CN110224441A - Power Plant restores sequence optimizing method and device - Google Patents
Power Plant restores sequence optimizing method and device Download PDFInfo
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- CN110224441A CN110224441A CN201910533714.1A CN201910533714A CN110224441A CN 110224441 A CN110224441 A CN 110224441A CN 201910533714 A CN201910533714 A CN 201910533714A CN 110224441 A CN110224441 A CN 110224441A
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- 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
- H02J3/40—Synchronising a generator for connection to a network or to another generator
-
- 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
-
- 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]
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- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a kind of Power Plant and restores sequence optimizing method and device, the application is contributed sequence by the history power generating value and its prediction within a preset period of time that obtain the second class unit to be restored of power plant to be restored, start force parameter out to calculate the simulation of the second class unit to be restored within a preset period of time, and it obtains the default of first kind unit to be restored in power plant to be restored and starts force parameter out, to calculate sequence fitness when all first kind unit to be restored and all second class units to be restored carry out unit recovery according to different unit recovery sequences within a preset period of time based on genetic algorithm, and the maximum unit recovery sequence of selection sequence fitness, as the power plant to be restored in the preset time period corresponding best unit recovery sequence, the power plant to be restored is set to carry out unit recovery according to best unit recovery sequence When the generating capacity that is shown and the ability to ward off risks can be optimal state.
Description
Technical field
This application involves electric system service restoration technical fields, in particular to a kind of Power Plant recovery sequence
Optimization method and device.
Background technique
With the continuous development of science and technology, clean energy resource generating set is (for example, wind power plant generating set, hydroelectric generation
Unit etc.) because of clean and environmental protection the characteristics of, installation accounting in the power system is also being continuously improved.Currently, industry mainstream is right
It is to restore (including the cleaning of each generating set according to set unit recovery sequence when this kind of electric system carries out service restoration
Energy generator group and non-clean energy generating set) working condition.Wherein, different unit recovery sequences necessarily leads to electricity
Different situation, while the hair of clean energy resource generating set is presented in the generating capacity and the ability to ward off risks of Restoration stage in Force system
Electric energy power would generally change with the number of external generation assets, and set unit recovery sequence can not usually make electric power
System has good generating capacity and the ability to ward off risks in Restoration stage.Therefore, for electric system, how determining can make
The electric system is optimal the unit recovery sequence of state in the generating capacity and the ability to ward off risks of Restoration stage, is one
Particularly important problem.
Summary of the invention
In order to overcome above-mentioned deficiency in the prior art, the application's is designed to provide a kind of Power Plant recovery sequence
Optimization method and device is capable of determining that power plant to be restored corresponding best unit recovery sequence within a preset period of time, makes
The power plant to be restored is carrying out the generating capacity shown when unit recovery and anti-risk energy according to best unit recovery sequence
Power can be optimal state.
For method, the embodiment of the present application provides a kind of Power Plant recovery sequence optimizing method, which comprises
It obtains the default of each first kind unit to be restored in power plant to be restored and starts force parameter out and each second class waits for
The history power generating value and its prediction within a preset period of time for restoring unit are contributed sequence；
Prediction power output sequence according to the history power generating value of each second class unit to be restored and its within a preset period of time,
It calculates simulation of each second class unit to be restored in the preset time period and starts force parameter out；
According to the default force parameter out and each second class unit to be restored of starting of each first kind unit to be restored described pre-
If the simulation in the period starts force parameter out, all first kind units to be restored and all second classes are calculated based on genetic algorithm
Unit to be restored carries out sequence fitness when unit recovery in the preset time period according to different unit recovery sequences；
The maximum unit recovery sequence of selection sequence fitness, as first kind machines to be restored all in the power plant to be restored
Group and all second class units to be restored corresponding best unit recovery sequence in the preset time period.
For device, the embodiment of the present application provides a kind of Power Plant recovery sequence optimizing device, and described device includes:
Power output data acquisition module, for obtaining default the starting out of each first kind unit to be restored in power plant to be restored
The history power generating value of force parameter and each second class unit to be restored and its prediction within a preset period of time are contributed sequence；
Power output parameter determination module, for the history power generating value according to each second class unit to be restored and its when default
Between prediction in section contribute sequence, calculate simulation starting power output ginseng of each second class unit to be restored in the preset time period
Number；
Sequence fitness computing module, for starting force parameter out and each according to the default of each first kind unit to be restored
Simulation of the two classes unit to be restored in the preset time period starts force parameter out, calculates all first kind based on genetic algorithm
Unit to be restored and all second class units to be restored carry out machine according to different unit recovery sequences in the preset time period
Sequence fitness when group is restored；
Optimal recovery sequence determining module, for selection sequence fitness maximum unit recovery sequence, as this wait for it is extensive
Send a telegram in reply in factory all first kind units to be restored and all second class units to be restored in the preset time period it is corresponding most
Good unit recovery sequence.
In terms of existing technologies, the application has the advantages that
The application is by obtaining the history power generating value of the second class unit to be restored in power plant to be restored and its when default
Between prediction in section contribute sequence, to calculate simulation starting power output ginseng of the second class unit to be restored in the preset time period
Number, and obtain the default of first kind unit to be restored in power plant to be restored and start force parameter out, to be waited for according to the first kind extensive
The default simulation starting power output ginseng for starting force parameter out and the second class unit to be restored in the preset time period for group of answering a pager's call
Number calculates all first kind units to be restored and all second class units to be restored in the preset time period based on genetic algorithm
Interior sequence fitness when carrying out unit recovery according to different unit recoveries sequence, and the maximum unit of selection sequence fitness is extensive
Multiple sequence, as the power plant to be restored, corresponding best unit recovery sequentially, makes the electricity to be restored in the preset time period
Factory can reach in the generating capacity and the ability to ward off risks for shown when unit recovery according to best unit recovery sequence
Optimum state.Wherein, first kind unit to be restored is the non-clean energy generating set to be restored in power plant to be restored,
The second class unit to be restored is the clean energy resource generating set to be restored in power plant to be restored.
To enable the above objects, features, and advantages of the application to be clearer and more comprehensible, the application preferred embodiment is cited below particularly,
And cooperate appended attached drawing, it is described in detail below.
Detailed description of the invention
Technical solution in ord to more clearly illustrate embodiments of the present application, below will be to needed in the embodiment attached
Figure is briefly described, it should be understood that the following drawings illustrates only some embodiments of the application, therefore is not construed as pair
The restriction of the application protection scope, for those of ordinary skill in the art, without creative efforts, also
Other relevant attached drawings can be obtained according to these attached drawings.
Fig. 1 is the structure block diagram provided by the embodiments of the present application for calculating equipment；
Fig. 2 is the flow diagram that Power Plant provided by the embodiments of the present application restores sequence optimizing method；
Fig. 3 is the flow diagram for the sub-step that the step S220 in Fig. 2 includes；
Fig. 4 is the relation schematic diagram provided by the embodiments of the present application started between force parameter out and recovery moment collection；
Fig. 5 is the functional block diagram that Power Plant provided by the embodiments of the present application restores sequence optimizing device；
Fig. 6 is the functional block diagram of the power output parameter determination module in Fig. 5；
Fig. 7 is the functional block diagram of the sequence fitness computing module in Fig. 5.
Icon: 10- calculates equipment；11- memory；12- processor；13- communication unit；100- Power Plant recovery sequence
Optimize device；110- power output data acquisition module；120- power output parameter determination module；130- sequence fitness computing module；
140- optimal recovery sequence determining module；121- power output sequential extraction procedures submodule；122- numerical characteristic computational submodule；123- cloud
Similarity calculation submodule；124- simulated series construct submodule；125- simulation power generating value determines submodule；126- simulates load
It is worth and determines submodule；131- moment collection determines submodule；132- fitness computational submodule.
Specific embodiment
To keep the purposes, technical schemes and advantages of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.The application being usually described and illustrated herein in the accompanying drawings is implemented
The component of example can be arranged and be designed with a variety of different configurations.
Therefore, the detailed description of the embodiments herein provided in the accompanying drawings is not intended to limit below claimed
Scope of the present application, but be merely representative of the selected embodiment of the application.Based on the embodiment in the application, this field is common
Technical staff's every other embodiment obtained without creative efforts belongs to the model of the application protection
It encloses.
It should also be noted that similar label and letter indicate similar terms in following attached drawing, therefore, once a certain Xiang Yi
It is defined in a attached drawing, does not then need that it is further defined and explained in subsequent attached drawing.
In the description of the present application, it should be noted that term " first ", " second ", " third " etc. are only used for distinguishing and retouch
It states, is not understood to indicate or imply relative importance.It for the ordinary skill in the art, can be with concrete condition
Understand the concrete meaning of above-mentioned term in this application.
With reference to the accompanying drawing, it elaborates to some embodiments of the application.In the absence of conflict, following
Feature in embodiment and embodiment can be combined with each other.
Fig. 1 is please referred to, Fig. 1 is the structure block diagram provided by the embodiments of the present application for calculating equipment 10.In the application
In embodiment, the calculating equipment 10 can be determined when it carries out unit recovery within a preset period of time for power plant to be restored
Best unit recovery sequence, the power generation for showing the power plant to be restored in the corresponding unit recovering process of the preset time period
Ability and the ability to ward off risks are optimal state.Wherein, the preset time period can be the power failure moment from power plant to be restored
The period of the interval preset duration risen is also possible to some duration during the power plant to be restored carries out service restoration
Equal to the period of preset duration, the preset duration be can be 4 hours, is also possible to 8 hours, can also be 6 hours, specifically
Duration numerical value can carry out different configurations according to demand；The power plant to be restored includes at least one first kind unit and at least
One the second class unit, wherein the first kind unit is the non-clean energy generating set in power plant to be restored (for example, thermoelectricity
Generating set), the second class unit be power plant to be restored in clean energy resource generating set (for example, wind power plant generating set,
Hydro-generating Unit, photovoltaic power generation unit)；The calculating equipment 10 may be, but not limited to, server, mobile terminal, individual
Computer (personal computer, PC), tablet computer, personal digital assistant (personal digital assistant,
PDA), mobile internet surfing equipment (mobile Internet device, MID) etc..
In the embodiment of the present application, the calculating equipment 10 includes that Power Plant restores sequence optimizing device 100, memory
11, processor 12 and communication unit 13.The memory 11, the processor 12 and each element of the communication unit 13 are mutual
Between be directly or indirectly electrically connected, to realize the transmission or interaction of data.For example, the memory 11, the processor
12 and the communication unit 13 these elements can be realized by one or more communication bus or signal wire electrically connect between each other
It connects.
In the present embodiment, the memory 11 can be used for storing the distribution situation letter of all units in power plant to be restored
Route distribution situation information between breath and any two unit.The memory 11 can also be used to store the electricity to be restored
The default starting of every route each first kind unit in the operational risk value and the power plant to be restored when being resumed in factory
Out in force parameter and the power plant to be restored each second class unit default subsidiary engine load value, default start out wherein described
Force parameter includes that the default unit output value of corresponding first kind unit and default subsidiary engine load value, the default unit output value are used
In indicating effective output performance number of the corresponding unit when operating normally, the default subsidiary engine load value is for indicating corresponding unit
The load power value applied on startup by subsidiary engine, the operational risk value are used to indicate risk when corresponding line is resumed
Size.Wherein operational risk value can be used following formula to be indicated:
wm=bm+cL
Wherein, wmIndicate the operational risk value of the m articles route, bmIndicate the m articles route by reduction to unified voltage class
Susceptance over the ground when lower, cLIndicate value-at-risk when corresponding line carries out line switching combined floodgate.
In the present embodiment, the memory 11 can also be used to store program, and the processor 12 refers to receiving execution
After order, described program can be correspondingly executed.Wherein, the memory 11 may be, but not limited to, random access memory
(Random Access Memory, RAM), read-only memory (Read Only Memory, ROM), programmable read only memory
(Programmable Read-Only Memory, PROM), erasable read-only memory (Erasable Programmable
Read-Only Memory, EPROM), electricallyerasable ROM (EEROM) (Electric Erasable Programmable
Read-Only Memory, EEPROM) etc..
In the present embodiment, the processor 12 can be a kind of IC chip of processing capacity with signal.
The processor 12 can be general processor, including central processing unit (Central Processing Unit, CPU) and net
Network processor (Network Processor, NP) etc..General processor can be microprocessor or the processor is also possible to
Any conventional processor etc., may be implemented or execute disclosed each method, step and the logical box in the embodiment of the present application
Figure.
In the present embodiment, the communication unit 13 is used to establish the calculating equipment by cable network or wireless network
Communication connection between 10 and other electronic equipments, and pass through the network sending and receiving data.For example, the calculating equipment 10 passes through
The communication unit 13 obtains the relevant information of power plant to be restored.
In the present embodiment, the Power Plant restore sequence optimizing device 100 include at least one can with software or
The form of firmware is stored in the memory 11 or is solidificated in the software function mould in the operating system for calculating equipment 10
Block.The processor 12 can be used for executing the executable module that the memory 11 stores, such as the Power Plant restores suitable
Sequence optimizes software function module and computer program etc. included by device 100.
It is understood that block diagram shown in FIG. 1 is only a kind of structure composition schematic diagram for calculating equipment 10, institute
Stating calculating equipment 10 may also include the more perhaps less component than shown in Fig. 1 or matches with different from shown in Fig. 1
It sets.Each component shown in Fig. 1 can be realized using hardware, software, or its combination.
Referring to figure 2., Fig. 2 is the process signal that Power Plant provided by the embodiments of the present application restores sequence optimizing method
Figure.In the embodiment of the present application, the Power Plant restores sequence optimizing method and is applied to above-mentioned calculating equipment 10, below it is right
Power Plant shown in Fig. 2 restores the detailed process of sequence optimizing method and step is described in detail.
Step S210 obtains the default of each first kind unit to be restored in power plant to be restored and starts force parameter out, and
The history power generating value of each second class unit to be restored and its prediction within a preset period of time are contributed sequence.
In the present embodiment, first kind unit to be restored is to need to carry out unit recovery in the power plant to be restored
First kind unit, the second class unit to be restored are the second class machine for needing to carry out unit recovery in the power plant to be restored
Group.The history power generating value is when corresponding second class unit to be restored operates normally in historical time section according to preset time
It is spaced the effective output performance number extracted.The prediction power output sequence is the second class of correspondence unit to be restored of prediction described pre-
If according to the set of the effective output performance number of prefixed time interval output in the period.Wherein, the historical time section is corresponding
Duration be greater than the corresponding duration of the preset time period, the prefixed time interval can be 15min, is also possible to 20min,
It can also be that 4min, specific prefixed time interval numerical value can carry out different configurations according to demand.
Step S220, prediction according to the history power generating value of each second class unit to be restored and its within a preset period of time
Power output sequence calculates simulation of each second class unit to be restored in the preset time period and starts force parameter out.
In the present embodiment, it is to be restored that each second class can be calculated in the calculating equipment 10 according to cloud similarity algorithm
Simulation of the unit in the preset time period starts force parameter out, wherein it includes corresponding second that the simulation, which starts force parameter out,
The simulation unit power generating value and simulation subsidiary engine load value of class unit to be restored.
Optionally, referring to figure 3., Fig. 3 is the flow diagram for the sub-step that the step S220 in Fig. 2 includes.In this reality
It applies in example, the step S220 includes sub-step S221, sub-step S222, sub-step S223, sub-step S224, sub-step S225
And sub-step S226.
Sub-step S221, for each second class unit to be restored, from the history power generating value of the second class unit to be restored,
Extract multiple groups power output duration history power output sequence identical with duration corresponding to the preset time period.
In the present embodiment, for each second class unit to be restored, the calculating equipment 10 will be preset according to described
Period corresponding duration extracts multiple groups history power output sequence from the history power generating value of the second class unit to be restored,
In every group of history power output sequence include corresponding second class unit to be restored corresponding to the power output duration and the preset time period
In the period of duration, according to the history effective output performance number of prefixed time interval output.
Sub-step S222, the prediction power output sequence and history power output sequence for calculating the second class unit to be restored respectively correspond to
Cloud model numerical characteristic.
In the present embodiment, the cloud model numerical characteristic of a power output sequence can use C (Ex,En,He) indicate.Wherein, ExFor
The mathematic expectaion of corresponding power output sequence indicates the size of the average effective power output performance number of corresponding power output sequence；EnTo correspond to
The entropy of power sequence indicates the random probability distribution situation and ambiguity of corresponding power output sequence；HeFor the super entropy of corresponding power output sequence,
Indicate the uncertainty measure of the entropy of corresponding power output sequence.
In the present embodiment, the equipment 10 that calculates can be by seeking each effective output performance number in corresponding power output sequence
Average value obtains corresponding Ex。
In the present embodiment, the calculating equipment 10 can extract a by carrying out random repeatable sampling to the power output sequence
Group sample, n sample point of every group of sampling, and the variance of every group of sample is calculated, wherein the variance can be used following formula to carry out
It indicates:
Wherein, PwijIndicate the effective output performance number of the sample point j in i-th group of sample, i=1~a, j=1~n, var
Function is sample variance function.
Then, corresponding E will be calculated in the calculating equipment 10 according to the following formulanAnd He, wherein mean function is flat
Mean function:
In the present embodiment, the calculating equipment 10 calculates the second class machine to be restored by using above three formula
The prediction power output sequence and the history power output corresponding cloud model numerical characteristic of sequence of group.
Step S223 calculates the cloud model numerical characteristic of the prediction power output sequence, with each history power output sequence
Cloud model numerical characteristic between cloud similarity.
In the present embodiment, the equipment 10 that calculates is obtaining the cloud model numerical characteristic C of two power output sequences1(Ex1,
En1,He1) and C2(Ex2,En2,He2), and when need to calculate the cloud similarity between the two cloud model numerical characteristics, it can be used as follows
Calculate the intersection point x that formula calculates the expectation curve of the two cloud model numerical characteristics1And x2, and then calculate the two cloud model numbers
Expectation curve overlapping area S between word feature.Wherein, about x1And x2Calculating formula it is as follows:
Then, the calculating equipment 10 will calculate C according to following equation1(Ex1,En1,He1) and C2(Ex2,En2,He2) between
Cloud similarity Sim:
Wherein, C1For C1(Ex1,En1,He1) abbreviation, C2For C2(Ex2,En2,He2) abbreviation.
In the present embodiment, the cloud mould for calculating equipment 10 and calculating the prediction power output sequence according to above-mentioned two formula
Cloud similarity between type numerical characteristic, and the cloud model numerical characteristic of each history power output sequence.
Sub-step S224 chooses cloud similarity and is not less than in each history power output sequence of default similarity threshold most
Minimum prediction power generating value in small history power generating value and the prediction power output sequence, building form corresponding simulation power output sequence.
In the present embodiment, when the calculating equipment 10 calculates each history power output sequence and prediction power output sequence
Between cloud similarity after, the corresponding cloud similarity of sequence that each history can be contributed compare with default cloud similarity threshold
Compared with determining that cloud similarity is not less than each history power output sequence of default similarity threshold, and extract the cloud similarity determined
Not less than the minimum history power output performance number and prediction power output sequence in each history of default similarity threshold power output sequence
In minimum predict activity of force value, building forms corresponding simulation power output sequence, wherein described in simulate it is each in power sequence
Power output performance number is arranged in the way of descending.
Sub-step S225 chooses corresponding power generating value from simulation power output sequence according to default confidence level, as this
Simulation unit power generating value of the second class unit to be restored in the preset time period.
In the present embodiment, the calculating equipment 10 by will the default confidence level and the simulation power output sequence in
The number for performance number of contributing carries out product calculation, and chooses corresponding power output in simulation power output sequence with the numerical value that operation obtains
Performance number, as simulation unit power generating value of the second class unit to be restored in the preset time period.Wherein, it is selected
Position of the power output performance number in the simulation power output sequence is corresponded to each other with the numerical value that the operation obtains.In the present embodiment
In a kind of embodiment, the numerical value of the default confidence level is 1, then the simulation unit power generating value is that corresponding simulation is contributed sequence
The smallest power output performance number of numerical value in column.
Sub-step S226, with the default subsidiary engine load value of the second class unit to be restored, as the second class machine to be restored
Simulation subsidiary engine load value of the group in the preset time period.
In the present embodiment, the calculating equipment 10 will be directly corresponding default by each second class unit to be restored itself
Subsidiary engine load value, as simulation subsidiary engine load value of the second class unit to be restored in the preset time period.
Referring once again to Fig. 2, step S230, default according to each first kind unit to be restored starts force parameter out and each
Simulation of the two classes unit to be restored in the preset time period starts force parameter out, calculates all first kind based on genetic algorithm
Unit to be restored and all second class units to be restored carry out machine according to different unit recovery sequences in the preset time period
Sequence fitness when group is restored.
In the present embodiment, the sequence fitness is for indicating that corresponding unit recovery sequence is shown in genetic algorithm
Fitness relevant to generated energy and rack different degree.The calculating equipment 10 can determine that this is to be restored based on genetic algorithm
All first kind unit to be restored and all second class units to be restored in power plant are in the preset time period according to difference
Sequence fitness when unit recovery sequence carries out unit recovery then shows to make wherein the numerical value of the sequence fitness is bigger
The power plant to be restored is carrying out the generating capacity shown when unit recovery and anti-risk according to corresponding unit recovery sequence
Ability is better.
Optionally, the calculating equipment 10 is based on genetic algorithm and calculates all first kind units to be restored and all second classes
Sequence fitness when unit to be restored carries out unit recovery in the preset time period according to different unit recoveries sequence
Step, comprising:
The genetic algorithm parameter using unit recovery sequence as chromosome is improved by generation, and is completed in each improve
When, it determines each unit recovery sequence under current genetic algorithm parameter, determines corresponding to each unit recovery sequence and own
The recovery moment collection of unit to be restored, and sequence fitness corresponding to each unit recovery sequence is calculated, until continuous default
Unit recovery sequence under the genetic algorithm parameter of algebra is consistent.
In the present embodiment, the evolutional operation of improved adaptive GA-IAGA parameter includes: selection operation, crossover operation, variation behaviour
Make and evolve to reverse operation.The calculating equipment 10 can realize these evolution by using Sheffield GAs Toolbox
Operation, wherein the calculating equipment 10 is by using the rws function (roulette algorithm) in Sheffield GAs Toolbox
It realizes selection operation, is realized using the xovsp function (single point crossing algorithm) in Sheffield GAs Toolbox and intersect behaviour
Make, mutation operation is realized using the mut function (discrete variation algorithm) in Sheffield GAs Toolbox.It wherein, is guarantor
The individual difference never more optimal than parent of optimum individual corresponding to filial generation is demonstrate,proved, elite reservation can be used in the calculating equipment 10
Strategy restores suitable to leave the sequence fitness in each unit recovery sequence corresponding to parent greater than the unit of fitness threshold value
Sequence, and each unit recovery sequence corresponding to filial generation is gone out with the unit recovery sequence guidance confirmation left.Wherein, the default generation
Several numerical value is not less than 3.
In the present embodiment, it is described calculate equipment 10 determine each genetic algorithm parameter improve when completing with it is current
After the corresponding each unit recovery sequence of genetic algorithm parameter, determine that the unit recovery sequence is right according to each unit recovery sequence
Recovery moment collection of all units to be restored answered in the preset time period.Wherein, all units to be restored include
All first kind unit to be restored and all second class units to be restored in the power plant to be restored, the recovery moment collection are available
tgen=[tp,tm,tg,tn] be indicated, tpIndicate that the scheduling of corresponding unit to be restored is ordered Startup time, tmIndicate it is corresponding to
The subsidiary engine for restoring unit charges moment, tgIndicate the grid-connected on-load moment of corresponding unit to be restored, tnIndicate corresponding machine to be restored
At the time of group climbing reaches corresponding unit output value, tpWith tmBetween time interval be to be held to restore the unit to be restored
Capable closing operation, charge path and the total time cost for putting into pressure stabilizing load, tmWith tgBetween time interval be corresponding to extensive
The starting used time for group of answering a pager's call, tgWith tnBetween time interval be corresponding unit to be restored the climbing used time, specifically can refer to figure
Shown in 4.
Optionally, the step of the recovery moment collection of all units to be restored corresponding to each unit recovery sequence of the determination
Suddenly, comprising:
For each unit recovery sequence, successively determines in the power plant to be restored and charged according to the unit recovery sequence
The most short restoration path for being used to indicate path recovery operation least risk between region and each unit to be restored；
When determining the corresponding most short restoration path of a unit to be restored every time, by the most short restoration path and should be to
Restore unit to be added in the charging zone, and according to the starting for being added into the unit to be restored of charging zone
Force parameter calculates corresponding recovery moment collection out.
Wherein, the charging zone is the power plant to be restored when carrying out unit recovery according to corresponding unit recovery sequence
It is assumed that the unit being resumed and route set.The calculating equipment 10, can be with after determining a unit recovery sequence
In the power plant to be restored that the calculating equipment 10 currently determines on the basis of charging zone, determined according to unit recovery sequence
Most short restoration path between the charging zone and next unit to be restored.Wherein, the most short restoration path can indicate
The sum of recovery operation value-at-risk of all routes to be restored minimum involved by respective path, the calculating equipment 10 can be used
Dijkstra's algorithm determines line corresponding to every restoration path between charging zone and next unit to be restored
Road recovery operation risk total value, and the access line the smallest restoration path of recovery operation risk total value is as corresponding most short recovery
Path.
It, can be to be restored by this when the calculating equipment 10 is after determining a unit to be restored corresponding most short restoration path
Unit and corresponding most short restoration path are added into the charging zone, and based on the trend in the tool box matpower
It calculates, to determine that it is negative that the unit to be restored and corresponding most short restoration path are added into pressure stabilizing needed for the charging zone
The investment point and input amount of lotus then determine the recovery moment collection of the unit to be restored according to every recovery operation typical used time
In tpWith tm, wherein tpWith tmBetween time interval summation operation carried out by every recovery operation typical used time obtain.
Then, the calculating equipment 10 is asked according to the typical cylinder temperature of the unit to be restored and the corresponding relationship between the unit starting used time
Obtain the t for restoring moment concentration of the unit to be restoredg, and t according to Fig.4,gWith tnBetween time interval and this is to be restored
The corresponding relationship for starting force parameter out of unit calculates the t for restoring moment concentration of the unit to be restoredn.Wherein, the tgWith
tnBetween time interval (P can be usedn+Pcr)/CrIt is calculated, wherein PnIndicate the unit output value of corresponding unit to be restored,
PcrIndicate the subsidiary engine load value of corresponding unit to be restored, CrIndicate the creep speed of corresponding unit to be restored.
Wherein, it if some unit to be restored for being accessed charging zone is first kind unit to be restored, is accessed
The P of the unit to be restored of charging zonenIt, should be to extensive for its corresponding default default unit output value started in force parameter out
The P for group of answering a pager's callcrFor its corresponding default default subsidiary engine load value started in force parameter out.
If some unit to be restored for being accessed charging zone is the second class unit to be restored, live zone is accessed
The P of the unit to be restored in domainnStart the simulation unit power generating value in force parameter out, the unit to be restored for its corresponding simulation
PcrStart the simulation subsidiary engine load value in force parameter out for its corresponding simulation.
Optionally, the step of calculating equipment 10 calculates sequence fitness corresponding to each unit recovery sequence, packet
It includes:
For each unit recovery sequence, force parameter is gone out according to the starting of each unit to be restored under the unit recovery sequence
And restore moment collection, generated energy of each unit to be restored in the unit recovery sequence in the preset time period is calculated, is obtained
To total power generation corresponding with the unit recovery sequence；
According to the route distribution situation and unit distribution situation of power generation region corresponding with the unit recovery sequence, calculate
The corresponding rack different degree of unit recovery sequence；
The corresponding total power generation of unit recovery sequence and rack different degree are subjected to multiplying, obtain corresponding sequence
Fitness.
In the present embodiment, generated energy of the unit to be restored in the preset time period can be used following formula to carry out
It indicates:
Wherein, t0Indicate current time, T indicates the corresponding duration of the preset time period, PG(t) indicate that correspondence is to be restored
Active power output power function of the unit in different moments.PG(t) following formula can be used to be indicated:
The calculating equipment 10 can calculate each unit to be restored in each unit recovery sequence according to above-mentioned two formula
Generated energy in the preset time period, and exist for calculated each unit to be restored corresponding with the unit recovery sequence
Generated energy in the preset time period carries out summation operation, obtains total power generation corresponding with the unit recovery sequence.
It in the present embodiment, can be according to such as following formula after determining a unit recovery sequence corresponding power generation region
Son calculates the corresponding rack different degree of unit recovery sequence；
Wherein, K is the rack different degree of corresponding unit recovery sequence, ndFor in rack corresponding to the unit recovery sequence
Unit number to be restored, nlFor the number of lines to be restored in rack corresponding to the unit recovery sequence, dkIt is to be restored for k-th
The unit different degree of unit, LmFor the route different degree of the m articles route to be restored, c1It is important relative to route for unit different degree
The significance level of degree.
Wherein, the unit different degree d of k-th of unit to be restoredkAnd the route different degree L of the m articles route to be restoredmIt can divide
It is not indicated with following formula:
Wherein, N is the unit to be restored sum in corresponding rack, and i, j, k are machine group #, NijIt is arrived for unit i to be restored
The most short restoration path sum of unit j to be restored,For this NijBy the most short of unit k to be restored in the most short restoration path of item
Restoration path number.
Step S240, the maximum unit recovery sequence of selection sequence fitness, as in the power plant to be restored all first
Class unit to be restored and all second class units to be restored corresponding best unit recovery sequence in the preset time period.
In the present embodiment, the calculating equipment 10 is chosen suitable from each unit recovery sequence obtained based on genetic algorithm
The maximum unit recovery sequence of sequence fitness, as first kind units to be restored all in the power plant to be restored and all second classes
Unit to be restored corresponding best unit recovery sequence in the preset time period so that the power plant to be restored according to
Best unit recovery sequence, which carries out the generating capacity shown when unit recovery and the ability to ward off risks, can be optimal state.
Wherein, route recovery involved by the best unit recovery sequence can reduce power plant to be restored as much as possible and restore
Recovery risk in journey, while the best unit recovery sequence can improve hair of the power plant to be restored in recovery process as much as possible
Electric energy power.
Referring to figure 5., Fig. 5 is the function mould that Power Plant provided by the embodiments of the present application restores sequence optimizing device 100
Block schematic diagram.In the embodiment of the present application, it includes power output data acquisition module that the Power Plant, which restores sequence optimizing device 100,
110, power output parameter determination module 120, sequence fitness computing module 130 and optimal recovery sequence determining module 140.
The power output data acquisition module 110, for obtaining the pre- of each first kind unit to be restored in power plant to be restored
If start force parameter out and each second class unit to be restored history power generating value and its within a preset period of time prediction power output
Sequence.
The power output parameter determination module 120, for according to the history power generating value of each second class unit to be restored and its
Prediction power output sequence within a preset period of time, calculates simulation of each second class unit to be restored in the preset time period and opens
Dynamic force parameter out.
Optionally, Fig. 6 is please referred to, Fig. 6 is the functional block diagram of the power output parameter determination module 120 in Fig. 5.At this
In embodiment, start the unit output value and subsidiary engine load value that force parameter out includes corresponding unit, the force parameter out determines mould
Block 120 includes:
Power output sequential extraction procedures submodule 121, for being directed to each second class unit to be restored, from the second class machine to be restored
The history power generating value of group extracts multiple groups power output duration history power output sequence identical with duration corresponding to the preset time period
Column.
Numerical characteristic computational submodule 122, for calculating the prediction power output sequence and history of the second class unit to be restored
The power output corresponding cloud model numerical characteristic of sequence.
Cloud similarity calculation submodule 123, it is and each for calculating the cloud model numerical characteristic of the prediction power output sequence
Cloud similarity between the cloud model numerical characteristic of the history power output sequence.
Simulated series construct submodule 124, and being not less than each of default similarity threshold for choosing cloud similarity described goes through
Minimum history power generating value and the minimum prediction power generating value predicted in power output sequence in history power output sequence, construct formation pair
The simulation power output sequence answered, wherein each power generating value descending arrangement simulated in power sequence.
Simulation power generating value determines submodule 125, for according to the selection pair from simulation power output sequence of default confidence level
The power generating value answered, as simulation unit power generating value of the second class unit to be restored in the preset time period.
Simulation load value determines submodule 126, for the default subsidiary engine load value of the second class unit to be restored, as
Simulation subsidiary engine load value of the second class unit to be restored in the preset time period.
The sequence fitness computing module 130 is joined for being contributed according to the default starting of each first kind unit to be restored
Simulation of several and each second class unit to be restored in the preset time period starts force parameter out, calculates institute based on genetic algorithm
There are first kind unit to be restored and all second class units to be restored to restore suitable according to different units in the preset time period
Sequence carries out sequence fitness when unit recovery.
Wherein, the sequence fitness computing module 130 is specifically used for:
The genetic algorithm parameter using unit recovery sequence as chromosome is improved by generation, and is completed in each improve
When, it determines each unit recovery sequence under current genetic algorithm parameter, determines corresponding to each unit recovery sequence and own
The recovery moment collection of unit to be restored, and sequence fitness corresponding to each unit recovery sequence is calculated, until continuous default
Unit recovery sequence under the genetic algorithm parameter of algebra is consistent.
Optionally, Fig. 7 is please referred to, Fig. 7 is the functional block diagram of the sequence fitness computing module 130 in Fig. 5.?
In the present embodiment, the sequence fitness computing module 130 includes that moment collection determines submodule 131 and fitness computational submodule
132, wherein the moment collection determines submodule 131 for determining all units to be restored corresponding to each unit recovery sequence
Recovery moment collection, the fitness computational submodule 132 for calculate sequence corresponding to each unit recovery sequence adaptation
Degree.
Further, the moment collection determines that submodule 131 is specifically used for:
For each unit recovery sequence, successively determines in the power plant to be restored and charged according to the unit recovery sequence
The most short restoration path for being used to indicate path recovery operation least risk between region and each unit to be restored；
When determining the corresponding most short restoration path of a unit to be restored every time, by the most short restoration path and should be to
Restore unit to be added in the charging zone, and according to the starting for being added into the unit to be restored of charging zone
Force parameter calculates corresponding recovery moment collection out.
Further, the fitness computational submodule 132 is specifically used for:
For each unit recovery sequence, force parameter is gone out according to the starting of each unit to be restored under the unit recovery sequence
And restore moment collection, generated energy of each unit to be restored in the unit recovery sequence in the preset time period is calculated, is obtained
To total power generation corresponding with the unit recovery sequence；
According to the route distribution situation and unit distribution situation of power generation region corresponding with the unit recovery sequence, calculate
The corresponding rack different degree of unit recovery sequence；
The corresponding total power generation of unit recovery sequence and rack different degree are subjected to multiplying, obtain corresponding sequence
Fitness.
The optimal recovery sequence determining module 140, sequentially for the maximum unit recovery of selection sequence fitness, as
All first kind units to be restored and all second class units to be restored are right in the preset time period in the power plant to be restored
The best unit recovery sequence answered.
In conclusion restoring in sequence optimizing method and device in Power Plant provided by the present application, the application is by obtaining
Take the second class unit to be restored in power plant to be restored history power generating value and its within a preset period of time prediction power output sequence,
Start force parameter out to calculate simulation of the second class unit to be restored in the preset time period, and obtains in power plant to be restored
The default of first kind unit to be restored start force parameter out, thus according to the default starting of first kind unit to be restored contribute join
Simulation of several and the second class unit to be restored in the preset time period starts force parameter out, is calculated based on genetic algorithm all
First kind unit to be restored and all second class units to be restored are in the preset time period according to different unit recoveries sequences
Sequence fitness when unit recovery, and the maximum unit recovery sequence of selection sequence fitness are carried out, as the electricity to be restored
Factory's corresponding best unit recovery sequence in the preset time period, makes the power plant to be restored restore suitable according to best unit
Sequence, which carries out the generating capacity shown when unit recovery and the ability to ward off risks, can be optimal state.Wherein, described first
Class unit to be restored is the non-clean energy generating set to be restored in power plant to be restored, and the second class unit to be restored is
Clean energy resource generating set to be restored in power plant to be restored.
The above, the only various embodiments of the application, but the protection scope of the application is not limited thereto, it is any
Those familiar with the art within the technical scope of the present application, it is made readily occur in modification variation or
Equivalent replacement should all cover within the scope of protection of this application.
Claims (10)
1. a kind of Power Plant restores sequence optimizing method, which is characterized in that the described method includes:
It obtains the default of each first kind unit to be restored in power plant to be restored and starts force parameter out and each second class is to be restored
The history power generating value of unit and its prediction within a preset period of time are contributed sequence；
Prediction power output sequence according to the history power generating value of each second class unit to be restored and its within a preset period of time, calculates
Simulation of each second class unit to be restored in the preset time period starts force parameter out；
According to the default force parameter out and each second class unit to be restored of starting of each first kind unit to be restored when described default
Between simulation in section start force parameter out, all first kind units to be restored are calculated based on genetic algorithm and all second classes wait for it is extensive
Group of answering a pager's call carries out sequence fitness when unit recovery in the preset time period according to different unit recovery sequences；
Selection sequence fitness maximum unit recovery sequence, as the first kind all in the power plant to be restored unit to be restored and
All second class units to be restored corresponding best unit recovery sequence in the preset time period.
2. starting the unit that force parameter out includes corresponding unit the method according to claim 1, wherein described and going out
Force value and subsidiary engine load value, the history power generating value of each second class unit to be restored of basis and its within a preset period of time
Prediction power output sequence calculates simulation of each second class unit to be restored in the preset time period and starts force parameter out, comprising:
Multiple groups power output is extracted from the history power generating value of the second class unit to be restored for each second class unit to be restored
Duration history power output sequence identical with duration corresponding to the preset time period；
Prediction power output sequence and the corresponding cloud model number of history power output sequence for calculating the second class unit to be restored are special
Sign；
The cloud model numerical characteristic for calculating the prediction power output sequence, it is special with the cloud model number of each history power output sequence
Cloud similarity between sign；
The minimum history power generating value that cloud similarity is not less than in each history power output sequence of default similarity threshold is chosen, and
Minimum prediction power generating value in the prediction power output sequence, building forms corresponding simulation power output sequence, wherein described simulate
Each power generating value descending arrangement in power sequence；
Corresponding power generating value is chosen from simulation power output sequence according to default confidence level, as the second class unit to be restored
Simulation unit power generating value in the preset time period；
With the default subsidiary engine load value of the second class unit to be restored, as the second class unit to be restored in the preset time
Simulation subsidiary engine load value in section.
3. the method according to claim 1, wherein described to be restored based on all first kind of genetic algorithm calculating
Unit and all second class units to be restored carry out unit recovery according to different unit recovery sequences in the preset time period
When sequence fitness, comprising:
The genetic algorithm parameter using unit recovery sequence as chromosome is improved by generation, and when each improvement is completed, really
Each unit recovery sequence under settled preceding genetic algorithm parameter, determines all to be restored corresponding to each unit recovery sequence
The recovery moment collection of unit, and sequence fitness corresponding to each unit recovery sequence is calculated, until continuous default algebra
Unit recovery sequence under genetic algorithm parameter is consistent.
4. according to the method described in claim 3, it is characterized in that, owning corresponding to each unit recovery sequence of the determination
The recovery moment collection of unit to be restored, comprising:
For each unit recovery sequence, charging zone is successively determined in the power plant to be restored according to unit recovery sequence
The most short restoration path for being used to indicate path recovery operation least risk between each unit to be restored；
When determining the corresponding most short restoration path of a unit to be restored every time, by the most short restoration path and this is to be restored
Unit is added in the charging zone, and is contributed according to the starting for being added into the unit to be restored of charging zone
Parameter calculates corresponding recovery moment collection.
5. according to the method described in claim 4, it is characterized in that, described calculate sequence corresponding to each unit recovery sequence
Fitness, comprising:
For each unit recovery sequence, force parameter and extensive is gone out according to the starting of each unit to be restored under unit recovery sequence
Multiple moment collection, calculates generated energy of each unit to be restored in the unit recovery sequence in the preset time period, obtain with
The corresponding total power generation of unit recovery sequence；
According to the route distribution situation and unit distribution situation of power generation region corresponding with the unit recovery sequence, the machine is calculated
The corresponding rack different degree of group recovery sequence；
The corresponding total power generation of unit recovery sequence and rack different degree are subjected to multiplying, corresponding sequence is obtained and adapts to
Degree.
6. a kind of Power Plant restores sequence optimizing device, which is characterized in that described device includes:
Power output data acquisition module, the default starting for obtaining each first kind unit to be restored in power plant to be restored, which is contributed, to be joined
The history power generating value of several and each second class unit to be restored and its prediction within a preset period of time are contributed sequence；
Power output parameter determination module, for the history power generating value according to each second class unit to be restored and its in preset time period
Interior prediction power output sequence, calculates simulation of each second class unit to be restored in the preset time period and starts force parameter out；
Sequence fitness computing module, for starting force parameter out and each second class according to the default of each first kind unit to be restored
Simulation of the unit to be restored in the preset time period starts force parameter out, is waited for based on all first kind of genetic algorithm calculating extensive
It is extensive that group of answering a pager's call and all second class units to be restored carry out unit according to different unit recovery sequences in the preset time period
Sequence fitness when multiple；
Optimal recovery sequence determining module, for the maximum unit recovery sequence of selection sequence fitness, as the electricity to be restored
All first kind units to be restored and all second class units to be restored corresponding best machine in the preset time period in factory
Group recovery sequence.
7. device according to claim 6, which is characterized in that described to start the unit that force parameter out includes corresponding unit and go out
Force value and subsidiary engine load value, the power output parameter determination module include:
Power output sequential extraction procedures submodule, for being directed to each second class unit to be restored, from going through for the second class unit to be restored
History power generating value extracts multiple groups power output duration history power output sequence identical with duration corresponding to the preset time period；
Numerical characteristic computational submodule, for calculating the prediction power output sequence and history power output sequence of the second class unit to be restored
Corresponding cloud model numerical characteristic；
Cloud similarity calculation submodule described is gone through for calculating the cloud model numerical characteristic of the prediction power output sequence with each
Cloud similarity between the cloud model numerical characteristic of history power output sequence；
Simulated series construct submodule, each history power output sequence for being not less than default similarity threshold for choosing cloud similarity
The minimum prediction power generating value in minimum history power generating value and the prediction power output sequence in column, building form corresponding simulation
Power output sequence, wherein each power generating value descending arrangement simulated in power sequence；
Simulation power generating value determines submodule, for choosing corresponding power output from simulation power output sequence according to default confidence level
Value, as simulation unit power generating value of the second class unit to be restored in the preset time period；
Simulation load value determines submodule, for the default subsidiary engine load value of the second class unit to be restored, as this second
Simulation subsidiary engine load value of the class unit to be restored in the preset time period.
8. device according to claim 6, which is characterized in that the sequence fitness computing module is specifically used for:
The genetic algorithm parameter using unit recovery sequence as chromosome is improved by generation, and when each improvement is completed, really
Each unit recovery sequence under settled preceding genetic algorithm parameter, determines all to be restored corresponding to each unit recovery sequence
The recovery moment collection of unit, and sequence fitness corresponding to each unit recovery sequence is calculated, until continuous default algebra
Unit recovery sequence under genetic algorithm parameter is consistent.
9. device according to claim 8, which is characterized in that the sequence fitness computing module includes that moment collection determines
Submodule, wherein the moment collection determines that submodule determines the extensive of all units to be restored corresponding to each unit recovery sequence
The mode of multiple moment collection, comprising:
For each unit recovery sequence, charging zone is successively determined in the power plant to be restored according to unit recovery sequence
The most short restoration path for being used to indicate path recovery operation least risk between each unit to be restored；
When determining the corresponding most short restoration path of a unit to be restored every time, by the most short restoration path and this is to be restored
Unit is added in the charging zone, and is contributed according to the starting for being added into the unit to be restored of charging zone
Parameter calculates corresponding recovery moment collection.
10. device according to claim 9, which is characterized in that the sequence fitness computing module further includes fitness
Computational submodule, wherein the fitness computational submodule calculates the side of sequence fitness corresponding to each unit recovery sequence
Formula, comprising:
For each unit recovery sequence, force parameter and extensive is gone out according to the starting of each unit to be restored under unit recovery sequence
Multiple moment collection, calculates generated energy of each unit to be restored in the unit recovery sequence in the preset time period, obtain with
The corresponding total power generation of unit recovery sequence；
According to the route distribution situation and unit distribution situation of power generation region corresponding with the unit recovery sequence, the machine is calculated
The corresponding rack different degree of group recovery sequence；
The corresponding total power generation of unit recovery sequence and rack different degree are subjected to multiplying, corresponding sequence is obtained and adapts to
Degree.
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