CN107426671A - There is the data transmission method of energy capture function in a kind of intelligent grid - Google Patents
There is the data transmission method of energy capture function in a kind of intelligent grid Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
- H04W40/248—Connectivity information update
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/48—Routing tree calculation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04Q—SELECTING
- H04Q2209/00—Arrangements in telecontrol or telemetry systems
- H04Q2209/80—Arrangements in the sub-station, i.e. sensing device
- H04Q2209/88—Providing power supply at the sub-station
- H04Q2209/886—Providing power supply at the sub-station using energy harvesting, e.g. solar, wind or mechanical
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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
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
The invention provides the data transmission method in a kind of intelligent grid with energy capture function, this method includes a kind of convergence tree routing algorithm based on priority charging mechanism, using wireless sensor networking.Dispose initial ordinary node ON, functional node EPN in a network first and catch energy node EHN, at least one functional node can be set around node catching.The data transfer of energy-conservation is realized using integer uniform enconding and minimal weight capture spanning tree routing algorithm, selection load weight catches energy node in the tree finally built, enter row major charging to it in the network operation, so as to realize that network life extends the purpose with valid data transmission.
Description
Technical field
The present invention relates to the number in intelligent power grid technology field, more particularly to a kind of intelligent grid with energy capture function
According to transmission method.
Background technology
In intelligent grid, security, reliability and high efficiency are the targets of electrical power services, and this just needs one on a large scale
Interior low cost, become more meticulous and permanent monitoring scheme.Wireless sensor network is in monitoring range, cost, monitoring granularity, robustness etc.
Aspect can meet demand, but it has the problem of wireless sensor node energy content of battery is limited well.If node deployment
It is more difficult arrive at or harmfulness environment in, then the monitoring life-span of network will be affected.By application of higher wireless sensor network in
In intelligent grid, it is necessary to study energy efficiency and the correlation technique of energy capture.And in view of energy conversion convenience and
The characteristic of wireless sensor node, on the one hand realize that Technical comparing is simple based on the mode that RFID label tag is charged repeatedly, separately
On the one hand capture and conversion are of relatively low cost, and can be that node permanently energizes in RF energy capture technical know-hows, for
Independence and long-term monitoring are fit closely technologies in intelligent grid.
In RF energy capture technologies, because wireless transmitted power is limited in scope, RFDC is node energy in addition
The major part of consumption is measured, therefore Route Selection influences whether that energy is caught in the deployment and transmission of wireless sensor network interior joint
Obtain and data transfer effect.In multihop routing topology, each via node can be impacted because of load increase, and energy is opened
Pin will be bigger, it is necessary to be its design energy optimisation strategy than its source node.Structure convergence tree can allow wireless senser
The more efficient data transfer with energy-conservation of real-time performance, especially needs the occasion to be charged by way of RF catches energy, more in node
Need to optimize route.
Using convergence come to extend network life be a kind of common optimization method in wireless sensor network.Tradition
On mainly have two methods：Data are forwarded to base station based on tree and based on tufted structure, by charging and convergence
The method combined can cause network to have more multi-energy source, be a kind of newer method.But during energy capture
When building convergence tree, existing research is all based on some preferable hypothesis conditions, does not consider data transmission rate and the reality of charging
Border situation.
The content of the invention
In view of the drawbacks described above of prior art, the technical problems to be solved by the invention are to provide in a kind of intelligent grid
Data transmission method with energy capture function, for needing accurate monitoring and the equipment frequently reported to carry out in intelligent grid
Wireless sensor network disposition and monitoring, structure convergence tree are converged set upper further research herein to improve efficiency of transmission
How based on energy capture rate renewal route topological.By increasing functional node, make to undertake more data transformation task catches energy
Node obtains more high charge priority, so as to realize that network life extends the purpose with valid data transmission.
To achieve the above object, the invention provides the transmission side data in a kind of intelligent grid with energy capture function
Method, it is characterised in that comprise the following steps：
Equipment for needing accurate monitoring in intelligent grid and frequently reporting, deploy a kind of with priority charging work(
The wireless sensor network of energy；
A convergence tree is built in the charging network with priority, carries out realizing that energy-conservation is converged while energy capture
Poly- route；
Convergence type energy-efficient routing based on priority charging mechanism, increase functional node, make to undertake more data biography
The energy node of catching of defeated task obtains more high charge priority, and the EHN nodes preferentially to charge are selected out in charge node.
Further, it is described to deploy a kind of wireless sensor network with priority charge function and be specially：
Including a base station, some functional nodes need not shift to an earlier date the whole network portion with energy node, alternative functional node PEPN is caught
Administration and flexible allocation, energy conversion play the part of functional node EPN role, data transmission nodal include catching can node EHN and
Ordinary node ON, wherein functional node only communicate with catching energy node,
Each EHN at least configures an EPN and charged, the EHN for undertaking a greater amount of data transfer tasks in route,
Increase PEPN and realize preferential charging.
Further, the convergence tree-model is：
The model does not include EPN and PEPN, and the model is described as：One K node is shared in a network, wherein base station B is whole
There are n summit, be up to n-1 bars side in individual tree, and the data flow converged in route into B has K-1 bars side, owns in set M
Side be by two can direct communication node between line form, EHN sets of nodeON set of node O, namely N { H
∪ S }, EPN nodes are not embodied in N, namely in convergence tree and occur without EPN.
Further, the energy-conservation convergence route is specially：
Energy-conservation convergence route is the energy-conservation convergence route based on AR-ILP models, and AR-ILP structures are as follows：Model it is oriented
Topological diagram comes from base station B, and each node has a weight, and definition ON weights are 1, EHN nodes and B weights are 0, set one certainly
Plan Boolean variable X, if node i selects j as father node, Xij=1；Integer stream matrix FijRepresent the data flow structure from i to j
Into matrix, if XijFor 0, then FijAlso it is 0, passes through FijA connection topology will be obtained after optimizing, it is assumed that each node
(in addition to B) one and only one father node, child's number of all ON nodes can at least represent in wireless sensor network
For：
Wherein n (j) is all communication nodes in node i radio-frequency region.
Further, the data transfer of the wireless sensor network converges routing algorithm to complete road based on optimal data
By process, optimal data convergence routing algorithm step is：
The first step, Weighted Directed Graph is constructed in the non-directed graph that all ON nodes, EHN nodes, B node are formed, and
Each node is wherein found, weight is arranged to：ON node weights are 1, EHN nodes and B node weight is 0, if u is ON nodes,
W [u, v]=1 is arranged to by starting point, the directed edge weight for connecting u and v of u, if u be EHN nodes or B node, corresponding w [u,
V]=0；
Second step, situation containing ring in previous step result is checked, if acyclic, directly obtain reverse data convergence topological tree, enter
Enter the 4th step, if ring be present, it is destroyed, the EHN nodes that will be contained in ring merge, and form a new merging
Node, the emitting edge that minimal weight selects each node is again based on, forms a new minimal weight topological tree, repeat second
The operation of step, check the situation comprising ring in new tree and handled accordingly, until being free of ring in last tree；
3rd step, separates the merge node of previous step, and determines the emitting edge of each node in figure, obtains corresponding reverse
Converge topological tree；
4th step, each side that reverse support is converged to topological tree carry out reverse process, obtain the branch consistent with data transfer
Support tree convergence route；
5th step, the repetition first step to the 4th step, other possible spanning trees convergence routes are obtained, and contrasted, most
Optimal data convergence route is obtained eventually.
Further, in the convergence tree built, heavier transformation task catch can by node increase by one it is alternative
Functional node, the functional node are only to catch energy node to provide RF energy, and convergence route is not had an impact.
The beneficial effects of the invention are as follows：
(1) a kind of wireless-transmission network with energy supplement function is constructed, is to need accurately to monitor in intelligent grid
The equipment frequently reported carries out wireless sensor network disposition and monitoring.
(2) in energy-conservation convergence routing plan, MINIMUM WEIGHT recaptures energy spanning tree routing algorithm and can speed up convergence tree structure
Speed, and reduce its complexity.The convergence topology tree built is recalled, eventually finds an optimum aggregation topology tree；
(3) energy node is caught in the heavy duty in being route to optimum aggregation, is realized by increasing alternative functional node with optimization level
Charging effect, improve it and catch the convenience of energy and validity.
Design, concrete structure and the caused technique effect of the present invention are described further below with reference to accompanying drawing, with
It is fully understood from the purpose of the present invention, feature and effect.
Brief description of the drawings
Wireless sensor network models of the Fig. 1 based on priority charging mechanism
Fig. 2 charge type convergence tree basic models
The reverse spanning tree convergence route original topology figures of Fig. 3
The Weighted Directed Graph that Fig. 4 is tentatively constructed
Fig. 5 merge nodes are based on minimal weight deckle schematic diagram
Fig. 6 continues merge node and based on the final result figure after minimal weight deckle
Fig. 7 splits node and determines the result figure of corresponding edge
Fig. 8 reversely determines support convergence route topological tree
Embodiment
The present invention specifically uses following technical scheme：
Wireless sensor network of the structure with charge function first, and realize wherein based on priority charging mechanism
Convergence tree routing algorithm.Structure and energy-efficient routing of the whole scheme including network model realize two parts.
(1) network model is built
In the energy conversion of wireless energy capture, i.e. decay of the transmitting electromagnetic wave on path of footpath damage, depend primarily on
Signal frequency.For 2.54GHz frequency ranges used in domestic 4G movements at present, its footpath damage is just very big.In order to simplify problem,
The intelligent grid monitoring network that the present invention is discussed will use free space footpath damage model, and its power emission is assumed to be diameter R's
In circular scope.Receiving power is accordingly：
Wherein GrIt is the linear antenna gain of recipient, PtGtIt is transmission power, λ is wavelength.Actual acquisition to power be
The function that receiving power is passed through after certain circuit loss.
Power transmission scope very little is can be seen that from formula (1), if (being main electricity in intelligent grid using cellular basestation
Equipment after the decompression of source) supplement energy, will be not enough sensor node charging work, therefore in addition to main power supply unit, this hair
It is bright will further using portable alternative functional node for data transfer task in convergence route it is heavier catch energy node provide it is excellent
First charge, the task of these functional nodes is exactly to provide energy for wireless sensor node, and its cost is lower than main equipment (base station)
Much.In spanning tree energy-saving routing algorithm proposed by the invention, these functional nodes will not participate in the structure of convergence tree
Build and data transfer.
(2) energy-efficient routing scheme
It make use of three class nodes, i.e. ordinary node (ON) in this programme, functional node (EPN) and catch can node (EHN).It is first
Initial ordinary node is first disposed in a network and catches energy node, at least one functional node can be set around node catching.Profit
The data transfer of energy-conservation is realized with ILP (integral linear programming) and minimal weight capture spanning tree routing algorithm.Here ILP is
Min-max model, to realize the minimum of the downstream node upper limit of ordinary node, (convergence is from downstream node toward upstream
Node).Minimal weight capture spanning tree routing algorithm is intended to accelerate the speed of convergence tree structure, and reduces its complexity.To structure
The convergence topology tree built up is recalled again, until finding optimum aggregation topology tree.In order to realize optimization charging, to therein heavy
Load catches energy node, and energy is caught just by increasing alternative functional node PEPN (Prior Energy providing node) raisings
Profit and validity.
(a) tree-model is converged
A Weighted Directed Graph G=(N, M, w) is defined first, is made up of vertex set N and cum rights directed edge collection M, w is side
Weight is, it is necessary to distinguish the direction of each edge.Convergence route for the Design of Wireless Sensor Network of intelligent grid is also required to build
One Weighted Directed Graph S (subgraph for belonging to G), it comes from base station B, and includes the directed edge of each point in from B to N.For structure
Spanning tree, it is desirable to close ring is free of in S.If W (S) is the weight summation on each side in oriented spanning tree S.
An oriented spanning tree with minimum W (S) is found using ILP algorithms.
(b) energy-conservation convergence routing algorithm
In order to further speed up the convergence tree process, B can be allowed to play bigger effect, be built based on convergence tree root B
Reverse spanning tree, the direction of data flow originate the mode until leaf node with data transfer direction on the contrary, taking from B.In structure
During building reversely convergence spanning tree, controlled using opposite topology, weight controls and breaks the around-France son node number for making ON nodes
Minimum process is faster.Its basic ideas is：By the opposite direction of data flow in being set with convergence, from B, the side for entering B
Completely remove, further find out when entering while and going out of other each nodes.The selection on side makes to be carried out according to the weight of node.B
Weight with EHN nodes is that the weight of 0, ON nodes is 1.The weight of directed edge is set to set out the weight of node.Each node choosing
That selects minimal weight enters side to build tree (making ON and EHN nodes more select B and EHN nodes as father node).Such structure
Reverse convergence spanning tree when building up initial, checking whether there is loop wherein, (ring master is caused by NHN nodes, because its is existing
Enter side, there is side again).If loop be present, utilize and ring is broken to the mode that the EHN nodes for being related to loop merge, then again
It is determined that the side in tree (rule is with as before).The situation containing ring in new figure is checked, if there is ring, is continued with merging EHN nodes
Mode breaks ring, untill acyclic in tree.Finally merge node is taken apart, determines the side in tree again, is formed acyclic reverse
Spanning tree.Set as long as this reversely to be converged to spanning tree and reverts to converging for normal data transfer again by side in reverse spanning tree
Direction negates.
In the reverse spanning tree convergence route of above-mentioned acceleration, indivedual ON son node number may be unstable, and its reason is
The reverse spanning tree routing plan during achievement, be initially based on minimal weight selection side process and broken ring during merge
Process based on minimal weight selection side during node has nonuniqueness.Because equal in weight and when directed edge be present, not
There is restriction to select which ON node as father node, which results in child's number of some ON nodes more than 1.Therefore, it is right
This non-optimal topological tree needs that the optimum choice operation on side is repeated, until finding optimal data convergence route.
(c) charging process with priority
It is different to energy requirement because the transmission data rate for respectively catching energy node is different, it may not necessarily be captured in practical application
Enough RF energy, therefore, it is necessary to each juice point caught energy node and make a distinction priority in the convergence tree built
Reason, an alternative functional node can be increased by node in catching for heavier transformation task.The functional node is only to catch energy node to carry
For RF energy, convergence route is not had an impact.
Wireless sensor network model based on priority charging mechanism is as shown in Figure 1.Including a base station, if
Dry functional node and catch can node.Because alternative functional node PEPN (Prior Energy providing node) need not
The whole network deployment in advance and flexible allocation, do not embody in fig. 1.Play the part of base station B role, energy conversion by main power source
Play the part of functional node EPN (energy providing node) role, data transmission nodal includes catching energy node EHN
(energy harvesting node) and ordinary node ON (ordinary node), wherein functional node are only with catching energy node
Communication.
Each EHN at least configures an EPN and charged, the EHN for undertaking a greater amount of data transfer tasks in route,
Increase PEPN and realize preferential charging.The PEPN works to be portable, route change and data transmission rate in being set according to convergence
Situation does corresponding position adjustment, realizes that the energy-conservation based on dynamic priority charging converges route.The present invention using ILP models come
Realize that the son node number of the whole network ON nodes minimizes, it is assumed that all functional node transmitting boundaries are all.
The charge type convergence tree basic model of structure as shown in Figure 2, wherein not comprising EPN and PEPN.The model
It is described as：One K node is shared in a network, wherein base station B, entirely have n summit, be up to n-1 bars side in tree.And converge
Data flow in route into B has K-1 bars (quantity of directed edge should not be less than the number in this tree for also requiring to build) side collection
Closing side all in M is made up of the line between the node of two energy direct communications.EHN sets of nodeON set of node O,
Namely N { H ∪ S }, in order to simplify problem, EPN nodes are not embodied in N, namely in convergence tree and occur without EPN.
It is different to energy requirement because the transmission data rate for respectively catching energy node is different, it may not necessarily be captured in practical application
Enough RF energy, therefore in the convergence tree built, heavier transformation task catch can by node increase by one it is alternative
Functional node.The functional node is only to catch energy node to provide RF energy, and convergence route is not had an impact.Construct the topological tree
Afterwards, Fig. 2 can be abstracted as a kind of oriented topological form, wherein the side between neglecting the node of indirect communication.
Assuming that each the node in topological tree to be converged can handle the entire packet received from its child node, herein
On the basis of regenerate a packet of itself.So that energy is saved, node activates radio frequency only when there is data transmit-receive activity.
Therefore, the quantity of child node can produce material impact to network life.RF energy supplements, net can be carried out in view of EHN nodes
The network life-span is mainly influenceed by ON nodes, it is necessary to realize that the maximum son node number of ON nodes minimizes in the whole network.
Convergence route (IPL based aggressive routing, AR-ILP) based on IPL is intended to reduce ON
Nodes, so as to reach the effect of increase wireless sensor network life.AR-ILP model constructions are as follows：The oriented topology of model
Figure comes from base station B, and each node has a weight, and it is 1 to define ON weights, and other node (EHN nodes and B) weights are 0.Set
One decision-making Boolean variable X, if node i (being free of B) selects j as father node (i.e. the upstream node of convergence), Xij=
1.Integer stream matrix FijThe matrix that the data flow from i to j is formed is represented, if XijFor 0, then FijAlso it is 0.Pass through FijOptimize
A connection topology will be obtained afterwards.It is assumed that each node (in addition to B) one and only one father node, in wireless sensor network
In child's numbers of all ON nodes can at least be expressed as：
Wherein n (j) is all communication nodes in node i radio-frequency region.
Assuming that all data flows to base station B there are K-1 bars, there was only the data flow flowed into from base station B, not data out
Stream, therefore B is the root of whole tree.Each data flow has single transmission direction, in tree, the leaf node hair of each most downstream
A packet is sent, via node adds a bag again on the basis of the packet received, and final all data reach B, wireless biography
The data transfer of sensor network completes routing procedure based on the convergence tree.
Optimal data converges routing algorithm step：Initial time as shown in Figure 3, wherein EHN nodes two-wire circle
Represent.B is base station, and other nodes are ON nodes.
The first step, Weighted Directed Graph is constructed in the non-directed graph that all ON nodes, EHN nodes, B node are formed, and
Wherein find each node.Weight is arranged to：ON node weights are 1, EHN nodes and B node weight is 0, if u is ON nodes,
W [u, v]=1 is arranged to by starting point, the directed edge weight for connecting u and v of u, if u be EHN nodes or B node, corresponding w [u,
V]=0.This arrangement ensure that being 0 from the directed edge weight of EHN and B node, it is more beneficial for ON and is chosen as emitting edge,
Because convergence tree will select directed edge based on minimal weight.During structure reversely support convergence tree, base station B's is excellent
First level highest, therefore will be preferred using B as emitting edge during other nodes selection emitting edge.As the root of whole tree, base station B only has
Side is emitted, its emitting edge all removes.Provide that each EHN nodes will at least have an emitting edge, and ON nodes have a plurality of incidence
Side is alternative.The topology that the process is formed is not unique, and accompanying drawing 4 gives the result of certain selection.
The complexity of the first step includes determining vertex weights (complexity O | N |) in tree, determines that the weight of each edge is (multiple
Miscellaneous degree is O | M |).Base station B side (complexity O | M |) is removed in all directed edges.
Second step, check situation containing ring in previous step result.If acyclic, reverse data convergence topological tree is directly obtained.Enter
Enter the 4th step.If ring be present, it is destroyed.The EHN nodes that will be contained in ring merge, and form a new merging
Node.The emitting edge that minimal weight selects each node (containing merge node) is again based on, a new minimal weight is formed and opens up
Flutter tree.The operation of second step is repeated, the situation comprising ring in new tree is checked and is handled accordingly, until in last tree not
Containing ring.The process such as accompanying drawing 5 of broken ring, shown in 6.
Second step, recursive broken ring process complexity be O (Nlog | N |+| M |).
3rd step, separates the merge node of previous step, and determines the emitting edge of each node (removing B) in figure, obtains corresponding
Reverse convergence topological tree, as shown in Figure 7.The topological tree that the process is formed is not unique.
3rd complexity is mainly the separation process of merge node, and its value is O (| N | -1), i.e. O | N |.
4th step, each side that reverse support is converged to topological tree carry out reverse process, obtain the branch consistent with data transfer
Support tree convergence route.As shown in Figure 8.
5th step, the repetition first step to the 4th step, other possible spanning trees convergence routes are obtained, and contrasted, most
Optimal data convergence route is obtained eventually.
Complexity in above step is collected, in the present invention the total complexity of algorithm for O (3 | M |+Nlog | N |+2
|N|)。
In intelligent grid actual motion, the life-span of its monitoring network and transmission range, deployment region, around ON nodes
The efficiency that node density, the deployment of EPN nodes and EHN nodes, RF energy are collected has substantial connection, can not be by ideal style
(for example each node only produces a packet and is transferred to its upstream node) transmits.This just need consider routing optimality and
The relation that RF charges between data transmission rate, will be treated with a certain discrimination to EHN, in the optimal data convergence route of construction, to that
A little heavier EHN nodes of transformation task give higher priority, and method is exactly to utilize portable EPN, and by heavily loaded EHN nodes
One PEPN node is set.In addition, it is necessary to the heavily loaded EHN nodes preferentially to charge are selected, and common EHN nodes and preferential charging
Ratio of the EHN nodes in all nodes.Not increase network added burden as standard, 1-2 movement can be set in the whole network
PEPN nodes, using the node of pack heaviest in EPN as preferential charge node, realize its preferential charging process.
Preferred embodiment of the invention described in detail above.It should be appreciated that one of ordinary skill in the art without
Creative work can is needed to make many modifications and variations according to the design of the present invention.Therefore, all technologies in the art
Personnel are available by logical analysis, reasoning, or a limited experiment on the basis of existing technology under this invention's idea
Technical scheme, all should be in the protection domain being defined in the patent claims.
Claims (6)
1. there is the data transmission method of energy capture function in a kind of intelligent grid, it is characterised in that
Comprise the following steps：
Equipment for needing accurate monitoring in intelligent grid and frequently reporting, deploy a kind of with priority charge function
Wireless sensor network；
A convergence tree is built in the charging network with priority, carries out realizing energy-conservation convergence road while energy capture
By；
Convergence type energy-efficient routing based on priority charging mechanism, increase functional node, make to undertake more data transmission times
The energy node of catching of business obtains more high charge priority, and the EHN nodes preferentially to charge are selected out in charge node.
2. having the data transmission method of energy capture function in a kind of intelligent grid as claimed in claim 1, its feature exists
In described to deploy a kind of wireless sensor network with priority charge function and be specially：
Including a base station, some functional nodes and catch can node, alternative functional node PEPN need not shift to an earlier date the whole network deployment and
Flexible allocation, energy conversion play the part of functional node EPN role, and data transmission nodal includes catching can node EHN and common
Node ON, wherein functional node only communicate with catching energy node,
Each EHN at least configures an EPN and charged, the EHN for undertaking a greater amount of data transfer tasks in route, increase
PEPN realizes preferential charging.
3. having the data transmission method of energy capture function in a kind of intelligent grid as claimed in claim 1, its feature exists
In the convergence tree-model is：
The model does not include EPN and PEPN, and the model is described as：One share K node, wherein base station B, whole tree in a network
In have a n summit, be up to n-1 bars side, and the data flow converged in route into B has a K-1 bars side, all sides in set M
It is to be made up of the line between the node of two energy direct communications, EHN sets of nodeON set of node O, namely N { H ∪
S }, EPN nodes are not embodied in N, namely in convergence tree and occur without EPN.
4. having the data transmission method of energy capture function in a kind of intelligent grid as claimed in claim 1, its feature exists
In the energy-conservation convergence route is specially：
Energy-conservation convergence route is the energy-conservation convergence route based on AR-ILP models, and AR-ILP structures are as follows：The oriented topology of model
Figure comes from base station B, and each node has a weight, and definition ON weights are 1, EHN nodes and B weights are 0, set a decision-making cloth
That variable X, if node i selects j as father node, Xij=1；Integer stream matrix FijRepresent what the data flow from i to j was formed
Matrix, if XijFor 0, then FijAlso it is 0, passes through FijA connection topology will be obtained after optimizing, it is assumed that each node (except B it
One and only one father node outside), child's number of all ON nodes can be at least expressed as in wireless sensor network：
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<mi>N</mi>
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<mo>{</mo>
<mi>S</mi>
<mo>}</mo>
<mo>,</mo>
<mn>0</mn>
<mo>&le;</mo>
<msub>
<mi>F</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>&le;</mo>
<mi>K</mi>
<mo>-</mo>
<mn>1</mn>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Wherein n (j) is all communication nodes in node i radio-frequency region.
5. having the data transmission method of energy capture function in a kind of intelligent grid as claimed in claim 1, its feature exists
In the data transfer of the wireless sensor network converges routing algorithm to complete routing procedure, optimal number based on optimal data
It is according to convergence routing algorithm step：
The first step, Weighted Directed Graph is constructed in the non-directed graph that all ON nodes, EHN nodes, B node are formed, and wherein
Each node is found, weight is arranged to：ON node weights are 1, EHN nodes and B node weight is 0, if u is ON nodes, using u as
Starting point, connection u and v directed edge weight are arranged to w [u, v]=1, if u is EHN nodes or B node, correspond to w [u, v]=0；
Second step, situation containing ring in previous step result is checked, if acyclic, directly obtain reverse data and converge topological tree, into the
Four steps, if ring be present, it is destroyed, the EHN nodes that will be contained in ring merge, and form a new merging section
Point, the emitting edge that minimal weight selects each node is again based on, forms a new minimal weight topological tree, repeat second step
Operation, check the situation comprising ring in new tree and handled accordingly, up to being free of ring in last tree；
3rd step, separates the merge node of previous step, and determines the emitting edge of each node in figure, obtains corresponding reversely convergence
Topological tree；
4th step, each side that reverse support is converged to topological tree carry out reverse process, obtain the spanning tree consistent with data transfer
Convergence route；
5th step, the repetition first step to the 4th step, other possible spanning trees convergence routes are obtained, and contrasted, final
Converge and route to optimal data.
6. having the data transmission method of energy capture function in a kind of intelligent grid as claimed in claim 3, its feature exists
In in the convergence tree built, an alternative functional node, the energy supply can be increased by node in catching for heavier transformation task
Node is only to catch energy node to provide RF energy, and convergence route is not had an impact.
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