CN106300336B - It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method - Google Patents
It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method Download PDFInfo
- Publication number
- CN106300336B CN106300336B CN201610587240.5A CN201610587240A CN106300336B CN 106300336 B CN106300336 B CN 106300336B CN 201610587240 A CN201610587240 A CN 201610587240A CN 106300336 B CN106300336 B CN 106300336B
- Authority
- CN
- China
- Prior art keywords
- load
- power
- period
- vpp
- cost
- 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.)
- Expired - Fee Related
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 238000005265 energy consumption Methods 0.000 claims abstract description 19
- 230000007613 environmental effect Effects 0.000 claims abstract description 18
- 230000005611 electricity Effects 0.000 claims description 58
- 230000004044 response Effects 0.000 claims description 49
- 238000010248 power generation Methods 0.000 claims description 39
- MWUXSHHQAYIFBG-UHFFFAOYSA-N nitrogen oxide Inorganic materials O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 claims description 27
- 238000005457 optimization Methods 0.000 claims description 22
- 238000004519 manufacturing process Methods 0.000 claims description 15
- 230000009467 reduction Effects 0.000 claims description 15
- 230000006870 function Effects 0.000 claims description 14
- 238000009987 spinning Methods 0.000 claims description 12
- 230000008859 change Effects 0.000 claims description 11
- 230000001105 regulatory effect Effects 0.000 claims description 11
- 230000033228 biological regulation Effects 0.000 claims description 9
- 230000005284 excitation Effects 0.000 claims description 9
- 229960005486 vaccine Drugs 0.000 claims description 9
- 230000003044 adaptive effect Effects 0.000 claims description 8
- 240000002853 Nelumbo nucifera Species 0.000 claims description 7
- 235000006508 Nelumbo nucifera Nutrition 0.000 claims description 7
- 235000006510 Nelumbo pentapetala Nutrition 0.000 claims description 7
- 238000013178 mathematical model Methods 0.000 claims description 6
- 230000000694 effects Effects 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 230000029087 digestion Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 4
- 238000011160 research Methods 0.000 claims description 4
- 238000012546 transfer Methods 0.000 claims description 4
- 230000006866 deterioration Effects 0.000 claims description 3
- 238000009472 formulation Methods 0.000 claims description 3
- 230000002068 genetic effect Effects 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 230000007246 mechanism Effects 0.000 claims description 3
- 230000010534 mechanism of action Effects 0.000 claims description 3
- 239000000203 mixture Substances 0.000 claims description 3
- 239000003921 oil Substances 0.000 claims description 3
- 238000012913 prioritisation Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 230000001932 seasonal effect Effects 0.000 claims description 3
- 230000002787 reinforcement Effects 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 6
- 230000008901 benefit Effects 0.000 description 3
- 238000004146 energy storage Methods 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000010835 comparative analysis Methods 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000006116 polymerization reaction Methods 0.000 description 1
Classifications
-
- H02J3/005—
-
- 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]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a kind of meter and the virtual plant Multiobjective Optimal Operation method of load side and source side, the meter and load side and the virtual plant Multiobjective Optimal Operation method of source side include: the VPP Multiobjective Optimal Operation model for establishing meter and load side and source side coordinated operation and the solution to the meter and load side and the VPP Multiobjective Optimal Operation model of source side coordinated operation；The meter and load side and the virtual plant Multiobjective Optimal Operation method of source side have comprehensively considered load side and source side resource to the ability of raising new energy consumption, and reduce the cost of system operation and the influence to Environmental costs.
Description
Technical field
The present invention relates to the new-energy grid-connected dispatching technique fields of electric system more particularly to meter and load side and power supply
The virtual plant Multiobjective Optimal Operation method of side.
Background technique
New energy electric power is fast-developing, since the new energy electric power that China uses has randomness, intermittence, distribution
Formula and the characteristics of demodulate peak, and the new energy electric power that uses of China faces that generation of electricity by new energy power prediction precision is limited, China
Power supply architecture based on thermal power generation is unreasonable, can peaking power source is insufficient and traditional dispatching running way so that on a large scale
Uncontrollable generation of electricity by new energy base faces the horizontal limited predicament of power grid new energy consumption.Normal power supplies regulating power and power train
It unites traditional dispatching running way, is no longer satisfied the submitting demand of extensive new energy electric power.It is quickly sent out in smart grid
Under the background of exhibition, load side scheduling resource can effectively participate in network load Optimized Operation.The operation of electric system traditional scheduler
Mode is to dissolve new energy electric power by scheduling source side normal power supplies, not in view of load side user demand is responded to consumption
New energy electric power, the effect for reducing operating cost and Environmental costs.Demand response can make Demand-side resource become a kind of virtual
Resource participates in network load scheduling, and user demand response includes the demand response based on price and the demand response based on excitation.
Comprehensively consider load side resource and source side resource, dispatch load side with source side and mutually coordinate, is to solve uncontrollable new energy
The effective way of power consumption problem.
The it is proposed of virtual plant (Virtual Power Plant, VPP) concept is to solve the problems, such as that above-mentioned new-energy grid-connected mentions
New thought has been supplied, the system integration of power supply side and load side resource in smart grid is helped to realize.Virtual plant will be certain
Traditional power plants, distributed power generation (distributed generation, DG), controllable burden and energy-storage system in region have
Machine combines, and by the management of a control centre, merges into an entirety and participates in operation of power networks, can more fully play DG effect
Benefit improves customer power supply reliability.By power supply side and load side scheduling resource construction at VPP and have not been changed each distributed energy
The grid-connected mode in source (distributed energy resource, DER), but by technology polymerize DG, energy-storage system, can
The different types of DER such as load are controlled, the effective polymerization and management of DG are realized, to have operation function similar with conventional power plant
Can, participate in the transaction and system call of electricity market.
It is concentrated mainly on Generation Side or load side for the research of VPP at present, comprehensively considers the VPP of load side and Generation Side
Optimized Operation is considerably less, and only relates to the interruptible load of load side, not work of the in-depth study interruptible load to VPP
With not considering influence and load side and hair of demand response of the load side based on price and excitation to the Optimized Operation of VPP yet
Electric side coordinated scheduling is to new energy electric power consumption, the influence of system operation cost and environment.
Therefore, it is desirable to have a kind of meter and load side and the virtual plant Multiobjective Optimal Operation method of source side of being related to can be with
Overcome or at least mitigate the drawbacks described above of the prior art.
Summary of the invention
It is related to the virtual plant multiple-objection optimization tune of meter and load side and source side the purpose of the present invention is to provide a kind of
Degree method overcomes the above-mentioned problems in the prior art.
To achieve the above object, the present invention provide it is a kind of meter and load side and source side virtual plant multiple-objection optimization tune
Degree method, the VPP Multiobjective Optimal Operation model including establishing meter and load side and source side coordinated operation, foundations count and
Load side and the VPP Multiobjective Optimal Operation model of source side coordinated operation the following steps are included:
1) mathematical model of optimization aim, the virtual plant Multiobjective Optimal Operation side of the meter and load side and source side
With new energy consumption amount, maximum, system operation cost and the minimum target of Environmental costs, mathematical model are respectively as follows: method
A) new energy consumption amount maximum mathematic(al) representation are as follows:
Wherein: period number during T is scheduling；Nw、NPIt is wind power plant, photovoltaic power generation field number respectively；Point
Not Wei wind power plant i and photovoltaic DC field j the t period active power dispatch contribute；
B) operating cost minimum mathematic(al) representation are as follows:
Wherein: CgenFor the cost of electricity-generating of normal power supplies, it is made of the operating cost of normal power supplies；CILFor interruptible load
Switching cost；NGFor normal power supplies unit number of units；Start and stop state variable for normal power supplies unit x in the t period,For conventional power unit open stateFor conventional power unit shutdown status；It is conventional power unit x in the active of period t
Power output；ax、bx、cxFor the operating cost parameter of conventional power unit x；NHFor interruptible load group number；For interruptible load user
Electricity price discount of the k in period t；Be interruptible load user k in period t can outage capacity；For interruptible load
Unit interruptible load cost of the user k in period t；For interruptible load user k period t interruptible load；
C) pollution cost minimum mathematic(al) representation of the nitrogen oxides of fired power generating unit to environment are as follows:
In formula: αx、βx、γx、λxFor conventional power unit PGxDischarge nitrogen oxides characterisitic parameter, CeFor unit nitrogen oxides environment
Cost；
2) constraint condition of Optimal Operation Model:
Constraint condition includes system restriction, new energy operation constraint, normal power supplies operation constraint and interruptible load constraint；
A) system restriction are as follows:
1. power-balance constraint are as follows:
2. system spinning reserve capacity constrains are as follows:
Wherein:Respectively conventional power unit x can use power output with power output and minimum in period t maximum,
NHIt is interruptible load group number；WithRespectively the t period copes with positive and negative spinning reserve needed for load prediction error；WithRespectively the t period copes with wind-powered electricity generation and photovoltaic power fluctuates required positive and negative spinning reserve；
B) the new energy operation constraint are as follows:
1. wind-power electricity generation constrains are as follows:
2. photovoltaic power generation constrains are as follows:
Wherein:The active prediction of respectively wind power plant i, photovoltaic power generation field j in the t period
Power output；
C) the normal power supplies constraint are as follows:
1. output power bound constrains are as follows:
Wherein: PGx, min、PGx, maxFor the power bound of conventional power unit x；
2. minimum start-off time constraints are as follows:
3. Ramp Rate constrains are as follows:
Wherein:The respectively available machine time of conventional power unit x period t and downtime,The respectively minimum runing time of conventional power unit x and minimum downtime,For conventional power unit x when
The power output of section t-1, PGx, upAnd PGx, downRespectively conventional power unit x rises power limit out and declines power limit out；
D) the interruptible load constraint are as follows:
Wherein:Capacity bound, N are put into period t for interruptible load kHIt is interruptible load
Group number；PHkIt is interruptible load k in period t switching group number and investment capacity.
Preferably, the meter and load side and the virtual plant Multiobjective Optimal Operation method of source side further include to meter and
The solution of load side and the VPP Multiobjective Optimal Operation model of source side coordinated operation, the solution is using in conjunction with subhead scalar multiplication
The adaptive immune vaccine algorithm of division principle solves above-mentioned VPP multiple target Optimization of Load Dispatching；
A) the partial objectives for multiplication and division principle is the multiple target method for solving based on single goal thinking, is effectively avoided relying on
The experience of policymaker improves the terseness of prioritization scheme, formulation while reaching preferable effect of optimization are as follows:
One is sought to minimize containing m objective function simultaneously, it is excellent that n objective function seeks maximized multiple target
Change problem:
Wherein, F (x)=[f1(x), f2(x), Lfm(x)]T, G (x)=[g1(x), g2(x), Lgn(x)]T；It solves above-mentioned more
The partial objectives for multiplication and division thinking of objective optimisation problems are as follows: subhead scalar functions each in model are multiplied or are divided by place
After reason, solution single-object problem, specific mathematic(al) representation are carried out on feasible zone are as follows:
Objective function are as follows: minF=CGL*EC/EWP；
B) the adaptive immune vaccine algorithm can effectively overcome basic genetic algorithmic immature oils, local search energy
The shortcomings that power is poor, and diversity reduces effectively prevent population deterioration, improves convergence stability and convergence rate, shortens search time.
Preferably, influence of the load side to VPP Optimized Operation is mainly reflected on demand response, not according to response mechanism
Together, the meter and the load side demand response of load side and the virtual plant Multiobjective Optimal Operation method of source side, which are divided into, is based on
The demand response of tou power price and the demand response motivated based on interruptible load；
A) influence based on the demand response of tou power price to VPP Optimized Operation is embodied in user response tou power price
Variation, and adjust power demand accordingly, to change power mode, improve power structure, VPP passes through tou power price active
Guidance power consumer participate in Load Regulation, to carry out load peak load shifting, power grid is powered pressure when alleviating peak times of power consumption,
Research user response simultaneously predicts that load curve is the basis for formulating VPP generation schedule with this, according to consumer psychology principle, uses
There is response in various degree to different prices in family, implementing tou power price afterload curve can accordingly change, and be based on consumer
The day part fitting load that psychologic tou power price user response principle determines is expressed as:
Wherein λ is cool load translating ratio, i.e., after implementation tou power price, load is from high rate period to low rate period transfer amount
The ratio between with high rate period load, λpv、λpf、λfvThe respectively cool load translating ratio of peak period to paddy period, peak period to usually section
Cool load translating ratio, usually cool load translating ratio of the section to the paddy period；Tp、Tf、TvRespectively peak period, usually section, paddy period, t is
Any period；Lt0、LtThe fitting load of t period respectively after the actual measurement load of tou power price implementation preceding t period, implementation；Respectively implement leading peak, usually average value of the section total load within the corresponding period；
B) influence of the demand response based on interruptible load excitation to VPP Optimized Operation is embodied in by motivating political affairs
Plan makes can to interrupt that user responds when system reliability is affected or electricity price is higher and reduction plans are equivalent to increase and are
System spare capacity can obtain corresponding economic compensation, the virtual electricity of the meter and load side and source side when user's reduction plans
The high energy load that factory's Multiobjective Optimal Operation method is big using load power, can interrupt and adjust is high as interruptible load
Can be reached by carrying energy load responding speed by ms grades, can be realized high load by switching using the concatenated production method of a plurality of production line
Energy load range of capacity power regulation from 0% to 100%,
Interruptible load participates in system operational process and is based on following precondition:
1. interruptible load user declares next day to VPP on the day before mentioning can reduction plans and economic compensation standard；
2. VPP determination on the basis of comprehensively considering generator operation conditions, load condition and user and declaring can be interrupted negative
The calling situation of lotus includes whether to call and how much is calling；
3. interruptible load user calls situation according to the interruptible load that VPP is determined, next day production plan is corrected；
4. finally being compensated according to the practical calling situation of VPP to interruptible load user；
Interruptible load cost include can outage capacity cost and energy cost two parts can be interrupted can outage capacity cost
It is unrelated with whether VPP calls, it is fixed cost, the virtual plant Multiobjective Optimal Operation side of the meter and load side and source side
Method will not be reduced load is not disrupted this departmental cost by the way of electricity price discount, can interrupt energy cost be can in
Disconnected load it is practical it is called after caused by cost, buy k-th of interruptible load user the t period can outage capacity costAre as follows:
WhereinIt is interruptible load user k in t period electricity price discount；It is interruptible load user k in the t period
Can outage capacity, buying k-th of interruptible load user in the t period can interrupt energy costAre as follows:
WhereinIt is interruptible load user k in t period unit reduction plans cost；For t period of user k
Load reduction；For the calling state of interruptible load,Indicate that interruptible load is called,Expression is not adjusted
With.
Preferably, influence of the source side to VPP Optimized Operation, source side resource are normal power supplies and new energy, the meter
And the normal power supplies that load side and the virtual plant Multiobjective Optimal Operation method of source side use are Hydropower Unit and thermal motor
Group, new energy are wind-power electricity generation and photovoltaic power generation, and Hydropower Unit regulating power is strong, and adjustment speed is fast, but is influenced by seasonal factor
Greatly, fired power generating unit adjustment capacity is generally the 30%-50% of installed capacity, and adjustable range is smaller, and adjustment speed is slow, wind-force hair
Electricity and photovoltaic power generation are intermittent energy sources, and fluctuation can seriously threaten power grid security out, but the two power output has significantly mutually
Benefit property, when daytime, sunlight was most strong, wind very little, after the evening sun sets, illumination is very weak, but due to earth's surface difference variation wind greatly
It can reinforce, in summer, sunlight intensity is big and wind is small, winter, and sunlight intensity is weak and wind is big, and solar energy and wind energy are in time
Complementarity make wind light mutual complementing power generation that there is optimal matching in resource, it can be achieved that continuous, stable electric generation.
Preferably, load side and source side coordinated operation influence VPP Optimized Operation: the meter and load side and source side
Virtual plant Multiobjective Optimal Operation method mainly consider load side and source side coordinated operation to VPP Optimized Operation following
The influence of 3 aspects is to the influence in terms of VPP new energy consumption aspect, system operation cost aspect and environment respectively.
A) load side and source side coordinated operation dissolve VPP new energy and influence:
New energy is in the meter and the Generation Side of load side and the virtual plant Multiobjective Optimal Operation method of source side
Wind-power electricity generation and photovoltaic power generation, wind-force and photovoltaic power generation have the characteristics that fluctuation and can not Accurate Prediction, when wind-force, photovoltaic
When power generation ratio is exceeded to a certain degree, it only is unable to satisfy wind-force, photovoltaic power generation consumption and workload demand by normal power supplies adjusting, is examined
The mechanism of action for considering user demand response guides user to adjust and improve by tou power price and interruptible load incentive measure
Power structure and power mode carry out load peak load shifting, increase new energy digestion capability, reduce VPP cost of electricity-generating and to ring
The influence in border；Based on the new energy power output curve of cyclical fluctuations, analysis load side and Generation Side coordinated operation mode are to VPP Optimized Operation
Influence, for given daily load curve, in the case that meet it is maximum, minimum value, meter and load prediction error and scene are pre-
Spinning reserve needed for surveying error determines VPP generating set start-up mode, VPP online generating set peak power output are as follows:
Wherein: PG, max、PG, minFor VPP online generating set maximum, minimum generated output；PpeakiBeing includes Hydropower Unit
VPP online generating set nominal output inside；PforcejFor the forced power output of non-adjustable online generating set；CgiOn adjustable
Net generating set minimum technology power factor.
In the case where tradition only has source side power supply to participate in scheduling method, system equivalent load P after new energy electric power accessEFor
PE=PL-PW-PP
PLFor the original burden with power of system；PWFor wind power output；PPFor photovoltaic power generation power output.
When new energy power output regulating power downward beyond adjustable unit, if power grid fully receives this part new energy electricity
Power, adjustable unit will be forced to reduce power output to unconventional power output state, or even shutdown peak regulation, this will seriously affect operation of power networks
Safety and economy are limited new energy electricity E under whichW, abonAre as follows:
Wherein, Δ T is the time duration of period t；
Exceed the downward regulating power of adjustable unit in new energy power output using after load side and source side coordinated operation mode
Period, after user response tou power price price guidance and interruptible load excitation, former load valley period load increases, equivalent
LoadIt is with limited new energy electricity
Wherein:Burden with power after implementing tou power price for system, in t1-t2PeriodTherefore, load side and
New energy under source side coordinated operation mode is limited electricity and is less than the limited electricity of the new energy under traditional scheduler mode, i.e.,Therefore limited new energy electricity is dissolved by load side demand response, effectively increase consumption new energy
Electricity ability；
B) load side and source side coordinated operation influence VPP system operation cost and environment:
Traditional Optimization of Load Dispatching mode by dispatch normal power supplies achieve the goal, however normal power supplies cost of electricity-generating compared with
Height, and wherein thermal power generation can also generation environment pollution, by analyzing above it is found that after load side and source side coordinated operation, bear
Lotus curve changes, therefore it is inherently to system operation cost and environmental effects, after load curve changes, new energy consumption
Amount increases, and the lower power production of normal power supplies, the influence to environment will reduce, system after load side and source side coordinated operation
Operating cost includes interruptible load cost and cost of electricity-generating, and due to normal power supplies lower power production, cost of electricity-generating is certain to drop
It is low, suitable interruptible load cost is added, system operation cost will also decrease.
The present invention propose it is a kind of be related to meter and load side and source side virtual plant Multiobjective Optimal Operation method, it is described
Dispatching method has comprehensively considered load side and source side resource to the ability of raising new energy consumption, and reduces system operation
Cost and influence to Environmental costs.
Detailed description of the invention
Fig. 1 is that interruptible load user participates in system operational flow diagram.
Fig. 2 is that load side and source side coordinated operation dissolve influence schematic diagram to new energy.
Fig. 3 is adaptive immune vaccine algorithm flow chart.
Fig. 4 is that tou power price implements front and back network load prediction curve.
Fig. 5 is interruptible load standby message.
Fig. 6 is network load schematic diagram.
Fig. 7 is new energy consumption situation comparison schematic diagram.
Fig. 8 is conventional power unit operating condition schematic diagram.
Fig. 9 is interruptible load operating condition schematic diagram.
Specific embodiment
To keep the purposes, technical schemes and advantages of the invention implemented clearer, below in conjunction in the embodiment of the present invention
Attached drawing, technical solution in the embodiment of the present invention is further described in more detail.In the accompanying drawings, identical from beginning to end or class
As label indicate same or similar element or element with the same or similar functions.Described embodiment is the present invention
A part of the embodiment, instead of all the embodiments.The embodiments described below with reference to the accompanying drawings are exemplary, it is intended to use
It is of the invention in explaining, and be not considered as limiting the invention.Based on the embodiments of the present invention, ordinary skill people
Member's every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.Under
Face is described in detail the embodiment of the present invention in conjunction with attached drawing.
In a broad embodiment of the invention: the virtual plant Multiobjective Optimal Operation side of meter and load side and source side
Method, the VPP Multiobjective Optimal Operation model including establishing meter and load side and source side coordinated operation, the foundation meter and load
The VPP Multiobjective Optimal Operation model of side and source side coordinated operation the following steps are included:
1) mathematical model of optimization aim, the virtual plant Multiobjective Optimal Operation side of the meter and load side and source side
With new energy consumption amount, maximum, system operation cost and the minimum target of Environmental costs, mathematical model are respectively as follows: method
A) new energy consumption amount maximum mathematic(al) representation are as follows:
Wherein: period number during T is scheduling；NW、NPIt is wind power plant, photovoltaic power generation field number respectively；Point
Not Wei wind power plant i and photovoltaic DC field j the t period active power dispatch contribute；
B) operating cost minimum mathematic(al) representation are as follows:
Wherein: CgenFor the cost of electricity-generating of normal power supplies, it is made of the operating cost of normal power supplies；CILFor interruptible load
Switching cost；NGFor normal power supplies unit number of units；Start and stop state variable for normal power supplies unit x in the t period,For conventional power unit open stateFor conventional power unit shutdown status；It is conventional power unit x in the active of period t
Power output；ax、bx、cxFor the operating cost parameter of conventional power unit x；NHFor interruptible load group number；For interruptible load user
Electricity price discount of the k in period t；Be interruptible load user k in period t can outage capacity；For interruptible load
Unit interruptible load cost of the user k in period t；For interruptible load user k period t interruptible load；
C) pollution cost minimum mathematic(al) representation of the nitrogen oxides of fired power generating unit to environment are as follows:
In formula: αx、βx、γx、λxFor conventional power unit PGxDischarge nitrogen oxides characterisitic parameter, CeFor unit nitrogen oxides environment
Cost；
2) constraint condition of Optimal Operation Model:
Constraint condition includes system restriction, new energy operation constraint, normal power supplies operation constraint and interruptible load constraint；
A) system restriction are as follows:
1. power-balance constraint are as follows:
2. system spinning reserve capacity constrains are as follows:
Wherein:Respectively conventional power unit x can use power output, N with power output and minimum in period t maximumH
It is interruptible load group number；WithRespectively the t period copes with positive and negative spinning reserve needed for load prediction error；WithRespectively the t period copes with wind-powered electricity generation and photovoltaic power fluctuates required positive and negative spinning reserve；
B) the new energy operation constraint are as follows:
1. wind-power electricity generation constrains are as follows:
2. photovoltaic power generation constrains are as follows:
Wherein:Respectively wind power plant i, photovoltaic power generation field j are predicted in the active of t period
Power；
C) the normal power supplies constraint are as follows:
1. output power bound constrains are as follows:
Wherein: PGx, min、PGx, maxFor the power bound of conventional power unit x；
2. minimum start-off time constraints are as follows:
3. Ramp Rate constrains are as follows:
Wherein:The respectively available machine time of conventional power unit x period t and downtime, Point
Not Wei conventional power unit x minimum runing time and minimum downtime,Power output for conventional power unit x in period t-1, PGx, up
And PGx, downRespectively conventional power unit x rises power limit out and declines power limit out；
D) the interruptible load constraint are as follows:
Wherein:Capacity bound, N are put into period t for interruptible load kHIt is interruptible load group
Number；PHkIt is interruptible load k in period t switching group number and investment capacity.
The meter and load side and the virtual plant Multiobjective Optimal Operation method of source side further include to meter and load side
With the solution of the VPP Multiobjective Optimal Operation model of source side coordinated operation, the solution is using former in conjunction with partial objectives for multiplication and division
The adaptive immune vaccine algorithm of reason solves above-mentioned VPP multiple target Optimization of Load Dispatching；
A) the partial objectives for multiplication and division principle is the multiple target method for solving based on single goal thinking, is effectively avoided relying on
The experience of policymaker improves the terseness of prioritization scheme, formulation while reaching preferable effect of optimization are as follows:
One is sought to minimize containing m objective function simultaneously, it is excellent that n objective function seeks maximized multiple target
Change problem:
Wherein, F (x)=[f1(x), f2(x), Lfm(x)]T, G (x)=[g1(x), g2(x), Lgn(x)]T；It solves above-mentioned more
The partial objectives for multiplication and division thinking of objective optimisation problems are as follows: subhead scalar functions each in model are multiplied or are divided by place
After reason, solution single-object problem, specific mathematic(al) representation are carried out on feasible zone are as follows:
Objective function are as follows: minF=CGL*EC/EWP；
B) the adaptive immune vaccine algorithm can effectively overcome basic genetic algorithmic immature oils, local search energy
The shortcomings that power is poor, and diversity reduces effectively prevent population deterioration, improves convergence stability and convergence rate, shortens search time,
Its algorithm flow chart such as Fig. 3.
Influence of the load side to VPP Optimized Operation is mainly reflected on demand response, described according to the difference of response mechanism
Meter and the load side demand response of load side and the virtual plant Multiobjective Optimal Operation method of source side are divided into based on timesharing electricity
The demand response of valence and the demand response motivated based on interruptible load；
A) influence based on the demand response of tou power price to VPP Optimized Operation is embodied in user response tou power price
Variation, and adjust power demand accordingly, to change power mode, improve power structure, VPP passes through tou power price active
Guidance power consumer participate in Load Regulation, to carry out load peak load shifting, power grid is powered pressure when alleviating peak times of power consumption,
Research user response simultaneously predicts that load curve is the basis for formulating VPP generation schedule with this, according to consumer psychology principle, uses
There is response in various degree to different prices in family, implementing tou power price afterload curve can accordingly change, and be based on consumer
The day part fitting load that psychologic tou power price user response principle determines is expressed as:
Wherein λ is cool load translating ratio, i.e., after implementation tou power price, load is from high rate period to low rate period transfer amount
The ratio between with high rate period load, λpv、λpf、λfvThe respectively cool load translating ratio of peak period to paddy period, peak period to usually section
Cool load translating ratio, usually cool load translating ratio of the section to the paddy period；Tp、Tf、TvRespectively peak period, usually section, paddy period, t is
Any period；Lt0、LtThe fitting load of t period respectively after the actual measurement load of tou power price implementation preceding t period, implementation；Respectively implement leading peak, usually average value of the section total load within the corresponding period；
B) influence of the demand response based on interruptible load excitation to VPP Optimized Operation is embodied in by motivating political affairs
Plan makes can to interrupt that user responds when system reliability is affected or electricity price is higher and reduction plans are equivalent to increase and are
Unite spare capacity, can obtain corresponding economic compensation when user's reduction plans, the meter and load side and source side it is virtual
The high energy load that power plant's Multiobjective Optimal Operation method is big using load power, can interrupt and adjust as interruptible load,
High energy load responding speed can reach ms grades, can be realized height by switching using the concatenated production method of a plurality of production line
Energy load range of capacity power regulation from 0% to 100% is carried,
Interruptible load participate in system operational process as shown in Figure 1, and be based on following precondition:
1. interruptible load user declares next day to VPP on the day before mentioning can reduction plans and economic compensation standard；
2. VPP determination on the basis of comprehensively considering generator operation conditions, load condition and user and declaring can be interrupted negative
The calling situation of lotus includes whether to call and how much is calling；
3. interruptible load user calls situation according to the interruptible load that VPP is determined, next day production plan is corrected；
4. finally being compensated according to the practical calling situation of VPP to interruptible load user；
Interruptible load cost includes that outage capacity cost and can interrupt energy cost two parts, can outage capacity cost
It is unrelated with whether VPP calls, it is fixed cost, the virtual plant Multiobjective Optimal Operation side of the meter and load side and source side
Method will not be reduced load is not disrupted this departmental cost by the way of electricity price discount, can interrupt energy cost be can
Interruptible load it is practical it is called after caused by cost, k-th of interruptible load user of purchase the t period can outage capacity at
ThisAre as follows:
WhereinIt is interruptible load user k in t period electricity price discount；It is interruptible load user k in the t period
Can outage capacity, buying k-th of interruptible load user in the t period can interrupt energy costAre as follows:
WhereinIt is interruptible load user k in t period unit reduction plans cost；For t period of user k
Load reduction；For the calling state of interruptible load,Indicate that interruptible load is called,Expression is not adjusted
With.
Influence of the source side to VPP Optimized Operation, source side resource are normal power supplies and new energy, the meter and load side
It is Hydropower Unit and fired power generating unit, new energy with the normal power supplies that the virtual plant Multiobjective Optimal Operation method of source side uses
For wind-power electricity generation and photovoltaic power generation, Hydropower Unit regulating power is strong, and adjustment speed is fast, but is influenced by seasonal factor, thermal motor
Group adjustment capacity is generally the 30%-50% of installed capacity, and adjustable range is smaller, and adjustment speed is slow, wind-power electricity generation and photovoltaic
Power generation is intermittent energy source, and fluctuation can seriously threaten power grid security out, but the two power output has apparent complementary, daytime
When sunlight is most strong, wind very little, after the evening sun sets, illumination is very weak, but due to earth's surface difference variation is big and wind energy is reinforced,
Summer, sunlight intensity is big and wind is small, winter, and sunlight intensity is weak and wind is big, the complementarity of solar energy and wind energy in time
Wind light mutual complementing power generation is set in resource to there is optimal matching can realize continuous, stable electric generation.
Load side and source side coordinated operation influence VPP Optimized Operation: the meter and load side and source side it is virtual
Power plant's Multiobjective Optimal Operation method mainly considers load side and source side coordinated operation to VPP Optimized Operation in following 3 sides
The influence in face is to the influence in terms of VPP new energy consumption aspect, system operation cost aspect and environment respectively.
A) load side and source side coordinated operation dissolve VPP new energy and influence:
New energy is in the meter and the Generation Side of load side and the virtual plant Multiobjective Optimal Operation method of source side
Wind-power electricity generation and photovoltaic power generation, wind-force and photovoltaic power generation have the characteristics that fluctuation and can not Accurate Prediction, when wind-force, photovoltaic
When power generation ratio is exceeded to a certain degree, it only is unable to satisfy wind-force, photovoltaic power generation consumption and workload demand by normal power supplies adjusting, is examined
The mechanism of action for considering user demand response guides user to adjust and improve by tou power price and interruptible load incentive measure
Power structure and power mode carry out load peak load shifting, increase new energy digestion capability, reduce VPP cost of electricity-generating and to ring
The influence in border；Based on the new energy power output curve of cyclical fluctuations, analysis load side and Generation Side coordinated operation mode are to VPP Optimized Operation
It influences.
As shown in Fig. 2, for given daily load curve, when meeting its maximum, minimum value, meter and load prediction
Spinning reserve needed for error and scene prediction error, determines VPP generating set start-up mode, VPP online generating set maximum is defeated
Power out are as follows:
Wherein: PG, max、PG, minFor VPP online generating set maximum, minimum generated output；PpeakiBeing includes Hydropower Unit
VPP online generating set nominal output inside；PforcejFor the forced power output of non-adjustable online generating set；CgiOn adjustable
Net generating set minimum technology power factor.
In the case where tradition only has source side power supply to participate in scheduling method, system equivalent load P after new energy electric power accessEFor
PE=PL-PW-PP
PLFor the original burden with power of system；PWFor wind power output；PPFor photovoltaic power generation power output.
Such as Fig. 2 when new energy power output exceeds the downward regulating power, that is, t of adjustable unit1To t2Period, if power grid is fully received
This part new energy electric power, adjustable unit will be forced to reduce power output to unconventional power output state, or even shutdown peak regulation, this will be serious
The safety and economy of operation of power networks are influenced, is limited new energy electricity E under whichW, abonAre as follows:
Wherein, Δ T is the time duration of period t；
After load side and source side coordinated operation mode, in t1-t2Period, user response tou power price price guidance
After interruptible load excitation, former load valley period load increases, equivalent loadIt is with limited new energy electricity
Wherein:Burden with power after implementing tou power price for system, in t1-t2PeriodTherefore, load side and
New energy under source side coordinated operation mode is limited electricity and is less than the limited electricity of the new energy under traditional scheduler mode, i.e.,Therefore limited new energy electricity is dissolved by load side demand response, effectively increase consumption new energy
Electricity ability；
B) load side and source side coordinated operation influence VPP system operation cost and environment:
Traditional Optimization of Load Dispatching mode by dispatch normal power supplies achieve the goal, however normal power supplies cost of electricity-generating compared with
Height, and wherein thermal power generation can also generation environment pollution, by analyzing above it is found that after load side and source side coordinated operation, bear
Lotus curve changes, therefore it is inherently to system operation cost and environmental effects, after load curve changes, new energy consumption
Amount increases, and the lower power production of normal power supplies, the influence to environment will reduce, system after load side and source side coordinated operation
Operating cost includes interruptible load cost and cost of electricity-generating, and due to normal power supplies lower power production, cost of electricity-generating is certain to drop
It is low, suitable interruptible load cost is added, system operation cost will also decrease.
In an embodiment of the present invention, it is emulated using certain regional power grid as example, cool load translating ratio takes λpv=0.08,
λpf=0.06, λfv=0.04.Fig. 4 is to carry out network load prediction curve situation of change after tou power price.
Assuming that the regional power grid contains 3 conventional thermal power units, 1 heat supply fired power generating unit, 1 adjustable Hydropower Unit and
1 is shown in Table 1, table 2, Fig. 5 and Fig. 6 without adjusting Hydropower Unit, parameter information.
1 conventional power unit parameter of table
2 interruptible load parameter information of table
Adaptive immune vaccine algorithm parameter setting are as follows: population scale size=50；It is inoculated with coefficient ζ=0.3；Evolutionary generation
M=200；Crossover probability pc1=0.9, pc2=0.4；Mutation probability pm1=0.2, pm2=0.01；Vaccine threshold values ψ1=0.7, ψ2
=0.3.Table 1,2 parameter information of table are updated in the multi-objective optimization algorithm program of Matlab language establishment and obtain table 3, table 4
Optimum results.
The comparison of 3 new energy consumption amount of table
4 operating cost of table and Environmental costs comparison
Table 3 show new energy electric power consumption comparing result, and under traditional Optimized Operation mode, VPP dissolves new energy electric power
For 10381MWh.After addition tou power price under Optimized Operation mode, it is 12746MWh that VPP, which dissolves new energy electricity,.Timesharing is added
After electricity price and interruptible load under Optimized Operation mode, it is 12662MWh that VPP, which dissolves new energy electric power,.Know the optimization of VPP tradition
The new energy electricity for dispatching consumption is minimum, fewer than the VPP Optimized Operation mode after addition tou power price to dissolve new energy electricity
2365MWh, the Optimized Operation mode than VPP after addition tou power price and interruptible load are 2281MWh few.In interruptible load
Power grid total load is 55955MW before participating in scheduling, and power grid total load is 55415MW after participating in scheduling.Through single in comparison sheet 3
It is found that the VPP Optimized Operation mode after tou power price and interruptible load is added, specific load disappears position load consumption new energy amount
Electricity power of taking in the fresh is most, and it is horizontal to effectively increase new energy consumption.Fig. 7 is that day part new energy dissolves situation comparison.
Table 4 is operating cost and Environmental costs comparative analysis result:
1. VPP tradition Optimized Operation operating cost is 3861600 yuan, the VPP Optimized Operation mode after addition tou power price
Operating cost is 3071700 yuan, and the VPP Optimized Operation mode operating cost after tou power price and interruptible load is added is
3013200 yuan.The operating cost of VPP tradition Optimized Operation is maximum, more than VPP Optimized Operation mode after tou power price is added
789900 yuan, 848400 yuan more than the VPP Optimized Operation mode after addition tou power price and interruptible load.It can through comparing
Know, system operation cost can be effectively reduced in VPP Optimized Operation mode after tou power price and interruptible load is added；
2. VPP tradition Optimized Operation Environmental costs are 187100 yuan, the VPP Optimized Operation mode ring after addition tou power price
Border cost is 123330 yuan, and the VPP Optimized Operation mode Environmental costs after tou power price and interruptible load is added are 117190
Member.Know that Environmental costs caused by traditional Optimized Operation mode VPP are maximum, than optimizing VPP dispatching party after tou power price is added
The Environmental costs of formula are 63770 yuan more, than the VPP Optimized Operation mode Environmental costs after addition tou power price and interruptible load
It is 69910 yuan more.In terms of Environmental costs angle, the VPP Optimized Operation mode of tou power price and interruptible load is added than remaining
Two kinds of Optimized Operation modes are more preferable.
Each unit operating condition of VPP is shown in Fig. 8, Fig. 9, in conjunction with Fig. 7, Fig. 8, Fig. 9 analysis it is found that in VPP traditional scheduler model,
It contributes in period 1-8 new energy larger, and system loading is at a low ebb at this time, regulating power is insufficient, the consumption of VPP new energy electric power
It is less.Higher in period 13-18 system loading, conventional power unit will undertake higher base load, and regulating power is also insufficient.And negative
Under the VPP traffic control mode that lotus side and source side are coordinated, from the figure 3, it may be seen that after tou power price is added, loaded portion transfer.This
When normal power supplies to go out variation gentle, when period 1-8 new energy power output is big, system loading wants high compared to original system load, mentions
It is horizontal new energy consumption has been risen.The wave crest of original system load, conventional power unit have been reamed after tou power price is added in period 13-18
The base load undertaken reduces, and power output variation is gentle, and interruptible load also assists in scheduling at this time, increases new energy electric power consumption
Amount.
In conclusion invention will be by that will bear based on tou power price price and the demand response motivated based on interruptible load
Lotus side resource is included in VPP Optimization of Load Dispatching model.Compared to VPP tradition Optimization of Load Dispatching, meter and load side and source side
VPP Optimization of Load Dispatching, can effectively improve new energy digestion capability, reduce system operation cost, reduce thermal power generation to ring
The pollution in border.Under the background of smart grid fast development, load side demand response participates in Optimization of Load Dispatching, will alleviate often
Advise the important means of power supply scheduling pressure.
Finally it is noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations.To the greatest extent
Present invention has been described in detail with reference to the aforementioned embodiments for pipe, those skilled in the art should understand that: it is still
It is possible to modify the technical solutions described in the foregoing embodiments, or part of technical characteristic is equally replaced
It changes；And these are modified or replaceed, the essence for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution
Mind and range.
Claims (5)
1. a kind of virtual plant Multiobjective Optimal Operation method of meter and load side and source side, which is characterized in that including establishing
The VPP Multiobjective Optimal Operation model of meter and load side and source side coordinated operation, the foundation meter and load side and source side
The VPP Multiobjective Optimal Operation model of coordinated operation the following steps are included:
1) mathematical model of optimization aim, the meter and load side and the virtual plant Multiobjective Optimal Operation method of source side with
New energy consumption amount maximum, system operation cost and the minimum target of Environmental costs, mathematical model are respectively as follows:
A) new energy consumption amount maximum mathematic(al) representation are as follows:
Wherein: period number during T is scheduling；NW、NPIt is wind power plant, photovoltaic power generation field number respectively；Respectively
Active power dispatch of the wind power plant i and photovoltaic DC field j in the t period is contributed；
B) operating cost minimum mathematic(al) representation are as follows:
Wherein: CgenFor the cost of electricity-generating of normal power supplies, it is made of the operating cost of normal power supplies；CILFor the throwing of interruptible load
It is cut into this；NGFor normal power supplies unit number of units；For normal power supplies unit x the t period start and stop state variableIt is normal
Advise unit open stateFor conventional power unit shutdown status；For conventional power unit x period t active power output；ax、bx、
cxFor the operating cost parameter of conventional power unit x；NHFor interruptible load group number；It is interruptible load user k period t's
Electricity price discount；Be interruptible load user k in period t can outage capacity；For interruptible load user k when
The unit interruptible load cost of section t；For interruptible load user k period t interruptible load；
C) pollution cost minimum mathematic(al) representation of the nitrogen oxides of fired power generating unit to environment are as follows:
In formula: αx、βx、γx、λxFor conventional power unit PGxDischarge nitrogen oxides characterisitic parameter, CeFor unit nitrogen oxides Environmental costs；
2) constraint condition of Optimal Operation Model:
Constraint condition includes system restriction, new energy operation constraint, normal power supplies operation constraint and interruptible load constraint；
A) system restriction are as follows:
1. power-balance constraint are as follows:
2. system spinning reserve capacity constrains are as follows:
Wherein:Respectively conventional power unit x can use power output, N with power output and minimum in period t maximumHBeing can
Interruptible load group number；WithRespectively the t period copes with positive and negative spinning reserve needed for load prediction error；WithRespectively the t period copes with wind-powered electricity generation and photovoltaic power fluctuates required positive and negative spinning reserve；
B) the new energy operation constraint are as follows:
1. wind-power electricity generation constrains are as follows:
2. photovoltaic power generation constrains are as follows:
Wherein:The active prediction of respectively wind power plant i, photovoltaic power generation field j in the t period is contributed；
C) the normal power supplies constraint are as follows:
1. output power bound constrains are as follows:
Wherein: PGx, min、PGx, maxFor the power bound of conventional power unit x；
2. minimum start-off time constraints are as follows:
3. Ramp Rate constrains are as follows:
Wherein:The respectively available machine time of conventional power unit x period t and downtime,
The respectively minimum runing time of conventional power unit x and minimum downtime,For conventional power unit x period t-1 power output,
PGx, upAnd PGx, downRespectively conventional power unit x rises power limit out and declines power limit out；
D) the interruptible load constraint are as follows:
Wherein:Capacity bound, N are put into period t for interruptible load kHIt is interruptible load group number；PHkIt is interruptible load k in period t switching group number and investment capacity.
2. the virtual plant Multiobjective Optimal Operation method of meter as described in claim 1 and load side and source side, feature
Be: the meter and load side and the virtual plant Multiobjective Optimal Operation method of source side further include to meter and load side and electricity
The solution of the VPP Multiobjective Optimal Operation model of source coordinated operation, it is described to solve using in conjunction with partial objectives for multiplication and division principle
Adaptive immune vaccine algorithm solves above-mentioned VPP multiple target Optimization of Load Dispatching；
A) the partial objectives for multiplication and division principle is the multiple target method for solving based on single goal thinking, effectively avoids relying on decision
The experience of person improves the terseness of prioritization scheme, formulation while reaching preferable effect of optimization are as follows:
One is sought to minimize containing m objective function simultaneously, n objective function is sought maximized multiple-objection optimization and asked
Topic:
Wherein, F (x)=[f1(x), f2(x), L fm(x)]T, G (x)=[g1(x), g2(x), L gn(x)]T；Solve above-mentioned more mesh
Mark the partial objectives for multiplication and division thinking of optimization problem are as follows: subhead scalar functions each in model, which are multiplied or are divided by, handles it
Afterwards, solution single-object problem, specific mathematic(al) representation are carried out on feasible zone are as follows:
Objective function are as follows: min F=CGL*EC/EWP；
B) the adaptive immune vaccine algorithm can effectively overcome basic genetic algorithmic immature oils, local search ability
The shortcomings that difference, diversity reduces, effectively prevent population deterioration, improves convergence stability and convergence rate, shortens search time.
3. the virtual plant Multiobjective Optimal Operation method of meter as described in claim 1 and load side and source side, feature
Be: influence of the load side to VPP Optimized Operation is mainly reflected on demand response, according to the difference of response mechanism, the meter
And the load side demand response of load side and the virtual plant Multiobjective Optimal Operation method of source side is divided into based on tou power price
Demand response and based on interruptible load excitation demand response；
A) change for being embodied in user response tou power price to the influence of VPP Optimized Operation based on the demand response of tou power price
Change, and adjust power demand accordingly, to change power mode, improves power structure, VPP is drawn by tou power price active
It leads power consumer and participates in Load Regulation, so that load peak load shifting is carried out, power grid power supply pressure, research when alleviating peak times of power consumption
User response simultaneously predicts that load curve is the basis for formulating VPP generation schedule with this, according to consumer psychology principle, user couple
There is response in various degree in different prices, implementing tou power price afterload curve can accordingly change, and be based on consumer psychology
The day part fitting load that tou power price user response principle determines is expressed as:
Wherein λ is cool load translating ratio, i.e., after implementation tou power price, load is from high rate period to low rate period transfer amount and high
The ratio between rate period load, λpv、λpf、λfvRespectively the cool load translating ratio of peak period to paddy period, the peak period to usually section it is negative
The cool load translating ratio of the lotus rate of transform, usually section to the paddy period；Tp、Tf、TvRespectively peak period, usually section, paddy period, t are wherein
Any time period；Lt0、LtThe fitting load of t period respectively after the actual measurement load of tou power price implementation preceding t period, implementation；Respectively implement leading peak, usually average value of the section total load within the corresponding period；
B) influence of the demand response based on interruptible load excitation to VPP Optimized Operation is embodied in and is made by incentive policy
User can be interrupted and respond simultaneously reduction plans when system reliability is affected or electricity price is higher, it is standby to be equivalent to the system of increasing
With capacity, corresponding economic compensation, the virtual plant of the meter and load side and source side can be obtained when user's reduction plans
The high energy load that Multiobjective Optimal Operation method is big using load power, can interrupt and adjust is carried as interruptible load, height
Energy load responding speed can reach ms grades, can be realized high energy by switching using the concatenated production method of a plurality of production line
Load range of capacity power regulation from 0% to 100%,
Interruptible load participates in system operational process and is based on following precondition:
1. interruptible load user declares next day to VPP on the day before mentioning can reduction plans and economic compensation standard；
2. VPP determines interruptible load on the basis of comprehensively considering generator operation conditions, load condition and user and declaring
Situation is called, includes whether to call and how much is calling；
3. interruptible load user calls situation according to the interruptible load that VPP is determined, next day production plan is corrected；
4. finally being compensated according to the practical calling situation of VPP to interruptible load user；
Interruptible load cost includes that outage capacity cost and can interrupt energy cost two parts, can outage capacity cost with
It is unrelated whether VPP calls, and is fixed cost, the virtual plant Multiobjective Optimal Operation method of the meter and load side and source side
By the way of electricity price discount, will not be reduced load is not disrupted this departmental cost, can interrupt energy cost be can in
Disconnected load it is practical it is called after caused by cost, buy k-th of interruptible load user the t period can outage capacity costAre as follows:
WhereinIt is interruptible load user k in t period electricity price discount；For interruptible load user k the t period can in
Disconnected capacity, energy cost can be interrupted by buying k-th of interruptible load user in the t periodAre as follows:
WhereinIt is interruptible load user k in t period unit reduction plans cost；For the load of the t period of user k
Reduction；For the calling state of interruptible load,Indicate that interruptible load is called,Expression is not called upon.
4. the virtual plant Multiobjective Optimal Operation method of meter as described in claim 1 and load side and source side, feature
Be: influence of the source side to VPP Optimized Operation, source side resource be normal power supplies and new energy, it is described meter and load side and
The normal power supplies that the virtual plant Multiobjective Optimal Operation method of source side uses are Hydropower Unit and fired power generating unit, and new energy is
Wind-power electricity generation and photovoltaic power generation, Hydropower Unit regulating power is strong, and adjustment speed is fast, but is influenced by seasonal factor, fired power generating unit
Adjustment capacity is generally the 30%-50% of installed capacity, and adjustable range is smaller, and adjustment speed is slow, wind-power electricity generation and photovoltaic hair
Electricity is intermittent energy source, and fluctuation can seriously threaten power grid security out, but the two power output has apparent complementarity, and daytime is too
When sunlight is most strong, wind very little, after the evening sun sets, illumination is very weak, but due to the wind energy reinforcement greatly of earth's surface difference variation, in the summer
In season, sunlight intensity is big and wind is small, winter, and sunlight intensity is weak and wind is big, and the complementarity of solar energy and wind energy in time makes
Wind light mutual complementing power generation has optimal matching in resource, it can be achieved that continuous, stable electric generation.
5. the virtual plant Multiobjective Optimal Operation method of meter as described in claim 1 and load side and source side, feature
Be: load side and source side coordinated operation influence VPP Optimized Operation: the virtual plant of the meter and load side and source side
Multiobjective Optimal Operation method mainly considers load side and source side coordinated operation to VPP Optimized Operation at following 3 aspects
It influences, is to the influence in terms of VPP new energy consumption aspect, system operation cost aspect and environment respectively；
A) load side and source side coordinated operation dissolve VPP new energy and influence:
New energy is wind-force in the meter and the Generation Side of load side and the virtual plant Multiobjective Optimal Operation method of source side
Power generation and photovoltaic power generation, wind-force, photovoltaic power generation have the characteristics that fluctuation and can not Accurate Prediction, when wind-force, photovoltaic power generation
When ratio is exceeded to a certain degree, wind-force, photovoltaic power generation consumption and workload demand, consideration only are unable to satisfy by normal power supplies adjusting and is used
The mechanism of action of family demand response guides user to adjust and improve electricity consumption by tou power price and interruptible load incentive measure
Structure and power mode carry out load peak load shifting, increase new energy digestion capability, reduce VPP cost of electricity-generating and to environment
It influences；It is contributed the curve of cyclical fluctuations based on new energy, the shadow of analysis load side and Generation Side coordinated operation mode to VPP Optimized Operation
It rings, for given daily load curve, when meeting its maximum, minimum value, meter and load prediction error and scene are predicted
Spinning reserve needed for error determines VPP generating set start-up mode, VPP online generating set peak power output are as follows:
Wherein: PG, max、PG, minFor VPP online generating set maximum, minimum generated output；PpeakiIt is including Hydropower Unit
VPP surf the Internet generating set nominal output；PforcejFor the forced power output of non-adjustable online generating set；CgiFor adjustable online hair
Motor group minimum technology power factor, tradition only have source side power supply participate in scheduling method under, new energy electric power access after be
Unite equivalent load PEFor
PE=PL-PW-PP
PLFor the original burden with power of system；PWFor wind power output；PPIt contributes for photovoltaic power generation,
When new energy power output regulating power downward beyond adjustable unit, if power grid fully receives this part new energy electric power,
Adjustable unit will be forced to reduce power output to unconventional power output state, or even shutdown peak regulation, this will seriously affect the peace of operation of power networks
Full property and economy are limited new energy electricity E under whichW, abonAre as follows:
Wherein, Δ T is the time duration of period t；
After load side and source side coordinated operation mode, when new energy power output exceeds the downward regulating power of adjustable unit
After section, user response tou power price price guidance and interruptible load excitation, former load valley period load increases, equivalent loadIt is with limited new energy electricity
Wherein:Burden with power after implementing tou power price for system adjusts downwards energy beyond adjustable unit in new energy power output
The power periodTherefore, the limited electricity of the new energy under load side and source side coordinated operation mode is less than traditional scheduler
New energy under mode is limited electricity, i.e.,Therefore limited new energy is dissolved by load side demand response
Electricity effectively increases consumption new energy electricity ability；
B) load side and source side coordinated operation influence VPP system operation cost and environment:
Traditional Optimization of Load Dispatching mode is achieved the goal by dispatching normal power supplies, however normal power supplies cost of electricity-generating is higher,
And wherein thermal power generation can also generation environment pollution, by analyzing above it is found that after load side and source side coordinated operation, load is bent
Line changes, therefore it inherently to system operation cost and environmental effects, after load curve changes, new energy consumption amount increases
Add, the lower power production of normal power supplies, the influence to environment will reduce, and system is run after load side and source side coordinated operation
Cost includes interruptible load cost and cost of electricity-generating, and due to normal power supplies lower power production, cost of electricity-generating is certain to reduce, then
In addition suitable interruptible load cost, system operation cost will also decrease.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610587240.5A CN106300336B (en) | 2016-07-22 | 2016-07-22 | It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610587240.5A CN106300336B (en) | 2016-07-22 | 2016-07-22 | It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106300336A CN106300336A (en) | 2017-01-04 |
| CN106300336B true CN106300336B (en) | 2018-12-18 |
Family
ID=57652247
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610587240.5A Expired - Fee Related CN106300336B (en) | 2016-07-22 | 2016-07-22 | It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106300336B (en) |
Families Citing this family (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106712040B (en) * | 2017-02-16 | 2019-07-30 | 深圳供电局有限公司 | Power grid demand side load balancing processing method and system |
| CN107171356B (en) * | 2017-04-20 | 2019-09-17 | 国家电网公司 | A kind of wind fire for wind-powered peak regulation demand sends power-supply curve research method outside |
| CN107069833B (en) * | 2017-04-24 | 2021-01-08 | 国家电网公司 | Optimal matching method for load of power distribution network and latest energy access |
| CN107425537B (en) * | 2017-05-07 | 2019-10-22 | 东北电力大学 | It is a kind of meter and peak regulation cost the heat storage capacity configuration method of photo-thermal power station containing heat accumulation |
| CN106950840B (en) * | 2017-05-11 | 2020-05-19 | 山东理工大学 | Power grid peak clipping-oriented hierarchical distributed coordination control method for comprehensive energy system |
| CN107464010B (en) * | 2017-06-29 | 2021-10-29 | 河海大学 | Virtual power plant capacity optimal configuration method |
| CN108876091A (en) * | 2018-04-20 | 2018-11-23 | 浙江大学 | A kind of virtual plant realized based on software definition power grid |
| CN108808734A (en) * | 2018-07-09 | 2018-11-13 | 东北电力大学 | A kind of wind-electricity integration system distributed optimization scheduling modeling method containing virtual plant |
| CN111384728A (en) * | 2018-12-27 | 2020-07-07 | 中国电力科学研究院有限公司 | Power grid peak regulation resource coordination optimization method and system |
| CN109888775B (en) * | 2019-03-06 | 2020-08-07 | 清华大学 | Low-load operation day power transmission network structure optimization method considering wind power access |
| CN110188950B (en) * | 2019-05-30 | 2022-12-02 | 三峡大学 | Multi-agent technology-based optimal scheduling modeling method for power supply side and demand side of virtual power plant |
| CN110401192B (en) * | 2019-08-09 | 2022-09-16 | 长沙理工大学 | Power system dynamic economic dispatching method considering optimal load transfer proportion and optimal wind and light grid-connection proportion |
| CN110910016A (en) * | 2019-11-21 | 2020-03-24 | 青海格尔木鲁能新能源有限公司 | New energy storage system scheduling optimization method considering demand response resources |
| CN111244946B (en) * | 2020-02-18 | 2021-11-09 | 国网江苏省电力有限公司 | Method and device for regulating and controlling power generation and utilization resources of self-contained power plant |
| CN111509784B (en) * | 2020-04-24 | 2022-03-15 | 清华大学 | Uncertainty-considered virtual power plant robust output feasible region identification method and device |
| CN112366706B (en) * | 2020-11-17 | 2022-12-30 | 国家电网公司华北分部 | Load side peak regulation resource scale demand prediction method |
| CN112488374B (en) * | 2020-11-24 | 2022-07-19 | 国网江苏省电力有限公司经济技术研究院 | Generalized demand response optimization proportioning research method based on time sequence production simulation |
| CN112634080A (en) * | 2020-12-24 | 2021-04-09 | 沈阳工程学院 | Multi-target demand response management method based on Pareto optimal theory |
| CN113077111A (en) * | 2021-04-26 | 2021-07-06 | 上海电机学院 | Virtual power plant optimal scheduling method based on plug-in hybrid electric vehicle V2G technology |
| CN113627762B (en) * | 2021-07-30 | 2024-03-22 | 国网山西省电力公司电力科学研究院 | Virtual power plant peak shaving method based on excitation electricity price |
| CN113972699B (en) * | 2021-10-22 | 2023-07-18 | 国网安徽省电力有限公司经济技术研究院 | Power grid peak load optimization method |
| CN114491997B (en) * | 2022-01-13 | 2024-05-10 | 国网江苏省电力有限公司营销服务中心 | Virtual power plant operation optimization method and system considering demand response and electric automobile |
| CN116345575B (en) * | 2023-03-30 | 2024-05-03 | 湖北清江水电开发有限责任公司 | Hydropower plant automatic power generation control method based on multiple external voltage levels |
| CN116231765B (en) * | 2023-05-09 | 2023-09-19 | 上海融和元储能源有限公司 | Virtual power plant output control method |
| CN116760122B (en) * | 2023-08-21 | 2023-12-26 | 国网浙江省电力有限公司宁波供电公司 | Virtual power plant resource management and control method and device, computer equipment and storage medium |
| CN118554547A (en) * | 2024-07-25 | 2024-08-27 | 广东电网有限责任公司汕尾供电局 | Power supply and load coordination method, device, equipment and medium in power system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103903066A (en) * | 2014-04-04 | 2014-07-02 | 东南大学 | Virtual power plant stratified random optimized dispatching method |
| CN105631599A (en) * | 2015-12-30 | 2016-06-01 | 国网甘肃省电力公司电力科学研究院 | Multi-target operation scheduling method of virtual power plant |
-
2016
- 2016-07-22 CN CN201610587240.5A patent/CN106300336B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103903066A (en) * | 2014-04-04 | 2014-07-02 | 东南大学 | Virtual power plant stratified random optimized dispatching method |
| CN105631599A (en) * | 2015-12-30 | 2016-06-01 | 国网甘肃省电力公司电力科学研究院 | Multi-target operation scheduling method of virtual power plant |
Non-Patent Citations (2)
| Title |
|---|
| 基于分时电价的虚拟电厂经济性优化调度;袁桂丽等;《电网技术》;20160301;第40卷(第3期);第826-832页 * |
| 计及环境效益的虚拟电厂经济性优化调度;袁桂丽等;《新能源进展》;20151103;第3卷(第5期);第398-404页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106300336A (en) | 2017-01-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106300336B (en) | It is a kind of meter and load side and source side virtual plant Multiobjective Optimal Operation method | |
| CN106992556B (en) | Optimal scheduling method based on hybrid power supply multi-time scale complementation | |
| CN106532769B (en) | Optimization method based on grid-connected probabilistic Demand-side tou power price | |
| CN107958300A (en) | A kind of more microgrid interconnected operation coordinated scheduling optimization methods for considering interactive response | |
| CN112465181A (en) | Two-stage optimization scheduling method supporting source-network-load-storage multi-element ubiquitous coordination | |
| CN112039056A (en) | Two-stage optimal scheduling method for new energy | |
| CN104616069A (en) | Annual power generation plan rolled decomposition optimization method taking balance between plan finishing rate and load rate into consideration | |
| CN104795846A (en) | Optimized operation method of pumped-storage power station and wind power combined system | |
| CN103296682A (en) | Multiple spatial and temporal scale gradually-advancing load dispatching mode designing method | |
| CN104376412A (en) | High energy-consuming enterprise peak regulation control method used in new energy power generation mode | |
| CN109936162A (en) | Power grid generation schedule optimization method and the system a few days ago that new energy receives ability are promoted based on controllable burden | |
| CN109301876B (en) | Constraint condition elasticized electric power day-ahead market clearing method | |
| CN110046780B (en) | Islanding micro-grid demand response economic dispatching method and system based on time-of-use electricity price | |
| CN110829408A (en) | Multi-domain scheduling method considering energy storage power system based on power generation cost constraint | |
| Li et al. | An integrated energy exchange scheduling and pricing strategy for multi-microgrid system | |
| CN108805326A (en) | A kind of electricity price pricing method based on Multiple Time Scales demand response model | |
| CN109726894A (en) | Ensure the new energy active command calculation method of spot exchange and medium-term and long-term electricity | |
| CN111682531A (en) | PL-IMOCS-based wind, light, water and fire primary energy complementation short-term optimization scheduling method and device | |
| Yujie et al. | Optimal operation of new coastal power systems with seawater desalination based on grey wolf optimization | |
| CN109474015A (en) | Active distribution network energy-storage system Optimal Configuration Method and system based on bilevel optimization | |
| CN105811454A (en) | Direct load control resource optimization method considering wind power integration | |
| CN109066769A (en) | Wind-powered electricity generation, which totally disappeared, receives lower virtual plant internal resource dispatch control method | |
| CN113765098B (en) | Load source interaction peak shaving control method based on demand side load response | |
| CN115935619A (en) | Demand response-based day-ahead low-carbon scheduling method and device for active power distribution network | |
| CN115207906A (en) | Multi-time scale scheduling method considering high energy-carrying load to participate in regulation and control |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20181218 Termination date: 20190722 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |