CN106655226B - Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch - Google Patents
Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch Download PDFInfo
- Publication number
- CN106655226B CN106655226B CN201611034925.3A CN201611034925A CN106655226B CN 106655226 B CN106655226 B CN 106655226B CN 201611034925 A CN201611034925 A CN 201611034925A CN 106655226 B CN106655226 B CN 106655226B
- Authority
- CN
- China
- Prior art keywords
- node
- phase
- sofe switch
- active power
- constraint
- 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.)
- Active
Links
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/26—Arrangements for eliminating or reducing asymmetry in polyphase networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/50—Arrangements for eliminating or reducing asymmetry in polyphase networks
Abstract
A kind of active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch: the structure and parameter of distribution system are inputted；According to distribution system structure and parameter, while considering system loss, system voltage imbalance degree and distribution transformer outlet side current imbalance degree, establishes the active power distribution network asymmetric operation Optimized model based on intelligent Sofe Switch；Nonlinear Constraints in the active power distribution network asymmetric operation Optimized model based on intelligent Sofe Switch are subjected to linearisation and convex relaxation processes according to the canonical form of semi definite programming, are converted into semi definite programming model；Obtained semi definite programming model is solved using the mathematics solver for solving semi definite programming；Solving result is exported, and verifies the accuracy of positive semidefinite relaxation.The present invention can carry out Unify legislation to the active power distribution network asymmetric operation optimization problem based on intelligent Sofe Switch, reduce model solution difficulty, have in calculating speed and significantly promoted, can be quickly obtained optimal system operating scheme.
Description
Technical field
The present invention relates to a kind of power distribution network running optimizatin methods.Matched more particularly to a kind of based on the active of intelligent Sofe Switch
Power grid asymmetric operation optimization method.
Background technique
At this stage, renewable energy mostly in a distributed manner power supply (Distributed Generation, DG) mode extensively,
Power distribution network is accessed to high-density.After a large amount of distributed generation resource access distribution systems, mesolow level electric system will be significantly changed
Structure and the method for operation, make distribution system from traditional Radial network development be active power distribution network, functionally also by single
Electric energy distribution diversification in role be the novel electric power exchange system for integrating electricity collection, transmission, storage, distribution.Active
In power distribution network, controllable device is increasing, and network structure and the method for operation are more flexible changeable, the diversified power generation of user side,
Power demand and then make the energy flow of active power distribution network further complicated with the flexible interaction mechanism of net side.
Power distribution network itself has the characteristics that three-phase line parameter unbalance, three-phase load unbalance, with active power distribution network
In the distributed generation resource permeability of single-phase access be continuously improved and the asymmetric Demand Side Response such as electric car, smart home is set
Standby extensive access, the three-phase imbalance feature of active power distribution network is more prominent, if being still reduced to balanced system using single-phase
Model is calculated, and does not meet the actual conditions of power distribution network operation, and can generate biggish error, therefore, using three-phase
It is very necessary that model optimizes analysis to active power distribution network.
In active power distribution network, the shortcoming that primary equipment adjusts control ability has become the raising of its operation level of restricting current
Main bottleneck.The control modes such as conventional interconnection switch reconstruct, load tap changer adjustment, compensating capacitor switching are due to tune
Energy saving power is limited, response speed is slow and precision is insufficient, it is difficult to which power distribution network is high-precision when meeting renewable energy and load frequent fluctuation
It spends real time execution and optimizes demand.And the rapid development of the novel flexible distribution technique based on power electronic equipment is active power distribution system
System the further of operation level provides opportunity.Wherein, intelligent Sofe Switch (the Soft Open towards distribution level
Points, SOP) technology be traditional feeder line interconnection switch is substituted with controllable converters, thus between realizing feeder line often
Stateization flexibility " being flexible coupling ".Compared with traditional interconnection switch, intelligent Sofe Switch avoids safety caused by switch frequently conjugates
Hidden danger, movement speed faster, and act cost it is lower, failure influence it is smaller, substantially increase distribution control flexibility and
Rapidity.Therefore, the asymmetrical three-phase model based on power distribution network proposes that a kind of active power distribution network based on intelligent Sofe Switch is not right
Claim running optimizatin method, by adjusting the operation reserve of intelligent Sofe Switch in active power distribution network, with reduce distribution system loss and
Three-phase imbalance degree.
For the active power distribution network asymmetric operation optimization problem based on intelligent Sofe Switch, controlling variable is intelligent Sofe Switch
The idle power output of reactive power and schedulable distributed generation resource that the active power of transmission and both ends issue, mathematics essence are
Extensive nonconvex nonlinear programming problems.For this kind of nonlinear mathematics optimization problem, it has been suggested that and developed a variety of optimizations
Method specifically includes that 1) traditional mathematics optimization method, including analytic method, original dual interior point etc.；2) heuristic calculation
Method, including genetic algorithm, simulated annealing etc..Although traditional mathematics optimization method can theoretically carry out global optimizing,
But can there is a problem of that computational efficiency is low in the extensive nonconvex nonlinear programming problems of actual treatment；Heuritic approach is in the time
Require have a polynomial time in terms of complexity, calculating speed is very fast, but can only obtain locally optimal solution, not can guarantee solution
Global Optimality.So speed or precision are mostly not on such issues that traditional mathematics optimization method, heuritic approach are for solving
It can meet the requirements simultaneously.Therefore, it is necessary to a kind of accurate, the above-mentioned optimization problem of rapid solving models and algorithm.
Semi definite programming (Semi Definite Programming, SDP) is pushing away for linear programming and Non-Linear Programming
It extensively, is to make asking for linear function greatly (minimum) change under conditions of meeting and constraining " the radiation combination positive semidefinite of symmetrical matrix "
Topic.Semi definite programming belongs to convex programming, can guarantee the Global Optimality of solution, compared with other common algorithms, semi definite programming
Method is effectively reduced heavy calculating pressure, there is biggish advantage in calculating speed and EMS memory occupation.
Summary of the invention
The technical problem to be solved by the invention is to provide one kind can be realized take into account three-phase power distribution system economical operation and
Reduce the active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch of uneven degree.
The technical scheme adopted by the invention is that: a kind of active power distribution network asymmetric operation optimization based on intelligent Sofe Switch
Method includes the following steps:
1) distribution system: three-phase line parameter, load level and network topology connection relationship, schedulable distribution is inputted
On-position, type, capacity and the parameter of formula power supply, on-position, capacity and the parameter of intelligent soft switch device, system operation
Voltage level and branch current limitation, system reference voltage and reference power；
2) the distribution system structure and parameter provided according to step 1), while considering distribution system loss, system voltage not
It is asymmetric to establish the active power distribution network based on intelligent Sofe Switch for balanced degree and distribution transformer outlet side current imbalance degree
Optimal operation model, comprising: selection root node be balance nodes, setting distribution system loss, system voltage imbalance degree and
The minimum objective function of the sum of the linear weighted function of distribution transformer outlet side current imbalance degree, considers active power distribution network respectively
Run constraint, system security constraint, intelligent Sofe Switch operation constraint, distributed generation resource operation constraint；
3) the active power distribution network asymmetric operation based on intelligent Sofe Switch is optimized according to the canonical form of semi definite programming
Nonlinear Constraints carry out linearisation and positive semidefinite relaxation processes in model, are converted into semi definite programming model；
4) obtained semi definite programming model is solved using the mathematics solver for solving semi definite programming, is obtained:
Three phase reactive power value, the active reactive of distributed generation resource that the three phases active power value of intelligent Sofe Switch transmission and both ends issue
The uneven degree that power generating value, network power flow solutions, distribution system loss and system are run；
5) solving result of step 4) is exported, and verifies the accuracy of positive semidefinite relaxation processes.
The loss of distribution system described in step 2), system voltage imbalance degree and distribution transformer outlet side electric current are uneven
The minimum objective function of the sum of the linear weighted function of weighing apparatus degree indicates are as follows:
In formula, f is lost in distribution systemloss, system voltage imbalance degreeNot with distribution transformer outlet side electric current
Balanced degreeIndicated respectively with following formula, α, β and γ be corresponding weight coefficient, alpha+beta+γ=1,
In formula, NNFor the node total number of system；For what is injected in node iPhase apparent energy,WhereinEach for node i is mutually gathered, and a, b, c are respectively the three-phase of node i；For node iPhase voltage, For distribution transformer outlet side routePhase current,WhereinFor route ij's
It is each mutually to gather.
Active power distribution network described in step 2) runs constraint representation are as follows:
Basic trend constraint:
Positive semidefinite constraint:
Order is 1 constraint:
In formula, ΩbFor line set；zijFor the complex impedance of branch ij；Indicate each phase of node j
Apparent energy；Auxiliary variableIndicate each phase voltage of node i；Auxiliary variable Each phase current of branch ij is flowed through in expression,For what is flowed through on branch ijMutually electricity
Stream；For the apparent energy for flowing through branch ij；WithDistributed generation resource injects on respectively node j
'sPhase active power, intelligent Sofe Switch transmitWhat phase active power and load consumedPhase active power；
WithDistributed generation resource injects on respectively node jPhase reactive power, intelligent Sofe Switch issuePhase reactive power and
Load consumptionPhase reactive power；Jk is route jk；SjkFor the apparent energy for flowing through route jk；Auxiliary variable
VjIndicate each phase voltage of node j；Each for node j is mutually gathered.
System security constraint described in step 2) indicates are as follows:
In formula,Vi WithFor each phase minimum allowable voltage value and maximum allowable voltage of node i；For each of branch ij
Phase maximum allowed current value；Auxiliary variableViIndicate each phase voltage of node i；IijThe each of route ij is flowed through in expression
Phase current；Auxiliary variable For the reference voltage of distribution transformer outlet.
Intelligent Sofe Switch described in step 2) runs constraint representation are as follows:
Active transmission constraint:
Idle units limits:
Capacity-constrained:
In formula,WithThe intelligent Sofe Switch injection respectively in node iPhase active power and reactive power；WithThe active loss of intelligent Sofe Switch both ends inverter between access node i and j,
Respectively corresponding loss factor；Respectively between access node i and j
Intelligent Sofe Switch both ends invertersPhase access capacity and the reactive power upper and lower limit that can be output；For in node j
Upper intelligence Sofe Switch injectionPhase active power；For Sofe Switch injection intelligent on node jMutually there is reactive power.
Distributed generation resource described in step 2) runs constraint representation are as follows:
Active power output constraint:
Idle units limits:
Capacity-constrained:
In formula,For distributed generation resource in node iPhase active power predicted value；Respectively
For distributed generation resource in node iPhase access capacity and the reactive power upper and lower limit that can be output；To divide in node i
The injection of cloth power supplyPhase active power；For the distributed generation resource injection in node iMutually there is reactive power.
It is according to the canonical form of semi definite programming that the active power distribution network based on intelligent Sofe Switch is not right described in step 3)
Claim Nonlinear Constraints in optimal operation model to carry out linearisation and positive semidefinite relaxation processes, is converted into semi definite programming mould
Type, specific method for transformation are as follows:
(1) contain absolute value term in intelligent Sofe Switch operation constraint conditionWithIntroduce auxiliary variable
WithInstead of former absolute value term, then intelligent Sofe Switch operation constraint condition linearisation indicates are as follows:
And increase following equivalent constraint:
In formula,WithThe active damage of intelligent Sofe Switch both ends inverter between access node i and j
Consumption； Respectively corresponding loss factor；WithThe intelligent Sofe Switch injection respectively in node i
Phase active power and reactive power；WhereinEach for route ij is mutually gathered；
(2) in view of the non-convex non-linear form of active power distribution network operation constraint, it is difficult to obtain optimal solution, and solution efficiency
It is not high, it is further processed using positive semidefinite relaxation processes, is that 1 constraint relaxation is fallen by order in active power distribution network operation constraint；
(3) capacity-constrained of intelligent Sofe Switch operation constraint and the capacity-constrained of distributed generation resource operation constraint are non-thread
Property second order rotating cone constraint, common version indicate are as follows:
In formula, x1It indicatesMeaning is intelligent Sofe Switch injection in node iPhase active powerIt is injected with distributed generation resource in node iPhase active powerx2It indicatesMeaning is node i
Upper intelligence Sofe Switch injectionPhase reactive powerIt is injected with distributed generation resource in node iPhase reactive powerx3
It indicates Meaning is intelligent Sofe Switch in node iPhase access capacityWith distributed electrical in node i
SourcePhase access capacity
Mutual-through type form carries out ε-relaxation, and wherein ε is relaxation precision, obtains the following institute of ε-relaxation form of rotating cone constraint
Show:
Polyhedron approximation is carried out to the relaxation form of rotating cone constraint, i.e. 2 (v+1) a auxiliary variables of introducingAnd ηi, approximate
Equivalence is converted to one group of linear equality and inequality group, wherein i=0,1 ... v, as follows:
η0≥x2, η0≥-x2
Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch of the invention is calculated according to semi definite programming
The basic principle of method has carried out linearisation and positive semidefinite relaxation to Nonlinear Constraints in Optimized model, will be former non-convex non-thread
Property model conversation be semi definite programming model, be easy to use mathematical optimization packet solved.Positive semidefinite rule of the present invention
Unify legislation can be carried out to the active power distribution network asymmetric operation optimization problem based on intelligent Sofe Switch by drawing, and reduced model and asked
Difficulty is solved, has in calculating speed and is significantly promoted.It, can and because of excellent mathematical characteristic possessed by semi definite programming
Enough optimalitys for guaranteeing to solve, apply it in active power distribution network asymmetric operation optimization problem, can be quickly obtained optimal
System operating scheme.
Detailed description of the invention
Fig. 1 is modified 123 node example of IEEE and distributed generation resource, intelligent Sofe Switch on-position figure；
Fig. 2 is the flow chart of the active power distribution network asymmetric operation optimization method the present invention is based on intelligent Sofe Switch；
Fig. 3 a is each phase active power situation of intelligent Sofe Switch SOP1 transmission；
Fig. 3 b is each phase active power situation of intelligent Sofe Switch SOP2 transmission；
Fig. 3 c is each phase reactive power situation that the both ends intelligent Sofe Switch SOP1 issue；
Fig. 3 d is each phase reactive power situation that the both ends intelligent Sofe Switch SOP2 issue；
Fig. 4 is the voltage unbalance factor optimization situation using intelligent Sofe Switch optimization front and back each node of active power distribution network；
Fig. 5 a is each phase voltage distribution situation of system before being optimized using intelligent Sofe Switch；
Fig. 5 b is using each phase voltage distribution situation of system after intelligent Sofe Switch optimization；
Fig. 6 is the verifying situation of positive semidefinite relaxation accuracy.
Specific embodiment
It is excellent to the active power distribution network asymmetric operation of the invention based on intelligent Sofe Switch below with reference to embodiment and attached drawing
Change method is described in detail.
Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch of the invention is used for three-phase power distribution system
Asymmetric operation optimization problem research can be solved using solvers such as MOSEK, the SEDUMI being integrated on MATLAB.
The present invention solves above-mentioned semi definite programming problem using MOSEK solver, is surveyed with modified 123 node of IEEE shown in FIG. 1
Test system is embodiment.
Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch of the invention, as shown in Fig. 2, including such as
Lower step:
1) distribution system: three-phase line parameter, load level and network topology connection relationship, schedulable distribution is inputted
On-position, type, capacity and the parameter of formula power supply, on-position, capacity and the parameter of intelligent soft switch device, system operation
Voltage level and branch current limitation, system reference voltage and reference power；
For the embodiment of the present invention, the impedance value of circuit element, load member first in input 123 node system of IEEE
The active power and reactive power of part, detail parameters are shown in Table 1；For the asymmetric access bring for fully considering high permeability photovoltaic
It influences, 10 groups of photovoltaic systems is respectively connected in IEEE123 node example, idle power output is adjusted within the scope of capacity limit
Section, basic configuration parameter are shown in Table 2；One group of intelligence is respectively connected between node 55 and node 93 and between node 117 and node 123
Energy Sofe Switch, the total capacity of intelligent Sofe Switch both ends inverter is 2000kVA, and each phase reactive power output upper limit is
The active loss coefficient of 500kVar, both ends inverter are set as 0.02, and provide to node injecting power to be positive direction；Node 1 is
Distribution transformer outlet, reference voltage (per unit value) are set as 1.0, and the alternate differential seat angle of three-phase voltage is set as 120 °；Each node voltage
The safe operation bound of amplitude (per unit value) is respectively 1.05 and 0.95；Finally be arranged system reference voltage be 4.16kV,
Reference power is 1MVA.
2) the distribution system structure and parameter provided according to step 1), while considering distribution system loss, system voltage not
It is asymmetric to establish the active power distribution network based on intelligent Sofe Switch for balanced degree and distribution transformer outlet side current imbalance degree
Optimal operation model, comprising: selection root node be balance nodes, setting distribution system loss, system voltage imbalance degree and
The minimum objective function of the sum of the linear weighted function of distribution transformer outlet side current imbalance degree, considers active power distribution network respectively
Run constraint, system security constraint, intelligent Sofe Switch operation constraint, distributed generation resource operation constraint；Wherein,
(1) distribution system loss, system voltage imbalance degree and distribution transformer outlet side current imbalance described in
The minimum objective function of the sum of linear weighted function of degree indicates are as follows:
In formula, f is lost in distribution systemloss, system voltage imbalance degreeNot with distribution transformer outlet side electric current
Balanced degreeIndicated respectively with following formula, α, β and γ be corresponding weight coefficient, alpha+beta+γ=1,
In formula, NNFor the node total number of system；For what is injected in node iPhase apparent energy,WhereinIndicate that each of node i is mutually gathered, a, b, c are respectively the three-phase of node i；For node iPhase voltage, For distribution transformer outlet side routePhase current,WhereinIndicate route ij
It is each mutually gather.
(2) active power distribution network described in runs constraint representation are as follows:
In formula, ΩbFor line set；zijFor the complex impedance of branch ij；Indicate each phase of node j
Apparent energy；Auxiliary variableIndicate each phase voltage of node i；Auxiliary variable Each phase current of branch ij is flowed through in expression,For what is flowed through on branch ijMutually electricity
Stream；For the apparent energy for flowing through branch ij；WithDistributed generation resource injects on respectively node j
'sPhase active power, intelligent Sofe Switch transmitWhat phase active power and load consumedPhase active power；
WithDistributed generation resource injects on respectively node jPhase reactive power, intelligent Sofe Switch issuePhase reactive power and
Load consumptionPhase reactive power, jk are route jk；SjkFor the apparent energy for flowing through route jk；Auxiliary variable
VjIndicate each phase voltage of node j；Each for node j is mutually gathered.Formula (5)~(7) indicate active power distribution network base
This trend constraint, formula (8) and (9) respectively indicate the positive semidefinite constraint of routing matrix variable and order is 1 constraint.
(3) the system security constraint described in indicates are as follows:
In formula,Vi WithFor each phase minimum allowable voltage value and maximum allowable voltage of node i；For each of branch ij
Phase maximum allowed current value；Auxiliary variableViIndicate each phase voltage of node i；IijThe each of route ij is flowed through in expression
Phase current；Auxiliary variable For the reference voltage of distribution transformer outlet.
(4) the intelligent Sofe Switch described in runs constraint representation are as follows:
In formula,WithThe intelligent Sofe Switch injection respectively in node iPhase active power and reactive power；WithThe active loss of intelligent Sofe Switch both ends inverter between access node i and j,
Respectively corresponding loss factor；Respectively between access node i and j
Intelligent Sofe Switch both ends invertersPhase access capacity and the reactive power upper and lower limit that can be output；For in node j
Upper intelligence Sofe Switch injectionPhase active power；For Sofe Switch injection intelligent on node jMutually there is reactive power.
Formula (13) indicates that the active power transfer for considering intelligent Sofe Switch running wastage constrains, and formula (16) and (17) indicate that intelligence is soft and open
The reactive power constraint that both ends issue is closed, formula (18) and (19) indicate the capacity-constrained of intelligent Sofe Switch.
(5) distributed generation resource described in runs constraint representation are as follows:
In formula,For distributed generation resource in node iPhase active power predicted value；Respectively
For distributed generation resource in node iPhase access capacity and the reactive power upper and lower limit that can be output；To divide in node i
The injection of cloth power supplyPhase active power；For the distributed generation resource injection in node iMutually there is reactive power.Formula
(20) and (21) indicate that the active power of distributed generation resource and reactive power constraint, formula (22) indicate the capacity of distributed generation resource about
Beam.
3) the active power distribution network asymmetric operation based on intelligent Sofe Switch is optimized according to the canonical form of semi definite programming
Nonlinear Constraints carry out linearisation and positive semidefinite relaxation processes in model, are converted into semi definite programming model；Specific conversion
Method is as follows:
(1) contain absolute value term in intelligent Sofe Switch operation constraint equation (14) and (15)WithIt introduces
Auxiliary variableWithInstead of former absolute value term, then intelligent Sofe Switch operation constraint equation (14) and (15) can be linear
Changing indicates are as follows:
And increase following equivalent constraint:
In formula,WithThe active damage of intelligent Sofe Switch both ends inverter between access node i and j
Consumption； Respectively corresponding loss factor；WithThe intelligent Sofe Switch injection respectively in node i
Phase active power and reactive power；WhereinEach for route ij is mutually gathered；
(2) in view of the non-convex non-linear form of active power distribution network operation constraint, it is multinomial that the above problem belongs to uncertainty
Formula (Non-deterministic Polynomial, NP) hardly possible problem, it is difficult to obtain optimal solution, and solution efficiency is not high, use
Positive semidefinite relaxation method is further processed, and is that 1 constraint formula (9) relaxation is fallen by order in active power distribution network operation constraint；
(3) the capacity-constrained formula (22) that intelligent Sofe Switch capacity-constrained formula (18), (19) and distributed generation resource operation constrain
It is nonlinear second order rotating cone constraint, common version indicates are as follows:
In formula, x1It indicatesMeaning is intelligent Sofe Switch injection in node iPhase active powerIt is injected with distributed generation resource in node iPhase active powerx2It indicatesMeaning is node i
Upper intelligence Sofe Switch injectionPhase reactive powerIt is injected with distributed generation resource in node iPhase reactive powerx3
It indicates Meaning is intelligent Sofe Switch in node iPhase access capacityWith distributed electrical in node i
SourcePhase access capacity
Mutual-through type form carries out ε-relaxation, and wherein ε is relaxation precision, obtains the following institute of ε-relaxation form of rotating cone constraint
Show:
Polyhedron approximation is carried out to the relaxation form formula (29) of rotating cone constraint, i.e. 2 (v+1) a auxiliary variables of introducingWith
ηi, approximately equivalent is converted to one group of linear equality and inequality group, wherein i=0,1 ... v, as follows:
η0≥x2, η0≥-x2 (31)
4) obtained semi definite programming model is solved using the mathematics solver for solving semi definite programming, is obtained:
Three phase reactive power value, the active reactive of distributed generation resource that the three phases active power value of intelligent Sofe Switch transmission and both ends issue
The uneven degree that power generating value, network power flow solutions, distribution system loss and system are run；
5) solving result of step 4) is exported, and verifies the accuracy of positive semidefinite relaxation processes.
Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch of the invention establishes soft based on intelligence
The active power distribution network asymmetric operation Optimized model of switch improves active distribution to improve the economy of active power distribution network operation
Net the uneven degree of operation.
Modified 123 node example structure of IEEE is as shown in Figure 1, the present embodiment passes through intelligence in adjusting active power distribution network
The three phase reactive power that the three phases active power of energy Sofe Switch transmission and both ends issue, is improving active power distribution network performance driving economy
While, improve the uneven degree of three-phase distribution net operation, improve the safety of system operation, each of intelligent Sofe Switch is mutually adjusted
Degree strategy is as shown in Fig. 3 a to Fig. 3 d.
YALMIP Optimization Modeling platform based on MATLAB exploitation establishes the above-mentioned active power distribution network based on intelligent Sofe Switch
Asymmetric operation Optimized model, and solved using MOSEK algorithm packet.The hardware environment of test macro is Intel Xeon
(R) CPU2.60GHz, 32GB memory, operating system are Win 10 (64bit), and exploitation environment is MATLAB R2013b, YALMIP
Version is that 20150918, MOSEK version is V7.1.0.14.
The imbalance of three-phase voltage degree of each node is described using the uneven index degree of node voltage:
In formula, VI ,-And VI ,+The respectively negative sequence component and positive-sequence component of node i voltage value, can be by the three-phase electricity of node i
Pressure is calculated, as shown in formula (38) and (39).
In order to measure the imbalance of three-phase voltage degree of whole system, the total degree of unbalancedness for being further introduced into system voltage refers to
Mark:
Prioritization scheme reduces distribution system loss by the operation reserve of intelligent Sofe Switch in adjusting active power distribution network,
Decreasing loss rate is 53.28%, and improves the uneven degree of active power distribution network, system voltage degree of unbalancedness λUI, sysIt has dropped
99.26%, the three-phase current of active balance distribution transformer outlet, effect of optimization is obvious, optimization front and back running situation
Comparison result be shown in Table 3.
Using the negative phase-sequence electricity for reducing system after the active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch
Pressure, the voltage unbalance factor of each node are substantially reduced, and the voltage unbalance factor of each node in optimization front and back optimizes situation such as Fig. 4 institute
Show.
By adjusting the operation reserve of intelligent Sofe Switch in active power distribution network, distribution system loss and operation can reduced
While uneven degree, improve the voltage's distribiuting of power distribution network, effectively reduce the voltage deviation between each phase of node, improves power supply
Quality of voltage guarantees the operation of system long-term safety, and optimization front and back node three-phase voltage amplitude situation is as shown in figure 5 a and 5b.
In order to verify the accuracy of positive semidefinite relaxation, maximum two eigenvalue λs of matrix variables in calculating formula (9)1And λ2(|
λ1|≥|λ2| >=0), and obtain ratio r atio=| λ2/λ1|, the orders of the smaller then matrix variables of ratio value is closer to 1, each route
The ratio ratio calculation result of matrix variables is shown in Fig. 6, respectively less than 10-6, i.e. positive semidefinite relaxation is accurate.
The mathematics essence of active power distribution network asymmetric operation optimization problem is extensive nonconvex nonlinear programming problems, at present
Existing optimization method can not carry out Efficient Solution, a kind of active power distribution network based on intelligent Sofe Switch proposed by the present invention mostly
Running optimizatin method uses semi definite programming, can fast and accurately solve problems, by adjusting intelligence in active power distribution network
The operation reserve of energy Sofe Switch carries out asymmetrical three-phase running optimizatin to power distribution network.
In active power distribution network, by rationally adjusting the operation reserve of intelligent Sofe Switch, optimization system it is active and idle
Trend distribution, can effectively improve the economy of active power distribution network operation, and improve the uneven journey of three-phase distribution net operation
Degree, the safety of safeguards system operation.
1 IEEE of table, 123 node example line information and load power
2 distributed generation resource configuration parameter of table
The optimization of table 3 front and back running situation compares
Claims (7)
1. the active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch, which comprises the steps of:
1) distribution system: three-phase line parameter, load level and network topology connection relationship, schedulable distributed electrical is inputted
On-position, type, capacity and the parameter in source, on-position, capacity and the parameter of intelligent soft switch device, system working voltage
The limitation of horizontal and line current, system reference voltage and reference power；
2) the distribution system structure and parameter provided according to step 1), while considering that distribution system loss, system voltage are uneven
Degree and distribution transformer outlet side current imbalance degree establish the active power distribution network asymmetric operation based on intelligent Sofe Switch
Optimized model, comprising: selection root node is balance nodes, the loss of setting distribution system, system voltage imbalance degree and distribution
The minimum objective function of the sum of the linear weighted function of transformer outlet side current imbalance degree considers active power distribution network operation respectively
Constraint, system security constraint, intelligent Sofe Switch operation constraint, distributed generation resource operation constraint；
3) according to the canonical form of semi definite programming by the active power distribution network asymmetric operation Optimized model based on intelligent Sofe Switch
Middle Nonlinear Constraints carry out linearisation and positive semidefinite relaxation processes, are converted into semi definite programming model；
4) obtained semi definite programming model is solved using the mathematics solver for solving semi definite programming, is obtained: intelligence
The three phases active power value of Sofe Switch transmission and three phase reactive power value, the active reactive of the distributed generation resource power output of both ends sending
Value, the uneven degree of the loss of network power flow solutions, distribution system and system operation；
5) solving result of step 4) is exported, and verifies the accuracy of positive semidefinite relaxation processes.
2. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, the loss of distribution system described in step 2), system voltage imbalance degree and distribution transformer outlet side current imbalance
The minimum objective function of the sum of linear weighted function of degree indicates are as follows:
In formula, f is lost in distribution systemloss, system voltage imbalance degreeWith distribution transformer outlet side current imbalance
Degree fI unbanIndicated respectively with following formula, α, β and γ be corresponding weight coefficient, alpha+beta+γ=1,
In formula, NNFor the node total number of system；For what is injected in node iPhase apparent energy,WhereinEach for node i is mutually gathered, and a, b, c are respectively the three-phase of node i；For node iPhase voltage, For distribution transformer outlet side routePhase current,WhereinFor route ij's
It is each mutually to gather.
3. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, active power distribution network described in step 2) runs constraint representation are as follows:
Basic trend constraint:
Positive semidefinite constraint:
Order is 1 constraint:
In formula, ΩbFor line set；zijFor the complex impedance of route ij；Indicate that each of node j mutually regards
In power；Auxiliary variable vi=ViVi H,Indicate each phase voltage of node i,For node
The each of i is mutually gathered；Auxiliary variableEach phase current of route ij is flowed through in expression,
For what is flowed through on route ijPhase current,Each for route ij is mutually gathered；To flow through route ij
Apparent energy；WithDistributed generation resource injects on respectively node jPhase active power, intelligent Sofe Switch
TransmissionWhat phase active power and load consumedPhase active power；WithIt is distributed on respectively node j
Power supply injectionPhase reactive power, intelligent Sofe Switch issueWhat phase reactive power and load consumedPhase reactive power；jk
For route jk；SjkFor the apparent energy for flowing through route jk；Auxiliary variable vj=VjVj H, VjIndicate each phase voltage of node j；Each for node j is mutually gathered.
4. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, system security constraint described in step 2) indicates are as follows:
In formula,Vi WithFor each phase minimum allowable voltage value and maximum allowable voltage of node i；For route ij it is each mutually most
It is big to allow current value；Auxiliary variable vi=ViVi H, ViIndicate each phase voltage of node i；lijIt indicates to flow through each mutually electric of route ij
Stream；Auxiliary variable For the reference voltage of distribution transformer outlet.
5. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, intelligent Sofe Switch described in step 2) runs constraint representation are as follows:
Active transmission constraint:
Idle units limits:
Capacity-constrained:
In formula,WithThe intelligent Sofe Switch injection respectively in node iPhase active power and reactive power；Pi SOP ,lossAnd Pj SOP,lossThe active loss of intelligent Sofe Switch both ends inverter between access node i and j,Point
It Wei not corresponding loss factor；Respectively between access node i and j
Intelligent Sofe Switch both ends invertersPhase access capacity and the reactive power upper and lower limit that can be output；For in node j
Upper intelligence Sofe Switch injectionPhase active power；For Sofe Switch injection intelligent on node jMutually there is reactive power.
6. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, distributed generation resource described in step 2) runs constraint representation are as follows:
Active power output constraint:
Idle units limits:
Capacity-constrained:
In formula,For distributed generation resource in node iPhase active power predicted value；Respectively save
Distributed generation resource on point iPhase access capacity and the reactive power upper and lower limit that can be output；It is distributed in node i
Power supply injectionPhase active power；For the distributed generation resource injection in node iMutually there is reactive power.
7. the active power distribution network asymmetric operation optimization method according to claim 1 based on intelligent Sofe Switch, feature
It is, is transported the active power distribution network asymmetry based on intelligent Sofe Switch according to the canonical form of semi definite programming described in step 3)
Nonlinear Constraints carry out linearisation and positive semidefinite relaxation processes in row Optimized model, are converted into semi definite programming model, have
Body method for transformation is as follows:
(1) contain absolute value term in intelligent Sofe Switch operation constraint conditionWithIntroduce auxiliary variableWithInstead of former absolute value term, then intelligent Sofe Switch operation constraint condition linearisation indicates are as follows:
And increase following equivalent constraint:
In formula, Pi SOP,lossAnd Pj SOP,lossThe active loss of intelligent Sofe Switch both ends inverter between access node i and j；Respectively corresponding loss factor；WithThe intelligent Sofe Switch injection respectively in node iPhase
Active power and reactive power；WhereinEach for route ij is mutually gathered；
(2) in view of the non-convex non-linear form of active power distribution network operation constraint, it is difficult to obtain optimal solution, and solution efficiency is not
Order in active power distribution network operation constraint is that 1 constraint relaxation is fallen using positive semidefinite relaxation processes by height；
(3) capacity-constrained of intelligent Sofe Switch operation constraint and the capacity-constrained of distributed generation resource operation constraint are nonlinear
The constraint of second order rotating cone, common version indicate are as follows:
In formula, x1It indicatesMeaning is intelligent Sofe Switch injection in node iPhase active powerWith
Distributed generation resource injects in node iPhase active powerx2It indicatesMeaning is intelligence in node i
Energy Sofe Switch injectionPhase reactive powerIt is injected with distributed generation resource in node iPhase reactive powerx3It indicatesMeaning is intelligent Sofe Switch in node iPhase access capacityWith distributed generation resource in node i
'sPhase access capacity
Mutual-through type form carries out ε-relaxation, and wherein ε is relaxation precision, and the ε-relaxation form for obtaining rotating cone constraint is as follows:
Polyhedron approximation is carried out to the relaxation form of rotating cone constraint, i.e. 2 (v+1) a auxiliary variables of introducingAnd ηi, approximately equivalent
One group of linear equality and inequality group are converted to, wherein i=0,1 ... v is as follows:
η0≥x2,η0≥-x2
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611034925.3A CN106655226B (en) | 2016-11-18 | 2016-11-18 | Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611034925.3A CN106655226B (en) | 2016-11-18 | 2016-11-18 | Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106655226A CN106655226A (en) | 2017-05-10 |
| CN106655226B true CN106655226B (en) | 2019-07-26 |
Family
ID=58807962
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611034925.3A Active CN106655226B (en) | 2016-11-18 | 2016-11-18 | Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106655226B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106972513B (en) * | 2017-05-22 | 2019-04-26 | 天津威瀚电气股份有限公司 | A kind of three-phase and four-line uncompensated load only utilizes the compensation method of capacitive element |
| CN109217316A (en) * | 2017-06-30 | 2019-01-15 | 国网山西省电力公司经济技术研究院 | A kind of distribution power flow optimizing operation method containing three end SNOP based on genetic algorithm |
| CN108512215B (en) * | 2017-12-30 | 2022-03-22 | 中国电力科学研究院有限公司 | Power distribution network switch planning method based on reliability improvement |
| CN108923459A (en) * | 2018-07-10 | 2018-11-30 | 华北电力大学（保定） | A kind of alternating current-direct current power distribution network optimal control method based on intelligent Sofe Switch |
| CN109787256A (en) * | 2019-02-15 | 2019-05-21 | 合肥工业大学 | Three-phase imbalance reactive voltage control method based on flexible multimode switch |
| CN110008532B (en) * | 2019-03-18 | 2020-10-30 | 华中科技大学 | Commutation opportunity determination method and commutation system for three-phase unbalanced commutation |
| CN110048433B (en) * | 2019-05-24 | 2023-05-26 | 青岛大学 | Intelligent power distribution network control method based on intelligent soft switch |
| CN110490376B (en) * | 2019-08-05 | 2023-04-07 | 天津大学 | Intelligent soft switch planning method for improving reliability and economy of power distribution network |
| CN113595106B (en) * | 2021-07-30 | 2024-04-19 | 中国矿业大学 | Asynchronous power grid interconnection three-phase imbalance treatment method based on intelligent soft switch |
| CN113705892B (en) * | 2021-08-30 | 2023-08-15 | 天津大学 | Demand side resource and intelligent soft switch distribution robust joint planning method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104979840A (en) * | 2015-07-30 | 2015-10-14 | 中国电力科学研究院 | Three-phase reactive power optimization method of active power distribution network |
| CN105119280A (en) * | 2015-08-31 | 2015-12-02 | 天津大学 | Conic optimization-based AC/DC hybrid structure active power distribution network operation optimization method |
| CN105719196A (en) * | 2016-01-18 | 2016-06-29 | 天津大学 | Active power distribution network pressure reactive power control method based on intelligent soft normally open point |
| CN105896537A (en) * | 2016-06-21 | 2016-08-24 | 中国南方电网有限责任公司电网技术研究中心 | Power supply restoration method for power distribution network based on intelligent soft switch |
-
2016
- 2016-11-18 CN CN201611034925.3A patent/CN106655226B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104979840A (en) * | 2015-07-30 | 2015-10-14 | 中国电力科学研究院 | Three-phase reactive power optimization method of active power distribution network |
| CN105119280A (en) * | 2015-08-31 | 2015-12-02 | 天津大学 | Conic optimization-based AC/DC hybrid structure active power distribution network operation optimization method |
| CN105719196A (en) * | 2016-01-18 | 2016-06-29 | 天津大学 | Active power distribution network pressure reactive power control method based on intelligent soft normally open point |
| CN105896537A (en) * | 2016-06-21 | 2016-08-24 | 中国南方电网有限责任公司电网技术研究中心 | Power supply restoration method for power distribution network based on intelligent soft switch |
Non-Patent Citations (1)
| Title |
|---|
| 一种联络开关和智能软开关并存的配电网运行时序优化方法;王成山等;《中国电机工程学报》;20160505;第36卷(第9期);第2315-2321页 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106655226A (en) | 2017-05-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106655226B (en) | Active power distribution network asymmetric operation optimization method based on intelligent Sofe Switch | |
| CN110690732B (en) | Photovoltaic reactive power partition pricing power distribution network reactive power optimization method | |
| CN106655177B (en) | Distributed generation resource maximum access capability calculation method based on extension Second-order cone programming | |
| CN108023364B (en) | Power distribution network distributed generation resource maximum access capability calculation method based on convex difference planning | |
| CN106655227B (en) | A kind of active power distribution network feeder line balancing method of loads based on intelligent Sofe Switch | |
| CN109361242B (en) | Automatic voltage control method for photovoltaic power generation | |
| Rosini et al. | A review of reactive power sharing control techniques for islanded microgrids | |
| CN107732917B (en) | A kind of closed loop network turn power supply Load flow calculation optimization method | |
| CN109149620A (en) | One kind is from the soft straight system control method of energy storage multiterminal and system | |
| CN111490542B (en) | Site selection and volume fixing method of multi-end flexible multi-state switch | |
| Kılıç et al. | Optimal power flow solution of two-terminal HVDC systems using genetic algorithm | |
| Kamarposhti et al. | Optimal location of FACTS devices in order to simultaneously improving transmission losses and stability margin using artificial bee colony algorithm | |
| Sindi et al. | Robust control of adaptive power quality compensator in Multi-Microgrids for power quality enhancement using puzzle optimization algorithm | |
| Khaleel et al. | Technical challenges and optimization of superconducting magnetic energy storage in electrical power systems | |
| CN106021754B (en) | Consider the serial-parallel power grid Probabilistic Load Flow algorithm of VSC reactive power constraints adjustable strategies | |
| CN116388153A (en) | Optimal configuration method for flexible interconnection equipment in active power distribution network | |
| Santos et al. | Use of an interline power flow controller model for power flow analysis | |
| CN110751328A (en) | High-proportion renewable energy power grid adaptive planning method based on joint weighted entropy | |
| Mahmoudian Esfahani et al. | Optimal power routing scheme between and within interlinking converters in unbalanced hybrid AC–DC microgrids | |
| CN109586276A (en) | A kind of alternating current-direct current power grid flow control method and device containing flexible DC transmission | |
| CN112736913B (en) | Method for analyzing influence factors of power optimization mode of power distribution network containing distributed power supply | |
| Zhang et al. | Day-ahead stochastic optimal dispatch of LCC-HVDC interconnected power system considering flexibility improvement measures of sending system | |
| Ogunwole | Optimal placement of statcom controllers with metaheuristic algorithms for network power loss reduction and voltage profile deviation minimization. | |
| Eissa et al. | A novel approach for optimum allocation of Flexible AC Transmission Systems using Harmony Search technique | |
| Karimi et al. | Novel distributed active and reactive power management approach for renewable energy resource and loads in distribution network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |