 description 1
- 230000003466 anti-cipated effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003139 buffering effect Effects 0.000 description 1
- 239000003990 capacitor Substances 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 239000013257 coordination network Substances 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005183 dynamical system Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000013277 forecasting method Methods 0.000 description 1
- 238000002309 gasification Methods 0.000 description 1
- 238000002347 injection Methods 0.000 description 1
- 239000007924 injection Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000036316 preload Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
- 238000007794 visualization technique Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
-
- H02J3/386—
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The present invention provides a kind of active power dispatch model for abandoning wind minimum and scheduling system, dispatches system, including unit role's distribute module, rolling scheduling module, Real-Time Scheduling module and AGC control modules；Abandon the minimum active power dispatch model of wind to be applied in Real-Time Scheduling module.Advantage is：According to wind-powered electricity generation real-time estimate result, power generation needs are revised in real time, so as to revise the plan of exerting oneself in the remaining period of each unit, so that the gross capability of unit is close to step by step with actual power demand, reduce the uncertainty that plans a few days ago, ensure the plan of exerting oneself of each unit more rationally, also more meaningful.
Description
Technical field
The invention belongs to power scheduling technical field, and in particular to a kind of active power dispatch model for abandoning wind minimum and scheduling system
System.
Background technology
Economic Dispatch is referred in the case where network security, generation load equilibrium condition is met, with most economical fortune
Row cost realizes the reasonable distribution of generation load between unit, and ensures a kind of dispatching method to user's reliable power supply.By optimization
The difference of period, power system optimal dispatch problem can be divided into two aspects：Static optimization scheduling and dynamically optimized scheduling.
Static optimization scheduling is referred to：Economic load Optimizing Allocation to the single run time section of power system.
Static optimization scheduling is algorithmically broadly divided into two classes：Classic economic dispatch based on equal consumed energy ratio and with optimum tide
Safety economy scheduling based on stream.
As power system is the dynamical system in a continuous service, change when occurring larger workload demand in system
When, being limited by generator adjustment capability, the getted over ability between each static scheduling result cannot ensure.Accordingly, it would be desirable to grind
Study carefully the continuous feasibility problems of economic load dispatching result, i.e. dynamic economic dispatch problem.
Conventional open-loop dynamic scheduling mode was carried out a suboptimization and will solve sequence in the optimization starting stage to whole optimization cycle
Row all issue execution, due to load prediction precision higher so that this scheduling method applies effect in traditional power system
Fruit disclosure satisfy that requirement substantially.However, after large-scale wind power is accessed, prediction essence of the wind-powered electricity generation precision of prediction far below traditional load
Degree, and the prolongation with the time of optimization, wind-powered electricity generation predicated error significantly increases, cause the characteristics of wind-powered electricity generation this is difficult to Accurate Prediction according to
The result of the conventional open-loop dynamic scheduling mode of Lai Yu wind-powered electricity generation predictions a few days ago is larger with actual electric network demand disruption, needs badly to this
Scheduling method is improved.
Content of the invention
For the defect that prior art is present, the present invention provides a kind of gasification furnace dry state slag-draining device and method, can be effective
Solve the above problems.
The technical solution used in the present invention is as follows：
The present invention provides a kind of active power dispatch model for abandoning wind minimum, including following optimization object function and optimization constraint
Condition；
Wherein：
riIt is the current generating unit Setup Costs of conventional power unit i；
ΔpiFor the regulation total amount of exerting oneself of i-th conventional power unit subsequent time, it is controlled output amount；
wjBe that wind energy turbine set abandons wind power cost, wind is abandoned in order to reduce, wjNumerically current much larger than conventional power unit generating list
Position Setup Cost ri；
It is that wind energy turbine set j abandons wind electric, equal to the wind power output predicted value of subsequent period predictionWith subsequent period
Real-Time Scheduling planned valueDifference；
NG cagcFor the whole network Real-Time Scheduling unit, the number of Wind turbines is not included
NG WindFor Wind turbines set；
Currently go out force value for wind energy turbine set j；
Exert oneself regulation total amounts of the Δ P for Real-Time Scheduling unit subsequent time：
Wherein,Be ultra-short term value increment,Be tie line plan subsequent time increment,
It is to plan unit output subsequent time increment a few days ago；ΔPn AGCAmount was not completed for an AGC upper moment；
MintThe whole network circuit and intranet security power transmission section set is represented,For the power transmission upper limit of section,T j For
The power transmission lower limit of section, TjFor the current transmission power of section, inequality constraints guarantee transmission section nonoverload；
SijUsing balancing the load sensitivity, wherein in order to reach partition balancing, need to introduce in the bus load factor and divide
The information of area's load prediction；
SkjIt is balancing the load sensitivity, △ Pk wIt is that wind energy turbine set k abandons wind-powered electricity generation amount, the product representation wind-powered electricity generation of two abandons wind-powered electricity generation
Real Time Effect of the amount to section power；
ΔCgjImpact of the planned regulation amount to section power for the unit of non real-time scheduling；
Above-mentioned object function is solved, the predicted value that exerts oneself to following wind field and unit unit is obtained.
The present invention also provides a kind of application the above-mentioned scheduling system for abandoning the minimum active power dispatch model of wind, including unit angle
Color distribute module, rolling scheduling module, Real-Time Scheduling module and AGC control modules；
The minimum active power dispatch model of wind of abandoning is applied in Real-Time Scheduling module；
The unit role distribute module carries out the division of unit role using following steps：
Step 1, counts ACE according to historical data first and falls in the probability of each control zone, and order falls in the general of dead band
Rate is pro1, and the probability fallen within normal area is pro2, and the probability fallen in coordinated regions is pro3, falls in urgent area and urgent
Probability outside area is pro4, then have：
Step 2, the AGC units for participating in regulation ACE meet the requirement of total spinning reserve in each period, therefore, if being
The AGC units that n platforms participate in ACE controls, 1≤n≤N, and the set note being made up of n platform units is had in N platform units in system
For SetA；The lower limit of spinning reserve should be given according to the practical operation situation of electrical network, is set as SRt, and its value have to be larger than ACEE；
Belonging to the n platform conventional racks of set SetA, to have 4 kinds of roles available, i.e.,：1 corresponding control mould of unit role
Block is bias adjustment；2 corresponding control model of unit role is planned in real time for tracking；3 corresponding control model of unit role is
Tracking rolling planning；4 corresponding control model of unit role is planned a few days ago for tracking；
Variable R oleID represents unit role, and value is 1,2,3,4, and corresponding control model is respectively：Bias adjustment, with
Track is planned in real time, tracks rolling planning and track and plan a few days ago；Its corresponding unit role is respectively：AGC units, Real-Time Scheduling
Unit, rolling planning unit and a few days ago plan unit；
Gone out according to RoleID vectorial structures map therewith 4 vector Role (1), Role (2), Role (3), Role (4),
It is used for preserving the AGC unit subscripts that role is respectively 1,2,3,4；
Thus the object function for being building up to following optimization problem is：
Wherein：Pit：Unit i goes out force value in t；
ai：The secondary term coefficient of non-linear relation；
bi：The Monomial coefficient of non-linear relation；
ci：The constant term of non-linear relation；
d：Currently exert oneself worth correction factor；
Above-mentioned object function ensures that ACE of all AGC units for belonging to Role (j) in one day adjusts the expectation of total cost
Minimum；
And need to ensure that ACE falls to having in regional enough AGC to adjust nargin after unit role distribution, therefore,
Generate following constraint：
sitFor i-th unit t spinning reserve；
Object function is solved under above-mentioned constraints, that is, obtain the AGC role of final determination.
The rolling scheduling module is used for：Based on planning, according to the load prediction of electrical network Extended short-term model a few days ago
As a result and Extended short-term wind-powered electricity generation predicts the outcome that unit generation plan goes out activity of force to rolling amendment a few days ago so that system generating gross capability
Power is gradually approached with actual power demand, and the unit generation plan for obtaining economic optimum is exerted oneself, and by the economic optimum
Unit generation plan is exerted oneself and acts on the rolling planning unit；
The Real-Time Scheduling module is used for：Exerted oneself as basic point power, according to electricity using the unit generation plan of economic optimum
Net ultra-short term result and ultra-short term wind-powered electricity generation predict the outcome adjustment unit output, generate to planning the system shape in the period
State carries out the Real-Time Scheduling correction Planning Directive of minimum unit output adjustment, and the Real-Time Scheduling correction Planning Directive is acted on
In Real-Time Scheduling unit, and then eliminate the random change that unit executes the calculated unbalanced power amount of economic optimum and wind-powered electricity generation load
Change the amount of unbalance for causing；
The AGC control modules are used for：The Real-Time Scheduling correction Planning Directive be given using the Real-Time Scheduling module as
Control basic point, is revised in real time to the stochastic prediction error that advanced prediction link is produced, and is generated for controlling to AGC units
The AGC unit output adjust instructions of system, and the AGC unit outputs adjust instruction is issued to AGC units, realize to AGC machines
The control of group.
The active power dispatch model for abandoning wind minimum of present invention offer and scheduling system have advantages below：
According to wind-powered electricity generation real-time estimate result, power generation needs are revised in real time, so as to revise each unit in residue
The plan of exerting oneself of period so that the gross capability of unit is close to step by step with actual power demand, reduces the uncertainty that plans a few days ago,
Ensure the plan of exerting oneself of each unit more rationally, also more meaningful.
Scheduling model is substantially to increase rolling planning scheduling, in real time between generation schedule a few days ago and AGC Generation Controls
In the operation plan stage, set up the technical support link of intelligent decision making and self-adaptive wavelet base in this stage, so as to substitute
Traditional manually adjust pattern, mitigate the labour intensity of Dispatchers on duty, at utmost dissolve and wind-powered electricity generation realize the electricity of high-quality
Power is supplied.
Description of the drawings
1st kind of structural representation of the scheduling system that Fig. 1 is provided for the present invention；
2nd kind of structural representation of the scheduling system that Fig. 2 is provided for the present invention；
3rd kind of structural representation of the scheduling system that Fig. 3 is provided for the present invention；
A kind of specific actual load and plan load curve comparison chart that Fig. 4 is provided for the present invention；
Fig. 5 gives the schematic diagram that defined each prediction concept is arranged by predetermined period；
Fig. 6 is that ACE divides schematic diagram.
Specific embodiment
In order that technical problem solved by the invention, technical scheme and beneficial effect become more apparent, below in conjunction with
Drawings and Examples, the present invention will be described in further detail.It should be appreciated that specific embodiment described herein only in order to
The present invention is explained, is not intended to limit the present invention.
For convenience of understanding, the technical term of correlation is introduced to the present invention first：
(1) power scheduling：
Power scheduling is to ensure that power network safety operation, external reliable power supply, the work of all kinds of power generations in order
A kind of effective management means for carrying out and adopting.The specific works content of power scheduling is anti-according to various information collecting device
Be fed back to the data message for coming, or the information that monitoring personnel is provided, in conjunction with electrical network actual operation parameters, such as voltage, electric current, frequency,
Load etc., considers every production work development condition, power grid security, economical operation state is judged, by phone
Or automatic system issues operational order, commander site operation personnel or automatic control system are adjusted, and such as adjustment generator goes out
Power, Load adjustment distribution, switched capacitor, reactor etc., so that it is guaranteed that electrical network continues safe and stable operation.
(2) load prediction：
Load prediction be according to many factors such as the operation characteristic of system, increase-volume decision-making, natural conditions and social influences,
Under conditions of meeting certain required precision, determine that the load data of certain particular moment following, wherein load refer to power demand
(power) or power consumption；Load prediction is an important content in Economic Dispatch, is EMS (EMS)
An important module.
(3) generation schedule：
Generation schedule is according to load prediction, on the premise of power-balance is met, in conjunction with each unit output bound, respectively
The constraintss such as the maximum climbing power of unit, it is considered to the actual conditions such as the start and stop of each unit and minimum downtime, and shift to an earlier date
The generated output of each unit of layout.
(4)AGC：
Automation generation control (Automatic Generation Control) is in EMS EMS
Item critical function, it controls exerting oneself for frequency modulation unit, to meet the custom power demand being continually changing, and makes system in warp
The running status of Ji.
(5) rolling planning：
Rolling planning (also referred to as sliding plan) is a kind of method of dynamic manning quotas plan.It not as static analysis, etc.
One plan all executes the plan for regrouping next period after being over again, but in establishment every time or plan for adjustment,
It is intended to push ahead a plan phase, i.e. rolls forward in chronological order once.
The Developed Background of the present invention
(1) needs that plans a few days ago
As time goes on, the impact of the uncertain factor of power generation needs prediction will increased, and power generation needs are predicted
The degree of accuracy can also be gradually lowered.Therefore, it is possible to carry out to the power generation needs of the remaining period after one day each period in real time
Rolling amendment, so that rollably revise exert oneself plan of each unit in the remaining period so that the gross capability of unit is sent out with actual
Electric demand is more nearly.In this manner it is ensured that the plan of exerting oneself of each unit is more rationally, rolling scheduling is to planning a few days ago
Constantly revise.
(2) needs of Real-Time Scheduling
Active balance and the ultimate aim that security control is dispatching of power netwoks is realized, therefore, the Real-Time Scheduling of advanced intelligent will
More rational scientific basis is provided for dispatcher, it is ensured that the correctness of dispatching of power netwoks commander.
(3) needs of load prediction
For improving receiving ability of the electrical network to wind-powered electricity generation, wind power prediction and system loading prediction are element tasks, but
Be wind power prediction result with the increase of predicted time, predicated error can also increase, therefore, by wind power prediction a few days ago and
The actual power demand and wind-powered electricity generation actual power ability that the unit that system loading prediction a few days ago is made is planned a few days ago with second day is deposited
In relatively large deviation, if it is possible to more accurately in a few days roll wind power prediction result rolling amendment according to second day and plan to tie a few days ago
Really, then wind power prediction deviation a few days ago and system loading prediction deviation can be further eliminated, reaches large-scale wind power of dissolving
Purpose.
Target of the present invention is：
Using closed loop feedback dynamic adjustment various dimensions optimal dispatch decision-making technic, with unit actual exert oneself, bus
Based on load, operation of power networks state and network topology structure, through the Security Checking and congestion management of multi-period multiple constraint, real
The multiple target rapid Optimum decision-making of existing operation plan, system-computed result not only should ensure that balance of electric power and ener and circuit, section
Trend is not out-of-limit, at the same realize circuit N 1 scan, fault set scanner uni self-adaptative adjustment function.
Finally, realize that " days quantity of electricity plan balance, week moon operation plan decompose management, operation plan optimization a few days ago
The target of establishment, in a few days operation plan rolling adjustment, real-time active balance and coordination control "；Actively push forward water, fire, wind, core connection
Optimal Scheduling construction is closed, quantifying thermoelectricity peak modulation capacity affects, wind-powered electricity generation is brought into a few days ago, in a few days in balance of electric power and ener,
And the probability nature of wind power prediction is taken into full account, to meet the target of wind-powered electricity generation maximum ability to arrange jobs.
The key technology of the Optimal Scheduling that the present invention is provided
(1) the optimal dispatch control pattern that Multiple Time Scales are coordinated
Up to the present, domestic scheduling mode is mainly using the two time chis of+AGC of Optimized Operation plan a few days ago controls
The scheduling mode of degree, time scale span is big, scheduling method is more extensive, it is impossible to adapts to the electrical network after large-scale wind power is accessed and adjusts
Degree.
According to unit responding ability, in conjunction with scheduling production status, active power dispatch strategy is decomposed into day on time dimension
Level, 1 hour level, 15 minutes levels, second levels.According to the characteristics of load fluctuation and unit control characteristic, control can be decomposed into
Four-stage：Plan a few days ago and rolling planning rolling scheduling, Real-Time Scheduling plan and AGC control.As shown in Fig. 2 whole for system
Body control model figure, its feature include：
1) time that plan has abundance carries out dynamic optimization calculating, and this time stage is controlled with safety as constraint, to pass through
Help as target, be properly termed as optimum control.
2) based on short-term forecast, the rolling scheduling for the startup cycle makes full use of newest letter within 1 hour for rolling planning
Breath, is modified to plan a few days ago, gradually reduces uncertainty.
3) Real-Time Scheduling plan implement when, in the face of operating point be close to the tracking plan not yet in effect of security domain edge, unit,
The uncertain factors such as AGC unit capacity deficiencies.The good unit of functional in selecting system, executive plan is used as buffer
Group, is predicted by ultra-short term and was exerted oneself as period modulation with 15 minutes, for eliminating these uncertain factors.Buffering unit is with safety
For first object, economical is the second target, unbalanced power amount on the one hand during absorption optimum control, improvement operation safety
Property, it is ensured that optimum control link is normally run；On the other hand space is adjusted for second level AGC unit is reserved, it is ensured that AGC links are just
Often run.
4) AGC controls, AGC controls are processed immediately to situation about occurring at that time, are controlled including Corrective control and Security corrective
(congestion management).Wherein, Corrective control is scheduling second level AGC unit, makes frequency and dominant eigenvalues meet CPS performance assessment criteria；
It is out-of-limit that Security corrective controls instant process circuit section tidal current.The target of AGC controls is quickly to eliminate safe hidden trouble, it is ensured that system
Frequency quality.
This scheduling method be substantially between generation schedule a few days ago and AGC Generation Controls increase rolling planning scheduling,
Real-Time Scheduling programming phase, sets up the technical support link of intelligent decision making and self-adaptive wavelet base, in this stage to replace
For traditional pattern that manually adjusts, mitigate the labour intensity of Dispatchers on duty, at utmost dissolve and wind-powered electricity generation realize high-quality
Supply of electric power.
All units are divided into four classes under this control model：Plan unit, rolling scheduling unit a few days ago, coordinate unit
(Real-Time Scheduling unit) and manually fix unit.Plan unit is executed in strict accordance with plan a few days ago a few days ago, and rolling scheduling unit is pressed
Plan after according to rolling amendment is executed, and coordinates the balance that unit is responsible for the larger load power change of regular amplitude, control
Cycle is 15min.So, by adjusting exerting oneself for coordination unit, make AGC units remain with larger adjustment nargin, improve
The security and economy of system operation；Simultaneously by the adjustment to real-time control unit, wind-powered electricity generation of farthest having dissolved is carried
High wind power utilization.
(1) Extended short-term load prediction
Rolling scheduling link needs monitoring when the implementation status of daily trading planning, occurs in original plan and actual load serious
In the case of deviation, the again prediction and generation schedule adjustment of this day remaining period load are completed in time.Referring to Fig. 4, it is a kind of
Specific actual load and plan load curve comparison chart.Solid line in Fig. 4 is that certain electrical network works as the morning 10 January 11:See when 00
The system actual load operation curve figure for measuring.The plan load that figure dashed lines are represented is morning 11 day before yesterday:00 prediction is out
's.As illustrated, the load-sensitive such as climate factor affects, the daily load is from 9:00 actual load operation curve begins to deviate from
Its Plan Curve, and its deviation has change trend.Now, if not being modified to the daily load plan, it would be possible to cause very
Big load prediction error.Using the information of newest acquisition, prediction again is carried out to this day later half daily load, adjust later half day
Plan Curve, then plan and actual deviation can be retrieved with maximum possible, reduce load prediction error.
In order to meet above-mentioned application demand, Extended short-term load prediction concept is proposed：Using can currently obtain most
Fresh information (including information on load, weather information, electricity price etc.), unknown 1 hour～many hours after predicting current time on the same day
Load.
From from predetermined period, Extended short-term load prediction circle is between ultra-short term, short-term load forecasting.Fig. 5 gives
Defined each prediction concept presses the schematic diagram of predetermined period arrangement.
Extended short-term load prediction and the main application of short-term load forecasting are all to formulate daily load plan, and the former is to rear
Extension of the person on predetermined period, table 1 have compareed the Main Differences (by taking 96 points of daily sampling as an example) between both.
Table 1
Historical information has not only been used in Extended short-term load prediction, also used the same day newest load, meteorology, failure,
Plan information etc., therefore can improve precision of prediction.In a word, the target of Extended short-term load prediction is known same day sub-load
In the case of data, reasonable, effective prediction is carried out to remaining load data of the same day.By tracking and detection load correlative factor
Change anticipated that load variations situation.In precognition realized load curve by under substantial deviation original plan curve condition, can be with
Pre-cooling Extended short-term load prediction, improves the degree of accuracy of load prediction, and the important step for realizing generating rolling scheduling.
(2) ultra-short term
Super short period load forecast (from a few minutes to one hour) is the premise of real-time active power dispatch, it is ensured that its precision is to realize
The key of Real-Time Scheduling.The characteristics of super short period load forecast is forecast cycle is short, and key technology is precision.Will in forecasting procedure
Seek the statistical information for being capable of application data as far as possible.It has following spy compared with short-term or even medium-term and long-term Load Forecasting
Point：
1) cycle is short is forecast, therefore requires on-line operation, and have higher requirement to the calculating time；
2) in the concept of " ultra-short term ", Changes in weather, festivals or holidays, the impact of two-day weekend are less obvious；
3) load curve is not so good as short-term steadily, and higher harmonic components are relatively more, and amplitude is big
The present invention is using the very Short-Term Load Forecasting Method based on load curve section morphic similarity.According to historical load
Go out force data, the Auto-matching similar period is predicted.It is different from the similar selection similar day of traditional value according to load curve
Method, and ultra-short term can preferably be improved come choice of dynamical similar day according to the morphic similarity of load curve
Precision be particularly flex point at precision of prediction.
(3) rolling scheduling technology
In the works, As time goes on, power generation needs prediction is particularly the uncertain factor of wind power output prediction a few days ago
Impact will increased, power generation needs and wind power output prediction the degree of accuracy can also be gradually lowered, so as to have influence on unit
Reasonability and practicality that plan is exerted oneself.Due to due to wind power prediction error increases with predicted time, it is considered to the rolling of wind-powered electricity generation
Dynamic scheduling should not adopt too long of time window, it is contemplated that the rolling wind power prediction result of wind energy turbine set can be given every 15 minutes
The predicted value of following 4 hours, if it is possible to according to during wind-powered electricity generation rolling forecast fructufy to one day each period after
The power generation needs of following 4 hours carry out rolling amendment, so as to rollably revise the meter of exerting oneself in the remaining period of each unit
Draw so that the gross capability of unit is close to step by step with actual power demand, so just can reduce the uncertainty that plans a few days ago, protect
Demonstrate,prove the plan of exerting oneself of each unit more rationally, also more meaningful.So, one can consider that rolling scheduling is exactly to a few days ago
Plan is constantly revised, the process for constantly refreshing.
Rolling scheduling is the dynamic optimization between present period to processing completion time used for them, is mathematically a difficult problem, model
Complicated and time-consuming more.Accordingly, it would be desirable to how study by carrying out time dimension and Spatial Dimension to dynamic optimization model
Decoupling and coordination obtain being suitable for scrolling through the practical Optimized model for dispatching link application on site.This is just to rolling scheduling algorithm
High efficiency proposes requirement；Secondly as the uncertainty that daily load fluctuating brings, algorithm and its Optimized model also need to have
Good robustness.
In the formulation of rolling scheduling, the economic benefit for considering energy-saving and emission-reduction is not only needed, each unit must be ensured surplus
The feasibility that the remaining period exerts oneself, including meeting the constraint of unit climbing rate, meets generation load power-balance constraint, network security
Constraint etc..
The time span of the Mathematical Modeling of rolling scheduling is [t0+ 1, T], target is the system synthesis sheet of following a period of time
Minimum, can specifically be expressed as：
Online rolling optimal dispatching model, including optimization object function and optimizes constraints；
The time span of the Mathematical Modeling of online rolling planning is [t0+ 1, T], target is that the system of following a period of time is total
Cost is minimum, specifically can be with
Wherein：I, j are respectively the numbering of conventional power unit and Wind turbines, and span is i ∈ [1, N], j ∈ [1, M]；Its
In, N is conventional power unit total quantity；M is Wind turbines total quantity；Segment number when t is, span are t ∈ [t0+1,T]；t0For
Optimize start periods；T is optimization Period Length；pit,I-th conventional power unit and jth typhoon motor respectively in rolling planning
Be planned out force value of the group in the t periods,For t0Period predicts prediction peak power of the jth typhoon group of motors in the t periods
Value；ai,bi,ciFor the quadratic term of i-th conventional power unit generating expense, first order and constant term coefficient, and λjAbandon for Wind turbines
Wind cost factor；Work as λjWith biSame magnitude and value are timing, and achievable minimum abandons wind；
Optimizing constraints includes：
(1) unit output bound constraints：
Wherein, pait,piitThe upper bound and lower bound that respectively i-th conventional power unit was exerted oneself in the t periods；When certain unit
When at a time shutting down, the EIAJ and minimum load at the unit moment are all set to null value；
(2) unit climbing rate constraint
pi,t-1-Δpdit≤pit≤pi,t-1+Δpuit(3)
Wherein：Δpdit,ΔpuitExert oneself from the t-1 periods to the drop that the t periods allow maximum for i-th conventional power unit
Value and liter are exerted oneself maximum；pi,t-1Be i-th conventional power unit in rolling planning in the t-1 periods is planned out force value；Wind turbine
The group restriction that climbing rate is not constrained；
(3) section tidal current security constraint
L therein, L represent section numbering and total section number respectively；gli,Respectively i-th conventional power unit and jth platform
Sensitivity factor of the Wind turbines to l sections, can pass through the corresponding admittance matrix of DC power flow and obtain；TL lt ,It is disconnected
The minimum of a value and maximum of face trend；
(4) account load balancing constraints
Wherein, DtGo out force value for general plan；
As formula (2) and the corresponding constraint of formula (3) only include the information of single unit, it is unit by this constraint definition
Non-coupled constraint；And formula (4), formula (5) information of the constraint comprising multiple stage unit, therefore it is defined as unit coupling constraint.
Online rolling optimal dispatching model is planned out force value p with conventional power unititForce value is planned out with Wind turbines
For variable, formula (1) is optimization object function, and formula (2), (3), (4), (5) are for optimizing constraint.
Rolling amendment scheduling is a kind of application on site, and its algorithm should possess very high computational efficiency and stronger robust
Property.In the present invention, solved using Lagrange duality method.Certainly, in practical application, all kinds of methods can be adopted flexibly, to above-mentioned
Optimization object function is solved, and the present invention is not intended to limit to this.
(3) Real-Time Scheduling technology
1) relation of Real-Time Scheduling and other scheduling links
The load curve in one region can be analyzed to fixed component, trend component and random component.Therefore three kinds points are directed to
Amount is divided into four classes unit, i.e., plan unit, rolling planning unit, real-time unit and AGC units a few days ago.A few days ago and rolling planning
Unit is responsible for short term scheduling plan execution, and real-time unit is formulated according to ultra-short term and plans in real time and execute, AGC units
Then it is responsible for the Corrective control of fluctuating load.
In addition, the scheduling model that the present invention is provided, also includes unit role's distribute module, the unit role distribute module
For being allocated to the role of the whole network unit in real time, unit role includes planning unit, rolling planning unit a few days ago, counts in real time
Draw unit and AGC units；
The unit role distribute module adopts following methods, every the role that Preset Time determines each unit of the whole network：
Step 1, according to the departure degree of electrical network real-time frequency and normal setpoint frequency, by from irrelevance from light to the suitable of weight
Sequence, is in turn divided into 4 control zones, respectively：Dead band, normal area, auxiliary region and coordinated regions；
Specifically, it is to ensure that AGC is smooth, stablize the Real-time Balancing for being effectively realized power supply and demand, it is to avoid reducing ACE
During there is the situation of toning or less stress, need to divide control zone (Control Zone).Control zone is used for table
Show the order of severity of ACE, command area is also referred to as including dead band (Dead Band Zone), normal area (Normal Zone)
(Command Zone), auxiliary region (Assist Zone) also referred to as allow area (Permissive Zone), coordinated regions
(Cooperation Zone) is also referred to as urgent area (Emergency Zone).Wherein ACE divides schematic diagram and refers to Fig. 6：
Step 2, determines deadband boundaries value ACE respectively by below equationD, normal area's boundary value ACEN, auxiliary region boundary value
ACEAWith coordinated regions boundary value ACEE：
Wherein：Bi：The frequency bias coefficient that control area sets, unit MW/0.1HZ take positive sign；
ε1：Root mean square control targe of the interconnected network to annual one minute frequency averaging deviation；
L10：The control limit of the absolute value of ten minutes ACE mean values；
LOSS：Unstability power；
According to the occurrence of ACE, the coordination control strategy of each AGC unit is as shown in the table：
AGC unit cooperative control scheme lists
In table：" not controlling " represents does not carry out any regulation；" bias adjustment " is represented and need to leave basic point value, participate in
ACE is adjusted, and promotes ACE to reduce." basic point is close " represents directly carries out basic point regulation, does not consider the impact to ACE；" condition is returned
Return " represent carry out basic point adjust when, consider whether to impact ACE, if approach to basic point value can cause ACE increase,
Remain stationary as；If approach to basic point value to promote ACE to reduce, changed.
Basic point value is set with various ways, and the basic point value that the present invention is adopted is a company for plan basic point, i.e. basic point value
Continuous curve.
Step 3, is ranked up to all units of the whole network according to unit performance, according to unit performance order from high to low,
Unit is designated as respectively：Unit 1, unit 2 ..., obtain sequencing table；
The minimum m values of following condition are met in selected and sorted table, are obtained numbering and are followed successively by：Unit 1, unit 2 ... unit m
M AGC unit；AGC units are adjusted according to the control strategy of bias adjustment：
Wherein：capagc：AGC bias adjustment capacity；
Pi,max：The EIAJ value of unit i；
Pi,min：The minimum load value of unit i；
Step 4, selects numbering to be followed successively by：Unit m+1, the n platforms unit of unit m+2 ... unit n plan unit as real-time,
Plan unit is controlled according to real-time planning strategy is tracked in real time, and wherein, n is the minimum of a value for meeting following constraint：
Due to piTo exert oneself be continually varying value, therefore, n is also the numerical value of a dynamic change；
Step 5, selects numbering to be followed successively by unit n+1, the k platforms unit of unit n+2 ... unit n+k as rolling planning machine
Group, rolling planning unit are controlled according to tracking rolling planning strategy, and wherein, k is the minimum of a value for meeting following constraint：
Step 6, the remaining unit in sequencing table for planning unit a few days ago, plan according to tracking a few days ago a few days ago by plan unit
Control strategy is adjusted.
The distribution of above unit role can carry out statistics selection automatically by program, for avoiding frequently changing role, can
One subseries is carried out with Δ t at set intervals.For the unit by bias adjustment, according to the requirement of energy-saving distribution, with coal consumption
The size proportional assignment imbalance power of coefficient.
In addition, unit role distribute module can also determine unit role using following methods：
Step 1, counts ACE according to historical data first and falls in the probability of each control zone, might as well make in dead band
Probability be pro1, the probability fallen within normal area is pro2, and the probability fallen in coordinated regions is pro3, fall in urgent area and
Probability outside urgent area is pro4, then have：
Step 2, the AGC units for participating in adjusting ACE must also meet the requirement of total spinning reserve in each period, might as well
If the AGC units (1≤n≤N) that n platforms participate in ACE controls are had in the N platform units in system, and be made up of this n platform unit
Set is designated as SetA；The lower limit of spinning reserve should be given according to the practical operation situation of electrical network, might as well be set to SRt, and its value is necessary
It is more than ACEE (namely 0.8LOSS)；
Belonging to the n platform conventional racks of set SetA, to have 4 kinds of roles available：
Unit role and control model
Variable R oleID represents unit role, and value is 1,2,3,4, and corresponding control model is respectively：Bias adjustment, with
Track is planned in real time, tracks rolling planning and track and plan a few days ago；Its corresponding unit role is respectively：AGC units, real-time machine
Group, rolling planning unit and a few days ago plan unit；
Can be constructed according to RoleID vectors map therewith 4 vector Role (1), Role (2), Role (3), Role
(4), for preserving the AGC unit subscripts that role is respectively 1,2,3,4；
Thus the object function for being building up to following optimization problem is：
Wherein：Pit：Unit i goes out force value in t；
ai：The secondary term coefficient of non-linear relation；
bi：The Monomial coefficient of non-linear relation；
ci：The constant term of non-linear relation；
d：Currently exert oneself worth correction factor；
Above-mentioned object function ensures that ACE of all AGC units for belonging to Role (j) in one day adjusts the expectation of total cost
Minimum.
And need to ensure that ACE falls to having in regional enough AGC to adjust nargin after unit role distribution, therefore,
Generate following constraint：
sitFor i-th unit t spinning reserve；
Object function is solved under above-mentioned constraints, that is, obtain the AGC role of final determination.
Real-Time Scheduling is the advanced scheduling based on ultra-short term.Usually in t=t1When to t=t1+ T the moment enters
Row optimizes, and revises operation plan and the deviation for predicting the outcome.
The target of Real-Time Scheduling is to coordinate rolling scheduling, coordinate AGC, coordination network safety.
2) coordination of Real-Time Scheduling and generation schedule
Real-Time Scheduling can not be overthrown generation schedule to come again, but will make full use of generation schedule.Real-Time Scheduling both can be with
Based on the result of operation plan a few days ago, it is also possible to based on the result of rolling scheduling plan, enter to advance on its basis
The check and correction of one step.Real-Time Scheduling is " sound is connected, and seamlessly transits " with the coordination principle of generation schedule.
3) coodination modes that Real-Time Scheduling is controlled with AGC
In the scheduling process of power system, various accidents can constantly occur, for example occur wind-power electricity generation fluctuation,
Load deviation, generator non-programmed halt, circuit overload etc..Real-Time Scheduling not only needs and plan coordination a few days ago, in addition it is also necessary to
Mutually coordinate with AGC controls, auxiliary adjustment is played a part of to AGC system.Real-Time Scheduling is responsible for larger negative of amplitude of regularity
The power distribution of lotus, and the quick change at random of the less load of amplitude is responsible in AGC controls.
The coodination modes that Real-Time Scheduling is controlled with AGC are：
First, safer operating point will be operated in as far as possible.
AGC control controls are that the correction after deviation occur, do not consider economy.The controls in advance of Real-Time Scheduling should be use up
Accurately, should not there is larger deviation in amount, not allow offset correction control to occur significantly adjusting, so compare on the whole through
Ji.Ensure the accuracy of generation schedule, first have to the accuracy for improving load prediction.
Second, in Real-Time Scheduling to control to retain enough adjustment spaces to AGC.
Power system is always among unordered dynamic change.Various offset correction control functions monitor power train in real time
Various deviations are corrected and are controlled by the running status of system.Real-Time Scheduling should control to retain certain adjustment space to AGC,
Meet the needs of offset correction.
The controlling cycle of Real-Time Scheduling is a period (such as 15 minutes), and the controlling cycle of AGC is in 10s or so.AGC
Unit is controlled by AGC softwares, is adjusted with the change of the ACE of one's respective area, can not be controlled it in Real-Time Scheduling.This
In the case of kind, this is thought of as the problem that AGC retains adjustment space.Real-Time Scheduling, can be with by the control to SCHED pattern units
The active balance of adjustment system, is that AGC units leave variable capacity.
4) the active power dispatch model that Real-Time Scheduling can be minimum using wind is abandoned
System should be supported 1 hour and the Real-Time Scheduling Planning Directive of minute level is adjusted, and realize mixed economy, energy-conservation and safety
Multiple Time Scales multilevel coordination scheduling method.Introduce Model Predictive Control Theory MPC, research Real-Time Scheduling model and calculation
Method, mainly includes：
A1) the active power dispatch Optimized model for abandoning wind minimum for meeting security constraint is set up.
A2) look to the future as, when skyrocketing occur in wind-power electricity generation and load and drop suddenly, system has main fast tunable capacity
Carry out balanced load and whether network occurs congestion.
A3) although Real-Time Scheduling meets network constraint in Security Checking, in operation of power networks, it would still be possible to tide occur
The out-of-limit situation of stream.Real-Time Scheduling needs the ruuning situation of all elements in online scanning electrical network, to sending out during the out-of-limit situation of appearance
Electricity carries out emergency adjustment, that is, will carry out congestion management.
A4) introducing MPC models is used for the Real-Time Scheduling modeling of large-scale wind power, gives full play to the regulation and control for playing wind-powered electricity generation itself
Ability, breaks through wind-powered electricity generation is simply equivalent for negative load way in traditional scheduler.
The minimum active real-time scheduling method of wind is abandoned according to ultra-short term wind power prediction value, is set up and is met abandoning for security constraint
The minimum active power dispatch Optimized model of wind.
Wherein, the real-time unit allocation cycle is 15 minutes (adjustable).Meeting safety, economy, before energy-conserving and environment-protective requirement
Put, the task that real-time unit plan in 15 minutes is completed includes：1) make up (Extended short-term) load prediction a few days ago to surpass with 15 minutes
The deviation of short-term load forecasting；2) enough spare capacities are reserved for AGC.
For this purpose, following linear programming model can be built to be described：
In model：
riIt is the current generating unit Setup Costs of conventional power unit i；
ΔpiFor the regulation total amount of exerting oneself of i-th conventional power unit subsequent time, it is controlled output amount；
wjBe that wind energy turbine set abandons wind power cost, wind is abandoned in order to reduce, general wjNumerically current much larger than conventional power unit sends out
Electric unit Setup Cost ri；
It is that wind energy turbine set j abandons wind electric, equal to the wind power output predicted value of subsequent period predictionWith subsequent period
Real-Time Scheduling planned valueDifference；
NG cagcFor the whole network Real-Time Scheduling unit, the number of Wind turbines is not included
NG WindFor Wind turbines set；
Currently go out force value for wind energy turbine set j；
Exert oneself regulation total amounts of the Δ P for Real-Time Scheduling unit subsequent time：
Wherein,Be ultra-short term value increment,Be tie line plan subsequent time increment,
It is to plan unit output subsequent time increment a few days ago；ΔPn AGCAmount was not completed for an AGC upper moment；
MintThe whole network circuit and intranet security power transmission section set is represented,For the power transmission upper limit of section,T j For
The power transmission lower limit of section, TjFor the current transmission power of section, inequality constraints guarantee transmission section nonoverload；
SijUsing balancing the load sensitivity, wherein in order to reach partition balancing, need to introduce in the bus load factor and divide
The information of area's load prediction；
SkjIt is balancing the load sensitivity, △ Pk wIt is that wind energy turbine set k abandons wind-powered electricity generation amount, the product representation wind-powered electricity generation of two abandons wind-powered electricity generation
Real Time Effect of the amount to section power；
ΔCgjImpact of the planned regulation amount to section power for the unit of non real-time scheduling.
The purpose of active power dispatch is to receive wind-powered electricity generation as much as possible.Therefore, the result of Real-Time Scheduling Optimized model, i.e., each wind
The real-time planned value of field generated output is typically exactly ultra-short term predicted value.But, due to being subject to electrical grid transmission ability, generating standby
Capacity etc. is constrained, it is impossible to guarantee that what output of wind electric field can reach which predicts exerts oneself, now corresponding output of wind electric field is real-time
Optimizing scheduling result be wind energy turbine set need abandon wind electric.The result of calculation of Real-Time Scheduling is sent to each wind energy turbine set as wind
The plan of electric field subsequent period is exerted oneself.
In addition, Real-Time Scheduling may also be employed following scheduling model：
f1(pit) it is scheduling model object function；T is the optimization time；t0For optimizing start periods；TlExcellent for basic point tracking layer
Change Period Length；N is conventional power unit number；ai、bi、ciCoal consumption coefficient for conventional power unit i；pitIt is conventional power unit i in the t periods
The active plan of exerting oneself；For i-th unit the t periods rolling optimal plan layer plan；ΔpitExist for i-th unit
The basic point of t periods follows the trail of plan adjustment amount, is controlled output amount；GwindFor Wind turbines number；λjFor abandoning wind cost factor；
Exert oneself for the prediction of Wind turbines Extended short-term；For Wind turbines j the t periods the active plan of exerting oneself.
(5) Security Checking technology
Security Checking is to the system under the generating set plan of exerting oneself by rolling scheduling module and the generation of Real-Time Scheduling module
The method of operation is checked, to guarantee the safe and reliable of system operation.
Calculated by AC power flow by check section intelligence systematic function first and form check section tidal current；Then to checking
Section carries out ground state tidal current analysis, judges the out-of-limit situation of electrical network under ground state trend；Then static security analysis are carried out, unit is judged
After part cut-offs, whether other branch roads are out-of-limit；Finally according to the out-of-limit of static security analysis discovery, heave-load device and stable cross section, enter
Out-of-limit, the heavily loaded branch road of row and the sensitivity analysis of out-of-limit, heavily loaded stable cross section, carry out the sensitivity analysis of voltage out-of-limit node,
Decision-making foundation is provided for follow-up aid decision.
By security analysis functional module, analysis determines the static security operation level for checking section, is follow-up steady
Devise a stratagem is calculated and is checked and aid decision offer security analysis result.
By means of the project, system realizes that the management such as energy-saving distribution, economic load dispatching is required, realize plan a few days ago, in a few days roll
Scheduling, in a few days Real-Time Scheduling, AGC control four layers of dispatch coordination control model, realize scheduling side to the closed-loop control of Power Plant Side.
The Optimal Operation Model that the present invention is provided, general structure include：
1st, integrated supervision module
Integrated supervision module will collect in a few days real-time data of power grid, ultra-short term prediction data, in real time rolling optimization data, tune
The information such as degrees of data, by various advanced visual information way of presentation, from leader's focus, dispatcher's focus,
Enter row information tissue and analysis by business-subject, cover load, plan and generating, section, wind-powered electricity generation, installation scale, electricity contract
The aspects such as implementation status.
1) information on load monitoring submodule
Load prediction information, Extended short-term load prediction information, ultra-short term are shown with patterned way contrast
Information, actual electric network information on load, heating demand information etc..
2) plan and the monitoring submodule that generates electricity
Patterned way contrast shows plan information, rolling scheduling information, Real-Time Scheduling plan information, actual power a few days ago
Information etc.；Show all kinds of generation planning power generation situations, actual power situation, wind-powered electricity generation receive situation, wind-powered electricity generation ration the power supply situation, water power adjust
Peak situation.
3) straight tune section monitoring submodule
Show active power, the load condition of interconnection and important section.
4) wind power information monitoring submodule
Collect in a few days wind-powered electricity generation full detail, exerted oneself including ultra-short term wind power prediction, wind field in real time, wind field report plan letter
Breath, rolling optimization wind-powered electricity generation situation, Real-Time Scheduling wind-powered electricity generation situation, wind-powered electricity generation are rationed the power supply situation etc..
5) installation situation analysis submodule
Patterned way shows water power, thermoelectricity, wind-powered electricity generation installation scale and accounting situation, Long-term change trend situation.
6) plan analysis of performance submodule
It is analyzed with electricity contract, the higher plant information of overall planning performance, completion rate of the plan, plan
Relatively low plant information of completion rate etc..
2nd, rolling scheduling module
Rolling scheduling module, the rolling scheduling module are used for the information on load that predicted with Extended short-term prediction module and are
Basis, 1 hour is the startup cycle, makes full use of newest real time information and information of forecasting, to following 4 hours loads and generation schedule
Again predicted, and then day of revising that schedule module is predicted a few days ago preload and generation schedule a few days ago, gradually reduce a few days ago
The uncertainty of plan；
The rolling scheduling module includes：Tie line plan management submodule, ultra-short term wind power prediction submodule, extension
Short-term load forecasting submodule, constraint adjustment submodule, online rolling optimization submodule and Planning Directive issue submodule；
Tie line plan management submodule be used for providing following 1 day～3 days tie line plans import, replicate, modification,
Look facility；
The ultra-short term wind power prediction submodule was used for the actual value for adjusting wind power according to current electric grid, every 15 minutes
Provide the wind power prediction value of following 4 hours；System sets up interface with wind power prediction system, daily timing acquisition future four
The ultra-short term wind power prediction information of hour.
The Extended short-term load prediction submodule is used for：Predicted according to the ultra-short term wind power prediction submodule
Wind power prediction value, the load value after predicting current time on the same day in unknown 1 hour～many hours；Wherein, load value is with 15
Minute is least unit, and then carries out rolling amendment to generation schedule a few days ago；
The constraint adjustment submodule is used for providing all kinds of constraintss, including：The upper and lower bound constrained of unit output, unit are climbed
Ratio of slope constraint, start-up mode constraint, section tidal current constraint and account load balancing constraints；
The online rolling optimization submodule is used for：Optimisation strategy is formulated, the pact that submodule is provided is adjusted with the constraint
Beam condition is constraint, is tied with the prediction of the ultra-short term wind power prediction submodule and the Extended short-term load prediction submodule
Structure is input, carries out water power, thermoelectricity, cogeneration of heat and power, wind-powered electricity generation, the different unit generation of water-storage characteristic and exerts oneself the online rolling of situation
Dynamic optimization, obtains online rolling optimization result, including：Following wind field plans in 4 hours and rolling scheduling unit plan；
Algorithm input data includes：Real-time grid model, a few days ago information on load, implementation of the plan, ultra-short term wind power
Information of forecasting, Extended short-term load prediction information, the constraint of Plan rescheduling amount, the constraint of climbing rate, heating demand constrain, exert oneself up and down
Limit constraint, security constraint etc..In order to ensure the enforceability of rolling optimization result, will be all kinds of in rolling optimization program process
Constraints enters line algorithm computing as precondition, and the planned outcome simultaneously for algorithm output directly carries out online static peace
Whole school's core.
The Rolling optimal strategy that the rolling scheduling module is adopted for：Using the economic optimum that is abandoned based on minimum on the basis of wind
Scheduling model, is shown in formula (1)：
Wherein, f1(pit) it is scheduling model object function；T is the optimization time；t0For optimizing start periods；ThFor optimum meter
Draw layer and optimize Period Length；N is conventional power unit number；ai、bi、ciCoal consumption coefficient for conventional power unit i；pitIt is conventional power unit i
The active plan of exerting oneself of t periods；GwindFor Wind turbines number；λjFor abandoning wind cost factor；Pre- for Wind turbines Extended short-term
Measure power；For Wind turbines j the t periods the active plan of exerting oneself.
The Planning Directive issues submodule to be used for：The online rolling optimization that the online rolling optimization submodule is obtained
As a result rolling planning unit is issued to.
(3) Real-Time Scheduling module
The Real-Time Scheduling module is used for：With the prediction of ultra-short term power generation needs, wind power output prediction, electric network model and in real time
Based on data, it is within 15 minutes the startup cycle, in consideration unit output restriction, climbing rate, in the case of rolling generation schedule, formulates
To the actual power plan for planning unit in real time, so as to be predicted to following 15 minutes loads again and generation schedule adjustment,
The deviation of predicted value and planned value is eliminated, power grid wind access capability is improved, as coordinated scheduling plan and AGC controls and net
One link that forms a connecting link of network safety.
The Real-Time Scheduling module includes：Ultra-short term submodule, online Real-Time Scheduling submodule, safety on line
Check submodule and automatically under send instructions submodule；
The ultra-short term submodule, for adopting the ultra-short term based on load curve section morphic similarity to bear
Lotus Forecasting Methodology, goes out force data according to historical load, the Auto-matching similar period, obtains ultra-short term data；
The online Real-Time Scheduling submodule, for the rolling of the ultra-short term prediction data, the rolling scheduling module
Based on dynamic scheduling unit plan, preset constraints and optimisation strategy are precondition, carry out Unit Combination computing, with 15
Minute is the cycle, and following 15 minutes wind fields, exerting oneself for unit unit are predicted；Specifically, the Real-Time Scheduling module is adopted
Scheduling model with formula (2)：
f1(pit) it is scheduling model object function；T is the optimization time；t0For optimizing start periods；TlExcellent for basic point tracking layer
Change Period Length；N is conventional power unit number；ai、bi、ciCoal consumption coefficient for conventional power unit i；pitIt is conventional power unit i in the t periods
The active plan of exerting oneself；For i-th unit the t periods rolling optimal plan layer plan；ΔpitExist for i-th unit
The basic point of t periods follows the trail of plan adjustment amount, is controlled output amount；GwindFor Wind turbines number；λjFor abandoning wind cost factor；
Exert oneself for the prediction of Wind turbines Extended short-term；For Wind turbines j the t periods the active plan of exerting oneself.
The safety on line checks submodule, for based on current real-time grid model and ultra-short term prediction data, to institute
The Real-Time Scheduling planned outcome for stating online Real-Time Scheduling submodule is checked, while considering the out-of-limit situation of section, is obtained
Line scheduling predicts the outcome, including：Following 15 minutes wind fields, unit unit go out force data；
Described automatically under send instructions submodule, for same day residue period Real-Time Scheduling planned outcome is passed through integrated data
Platform, is issued to plan unit in real time, realizes the state control to plan unit in real time.
(4) AGC control modules
AGC control modules, for, in units of second level, being processed to the situation of the current generation of unit immediately in real time, being entered
And control exerting oneself for AGC units；Including Corrective control submodule and Security corrective control submodule；The Corrective control submodule
Block, for dispatching second level AGC unit, makes frequency and dominant eigenvalues meet CPS performance assessment criteria；The Security corrective controls submodule
Block, out-of-limit for instant process circuit section tidal current.
In practical application, the Security Checking function that system is provided needs to call to come from rolling scheduling module, Real-Time Scheduling
The generating set that module is generated is exerted oneself arrangement data, and check result under planned manner is exported.
Based in a few days newest electric network model, status information of equipment, information of forecasting, static security analysis are carried out to plan,
Analysis power network topology, calculates power transfer distribution factor of each generator to Line Flow, and statistical system congestion situations are hindered
Plug management.Build-in function include checking section automatically generate, tidal current analysis, static security analysis, sensitivity analysis etc., system is carried
Support 1 minute for security analysis algorithm operational efficiency.
1) check section to automatically generate
Check section intelligence systematic function according to repair schedule, generation schedule, short-term trading plan, interim operation information,
Equipment operation information, coupling system load prediction and bus load prediction, and nothing is obtained according to user setup or similar day trend
Work(information of voltage, and intelligent integration is carried out to above-mentioned data, carry out AC power flow and calculate to be formed for dissimilar Security Checking
The check section tidal current of demand, including operation task check section, repair schedule check section, generator plan check section and
Section is checked in short-term trading plan.
2) ground state tidal current analysis
Ground state tidal current analysis are analyzed calculating according to the check section tidal current for checking section intelligence systematic function formation, will
Calculation of tidal current is compared with limit, judges the out-of-limit situation of electrical network under ground state trend.Heave-load device and phase can be given
The load factor answered, out-of-limit equipment and out-of-limit percentage accordingly.The object of out-of-limit inspection includes what line current, section were transmitted
The voltage of power, the capacity of transformer branch and bus.
3) static security analysis
Static security analysis for the check section tidal current that section intelligence systematic function is formed is checked, check N-1 failures and
After the fault set that user specifies, whether other elements occur out-of-limit.
This functional module supports multiple specific modes for cut-offfing element, including being cut-off one by one, root to the whole network main equipment
Cut-off according to component type that (class generator, transformer's type, circuit class, wherein circuit can be further divided into 500kV again one by one
Circuit and 220kV circuits), cut-off according to electric pressure one by one, cut-off according to region one by one.In addition, user
Can also self-defined fault set as needed, only to fault set in element carry out N-1 analyses, judge whether other elements occur
Out-of-limit.
This functional module can be simulated prepared auto restart, be cut the automatic safety devices such as machine, can be according to power system operating mode Auto-matching
Policy Table.Can be given causes heavily loaded, out-of-limit failure and heavily loaded accordingly, out-of-limit equipment, should provide fault severity level index.
4) Analysis of Short-Circuit Current
Analysis of Short-Circuit Current is calculated according to the section check section tidal current that intelligently generation is formed is checked, by short circuit current flow meter
Calculate exceeded with the presence or absence of capacity of short circuit in judgement check section.The whole network busbar short-circuit fault scanning can be carried out, also can according to
Family setup algorithm scope carries out short trouble scanning, supports that selecting computer capacity to carry out short trouble by electric pressure and subregion sweeps
Retouch.
Single-phase earthing fault scanning can be divided into according to fault type and three phase short circuit fault is scanned.Short circuit current flow can be given
The result of calculation of exceeded and close exceeded short trouble, including each bus and line short circuit current and corresponding failure.
5) sensitivity analysis
Sensitivity analysis and is stablized according to the out-of-limit of static security analysis discovery, heave-load device for check section tidal current
Section, carries out the sensitivity analysis of out-of-limit, heavily loaded branch road and out-of-limit, heavily loaded stable cross section, carries out the sensitive of voltage out-of-limit node
Degree analysis.This functional module supports following function：
1) sensitivity between calculating branch road or stable cross section active power and generated power are exerted oneself.
2) other circuits after branch breaking distribution factor, i.e. circuit or transformer branch are cut-off or transformer efficiency are calculated
Situation of change.
3) spirit between busbar voltage and the idle injection of node (including generator node and capacity reactance device node) is calculated
Sensitivity, the sensitivity between busbar voltage and transformer voltage ratio.
4) support that new sensitivity is calculated.
6) plan is issued
Plan release module provides function includes that planning data transparent transmission function and planning data represent two parts.
Planning data transparent transmission:It is primarily referred to as system and interface is provided, the wind that rolling scheduling module, Real-Time Scheduling module are calculated
Field plan, water power plan, thermoelectricity plan, pumped-storage scheme are transferred to III areas through safety insulating device, enter with OMS
Line interface, in OMS carries out approval distributing, and is issued to power plant by OMS.In order to meet Planning Directive automatic under
The demand for reach, executing, system provide the function that all kinds of planning datas are issued to AGC system by integrated data platform.
Planning data represents
Leaders are directly viewable all kinds of planning datas and newest wind power prediction information in management great Qu for convenience,
System provides planning data viewing client-side, planning data, real time data and comparative analysis data is carried out with visualizing means
Intuitively, visually represent.
(5) recruitment evaluation module
Means are represented using abundant visualization, all kinds of benefits that brings is optimized to the different power supply collaboration of characteristic and is analyzed
And represent；Introduce the working effect for bringing to be analyzed and represent in a few days multi-period dispatch coordination mechanism.Recruitment evaluation theme
Including：Clean energy resource utilization power, energy-saving and emission-reduction situation, generated energy, economy, start-up mode and unit affect, wind-powered electricity generation examination
Etc. aspect.
1) power-generation analysis
Show that content includes planning a few days ago, generated energy constitutes situation under rolling scheduling, Real-Time Scheduling planned manner；All kinds of
Generated energy of the power supply under different planned manners is to when variation tendency；Clean energy resource utilization rate, reduction coal consumption amount, carbon emission
Deng macro-indicators information.
2) economic analysis
Show content include planning a few days ago, rolling optimization plan, under Real-Time Scheduling planned manner, purchases strategies constitute feelings
Condition；The purchases strategies of water, fire, wind-powered electricity generation under different planned manners are to when variation tendency.
3) start-up mode analysis
Show content include planning a few days ago, rolling optimization plan, under Real-Time Scheduling planned manner, the start feelings of all kinds of units
Condition contrast, number change of starting shooting, volume change of starting shooting, pay close attention to unit impact analysis, system reserve nargin change, adjustable machine
Pool-size analysis etc..
4) wind-powered electricity generation examination
Examination wind field plan is reported and implementation status.According to the management rule for pre-setting, the wind to same time scale
Field reports plan, ultra-short term wind power prediction information, wind-powered electricity generation rolling optimization information, the wind field actual power situation of exerting oneself to be contrasted
Show and index is calculated.
(6) system management module
System administration part provides function to be included：Basic data maintenance, user management, rights management, log management function.
Wherein：
Basic data maintenance
All kinds of basic datas that offer rolling optimization, Real-Time Scheduling need are (such as：The static state base such as power plant, unit, electricity contract
Plinth information) batch import and maintenance function, thermal power plant collect information include thermal power plant report unit climbing rate, cost function,
Go out power restriction, exert oneself by fire coal, for information such as heat affectings.
User management：Realize scheduling end subscriber, the Back ground Information of power plant's end subscriber, the maintenance and management of log-on message.
Rights management：Resource management, Role Management are provided, assign the functions such as power, accomplish system application safety, data access peace
Entirely.
System journal：To in system, between important operation and system interface, ruuning situation is tracked and records, it is easy to afterwards
Recollect.
The system can pass through the fortune for studying the different power supplys of characteristic such as wind-powered electricity generation, cogeneration units, Hydropower Unit, fired power generating unit
Row characteristic and the Influencing Mechanism to management and running, set up multi-period, multi-objective coordinated Optimal Operation Model；Using closed loop feedback
The various dimensions optimal dispatch decision-making technic of dynamic adjustment, with unit actual exert oneself, bus load, operation of power networks state and net
Based on network topological structure, through the Security Checking and congestion management of multi-period multiple constraint, it is considered to abandon the warp of wind, energy-saving and emission-reduction less
Ji benefit, realizes that in a few days operation plan rolls adjustment, real-time active balance and the multiple target rapid Optimum decision-making for coordinating control.Tool
Body reaches following effect：
1) system is based on the prediction of Extended short-term power generation needs, a few days ago plan information, to during from present period to 4 hours futures
Plan between section carries out rolling on-line optimization, in the formulation of rolling scheduling, can not only consider the warp for abandoning wind, energy-saving and emission-reduction less
Ji benefit, moreover it is possible to ensure the feasibility that each unit is exerted oneself in the remaining period, constrains including meeting unit climbing rate, and satisfaction generating-
Load power Constraints of Equilibrium, Network Security Constraints etc..
2) system can provide an a kind of controls in advance strategy with 15 minutes as cycle, generate electricity by scheduling slot establishment
Plan, predicts according to the power generation needs of next scheduling slot and wind power output prediction, it is considered to unit limit value, creep speed, rolling
In the case of dynamic generation schedule, on the basis of system safe and stable operation is met, automatic by energy-saving and emission-reduction, economy principle of optimality
Each unit actual power plan is arranged, the deviation of predicted value and planned value can be eliminated with look-ahead, improve power grid wind and access
Ability, used as coordinated scheduling plan and a link that forms a connecting link of AGC controls and network security.
3) system can be with CC2000, D5000, the existing scheduling such as planning system, wind power prediction system, OMS a few days ago automatically
Change system enters line interface, obtains in a few days information of forecasting, plan information, real time information, is that online Extended short-term prediction, ultra-short term are pre-
Survey, rolling optimization, Real-Time Scheduling control strategy provide data basis, form the closed loop management of wind field control.
4) system can the value brought of the online rolling optimization of the different unit of comparative analysis multiple target characteristic, Real-Time Scheduling and effect
Really, from a few days operation plan and control visual angle, using visualization technique means, towards different user groups, formed and in a few days believed
The synthesis of breath represents.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
Depending on protection scope of the present invention.
Claims (2)
1. a kind of the minimum active power dispatch model of wind is abandoned, it is characterised in that including following optimization object function and optimize constraint
Condition；
Wherein：
riIt is the current generating unit Setup Costs of conventional power unit i；
ΔpiFor the regulation total amount of exerting oneself of i-th conventional power unit subsequent time, it is controlled output amount；
wjBe that wind energy turbine set abandons wind power cost, wind is abandoned in order to reduce, wjNumerically current much larger than conventional power unit generating unit is adjusted
It is made into this ri；
It is that wind energy turbine set j abandons wind electric, equal to the wind power output predicted value of subsequent period predictionReal-time with subsequent period
Operation plan valueDifference；
NG cagcFor the whole network Real-Time Scheduling unit, the number of Wind turbines is not included
NG WindFor Wind turbines set；
Currently go out force value for wind energy turbine set j；
Exert oneself regulation total amounts of the Δ P for Real-Time Scheduling unit subsequent time：
Wherein,Be ultra-short term value increment,Be tie line plan subsequent time increment,It is day
Front plan unit output subsequent time increment；ΔPn AGCAmount was not completed for an AGC upper moment；
MintThe whole network circuit and intranet security power transmission section set is represented,For the power transmission upper limit of section,T j For section
Power transmission lower limit, TjFor the current transmission power of section, inequality constraints guarantee transmission section nonoverload；
SijUsing balancing the load sensitivity, wherein in order to reach partition balancing, introducing subregion in the bus load factor is needed to bear
The information of lotus prediction；
SkjIt is balancing the load sensitivity, △ Pk wIt is that wind energy turbine set k abandons wind-powered electricity generation amount, the product representation wind-powered electricity generation of two abandons wind-powered electricity generation amount to disconnected
The Real Time Effect of face power；
ΔCgjImpact of the planned regulation amount to section power for the unit of non real-time scheduling；
Above-mentioned object function is solved, the predicted value that exerts oneself to following wind field and unit unit is obtained.
2. the scheduling system for abandoning the minimum active power dispatch model of wind described in a kind of application claim 1, it is characterised in that include
Unit role's distribute module, rolling scheduling module, Real-Time Scheduling module and AGC control modules；
The minimum active power dispatch model of wind of abandoning is applied in Real-Time Scheduling module；
The unit role distribute module carries out the division of unit role using following steps：
Step 1, counts ACE according to historical data first and falls in the probability of each control zone, and the probability that order falls in dead band is
Pro1, the probability fallen within normal area are pro2, and the probability fallen in coordinated regions is pro3, fall urgent area and urgent area it
Outer probability is pro4, then have：
Step 2, the AGC units for participating in regulation ACE meet the requirement of total spinning reserve in each period, therefore, if in system
N platform units in have the AGC units that n platforms participate in ACE controls, 1≤n≤N, and the set being made up of n platform units and be designated as
SetA；The lower limit of spinning reserve should be given according to the practical operation situation of electrical network, is set as SRt, and its value have to be larger than ACEE；
Belonging to the n platform conventional racks of set SetA, to have 4 kinds of roles available, i.e.,：1 corresponding control module of unit role is
Bias adjustment；2 corresponding control model of unit role is planned in real time for tracking；3 corresponding control model of unit role is tracking
Rolling planning；4 corresponding control model of unit role is planned a few days ago for tracking；
Variable R oleID represents unit role, and value is 1,2,3,4, and corresponding control model is respectively：Bias adjustment, tracking are real
When plan, tracking rolling planning and tracking plan a few days ago；Its corresponding unit role is respectively：AGC units, Real-Time Scheduling machine
Group, rolling planning unit and a few days ago plan unit；
Gone out according to RoleID vectorial structures map therewith 4 vector Role (1), Role (2), Role (3), Role (4), be used for
Preserve the AGC unit subscripts that role is respectively 1,2,3,4；
Thus the object function for being building up to following optimization problem is：
Wherein：Pit：Unit i goes out force value in t；
ai：The secondary term coefficient of non-linear relation；
bi：The Monomial coefficient of non-linear relation；
ci：The constant term of non-linear relation；
d：Currently exert oneself worth correction factor；
Above-mentioned object function ensures that ACE of all AGC units for belonging to Role (j) in one day adjusts the expectation of total cost most
Little；
And need to ensure that ACE falls to having in regional enough AGC to adjust nargin after unit role distribution, therefore, produce
Following constraint：
sitFor i-th unit t spinning reserve；
Object function is solved under above-mentioned constraints, that is, obtain the AGC role of final determination.
The rolling scheduling module is used for：Based on planning, according to the load prediction results of electrical network Extended short-term model a few days ago
And Extended short-term wind-powered electricity generation predicts the outcome that unit generation plan goes out activity of force to rolling amendment a few days ago so that system generating gross capability power
Gradually approach with actual power demand, the unit generation plan for obtaining economic optimum is exerted oneself, and the unit by the economic optimum
Generation schedule is exerted oneself and acts on the rolling planning unit；
The Real-Time Scheduling module is used for：Exerted oneself as basic point power using the unit generation plan of economic optimum, super according to electrical network
Short-term load forecasting result and ultra-short term wind-powered electricity generation predict the outcome adjustment unit output, generate and enter to planning the system mode in the period
The Real-Time Scheduling correction Planning Directive of row minimum unit output adjustment, and the Real-Time Scheduling correction Planning Directive is acted on reality
When dispatch unit, and then eliminate that unit executes the calculated unbalanced power amount of economic optimum and the change at random of wind-powered electricity generation load is made
Into amount of unbalance；
The AGC control modules are used for：The Real-Time Scheduling correction Planning Directive be given using the Real-Time Scheduling module is used as control
Basic point, is revised in real time to the stochastic prediction error that advanced prediction link is produced, and is generated for being controlled to AGC units
AGC unit output adjust instructions, and the AGC unit outputs adjust instruction is issued to AGC units, realize to AGC units
Control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610835721.3A CN106505635B (en) | 2016-09-20 | 2016-09-20 | Active scheduling model and scheduling system with minimum wind abandon |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610835721.3A CN106505635B (en) | 2016-09-20 | 2016-09-20 | Active scheduling model and scheduling system with minimum wind abandon |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106505635A true CN106505635A (en) | 2017-03-15 |
| CN106505635B CN106505635B (en) | 2020-05-12 |
Family
ID=58290576
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610835721.3A Active CN106505635B (en) | 2016-09-20 | 2016-09-20 | Active scheduling model and scheduling system with minimum wind abandon |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106505635B (en) |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107196294A (en) * | 2017-06-16 | 2017-09-22 | 国网江苏省电力公司电力科学研究院 | Micro-capacitance sensor Multiple Time Scales adaptive energy dispatching method under the net load interaction pattern of source |
| CN107194514A (en) * | 2017-05-27 | 2017-09-22 | 重庆大学 | A kind of demand response Multiple Time Scales dispatching method for wind power prediction error |
| CN107732962A (en) * | 2017-09-29 | 2018-02-23 | 国网辽宁省电力有限公司 | It is a kind of to abandon wind decrement method based on what ultra-short term abandoned wind curve prediction |
| CN107846045A (en) * | 2017-11-28 | 2018-03-27 | 国网甘肃省电力公司电力科学研究院 | The control method that a kind of battery energy storage system tracing wind-light plan is contributed |
| CN108054787A (en) * | 2017-12-07 | 2018-05-18 | 国网天津市电力公司 | A kind of definite method of wind-powered electricity generation electric system AGC regulations speed demands |
| CN108173293A (en) * | 2017-12-25 | 2018-06-15 | 国电南瑞科技股份有限公司 | Meter and the new energy active power output maximum value on-line calculation method of operation of power networks constraint |
| CN108363295A (en) * | 2017-12-27 | 2018-08-03 | 国网山东省电力公司电力科学研究院 | Fired power generating unit AGC Performance Assessment indexs based on System Discrimination calculate and prediction technique |
| CN109361243A (en) * | 2018-10-08 | 2019-02-19 | 国网天津市电力公司电力科学研究院 | A kind of wind power station active power control method considering the substitution transaction of wind fire |
| CN109672218A (en) * | 2018-12-25 | 2019-04-23 | 新疆金风科技股份有限公司 | The Poewr control method and device of Wind turbines |
| CN110084401A (en) * | 2019-03-21 | 2019-08-02 | 中车工业研究院有限公司 | A kind of method for optimizing scheduling and device based on reserved maintenance time |
| CN110610251A (en) * | 2019-01-14 | 2019-12-24 | 华北电力大学 | Super-short-term scheduling plan robust optimization method for high-proportion wind power access power grid |
| CN111342446A (en) * | 2020-03-02 | 2020-06-26 | 国网天津市电力公司电力科学研究院 | Three-dimensional household intelligent energy-consumption ubiquitous scheduling control method and system |
| CN111342499A (en) * | 2020-03-05 | 2020-06-26 | 宁夏嘉泽新能源股份有限公司 | Wind power plant real-time scheduling method based on wind power prediction data |
| CN114297186A (en) * | 2021-12-30 | 2022-04-08 | 广西电网有限责任公司 | Power consumption data preprocessing method and system based on deviation coefficient |
| CN117117993A (en) * | 2023-08-25 | 2023-11-24 | 国家电网有限公司西南分部 | Advanced control method based on ultra-short-term power generation and load prediction |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102075014A (en) * | 2011-01-06 | 2011-05-25 | 清华大学 | Large grid real-time scheduling method for accepting access of wind power |
| CN102170170A (en) * | 2011-04-02 | 2011-08-31 | 清华大学 | Wind-power adsorption connected large-power-grid scheduling rolling planning method |
| CN104181895A (en) * | 2014-08-28 | 2014-12-03 | 国家电网公司 | Strategy for optimizing short-term and ultra-short-term coordination rolling schedules adapting to access of new energy resources |
| CN105633949A (en) * | 2015-12-14 | 2016-06-01 | 云南电网有限责任公司电力科学研究院 | Economic operation real-time power generation dispatching and control method |
-
2016
- 2016-09-20 CN CN201610835721.3A patent/CN106505635B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102075014A (en) * | 2011-01-06 | 2011-05-25 | 清华大学 | Large grid real-time scheduling method for accepting access of wind power |
| CN102170170A (en) * | 2011-04-02 | 2011-08-31 | 清华大学 | Wind-power adsorption connected large-power-grid scheduling rolling planning method |
| CN104181895A (en) * | 2014-08-28 | 2014-12-03 | 国家电网公司 | Strategy for optimizing short-term and ultra-short-term coordination rolling schedules adapting to access of new energy resources |
| CN105633949A (en) * | 2015-12-14 | 2016-06-01 | 云南电网有限责任公司电力科学研究院 | Economic operation real-time power generation dispatching and control method |
Non-Patent Citations (4)
| Title |
|---|
| 白晓民 等: "《大型互联电网在线运行可靠性评估、预警和决策支持***》", 31 December 2010, 清华大学出版社 * |
| 贵州电网有限责任公司: "《实时发电调度及其职能控制技术研发与应用》", 31 December 2014, 贵州大学出版社 * |
| 赵园 等: "山西电网日内电力平衡在线化", 《电力学报》 * |
| 陈建华 等: "消纳大规模风电的热电联产机组滚动调度策略", 《电力***自动化》 * |
Cited By (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107194514A (en) * | 2017-05-27 | 2017-09-22 | 重庆大学 | A kind of demand response Multiple Time Scales dispatching method for wind power prediction error |
| CN107196294A (en) * | 2017-06-16 | 2017-09-22 | 国网江苏省电力公司电力科学研究院 | Micro-capacitance sensor Multiple Time Scales adaptive energy dispatching method under the net load interaction pattern of source |
| CN107732962A (en) * | 2017-09-29 | 2018-02-23 | 国网辽宁省电力有限公司 | It is a kind of to abandon wind decrement method based on what ultra-short term abandoned wind curve prediction |
| CN107732962B (en) * | 2017-09-29 | 2020-12-01 | 国网辽宁省电力有限公司 | Abandoned wind reduction method based on ultra-short term abandoned wind curve prediction |
| CN107846045A (en) * | 2017-11-28 | 2018-03-27 | 国网甘肃省电力公司电力科学研究院 | The control method that a kind of battery energy storage system tracing wind-light plan is contributed |
| CN107846045B (en) * | 2017-11-28 | 2023-06-02 | 国网甘肃省电力公司电力科学研究院 | Control method for tracking wind-solar planned output of battery energy storage system |
| CN108054787A (en) * | 2017-12-07 | 2018-05-18 | 国网天津市电力公司 | A kind of definite method of wind-powered electricity generation electric system AGC regulations speed demands |
| CN108173293A (en) * | 2017-12-25 | 2018-06-15 | 国电南瑞科技股份有限公司 | Meter and the new energy active power output maximum value on-line calculation method of operation of power networks constraint |
| CN108173293B (en) * | 2017-12-25 | 2021-11-05 | 国电南瑞科技股份有限公司 | New energy active output maximum value on-line calculation method considering power grid operation constraint |
| CN108363295B (en) * | 2017-12-27 | 2020-11-13 | 国网山东省电力公司电力科学研究院 | Thermal power generating unit AGC performance assessment index calculation and prediction method based on system identification |
| CN108363295A (en) * | 2017-12-27 | 2018-08-03 | 国网山东省电力公司电力科学研究院 | Fired power generating unit AGC Performance Assessment indexs based on System Discrimination calculate and prediction technique |
| CN109361243B (en) * | 2018-10-08 | 2022-05-24 | 国网天津市电力公司电力科学研究院 | Wind power plant active power control method considering wind and fire substitution transaction |
| CN109361243A (en) * | 2018-10-08 | 2019-02-19 | 国网天津市电力公司电力科学研究院 | A kind of wind power station active power control method considering the substitution transaction of wind fire |
| CN109672218A (en) * | 2018-12-25 | 2019-04-23 | 新疆金风科技股份有限公司 | The Poewr control method and device of Wind turbines |
| CN110610251B (en) * | 2019-01-14 | 2024-06-07 | 华北电力大学 | Ultra-short-term scheduling plan robust optimization method for high-proportion wind power access power grid |
| CN110610251A (en) * | 2019-01-14 | 2019-12-24 | 华北电力大学 | Super-short-term scheduling plan robust optimization method for high-proportion wind power access power grid |
| CN110084401B (en) * | 2019-03-21 | 2021-04-23 | 中车工业研究院有限公司 | Scheduling optimization method and device based on reserved maintenance time |
| CN110084401A (en) * | 2019-03-21 | 2019-08-02 | 中车工业研究院有限公司 | A kind of method for optimizing scheduling and device based on reserved maintenance time |
| CN111342446B (en) * | 2020-03-02 | 2023-10-27 | 国网天津市电力公司电力科学研究院 | Three-dimensional household intelligent energy ubiquitous dispatching control method and system |
| CN111342446A (en) * | 2020-03-02 | 2020-06-26 | 国网天津市电力公司电力科学研究院 | Three-dimensional household intelligent energy-consumption ubiquitous scheduling control method and system |
| CN111342499A (en) * | 2020-03-05 | 2020-06-26 | 宁夏嘉泽新能源股份有限公司 | Wind power plant real-time scheduling method based on wind power prediction data |
| CN111342499B (en) * | 2020-03-05 | 2023-09-08 | 宁夏嘉泽新能源股份有限公司 | Wind farm real-time scheduling method based on wind power prediction data |
| CN114297186A (en) * | 2021-12-30 | 2022-04-08 | 广西电网有限责任公司 | Power consumption data preprocessing method and system based on deviation coefficient |
| CN114297186B (en) * | 2021-12-30 | 2024-04-26 | 广西电网有限责任公司 | Power consumption data preprocessing method and system based on deviation coefficient |
| CN117117993A (en) * | 2023-08-25 | 2023-11-24 | 国家电网有限公司西南分部 | Advanced control method based on ultra-short-term power generation and load prediction |
| CN117117993B (en) * | 2023-08-25 | 2024-04-19 | 国家电网有限公司西南分部 | Advanced control method based on ultra-short-term power generation and load prediction |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106505635B (en) | 2020-05-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106505635A (en) | Abandon the minimum active power dispatch model of wind and scheduling system | |
| CN106384168A (en) | Multi-objective coordinated optimization scheduling model for different power sources | |
| CN106682808A (en) | Online rolling optimization scheduling model | |
| Carli et al. | Robust optimal control for demand side management of multi-carrier microgrids | |
| Liu et al. | Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition: Challenges and future perspectives | |
| CN110957758B (en) | Comprehensive energy efficiency evaluation and control performance optimization method based on wide-area situation awareness | |
| Tan et al. | Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading | |
| CN111478312A (en) | Comprehensive energy cluster coordination control method for improving power grid stability | |
| Bahramara et al. | Co-optimization of energy and reserve in standalone micro-grid considering uncertainties | |
| Sharma et al. | A critical and comparative review of energy management strategies for microgrids | |
| Marino et al. | A chance-constrained two-stage stochastic programming model for reliable microgrid operations under power demand uncertainty | |
| CN104537428B (en) | One kind meter and the probabilistic economical operation appraisal procedure of wind power integration | |
| CN101232182A (en) | Three-dimensional coordinated electric network energy managing system and method for controlling and evaluating electric network | |
| Hou et al. | Data-driven robust day-ahead unit commitment model for hydro/thermal/wind/photovoltaic/nuclear power systems | |
| Alhelou et al. | Decision-making-based optimal generation-side secondary-reserve scheduling and optimal LFC in deregulated interconnected power system | |
| Liu et al. | Bi-level fuzzy stochastic expectation modelling and optimization for energy storage systems planning in virtual power plants | |
| Wang et al. | Dynamic economic dispatch considering transmission–distribution coordination and automatic regulation effect | |
| Scarabaggio et al. | Stochastic model predictive control of community energy storage under high renewable penetration | |
| Xie et al. | Online optimal power control of an offshore oil-platform power system | |
| Zhu et al. | Hierarchical cluster coordination control strategy for large-scale wind power based on model predictive control and improved multi-time-scale active power dispatching | |
| Singh et al. | Comparison between PID and PSO-PID controllers in analysing the load frequency control in interconnected microgrids in a deregulated environment | |
| Chakravarthi et al. | Real Time Line Power flow Control using Model Agnostic Controller | |
| Zhang et al. | Multi-Resource Collaborative Service Restoration of a Distribution Network with Decentralized Hierarchical Droop Control | |
| Shendryk et al. | Study of Structural Relationships and models of Information Support for Energy Life Cycle Management in Microgrid | |
| Zhao et al. | Two-stage data-driven dispatch for integrated power and natural gas systems by using stochastic model predictive control |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |