CN110474320A - The distribution optimization method that Distributed sharing is mutually cooperateed with centralization clearance - Google Patents
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Abstract
The invention discloses the distribution optimization methods that Distributed sharing is mutually cooperateed with centralization clearance, the distribution network system mutually cooperateed with by building Distributed sharing with centralization clearance, distribution network operation business uniformly clears out the electricity price of each node according to the purchase of electricity that each polymerization quotient reports, polymerization quotient passes to node electricity price each micro-capacitance sensor of intra-node, each micro-capacitance sensor optimizes the operation of itself according to node electricity price and transaction and interacts with node aggregation quotient, using the model based on game theory or based on the model of Lagrange relaxation, solution obtains the purchase of electricity and power purchase price of each micro-capacitance sensor of intra-node, the purchase of electricity of micro-capacitance sensor inside polymerization quotient's collector node is simultaneously sent to power distribution network operator, clear out the electricity price of each node again by distribution network operation business, and so on until convergence.Guarantee the stability of operation of power networks and the fairness of electricity price clearance, realizes that each micro-capacitance sensor carries out free transaction under the premise of meeting electricity price clearance fairness.
Description
Technical field
It is mutually cooperateed with the present invention relates to operation of power networks distribution technique field more particularly to Distributed sharing with centralization clearance
Distribution optimization method.
Background technique
With the development of electricity market, the Price Mechanisms of electricity market cause the extensive concern of domestic and foreign scholars and become
Research hotspot.In current distribution optimization method, minimum is generally determined according to Marginal Pricing theory by distribution network operation business
Cost of electricity-generating uniformly clears out the Marginal Pricing of each node of distribution network system, and the mode of this centralization clearing price can
The stability of electric system and electricity market is effectively ensured, but for huge electric system, is not easy to calculate all
The node electricity price of node can only carry out the clearance of electricity price to the biggish node of load.
Meanwhile with the popularization and use of new energy, can be realized the distributed energy that energy complementation utilizes and share also becomes
Research hotspot, but in current distribution optimization method, the minority for being only applicable to adjoining area shared for distributed energy is micro-
Power grid is traded, if there are a large amount of micro-capacitance sensors to carry out point-to-point transaction in system, calculation amount is very big, and process of exchange
It is very complicated, it be easy to cause the unstable of electric system and electricity market.
Summary of the invention
The present invention is to solve existing distribution optimization method to be difficult to carry out huge electric system node clearance and excellent
The problem of change, provides the distribution optimization method that Distributed sharing is mutually cooperateed with centralization clearance.
To realize the above goal of the invention, and the technological means used is:
The distribution optimization method that Distributed sharing is mutually cooperateed with centralization clearance, comprising the following steps:
S1. the distribution network system that building Distributed sharing is mutually cooperateed with centralization clearance, including distribution network operation business, it is described
Distribution network operation business interconnects the polymerization quotient for having several nodes, and the polymerization quotient under each node is mutually associated with several intra-nodes
Micro-capacitance sensor；
S2. the distribution network operation business uniformly clears out each node according to the purchase of electricity that each node aggregation quotient reports
Electricity price and the polymerization quotient for being sent to corresponding node；
S3. the node electricity price that the distribution network operation business is fed back is sent to each micro- electricity of intra-node by the polymerization quotient
Net, the purchase of electricity of each micro-capacitance sensor inside collector node are simultaneously sent to the distribution operator；
S4. the micro-capacitance sensor optimizes the operation and transaction of itself, and the model based on game theory according to the node electricity price
Or the model based on Lagrange relaxation, solution are sent out after obtaining the purchase of electricity and power purchase price of each micro-capacitance sensor of each intra-node
It send to the polymerization quotient interaction of corresponding node；
S5. step S2~S4 is repeated until the power purchase price of each micro-capacitance sensor restrains.
In above scheme, the distribution network system mutually cooperateed with is cleared with centralization by building Distributed sharing, wherein distribution
Network operation business carries out centralized electricity price clearance, guarantees the stability of operation of power networks and the fairness of electricity price clearance；In node
Portion, each micro-capacitance sensor carry out free transaction under the premise of meeting electricity price clearance fairness, and electricity price is true by negotiating between micro-capacitance sensor
It is fixed, it can be realized energy complement, give full play to the advantage of Distributed sharing, and the comprehensive benefit of distribution network system is carried out excellent
Change.
Preferably, the purchase of electricity that distribution network operation business described in step S2 is reported according to each node aggregation quotient is unified to clear
The electricity price of each node out specifically: establish distribution network operation business and concentrate clearance node electricity price model, then pass through Lagrange
Function concentrates clearance node electricity price model to solve the distribution network operation business, obtains the electricity price of each node.
Preferably, the distribution network operation business concentrates clearance node electricity price model specifically:
Objective function: a.min ηp·Ps+ηq·Qs
Constraint condition includes:
The wherein η in the objective function ap, ηqIt is active specific power cost, idle specific power cost respectively,
Ps、QsIt is active power output power, idle activity of force out respectively；The constraint condition b and c respectively indicates the distribution network system
Active power balance, reactive power equilibrium；Pi GIndicate the generated output of node i；Pi DIndicate the load power of node i；DF is to pass
The factor is passed, is constant matrices；PLossAnd QLossRespectively indicate active loss and the reactive loss of the distribution network system；It is described about
Beam condition d, e respectively indicates the active power output bound of generator in the distribution network system, idle power output bound；It is described about
The bound of beam constraint f expression node voltage；SFvpIt is a sensitivity factor, is constant matrices；SFvp,i-jCharacterize node
J injects influence of the unit power to node j voltage magnitude；Vi=1Indicate the voltage magnitude of reference mode；The constraint condition g is
One dodecagon constraint, indicates the constraint of capacity of trunk；SFlpIt is a sensitivity factor, is constant matrices；SFlp,l-1Characterization
Node i injects influence of the unit power to route l trend；It is the maximum size of route l；ac,0、ac,1、ac,2It is to constitute institute
Dodecagonal coefficient is stated, is constant； ωl,cIt is the constraint item
The dual variable of part b-g.
Preferably, described to concentrate clearance node electricity price model to carry out the distribution network operation business by Lagrangian
It solves, obtains the specific steps of the electricity price of each node are as follows:
The distribution network operation business is concentrated objective function a and constraint condition b-f in clearance node electricity price model to constitute and is drawn
Ge Lang function L:
Local derviation is asked to obtain the electricity price of each node node load power by LagrangianL:
WhereinThe active and reactive Marginal Pricing of node i is respectively indicated,For the energy electricity price that node i is active,For the congestion pricing that node i is active,For the voltage support that node i is active
Electricity price,For the loss electricity price that node i is active；For the energy electricity price that node i is idle,For the congestion pricing that node i is idle,For the voltage support that node i is idle
Electricity price,For the loss electricity price that node i is idle.
Preferably, micro-capacitance sensor described in step S4 optimizes itself operation and transaction according to the node electricity price, and is based on
The model of game theory or model based on Lagrange relaxation, solve the purchase of electricity for obtaining each micro-capacitance sensor of each intra-node and
Power purchase price specifically: establish the Distributed sharing Trading Model between each micro-capacitance sensor, the model based on Lagrange relaxation
The Distributed sharing Trading Model is solved, the purchase of electricity and power purchase valence of each micro-capacitance sensor of each intra-node are obtained
Lattice.
Preferably, the Distributed sharing Trading Model between each micro-capacitance sensor specifically:
Objective function:
Constraint condition includes:
In the objective function A,Indicate the generator output of micro-capacitance sensor i,Indicate the power generation of micro-capacitance sensor i
Cost,Indicate the Marginal Pricing of t moment,Indicate purchase of electricity of the micro-capacitance sensor i to major network；MG is the index of micro-capacitance sensor；
The quantity of NMG expression micro-capacitance sensor；The constraint condition B indicates micro-capacitance sensor i power output bound；The constraint condition C indicates micro- electricity
Net the power-balance inside i；Indicate purchase of electricity of the micro-capacitance sensor j to micro-capacitance sensor i；Indicate total electricity sales amount of micro-capacitance sensor i；Indicate the load power of micro-capacitance sensor i；The constraint condition D indicates that the purchase of electricity between micro-capacitance sensor has to be larger than equal to zero, micro-
Power grid cannot be to oneself power purchase；The constraint condition E indicates that micro-capacitance sensor has to be larger than to the purchase of electricity of major network equal to zero；It is described about
Beam condition F indicates that the electricity sales amount of micro-capacitance sensor has to be larger than equal to zero；The constraint condition G indicates that the electricity sales amount of micro-capacitance sensor i is equal to
Total purchase of electricity of other micro-capacitance sensors to micro-capacitance sensor i.
Preferably, the Distributed sharing Trading Model is solved based on the model of Lagrange relaxation, is obtained every
The purchase of electricity and power purchase price of a each micro-capacitance sensor of intra-node specifically:
The constraint condition G is coupled by Lagrangian relaxation, then the transaction issues of each micro-capacitance sensor i are decoupled
Are as follows:
For each micro-capacitance sensor i, objective function are as follows:
Constraint condition includes:
Wherein Lagrange multiplierIt is updated using subgradient algorithm, as follows:
Wherein Lagrange multiplierIndicating the power purchase price between each micro-capacitance sensor of intra-node, k indicates the number of iterations,
P, q are constants, whenWhen, i.e. the demand of other micro-capacitance sensors has exceeded the supply of micro-capacitance sensor i,Greatly
InOtherwise,It is less than
Preferably, the condition of convergence described in step S5 are as follows:WithDifference be not more than threshold epsilon, ε=
0.001。
Compared with prior art, the beneficial effect of technical solution of the present invention is:
The present invention clears the distribution network system that mutually cooperates with by building Distributed sharing and centralization, distribution network operation business into
Row centralization electricity price clearance guarantees the stability of operation of power networks and the fairness of electricity price clearance；In intra-node, each micro- electricity
Net carries out free transaction under the premise of meeting electricity price clearance fairness, and electricity price is determined by negotiating between micro-capacitance sensor, can be realized
Energy complement gives full play to the advantage of Distributed sharing, under smart grid Power Market, takes into account electric network security and warp
Ji property, realizes the optimization of distribution network system comprehensive benefit, and solves existing distribution optimization method and be difficult to huge electricity
Force system carries out the problem of node clearance and optimization.
Detailed description of the invention
Fig. 1 is the block diagram for the distribution network system that Distributed sharing is mutually cooperateed with centralization clearance in embodiment 1.
Fig. 2 is the method flow diagram of embodiment 1.
Specific embodiment
The attached figures are only used for illustrative purposes and cannot be understood as limitating the patent；
In order to better illustrate this embodiment, the certain components of attached drawing have omission, zoom in or out, and do not represent actual product
Size；
To those skilled in the art, it is to be understood that certain known features and its explanation, which may be omitted, in attached drawing
's.
The following further describes the technical solution of the present invention with reference to the accompanying drawings and examples.
Embodiment 1
The distribution optimization method that Distributed sharing is mutually cooperateed with centralization clearance, as shown in Figure 2, comprising the following steps:
S1. the distribution network system that building Distributed sharing is mutually cooperateed with centralization clearance, including distribution network operation business, it is described
Distribution network operation business interconnects the polymerization quotient for having several nodes, and the polymerization quotient under each node is mutually associated with several intra-nodes
Micro-capacitance sensor；
Each main body of distribution network system that Distributed sharing in the present embodiment 1 and centralization clearance are mutually cooperateed with below into
Row is described in detail, as shown in Figure 2:
Distribution network operation business in the present embodiment 1 is uniformly cleared out each according to the purchase of electricity that each node aggregation quotient reports
The electricity price of node, polymerization quotient pass to node electricity price each micro-capacitance sensor of intra-node, and each micro-capacitance sensor is according to receiving
Node electricity price optimizes the operation of itself and transaction and interacts with the polymerization quotient of corresponding node, using model or base based on game theory
It in the model of Lagrange relaxation, solves and obtains the purchase of electricity and power purchase price of each micro-capacitance sensor of intra-node, under each node
The purchase of electricity of micro-capacitance sensor inside polymerization quotient's collector node is simultaneously sent to power distribution network operator, is cleared again by distribution network operation business
The electricity price of each node out；And so on, until convergence.
It polymerize quotient as unprofitable information centre, is responsible for the transmitting and interaction of information.Polymerization quotient be responsible for complete to upper layer,
The information exchange of lower layer polymerize quotient and is responsible for the purchase of electricity of each micro-capacitance sensor inside collector node and is sent to distribution for upper layer
Network operation business, and receive the node electricity price information of distribution network operation business clearance.For lower layer, it polymerize quotient and node electricity price information is sent out
Give each micro-capacitance sensor of intra-node, and the purchase of electricity of each micro-capacitance sensor in collector node inside.Meanwhile polymerizeing quotient and being also responsible for
The information centre of intra-node micro-capacitance sensor transaction, maintains the order of micro-capacitance sensor transaction, protects the information traded between micro-capacitance sensor.
Micro-capacitance sensor optimization operation and when carrying out trade decision, while considering between the operation constraint and micro-capacitance sensor of micro-capacitance sensor
Transaction constraint.Transaction constraint therein includes that micro-capacitance sensor cannot carry out simultaneously dealing electricity, a certain micro-capacitance sensor with some micro-capacitance sensor
Sell electricity equal to all micro-capacitance sensors to the sum of the micro-capacitance sensor purchase of electricity, and these transaction constraint be added to micro-capacitance sensor transaction determine
In plan.Information by polymerizeing quotient is transmitted and interacts the pricing for acquiring distribution network operation business and clearing out, and micro- electricity is optimized
The operation and trading activity of net, obtain the purchase of electricity between each micro-capacitance sensor；
S2. the distribution network operation business uniformly clears out each node according to the purchase of electricity that each node aggregation quotient reports
Electricity price and the polymerization quotient for being sent to corresponding node establish distribution network operation business and concentrate clearance node electricity price model, then pass through
Lagrangian concentrates clearance node electricity price model to solve the distribution network operation business, obtains the electricity of each node
Valence；
Wherein distribution network operation business concentrates clearance node electricity price model specifically:
Objective function: a.min ηp·Ps+ηq·Qs
Constraint condition includes:
The wherein η in the objective function ap, ηqIt is active specific power cost, idle specific power cost respectively,
Ps、QsIt is active power output power, idle activity of force out respectively；The constraint condition b and c respectively indicates the distribution network system
Active power balance, reactive power equilibrium；Pi GIndicate the generated output of node i；Pi DIndicate the load power of node i；DF is to pass
The factor is passed, is constant matrices；PLossAnd QLossRespectively indicate active loss and the reactive loss of the distribution network system；It is described about
Beam condition d, e respectively indicates the active power output bound of generator in the distribution network system, idle power output bound；It is described about
The bound of beam constraint f expression node voltage；SFvpIt is a sensitivity factor, is constant matrices；SFvp,i-jCharacterize node
J injects influence of the unit power to node j voltage magnitude；VI=1Indicate the voltage magnitude of reference mode；The constraint condition g is
One dodecagon constraint, indicates the constraint of capacity of trunk；SFlpIt is a sensitivity factor, is constant matrices；SFlp,l-1Characterization
Node i injects influence of the unit power to route l trend；It is the maximum size of route l；ac,0、ac,1、ac,2It is to constitute institute
Dodecagonal coefficient is stated, is constant； ωl,cIt is the constraint item
The dual variable of part b-g；
It wherein concentrates clearance node electricity price model to solve the distribution network operation business by Lagrangian, obtains
To the specific steps of the electricity price of each node are as follows:
The distribution network operation business is concentrated objective function a and constraint condition b-f in clearance node electricity price model to constitute and is drawn
Ge Lang function L:
Local derviation is asked to obtain the electricity price of each node node load power by LagrangianL:
WhereinThe active and reactive Marginal Pricing of node i is respectively indicated,For the energy electricity price that node i is active,For the congestion pricing that node i is active,For the voltage support that node i is active
Electricity price,For the loss electricity price that node i is active；For the energy electricity price that node i is idle,For the congestion pricing that node i is idle,For the voltage support that node i is idle
Electricity price,For the loss electricity price that node i is idle；
S3. the node electricity price that the distribution network operation business is fed back is sent to each micro- electricity of intra-node by the polymerization quotient
Net, the purchase of electricity of each micro-capacitance sensor inside collector node are simultaneously sent to the distribution operator；
S4. the micro-capacitance sensor optimizes the operation and transaction of itself according to the node electricity price, that is, establish each micro-capacitance sensor it
Between Distributed sharing Trading Model, and the Distributed sharing Trading Model is asked based on the model of Lagrange relaxation
Solution obtains the polymerization quotient interaction that corresponding node is sent to after the purchase of electricity and power purchase price of each micro-capacitance sensor of each intra-node；
The wherein Distributed sharing Trading Model between each micro-capacitance sensor specifically:
Objective function:
Constraint condition includes:
In the objective function A,Indicate the generator output of micro-capacitance sensor i,Indicate the power generation of micro-capacitance sensor i
Cost,Indicate the Marginal Pricing of t moment,Indicate purchase of electricity of the micro-capacitance sensor i to major network；MG is the index of micro-capacitance sensor；
The quantity of NMG expression micro-capacitance sensor；The constraint condition B indicates micro-capacitance sensor i power output bound；The constraint condition C indicates micro- electricity
Net the power-balance inside i；Indicate purchase of electricity of the micro-capacitance sensor j to micro-capacitance sensor i；Indicate total electricity sales amount of micro-capacitance sensor i；Indicate the load power of micro-capacitance sensor i；The constraint condition D indicates that the purchase of electricity between micro-capacitance sensor has to be larger than equal to zero, micro-
Power grid cannot be to oneself power purchase；The constraint condition E indicates that micro-capacitance sensor has to be larger than to the purchase of electricity of major network equal to zero；It is described about
Beam condition F indicates that the electricity sales amount of micro-capacitance sensor has to be larger than equal to zero；The constraint condition G indicates that the electricity sales amount of micro-capacitance sensor i is equal to
Total purchase of electricity of other micro-capacitance sensors to micro-capacitance sensor i.
The Distributed sharing Trading Model is solved based on the model of Lagrange relaxation, is obtained in each node
The purchase of electricity and power purchase price of each micro-capacitance sensor in portion specifically:
The constraint condition G is coupled by Lagrangian relaxation, then the transaction issues of each micro-capacitance sensor i are decoupled
Are as follows:
For each micro-capacitance sensor i, objective function are as follows:
Constraint condition includes:
In objective function,Indicate the generator output of micro-capacitance sensor i,Indicate micro-capacitance sensor i power generation at
This,Indicate the active Marginal Pricing of t moment,Indicate purchase of electricity of the micro-capacitance sensor i to major network；MG is the rope of micro-capacitance sensor
Draw；The quantity of NMG expression micro-capacitance sensor；The constraint condition B1 indicates micro-capacitance sensor i power output bound；The constraint condition C1 is indicated
Power-balance inside micro-capacitance sensor i；Indicate purchase of electricity of the micro-capacitance sensor j to micro-capacitance sensor i；Indicate always selling for micro-capacitance sensor i
Electricity；Indicate the load power of micro-capacitance sensor i；The constraint condition D1 indicates that the purchase of electricity between micro-capacitance sensor has to be larger than
In zero, micro-capacitance sensor cannot be to oneself power purchase；The constraint condition E1 indicates that micro-capacitance sensor has to be larger than to the purchase of electricity of major network and is equal to
Zero；The constraint condition F1 indicates that the electricity sales amount of micro-capacitance sensor has to be larger than equal to zero；The constraint condition G1 indicates micro-capacitance sensor i's
Electricity sales amount is equal to total purchase of electricity of other micro-capacitance sensors to micro-capacitance sensor i；
Wherein Lagrange multiplierIt is updated using subgradient algorithm, as follows:
Wherein Lagrange multiplierIndicating the power purchase price between each micro-capacitance sensor of intra-node, k indicates the number of iterations,
P, q are constants, whenWhen, i.e. the demand of other micro-capacitance sensors has exceeded the supply of micro-capacitance sensor i,Greatly
InOtherwise,It is less thanThe purchase of electricity and power purchase price of each micro-capacitance sensor are obtained after solution；
S5. step S2~S4 is repeated until the power purchase price of each micro-capacitance sensor restrains, i.e.,With's
Difference is not more than threshold epsilon, ε=0.001.
The terms describing the positional relationship in the drawings are only for illustration, should not be understood as the limitation to this patent；
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention.For those of ordinary skill in the art, may be used also on the basis of the above description
To make other variations or changes in different ways.There is no necessity and possibility to exhaust all the enbodiments.It is all this
Made any modifications, equivalent replacements, and improvements etc., should be included in the claims in the present invention within the spirit and principle of invention
Protection scope within.
Claims (8)
1. the distribution optimization method that Distributed sharing is mutually cooperateed with centralization clearance, which comprises the following steps:
S1. the distribution network system that building Distributed sharing is mutually cooperateed with centralization clearance, including distribution network operation business, the distribution
Network operation business is mutually associated with the polymerization quotient of several nodes, and the polymerization quotient under each node is mutually associated with micro- electricity of several intra-nodes
Net；
S2. the distribution network operation business uniformly clears out the electricity price of each node according to the purchase of electricity that each node aggregation quotient reports
And it is sent to the polymerization quotient of corresponding node；
S3. the node electricity price that the distribution network operation business is fed back is sent to each micro-capacitance sensor of intra-node by the polymerization quotient,
The purchase of electricity of each micro-capacitance sensor inside collector node is simultaneously sent to the distribution operator；
S4. the micro-capacitance sensor optimizes the operation and transaction of itself according to the node electricity price, and model or base based on game theory
In the model of Lagrange relaxation, solution is sent to after obtaining the purchase of electricity and power purchase price of each micro-capacitance sensor of each intra-node
The polymerization quotient interaction of corresponding node；
S5. step S2~S4 is repeated until the power purchase price of each micro-capacitance sensor restrains.
2. the distribution optimization method that Distributed sharing according to claim 1 is mutually cooperateed with centralization clearance, feature
It is, distribution network operation business described in step S2 uniformly clears out each node according to the purchase of electricity that each node aggregation quotient reports
Electricity price specifically: establish distribution network operation business concentrate clearance node electricity price model, then by Lagrangian to described
Distribution network operation business concentrates clearance node electricity price model to be solved, and obtains the electricity price of each node.
3. the distribution optimization method that Distributed sharing according to claim 2 is mutually cooperateed with centralization clearance, feature
It is, the distribution network operation business concentrates clearance node electricity price model specifically:
Objective function: a.min ηp·Ps+ηq·Qs
Constraint condition includes:
The wherein η in the objective function ap、ηqIt is active specific power cost, idle specific power cost, P respectivelys、Qs
It is active power output power, idle activity of force out respectively；The constraint condition b and c respectively indicates the active of the distribution network system
Power-balance, reactive power equilibrium；Pi GIndicate the generated output of node i；Pi DIndicate the load power of node i；DF be transmitting because
Son is constant matrices；PLossAnd QLossRespectively indicate active loss and the reactive loss of the distribution network system；The constraint item
Part d, e respectively indicate the active power output bound of generator in the distribution network system, idle power output bound；The constraint item
Part, which constrains f, indicates the bound of node voltage；SFvpIt is a sensitivity factor, is constant matrices；SFvp,i-jCharacterize node j note
Enter influence of the unit power to node j voltage magnitude；VI=1Indicate the voltage magnitude of reference mode；The constraint condition g is one
Dodecagon constraint, indicates the constraint of capacity of trunk；SFlpIt is a sensitivity factor, is constant matrices；SFlp,l-1Characterize node
I injects influence of the unit power to route l trend；It is the maximum size of route l；ac,0、ac,1、ac,2It is to constitute described ten
The coefficient of two side shapes is constant； ωl,cIt is the constraint condition b-
The dual variable of g.
4. the distribution optimization method that Distributed sharing according to claim 3 is mutually cooperateed with centralization clearance, feature
It is, it is described to concentrate clearance node electricity price model to solve the distribution network operation business by Lagrangian, it obtains
The specific steps of the electricity price of each node are as follows:
It is bright that the distribution network operation business concentrates objective function a and constraint condition b-f in clearance node electricity price model to constitute glug
Day function L:
Local derviation is asked to obtain the electricity price of each node node load power by LagrangianL:
WhereinThe active and reactive Marginal Pricing of node i is respectively indicated,For the energy electricity price that node i is active,For the congestion pricing that node i is active,For the voltage support that node i is active
Electricity price,For the loss electricity price that node i is active；For the energy electricity price that node i is idle,For the congestion pricing that node i is idle,For the voltage support that node i is idle
Electricity price,For the loss electricity price that node i is idle.
5. the distribution optimization method that Distributed sharing according to claim 4 is mutually cooperateed with centralization clearance, feature
It is, micro-capacitance sensor described in step S4 optimizes the operation and transaction of itself, and the mould based on game theory according to the node electricity price
Type or model based on Lagrange relaxation solve the purchase of electricity for obtaining each micro-capacitance sensor of each intra-node and power purchase price tool
Body are as follows: the Distributed sharing Trading Model between each micro-capacitance sensor is established, based on the model of Lagrange relaxation to the distribution
Formula is shared Trading Model and is solved, and the purchase of electricity and power purchase price of each micro-capacitance sensor of each intra-node are obtained.
6. the distribution optimization method that Distributed sharing according to claim 5 is mutually cooperateed with centralization clearance, feature
It is, the Distributed sharing Trading Model between each micro-capacitance sensor specifically:
Objective function:
Constraint condition includes:
In the objective function A,Indicate the generator output of micro-capacitance sensor i,Indicate the cost of electricity-generating of micro-capacitance sensor i,Indicate the Marginal Pricing of t moment,Indicate purchase of electricity of the micro-capacitance sensor i to major network；MG is the index of micro-capacitance sensor；NMG table
Show the quantity of micro-capacitance sensor；The constraint condition B indicates micro-capacitance sensor i power output bound；The constraint condition C is indicated in micro-capacitance sensor i
The power-balance in portion；Indicate purchase of electricity of the micro-capacitance sensor j to micro-capacitance sensor i；Indicate total electricity sales amount of micro-capacitance sensor i；
Indicate the load power of micro-capacitance sensor i；The constraint condition D indicates that the purchase of electricity between micro-capacitance sensor has to be larger than equal to zero, micro- electricity
Net cannot be to oneself power purchase；The constraint condition E indicates that micro-capacitance sensor has to be larger than to the purchase of electricity of major network equal to zero；The constraint
Condition F indicates that the electricity sales amount of micro-capacitance sensor has to be larger than equal to zero；The constraint condition G indicates that the electricity sales amount of micro-capacitance sensor i is equal to it
The total purchase of electricity of his micro-capacitance sensor to micro-capacitance sensor i.
7. the distribution optimization method that Distributed sharing according to claim 6 is mutually cooperateed with centralization clearance, feature
It is, the Distributed sharing Trading Model is solved based on the model of Lagrange relaxation, obtains each intra-node
The purchase of electricity and power purchase price of each micro-capacitance sensor specifically:
The constraint condition G is coupled by Lagrangian relaxation, then the transaction issues of each micro-capacitance sensor i are decoupled are as follows:
For each micro-capacitance sensor i, objective function are as follows:
Constraint condition includes:
Wherein Lagrange multiplierIt is updated using subgradient algorithm, as follows:
Wherein Lagrange multiplierIndicate the power purchase price between each micro-capacitance sensor of intra-node, k indicates the number of iterations, p, q
It is constant, whenWhen, i.e. the demand of other micro-capacitance sensors has exceeded the supply of micro-capacitance sensor i,It is greater thanOtherwise,It is less than
8. the distribution optimization method that Distributed sharing according to claim 7 is mutually cooperateed with centralization clearance, feature
It is, the condition of convergence described in step S5 are as follows:WithDifference be not more than threshold epsilon, ε=0.001.
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