CN109638874A - A kind of distributed photovoltaic cluster control method and device - Google Patents
A kind of distributed photovoltaic cluster control method and device Download PDFInfo
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- H02J3/383—
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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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
- 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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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B10/00—Integration of renewable energy sources in buildings
- Y02B10/10—Photovoltaic [PV]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/30—Reactive power compensation
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
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Abstract
The present invention provides a kind of distributed photovoltaic cluster control method and devices, obtain the active power and power distribution network operation data of distributed photovoltaic cluster；MIXED INTEGER Second-order cone programming model is solved using solver, and distributed photovoltaic cluster is controlled based on calculated result；Active power and power distribution network operation data building of the MIXED INTEGER Second-order cone programming model based on distributed photovoltaic cluster, solution difficulty is small, high-efficient, precision is high, can effectively acquire globally optimal solution.Technical solution provided by the invention can successfully manage photovoltaic power output fluctuation, guarantee power distribution network safety in operation, realize the on-site elimination of distributed photovoltaic；Non-convex nonlinear restriction in trend constraint is converted to the linear restriction in MIXED INTEGER Second-order cone programming model using second order cone relaxation method by technical solution provided by the invention, substantially increases computational efficiency.
Description
Technical field
The present invention relates to field of new energy technologies, and in particular to a kind of distributed photovoltaic cluster control method and device.
Background technique
In recent years, distributed photovoltaic shows the feature that exploitation, cluster are grid-connected in flakes.The large-scale cluster of distributed photovoltaic
Access produces significant impact to trend distribution, power quality, operational reliability and the stability etc. of power distribution network.Point
Cloth photovoltaic can realize the decoupling control of active reactive by inverter, make full use of the Reactive-power control ability of inverter, simultaneously
In view of a variety of active reactive Controllable regulation devices existing in power distribution network, such as on-load regulator transformer, compensation capacitor group, quiet
Only reactive power compensator, energy storage device, distributed photovoltaic clustered control essence are the non-convex nonlinear problems of MIXED INTEGER, it is difficult to be asked
Solution.State generally use in the prior art idle work optimization time-division transfer method and based on interior point method and penalty function combine from
It dissipates variable processing method and realizes distributed photovoltaic clustered control, wherein when the time-division transfer method using idle work optimization can weaken
Discontinuity surface constrain bring solve difficulty, based on the discrete variable processing method that interior point method and penalty function combine be will mix it is whole
Number planning problems become continuous problem, and then realize distributed photovoltaic clustered control, exist and solve that difficulty is big, low efficiency, precision
It is low, the problems such as being easily trapped into local optimum, it is difficult to meet efficient, the high precision computation demand of distributed photovoltaic clustered control.
Summary of the invention
In order to overcome above-mentioned big difficulty, low efficiency, the precision of solving in the prior art low, it is easily trapped into local optimum not
Foot, the present invention provide a kind of distributed photovoltaic cluster control method and device, solve that difficulty is small, high-efficient, precision is high, can have
Effect acquires globally optimal solution.
In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical scheme that:
On the one hand, the present invention provides a kind of distributed photovoltaic cluster control method, comprising:
Obtain the active power and power distribution network operation data of distributed photovoltaic cluster；
Bring the active power of the distributed photovoltaic cluster and power distribution network operation data into construct in advance MIXED INTEGER
Second-order cone programming model；
The model is solved using solver, and distributed photovoltaic cluster is controlled based on calculated result；
Active power and power distribution network fortune of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster
The building of row data.
The building of the MIXED INTEGER Second-order cone programming model, comprising:
Regulation stall, the static reactive dress of reactive power, on-load regulator transformer based on distributed photovoltaic cluster
The discharge power of reactive power, the regulation stall of compensation capacitor group, the charge power of energy storage device and the energy storage device set,
Construct power distribution network rolling optimization Controlling model；
For the power distribution network rolling optimization Controlling model, on-load regulator transformer is carried out in conjunction with piece-wise linearization linear
Change modeling；
The power distribution network rolling optimization Controlling model carried out after linearisation modeling is carried out using second order cone relaxing techniques
Conversion constructs MIXED INTEGER Second-order cone programming model.
The power distribution network rolling optimization Controlling model building, comprising:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, constructs the objective function of the model；
And it is the following constraint condition of the model construction:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load voltage regulation become
Depressor operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
The objective function such as following formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is
Step-length is controlled, n is node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；
For square of the electric current of t moment branch ij.
The trend constraint such as following formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end of the branch of first node
Node set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node
The active power and reactive power of j, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk,
Pcluster,j,t、Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster at respectively t moment node j,
Pload,j,t、Qload,j,tThe active power and reactive power of load, P at respectively t moment node jch,j,tAt t moment node j
The charge power of energy storage device, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tAt t moment node j
The reactive power of compensation capacitor group, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；When for t
Carve square of node i voltage magnitude, Ui,tFor the voltage magnitude of t moment node i,For the flat of t moment node i voltage magnitude
Side,For square of t moment node j voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor t moment
The current amplitude of branch ij；kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
It is describedIt determines as the following formula:
In formula,For square lower limit of t moment node j voltage magnitude,For square of t moment node j voltage magnitude
The upper limit；N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
The continuous variable w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t≥0 n∈{1,2,…,N} (7)
w1ij,1,t≤dij,1,t (9)
w2ij,1,t≤dij,1,t (10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
The voltage level restraint such as following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
The tributary capacity constraint such as following formula:
In formula,For the current amplitude upper limit of branch ij.
The operation of distributed photovoltaic the cluster constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,The reactive power lower and upper limit of distributed photovoltaic cluster at respectively t moment node j.
On-load regulator transformer the operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijBecome for on-load voltage regulation on branch ij
The adjusting step-length of depressor, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load voltage regulation transformation on t moment branch ij
N-th of regulation stall of device,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
Static passive compensation device the operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
The operation of compensation capacitor the group constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensation
The maximal regulated gear of capacitor group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jFor node j
Locate the reactive power variable quantity of every one grade of the tune of compensation capacitor group.
Energy storage device the operation constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTTo be stored up at t+ Δ T moment node j
The electricity of energy device,For the charging limit value of energy storage device at node j；Pch,j,tIt is filled for energy storage device at t moment node j
Electrical power, Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge of energy storage device at node j
Power,For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisFor energy storage device
Discharging efficiency；Dch,j,t、Ddis,j,tFor 0-1 variable, when the energy storage device charges, Dch,j,t=1, Ddis,j,t=0；The storage
When energy device electric discharge, Dch,j,t=0, Ddis,j,t=1.
It is described to be directed to the power distribution network rolling optimization Controlling model, on-load regulator transformer is carried out in conjunction with piece-wise linearization
Linearisation modeling, comprising:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
It is described using second order cone relaxing techniques to the power distribution network rolling optimization Controlling model carried out after linearisation modeling
It is converted, constructs MIXED INTEGER Second-order cone programming model, comprising:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
The solver includes MOSEK solver or Cplex solver；
The solving result includes the regulation stall, quiet of the reactive power of distributed photovoltaic cluster, on-load regulator transformer
The only reactive power of reactive power compensator, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage dress
The discharge power set.
On the other hand, the present invention provides a kind of distributed photovoltaic clustered control device, comprising:
Module is obtained, for obtaining the active power and power distribution network operation data of distributed photovoltaic cluster；
Module is brought into, for bringing the active power of the distributed photovoltaic cluster and power distribution network operation data into preparatory structure
The MIXED INTEGER Second-order cone programming model built；
Module is solved, for solving using solver to the model, and based on calculated result to distributed photovoltaic
Cluster is controlled；
Active power and power distribution network fortune of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster
The building of row data.
Described device further includes building module, and the modeling module is specifically used for:
First modeling unit, the adjusting shelves for reactive power, on-load regulator transformer based on distributed photovoltaic cluster
Position, the reactive power of static passive compensation device, the regulation stall of compensation capacitor group, the charge power of energy storage device and storage
The discharge power of energy device, constructs power distribution network rolling optimization Controlling model；
Modeling unit is linearized, for being directed to the power distribution network rolling optimization Controlling model, in conjunction with piece-wise linearization to having
Voltage adjustment of on-load transformer carries out linearisation modeling；
Converting unit, for using second order cone relaxing techniques to the power distribution network rolling optimization carried out after linearisation modeling
Controlling model is converted, and MIXED INTEGER Second-order cone programming model is constructed.
First modeling unit is specifically used for:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, constructs the objective function of the model；
And it is the following constraint condition of the model construction:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load voltage regulation become
Depressor operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
The objective function such as following formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is
Step-length is controlled, n is node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；
For square of the electric current of t moment branch ij.
The trend constraint such as following formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end of the branch of first node
Node set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node
The active power and reactive power of j, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk,
Pcluster,j,t、Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster at respectively t moment node j,
Pload,j,t、Qload,j,tThe active power and reactive power of load, P at respectively t moment node jch,j,tAt t moment node j
The charge power of energy storage device, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tAt t moment node j
The reactive power of compensation capacitor group, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；When for t
Carve square of node i voltage magnitude, Ui,tFor the voltage magnitude of t moment node i,For the flat of t moment node i voltage magnitude
Side,For square of t moment node j voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor t moment
The current amplitude of branch ij；kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
It is describedIt determines as the following formula:
In formula,For square lower limit of t moment node j voltage magnitude,For square of t moment node j voltage magnitude
The upper limit；N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
The continuous variable w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t≥0 n∈{1,2,…,N} (7)
w1ij,1,t≤dij,1,t (9)
w2ij,1,t≤dij,1,t (10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
The voltage level restraint such as following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
The tributary capacity constraint such as following formula:
In formula,For the current amplitude upper limit of branch ij.
The operation of distributed photovoltaic the cluster constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,
The reactive power lower and upper limit of distributed photovoltaic cluster at respectively t moment node j.
On-load regulator transformer the operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijBecome for on-load voltage regulation on branch ij
The adjusting step-length of depressor, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load voltage regulation transformation on t moment branch ij
N-th of regulation stall of device,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
Static passive compensation device the operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
The operation of compensation capacitor the group constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensation
The maximal regulated gear of capacitor group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jFor node j
Locate the reactive power variable quantity of every one grade of the tune of compensation capacitor group.
Energy storage device the operation constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTTo be stored up at t+ Δ T moment node j
The electricity of energy device,For the charging limit value of energy storage device at node j；Pch,j,tIt is filled for energy storage device at t moment node j
Electrical power, Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge of energy storage device at node j
Power,For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisFor energy storage device
Discharging efficiency；Dch,j,t、Ddis,j,tFor 0-1 variable, when the energy storage device charges, Dch,j,t=1, Ddis,j,t=0；The storage
When energy device electric discharge, Dch,j,t=0, Ddis,j,t=1.
The linearisation modeling unit is specifically used for:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
The converting unit is specifically used for:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
The solver includes MOSEK solver or Cplex solver；
The solving result includes the regulation stall, quiet of the reactive power of distributed photovoltaic cluster, on-load regulator transformer
The only reactive power of reactive power compensator, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage dress
The discharge power set.
Compared with the immediate prior art, technical solution provided by the invention is had the advantages that
In distributed photovoltaic cluster control method provided by the invention, obtains the active power of distributed photovoltaic cluster and match
Grid operation data；Bring the active power of the distributed photovoltaic cluster and power distribution network operation data into construct in advance mixing
Integer Second-order cone programming model；The model is solved using solver, and based on calculated result to distributed photovoltaic collection
Group is controlled；Active power and power distribution network of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster
Operation data building, solution difficulty is small, high-efficient, precision is high, can effectively acquire globally optimal solution；
Distributed photovoltaic clustered control device provided by the invention includes obtaining module to bring module into and solve module, is obtained
Module, for obtaining the active power and power distribution network operation data of distributed photovoltaic cluster；It brings module into, is used for the distribution
The active power and power distribution network operation data of formula photovoltaic cluster bring the MIXED INTEGER Second-order cone programming model constructed in advance into；It solves
Module for being solved using solver to the model, and controls distributed photovoltaic cluster based on calculated result；
Active power and power distribution network operation data building of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster, are asked
Solution difficulty is small, high-efficient, precision is high, can effectively acquire globally optimal solution；
Technical solution provided by the invention can successfully manage photovoltaic power output fluctuation, guarantee power distribution network safety in operation, real
The on-site elimination of existing distributed photovoltaic；
Technical solution provided by the invention is turned the non-convex nonlinear restriction in trend constraint using second order cone relaxation method
The linear restriction being changed in MIXED INTEGER Second-order cone programming model, substantially increases computational efficiency.
Detailed description of the invention
Fig. 1 is distributed photovoltaic cluster control method flow chart in the embodiment of the present invention 1.
Specific embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings.
Embodiment 1
The embodiment of the present invention 1 provides a kind of distributed photovoltaic cluster control method, and specific flow chart is as shown in Figure 1, tool
Body process is as follows:
S101: the active power and power distribution network operation data of distributed photovoltaic cluster are obtained；
S102: the active power of distributed photovoltaic cluster and power distribution network operation data are brought to the MIXED INTEGER constructed in advance into
Second-order cone programming model；
S103: solving model using solver, and is controlled based on calculated result distributed photovoltaic cluster；
Active power and power distribution network of the above-mentioned MIXED INTEGER Second-order cone programming model based on distributed photovoltaic cluster run number
According to building.
Since MIXED INTEGER Second-order cone programming model rolls distributed photovoltaic cluster by using second order cone relaxation method
Optimizing control models convert to obtain, and distributed photovoltaic cluster rolling optimization Controlling model also in a distributed manner photovoltaic cluster access
The minimum target of distribution network loss, but due to distributed photovoltaic cluster rolling optimization Controlling model it is non-convex it is non-linear, be difficult to solve,
And Second-order cone programming problem has solving speed fast, the features such as optimizing ability is strong, the control variable optimization more than the processing electric system
It is had a wide range of applications in control problem.So the present invention uses second order cone relaxation method by distributed photovoltaic cluster rolling optimization
Controlling model is converted into MIXED INTEGER Second-order cone programming model, i.e., by optimization problem be converted into can Efficient Solution Second-order cone programming
(Second-Order Cone Programming, SOCP) problem realizes the rapid solving of optimization problem, and required by guarantee
The optimality of solution.
The building of above-mentioned MIXED INTEGER Second-order cone programming model, detailed process is as follows:
Regulation stall, the static reactive dress of reactive power, on-load regulator transformer based on distributed photovoltaic cluster
The discharge power of reactive power, the regulation stall of compensation capacitor group, the charge power of energy storage device and the energy storage device set,
Construct power distribution network rolling optimization Controlling model；
For power distribution network rolling optimization Controlling model, linearisation is carried out to on-load regulator transformer in conjunction with piece-wise linearization and is built
Mould；
The power distribution network rolling optimization Controlling model after carrying out linearisation modeling is converted using second order cone relaxing techniques,
Construct MIXED INTEGER Second-order cone programming model.
Detailed process is as follows for above-mentioned power distribution network rolling optimization Controlling model building:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, building institute's power distribution network rolling optimization control mould
The objective function of type；
And following constraint condition is constructed for power distribution network rolling optimization Controlling model:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load voltage regulation become
Depressor operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
Objective function such as following formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is
Step-length is controlled, n is node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；
For square of the electric current of t moment branch ij,For the tune of the reactive power, on-load regulator transformer of photovoltaic cluster in a distributed manner
Save gear, the reactive power of static passive compensation device, the regulation stall of compensation capacitor group, energy storage device charge power with
And the discharge power of energy storage device is the function for controlling variable.
Trend constraint such as following formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end of the branch of first node
Node set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node
The active power and reactive power of j, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk,
Pcluster,j,t、Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster at respectively t moment node j,
Pload,j,t、Qload,j,tThe active power and reactive power of load, P at respectively t moment node jch,j,tAt t moment node j
The charge power of energy storage device, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tAt t moment node j
The reactive power of compensation capacitor group, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；When for t
Carve square of node i voltage magnitude, Ui,tFor the voltage magnitude of t moment node i,For the flat of t moment node i voltage magnitude
Side,For square of t moment node j voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor t moment
The current amplitude of branch ij；kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
It determines as the following formula:
In formula,For square lower limit of t moment node j voltage magnitude,For square of t moment node j voltage magnitude
The upper limit；N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
Continuous variable w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t≥0 n∈{1,2,…,N} (7)
w1ij,1,t≤dij,1,t (9)
w2ij,1,t≤dij,1,t (10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
Voltage level restraint such as following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
Tributary capacity constraint such as following formula:
In formula,For the current amplitude upper limit of branch ij.
Distributed photovoltaic cluster operation constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,
The reactive power lower and upper limit of distributed photovoltaic cluster at respectively t moment node j.
On-load regulator transformer operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijBecome for on-load voltage regulation on branch ij
The adjusting step-length of depressor, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load voltage regulation transformation on t moment branch ij
N-th of regulation stall of device,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
Static passive compensation device operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
Compensation capacitor group operation constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensation
The maximal regulated gear of capacitor group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jFor node j
Locate the reactive power variable quantity of every one grade of the tune of compensation capacitor group.
Energy storage device operation constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTTo be stored up at t+ Δ T moment node j
The electricity of energy device,For the charging limit value of energy storage device at node j；Pch,j,tIt is filled for energy storage device at t moment node j
Electrical power, Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge of energy storage device at node j
Power,For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisFor energy storage device
Discharging efficiency；Dch,j,t、Ddis,j,tFor 0-1 variable, when energy storage device charges, Dch,j,t=1, Ddis,j,t=0；Energy storage device is put
When electric, Dch,j,t=0, Ddis,j,t=1.
For power distribution network rolling optimization Controlling model, linearisation is carried out to on-load regulator transformer in conjunction with piece-wise linearization and is built
Mould, comprising:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
The power distribution network rolling optimization Controlling model after carrying out linearisation modeling is converted using second order cone relaxing techniques,
Construct MIXED INTEGER Second-order cone programming model, comprising:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
Solver includes MOSEK solver or Cplex solver；
Solving result includes the reactive power of distributed photovoltaic cluster, the regulation stall of on-load regulator transformer, static nothing
The reactive power of Reactive power compensation installations, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage device
Discharge power.
Embodiment 2
Based on the same inventive concept, the embodiment of the present invention 2 provides a kind of distributed photovoltaic clustered control device, including obtains
Module brings module into and solves module, and the concrete function of above-mentioned module is described in detail below:
Module is obtained, for obtaining the active power and power distribution network operation data of distributed photovoltaic cluster；
It brings module into, is constructed in advance for bringing the active power of distributed photovoltaic cluster and power distribution network operation data into
MIXED INTEGER Second-order cone programming model；
Module is solved, for solving using solver to model, and based on calculated result to distributed photovoltaic cluster
It is controlled；
Active power and power distribution network operation data structure of the MIXED INTEGER Second-order cone programming model based on distributed photovoltaic cluster
It builds.
The device that the embodiment of the present invention 2 provides further includes building module, and modeling module constructs MIXED INTEGER Second-order cone programming
Detailed process is as follows for model:
First modeling unit, the adjusting shelves for reactive power, on-load regulator transformer based on distributed photovoltaic cluster
Position, the reactive power of static passive compensation device, the regulation stall of compensation capacitor group, the charge power of energy storage device and storage
The discharge power of energy device, constructs power distribution network rolling optimization Controlling model；
Linearize modeling unit, for be directed to power distribution network rolling optimization Controlling model, in conjunction with piece-wise linearization to have carry adjust
Pressure transformer carries out linearisation modeling；
Converting unit, for being controlled using second order cone relaxing techniques the power distribution network rolling optimization after carrying out linearisation modeling
Model is converted, and MIXED INTEGER Second-order cone programming model is constructed.
The process of above-mentioned first modeling unit building power distribution network rolling optimization Controlling model is as follows:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, constructs power distribution network rolling optimization Controlling model
Objective function；
And following constraint condition is constructed for power distribution network rolling optimization Controlling model:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load voltage regulation become
Depressor operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
Objective function such as following formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is
Step-length is controlled, n is node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；
For square of the electric current of t moment branch ij.
Trend constraint such as following formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end of the branch of first node
Node set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node
The active power and reactive power of j, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk,
Pcluster,j,t、Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster at respectively t moment node j,
Pload,j,t、Qload,j,tThe active power and reactive power of load, P at respectively t moment node jch,j,tAt t moment node j
The charge power of energy storage device, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tAt t moment node j
The reactive power of compensation capacitor group, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；When for t
Carve square of node i voltage magnitude, Ui,tFor the voltage magnitude of t moment node i,For the flat of t moment node i voltage magnitude
Side,For square of t moment node j voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor t moment
The current amplitude of branch ij；kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
It determines as the following formula:
In formula,For square lower limit of t moment node j voltage magnitude,For square of t moment node j voltage magnitude
The upper limit；N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
Continuous variable w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t>=0 n ∈ 1,2 ..., N } (7)
w1ij,1,t≤dij,1,t(9)
w2ij,1,t≤dij,1,t(10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
Voltage level restraint such as following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
Tributary capacity constraint such as following formula:
In formula,For the current amplitude upper limit of branch ij.
Distributed photovoltaic cluster operation constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,
The reactive power lower and upper limit of distributed photovoltaic cluster at respectively t moment node j.
On-load regulator transformer operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijBecome for on-load voltage regulation on branch ij
The adjusting step-length of depressor, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load voltage regulation transformation on t moment branch ij
N-th of regulation stall of device,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
Static passive compensation device operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
Compensation capacitor group operation constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensation
The maximal regulated gear of capacitor group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jFor node j
Locate the reactive power variable quantity of every one grade of the tune of compensation capacitor group.
Energy storage device operation constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTTo be stored up at t+ Δ T moment node j
The electricity of energy device,For the charging limit value of energy storage device at node j；Pch,j,tIt is filled for energy storage device at t moment node j
Electrical power, Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge of energy storage device at node j
Power,For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisFor energy storage device
Discharging efficiency；Dch,j,t、Ddis,j,tFor 0-1 variable, when energy storage device charges, Dch,j,t=1, Ddis,j,t=0；Energy storage device is put
When electric, Dch,j,t=0, Ddis,j,t=1.
It linearizes modeling unit and is directed to power distribution network rolling optimization Controlling model, in conjunction with piece-wise linearization to on-load voltage regulation transformation
Device carries out linearisation modeling, and detailed process is as follows:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
Converting unit is using second order cone relaxing techniques to the power distribution network rolling optimization Controlling model after carrying out linearisation modeling
It is converted, constructs MIXED INTEGER Second-order cone programming model, detailed process is as follows:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
Above-mentioned solver includes MOSEK solver or Cplex solver；
Above-mentioned solving result includes the regulation stall, quiet of the reactive power of distributed photovoltaic cluster, on-load regulator transformer
The only reactive power of reactive power compensator, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage dress
The discharge power set.
For convenience of description, each section of apparatus described above is divided into various modules with function or unit describes respectively.
Certainly, each module or the function of unit can be realized in same or multiple softwares or hardware when implementing the application.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, institute
The those of ordinary skill in category field can still modify to a specific embodiment of the invention referring to above-described embodiment or
Equivalent replacement, these are applying for this pending hair without departing from any modification of spirit and scope of the invention or equivalent replacement
Within bright claims.
Claims (34)
1. a kind of distributed photovoltaic cluster control method characterized by comprising
Obtain the active power and power distribution network operation data of distributed photovoltaic cluster；
The active power of the distributed photovoltaic cluster and power distribution network operation data are brought into the MIXED INTEGER second order constructed in advance
Bore plan model；
The model is solved using solver, and distributed photovoltaic cluster is controlled based on calculated result；
Active power and power distribution network of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster run number
According to building.
2. distributed photovoltaic cluster control method according to claim 1, which is characterized in that the MIXED INTEGER second order cone
The building of plan model, comprising:
The regulation stall of reactive power, on-load regulator transformer based on distributed photovoltaic cluster, static passive compensation device
Reactive power, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage device discharge power, building
Power distribution network rolling optimization Controlling model；
For the power distribution network rolling optimization Controlling model, linearisation is carried out to on-load regulator transformer in conjunction with piece-wise linearization and is built
Mould；
The power distribution network rolling optimization Controlling model carried out after linearisation modeling is converted using second order cone relaxing techniques,
Construct MIXED INTEGER Second-order cone programming model.
3. distributed photovoltaic cluster control method according to claim 2, which is characterized in that the power distribution network rolling optimization
Controlling model building, comprising:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, constructs the objective function of the model；
And it is the following constraint condition of the model construction:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load regulator transformer
Operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
4. distributed photovoltaic cluster control method according to claim 3, which is characterized in that the objective function is as follows
Formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is control
Step-length, n are node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；For t
Square of the electric current of moment branch ij.
5. distributed photovoltaic cluster control method according to claim 3, which is characterized in that the trend constraint is as follows
Formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end-node of the branch of first node
Set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node j's
Active power and reactive power, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk, Pcluster,j,t、
Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster, P at respectively t moment node jload,j,t、Qload,j,tPoint
Not Wei at t moment node j load active power and reactive power, Pch,j,tFor the charging function of energy storage device at t moment node j
Rate, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tFor the nothing of compensation capacitor group at t moment node j
Function power, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；For t moment node i voltage magnitude
Square, Ui,tFor the voltage magnitude of t moment node i,For square of t moment node i voltage magnitude,For t moment node j
Square of voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor the current amplitude of t moment branch ij；
kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
6. distributed photovoltaic cluster control method according to claim 5, which is characterized in that describedIt determines as the following formula:
In formula,For square lower limit of t moment node j voltage magnitude,For square upper limit of t moment node j voltage magnitude；
N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
7. distributed photovoltaic cluster control method according to claim 6, which is characterized in that the continuous variable
w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t≥0 n∈{1,2,…,N} (7)
w1ij,1,t≤dij,1,t (9)
w2ij,1,t≤dij,1,t (10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
8. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the voltage level restraint is such as
Following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
9. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the tributary capacity constraint is such as
Following formula:
In formula,For the current amplitude upper limit of branch ij.
10. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the distributed photovoltaic collection
Group operation constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,Respectively
For the reactive power lower and upper limit of distributed photovoltaic cluster at t moment node j.
11. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the on-load voltage regulation transformation
Device operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijFor on-load regulator transformer on branch ij
Adjusting step-length, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load regulator transformer on t moment branch ij
N-th of regulation stall,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
12. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the static reactive
Device operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
13. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the compensation capacitor group
Operation constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensating electric capacity
The maximal regulated gear of device group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jTo be mended at node j
Repay the reactive power variable quantity of every one grade of the tune of capacitor group.
14. distributed photovoltaic cluster control method according to claim 5, which is characterized in that the energy storage device operation
Constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTFor energy storage device at t+ Δ T moment node j
Electricity,For the charging limit value of energy storage device at node j；Pch,j,tFor the charge power of energy storage device at t moment node j,
Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge power of energy storage device at node j,
For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisIt is imitated for the electric discharge of energy storage device
Rate；Dch,j,t、Ddis,j,tFor 0-1 variable, when the energy storage device charges, Dch,j,t=1, Ddis,j,t=0；The energy storage device is put
When electric, Dch,j,t=0, Ddis,j,t=1.
15. distributed photovoltaic cluster control method according to claim 10, which is characterized in that described to be directed to the distribution
Net rolling optimization Controlling model carries out linearisation modeling to on-load regulator transformer in conjunction with piece-wise linearization, comprising:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
16. distributed photovoltaic cluster control method according to claim 5, which is characterized in that described using second order cone pine
Relaxation technology converts the power distribution network rolling optimization Controlling model carried out after linearisation modeling, constructs MIXED INTEGER second order
Bore plan model, comprising:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
17. distributed photovoltaic cluster control method according to claim 1, which is characterized in that the solver includes
MOSEK solver or Cplex solver；
The solving result includes the reactive power of distributed photovoltaic cluster, the regulation stall of on-load regulator transformer, static nothing
The reactive power of Reactive power compensation installations, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage device
Discharge power.
18. a kind of distributed photovoltaic clustered control device characterized by comprising
Module is obtained, for obtaining the active power and power distribution network operation data of distributed photovoltaic cluster；
It brings module into, is constructed in advance for bringing the active power of the distributed photovoltaic cluster and power distribution network operation data into
MIXED INTEGER Second-order cone programming model；
Module is solved, for solving using solver to the model, and based on calculated result to distributed photovoltaic cluster
It is controlled；
Active power and power distribution network of the MIXED INTEGER Second-order cone programming model based on the distributed photovoltaic cluster run number
According to building.
19. distributed photovoltaic clustered control device according to claim 18, which is characterized in that described device further includes structure
Block is modeled, the modeling module is specifically used for:
First modeling unit, the regulation stall, quiet for reactive power, on-load regulator transformer based on distributed photovoltaic cluster
The only reactive power of reactive power compensator, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage dress
The discharge power set constructs power distribution network rolling optimization Controlling model；
Linearize modeling unit, for be directed to the power distribution network rolling optimization Controlling model, in conjunction with piece-wise linearization to have carry adjust
Pressure transformer carries out linearisation modeling；
Converting unit, for being controlled using second order cone relaxing techniques the power distribution network rolling optimization carried out after linearisation modeling
Model is converted, and MIXED INTEGER Second-order cone programming model is constructed.
20. distributed photovoltaic clustered control device according to claim 19, which is characterized in that first modeling unit
It is specifically used for:
The minimum target of distribution network loss of photovoltaic cluster access in a distributed manner, constructs the objective function of the model；
And it is the following constraint condition of the model construction:
Trend constraint, voltage level restraint, tributary capacity constraint, distributed photovoltaic cluster operation constraint, on-load regulator transformer
Operation constraint, static passive compensation device operation constraint, compensation capacitor group operation constraint and energy storage device operation constraint.
21. distributed photovoltaic clustered control device according to claim 20, which is characterized in that the objective function is as follows
Formula:
Wherein, F is the distribution network loss of distributed photovoltaic cluster access, t0For initial time, Δ T is time interval, and M is control
Step-length, n are node total number, and c (i) is using i as the minor details point set of the branch of first node；rijFor the resistance of branch ij；For t
Square of the electric current of moment branch ij.
22. distributed photovoltaic clustered control device according to claim 21, which is characterized in that the trend constraint is as follows
Formula:
In formula, α (j) is using j as the first node set of the branch of end-node, and β (j) is using j as the end-node of the branch of first node
Set；Pij,t、Qij,tThe respectively active power and reactive power of t moment branch ij, Pj,t、Qj,tRespectively t moment node j's
Active power and reactive power, Pjk,t、Qjk,tThe respectively active power and reactive power of t moment branch jk, Pcluster,j,t、
Qcluster,j,tThe active power and reactive power of distributed photovoltaic cluster, P at respectively t moment node jload,j,t、Qload,j,tPoint
Not Wei at t moment node j load active power and reactive power, Pch,j,tFor the charging function of energy storage device at t moment node j
Rate, Pdis,j,tFor the discharge power of energy storage device at t moment node j, Qc,j,tFor the nothing of compensation capacitor group at t moment node j
Function power, QSVC,j,tFor the reactive power of static passive compensation device at t moment node j；For t moment node i voltage magnitude
Square, Ui,tFor the voltage magnitude of t moment node i,For square of t moment node i voltage magnitude,For t moment node j
Square of voltage magnitude；xijFor the impedance of on-load regulator transformer on branch ij；Iij,tFor the current amplitude of t moment branch ij；
kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij.
23. distributed photovoltaic clustered control device according to claim 22, which is characterized in that describedAs the following formula really
It is fixed:
In formula,For square lower limit of t moment node j voltage magnitude,For square upper limit of t moment node j voltage magnitude；
N is the gear sum of on-load regulator transformer；w1ij,n,t、w2ij,n,tFor continuous variable.
24. distributed photovoltaic clustered control device according to claim 23, which is characterized in that the continuous variable
w1ij,n,t、w2ij,n,tMeet:
w1ij,n,t,w2ij,n,t≥0 n∈{1,2,…,N} (7)
w1ij,1,t≤dij,1,t (9)
w2ij,1,t≤dij,1,t (10)
w1ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (11)
w2ij,n,t≤dij,n-1,t+dij,n,t n∈{2,3,…N-1} (12)
dij,n,t∈{0,1} n∈{1,2,…,N-1} (14)
w1ij,N,t≤dij,N-1,t (15)
w2ij,N,t≤dij,N-1,t (16)
In formula, dij,n,t、dij,n-1,tFor 0-1 variable.
25. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the voltage level restraint
Such as following formula:
In formula,The respectively voltage magnitude lower and upper limit of node i.
26. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the tributary capacity constraint
Such as following formula:
In formula,For the current amplitude upper limit of branch ij.
27. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the distributed photovoltaic collection
Group operation constraint such as following formula:
In formula,For the active power predicted value of distributed photovoltaic cluster at t moment node j,Respectively
For the reactive power lower and upper limit of distributed photovoltaic cluster at t moment node j.
28. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the on-load voltage regulation transformation
Device operation constraint such as following formula:
kij,t=k0+Kij,n,tΔkij (21)
In formula, kij,tFor the no-load voltage ratio of on-load regulator transformer on t moment branch ij, Δ kijFor on-load regulator transformer on branch ij
Adjusting step-length, k0For the standard no-load voltage ratio of on-load regulator transformer, Kij,n,tFor on-load regulator transformer on t moment branch ij
N-th of regulation stall,The respectively lower and upper limit of branch ij on-load regulator transformer regulation stall.
29. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the static reactive
Device operation constraint such as following formula:
In formula,The reactive power lower and upper limit of static passive compensation device at respectively node j.
30. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the compensation capacitor group
Operation constraint such as following formula:
In formula, Hc,j,tFor the regulation stall of compensation capacitor group at t moment node j, and Hc,j,tFor integer, HmaxFor compensating electric capacity
The maximal regulated gear of device group, Qc,j,tFor the reactive power of compensation capacitor group at t moment node j, Δ Qc,jTo be mended at node j
Repay the reactive power variable quantity of every one grade of the tune of capacitor group.
31. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the energy storage device operation
Constraint such as following formula:
In formula, ESOC,j,tFor the electricity of energy storage device at t moment node j, ESOC,j,t+ΔTFor energy storage device at t+ Δ T moment node j
Electricity,For the charging limit value of energy storage device at node j；Pch,j,tFor the charge power of energy storage device at t moment node j,
Pdis,j,tFor the discharge power of energy storage device at t moment node j,For the maximum charge power of energy storage device at node j,
For the maximum discharge power of energy storage device at node j；ηchFor the charge efficiency of energy storage device, ηdisIt is imitated for the electric discharge of energy storage device
Rate；Dch,j,t、Ddis,j,tFor 0-1 variable, when the energy storage device charges, Dch,j,t=1, Ddis,j,t=0；The energy storage device is put
When electric, Dch,j,t=0, Ddis,j,t=1.
32. distributed photovoltaic clustered control device according to claim 27, which is characterized in that the linearisation modeling is single
Member is specifically used for:
Based on formula (6) and formula (21), formula (2) is converted to following formula:
33. distributed photovoltaic clustered control device according to claim 22, which is characterized in that the converting unit is specific
For:
Using second order cone relaxing techniques to the second order tapered be converted to formula (3) such as following formula:
34. distributed photovoltaic clustered control device according to claim 18, which is characterized in that the solver includes
MOSEK solver or Cplex solver；
The solving result includes the reactive power of distributed photovoltaic cluster, the regulation stall of on-load regulator transformer, static nothing
The reactive power of Reactive power compensation installations, the regulation stall of compensation capacitor group, the charge power of energy storage device and energy storage device
Discharge power.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210124A (en) * | 2019-05-31 | 2019-09-06 | 河海大学 | A kind of photovoltaic module inclination angle optimization method based on ANFIS algorithm |
| CN110380450A (en) * | 2019-08-13 | 2019-10-25 | 南方电网科学研究院有限责任公司 | A kind of photovoltaic control method, device, equipment and computer readable storage medium |
| CN112688334A (en) * | 2020-12-15 | 2021-04-20 | 国网河北省电力有限公司电力科学研究院 | Power distribution network voltage control method, device, equipment and storage medium |
| CN112821451A (en) * | 2021-01-11 | 2021-05-18 | 国网福建省电力有限公司泉州供电公司 | Distributed photovoltaic access coping method for smart town power distribution network based on demand side management and energy storage |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101593185B1 (en) * | 2014-11-21 | 2016-02-15 | 한국전자통신연구원 | Codebook design method and apparatus |
| CN105740973A (en) * | 2016-01-25 | 2016-07-06 | 天津大学 | Mixed integer cone programming based intelligent distribution system synthetic voltage reactive power optimization method |
| CN106921164A (en) * | 2017-04-05 | 2017-07-04 | 广东电网有限责任公司东莞供电局 | The MIXED INTEGER Second-order cone programming method and system of distribution voltage power-less collaboration optimization |
| CN106953359A (en) * | 2017-04-21 | 2017-07-14 | 中国农业大学 | A kind of active reactive coordinating and optimizing control method of power distribution network containing distributed photovoltaic |
-
2018
- 2018-10-24 CN CN201811241657.1A patent/CN109638874A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101593185B1 (en) * | 2014-11-21 | 2016-02-15 | 한국전자통신연구원 | Codebook design method and apparatus |
| CN105740973A (en) * | 2016-01-25 | 2016-07-06 | 天津大学 | Mixed integer cone programming based intelligent distribution system synthetic voltage reactive power optimization method |
| CN106921164A (en) * | 2017-04-05 | 2017-07-04 | 广东电网有限责任公司东莞供电局 | The MIXED INTEGER Second-order cone programming method and system of distribution voltage power-less collaboration optimization |
| CN106953359A (en) * | 2017-04-21 | 2017-07-14 | 中国农业大学 | A kind of active reactive coordinating and optimizing control method of power distribution network containing distributed photovoltaic |
Non-Patent Citations (1)
| Title |
|---|
| 刘一兵等: "基于混合整数二阶锥规划的三相有源配电网无功优化", 《电力系统自动化》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210124A (en) * | 2019-05-31 | 2019-09-06 | 河海大学 | A kind of photovoltaic module inclination angle optimization method based on ANFIS algorithm |
| CN110380450A (en) * | 2019-08-13 | 2019-10-25 | 南方电网科学研究院有限责任公司 | A kind of photovoltaic control method, device, equipment and computer readable storage medium |
| CN112688334A (en) * | 2020-12-15 | 2021-04-20 | 国网河北省电力有限公司电力科学研究院 | Power distribution network voltage control method, device, equipment and storage medium |
| CN112688334B (en) * | 2020-12-15 | 2023-05-09 | 国网河北省电力有限公司电力科学研究院 | Power distribution network voltage control method, device, equipment and storage medium |
| CN112821451A (en) * | 2021-01-11 | 2021-05-18 | 国网福建省电力有限公司泉州供电公司 | Distributed photovoltaic access coping method for smart town power distribution network based on demand side management and energy storage |
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