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CN109618358A - A kind of wireless sensor network node energy optimizing method based on self adaptive control - Google Patents

A kind of wireless sensor network node energy optimizing method based on self adaptive control Download PDF

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Publication number
CN109618358A
CN109618358A CN201910087036.0A CN201910087036A CN109618358A CN 109618358 A CN109618358 A CN 109618358A CN 201910087036 A CN201910087036 A CN 201910087036A CN 109618358 A CN109618358 A CN 109618358A
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time
energy
power
node
night
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CN109618358B (en
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杨俊杰
邵凌峰
方济城
刘子琦
刘军
朱彬斌
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Shanghai University of Electric Power
University of Shanghai for Science and Technology
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Shanghai University of Electric Power
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W24/00Supervisory, monitoring or testing arrangements
    • H04W24/02Arrangements for optimising operational condition
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W52/00Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02Power saving arrangements
    • H04W52/0209Power saving arrangements in terminal devices
    • H04W52/0261Power saving arrangements in terminal devices managing power supply demand, e.g. depending on battery level
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30Services specially adapted for particular environments, situations or purposes
    • H04W4/38Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The present invention relates to a kind of wireless sensor network node energy optimizing method based on self adaptive control, the sequence that this method is changed over time by self perception solar panel dump energy, to output power progress self selective change, comprising the following steps: S1: obtaining the power consumption of dormancy time and working time cross one another average power consumption and sensor all sensing elements simultaneously all one's effort work of the sensor node in the case where maximum permissible time delay using sensor node parameters;S2: the weather forecasting data of next consecutive days and the consumption parameter of self power are collected;S3: the Power operation in different time is carried out according to the dump energy at the current time in data and is judged;S4: the final Power operation judging result of different time is combined into final energy optimization operation result.Compared with prior art, the advantages that present invention optimizes with collective, self adaptive control, and the control time is short.

Description

A kind of wireless sensor network node energy optimizing method based on self adaptive control
Technical field
The present invention relates to wireless sensor network technology fields, more particularly, to a kind of wireless biography based on self adaptive control Sensor network node energy optimization method.
Background technique
Wireless sensor network (WSN) is a kind of emerging network technology, it is by having perception, calculating and communication capacity Sensor node cooperates network consisting in a manner of ad hoc network, passes through the letter of perceptive object in acquisition network's coverage area Breath with the communication of multi-hop will be collected, treated, and information is transmitted to base station, and can finally be provided to terminal user.? In power industry, with deepening continuously for smart grid construction, the links such as electric system power generation, transmission of electricity, power transformation, distribution, electricity consumption To the monitoring of equipment running status, more stringent requirements are proposed, and the power plant monitoring requirements for being then based on wireless sensor network are answered It transports and gives birth to.Therefore propose that a kind of energy strategy of the self adaptive control on WSN node based on greed selection optimizes with Logistics networks More long survival, so as to can be carried out self energy-optimised for sensor node.
In wireless sensor network, since node energy supplement is insufficient or energy supplement is unpredictable, EnergyPolicy The factor of overriding concern when optimization has become sensor network design.It is limited that power detection sensor network node is solved at present The effective way of life problems is using chargeable wireless sensor network technology.In chargeable electric power monitoring sensor network In network, if the energy of node acquisition is enough or energy can periodically, continuity be supplemented, node can Not limited completely by for electric flux.However, in many occasions of solar energy, powered by wind energy, due to weather, node The supplement of energy has unpredictability and unreliability.
The Main way studied at present is the optimization in the optimization and whole network node communication path for filling energy strategy, or Person is mainly for trolley path planning problem (being sensor node charging with moving trolley).
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind based on self-adaptive controlled The wireless sensor network node energy optimizing method of system.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of wireless sensor network node energy optimizing method based on self adaptive control, this method are perceived by self The sequence that solar panel dump energy changes over time carries out self selective change to output power, comprising the following steps:
S1: dormancy time of sensor node in the case where maximum permissible time delay is obtained using sensor node parameters The power consumption to work with all strength simultaneously with working time cross one another average power consumption and all sensing elements of sensor;
S2: the weather forecasting data of next consecutive days and the consumption parameter of self power are collected;
S3: the Power operation in different time is carried out according to the dump energy at the current time in data and is judged;
S4: the final Power operation judging result of different time is combined into final energy optimization operation result.
Further, the step S3 include it is following step by step:
S301: the interval judgement that makes a decision is carried out for moment at night dump energy;
S302: night Power operation scheme is determined according to different judging results.
Further, the step S301, describes formula are as follows:
En> Tn*Pmax+Eemonth
Tn*Pmax+Eemonth> En> Tn*Pmin+Eemonth
Tn*Pmin+Eemonth> En> Tn*Pmin
Tn*Pmin> En
In formula, EnFor moment at night dump energy, EemonthEnergy, T are ensured to be monthly minimumnFor All Through The Night duration, PmaxFor the power consumption that all sensing elements of sensor work simultaneously, P with all strengthminIt is sensor node in the maximum feelings for allowing time delay The cross one another average power consumption of dormancy time and working time under condition.
Further, the step 302, specifically includes:
Work as En> Tn*Pmax+EemonthWhen, keep node to export P always at nightmax
Work as Tn*Pmax+Eemonth> En> Tn*Pmin+EemonthWhen, keep node in night dynamic operation;
Work as Tn*Pmin+Eemonth> En> Tn*PminWhen, keep node to export P always at nightmin
Work as Tn*Pmin> EnWhen, carry out artificial charging supplement energy.
Further, the step S4 further includes by night node output scheme result and node on daytime output scheme result It combines, node on the daytime output scheme describes formula are as follows:
In formula, EE is photovoltaic energy.
Further, the monthly minimum guarantee energy, describes formula are as follows:
Eemonth=Pmin*Tmonthmax
In formula, TmonthmaxFor monthly night duration maximum value.
Further, the calculation constraint condition of the step S1 are as follows:
In formula, PZigBeeIt is about beam power, DZigBeeTo constrain propagation delay time, TC、TDWhen respectively node is powered and discharges Between, TSFor the sleeping time of transceiver, TTThe time mutually converted between state, T are sended and received for transceiverWFor transceiver The time mutually converted between sleep and idle state, PSFor the power that node is lost in a sleep state, PRXFor reception state The mean power of lower loss, PTXFor the mean power being lost under emission state, L is retrieval length, T1When working for maximum power Between, T2For the minimum power working time.
Further, the modifying factor for correcting daytime and the output of night node is additionally provided in the step S4, Formula is described are as follows:
In formula, AnFor modifying factor.
Compared with prior art, the invention has the following advantages that
(1) control is easy, the sequence that the present invention is changed over time by self perception solar panel dump energy, to output work Rate carries out self selective change, comprising the following steps: S1: obtaining sensor node using sensor node parameters can permit in maximum Perhaps the dormancy time in the case where time delay and working time cross one another average power consumption and all sensing elements of sensor be simultaneously The power consumption of work with all strength;S2: the weather forecasting data of next consecutive days and the consumption parameter of self power are collected;S3: according to The dump energy at the current time in data carries out the Power operation judgement in different time;S4: by the final function of different time Rate operation judging result is combined into final energy optimization operation result, and control is easy, is able to achieve node and preferably survives and more High service efficiency.
(2) scheme is simple, and accuracy rate is high, and material object of the present invention includes: data acquisition module;Data processing module communicates mould Block, energy storage module, energy collection module and energy management module, mainly for energy management module, 1, felt according to self Oneself remaining energy is answered to determine the working method of next moment point --- turn between period suspend mode and full working condition It changes and realizes power output as much as possible, node power is more accurately adjusted in the case where real-time, be divided into two cover dies at night daytime Formula selects and was changed out force data with 30 minutes for a node, it is possible to reduce and photovoltaic is contributed unstable influence, For optimizing the average output power of wireless sensor node.2, since " daytime " and " night " and actual day and night have one Determine difference, therefore carry out a modified operators in ending moment (illumination terminates) daily, carries out a correction for energy storage.3, it devises One least energy residue principle, that is, energy needed for preservation one guarded is similar to animal hibernation, to guarantee node more It works long hours, accuracy rate is higher.
Detailed description of the invention
Fig. 1 is the device collocation figure of sensor node;
Fig. 2 is intra-node energy and management module interaction mode schematic diagram;
Fig. 3 is flow chart of the present invention;
Fig. 4 is the power supply energy curve graph that the present invention is compared with other methods.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that described embodiment is a part of the embodiments of the present invention, rather than whole embodiments.Based on this hair Embodiment in bright, those of ordinary skill in the art's every other reality obtained without making creative work Example is applied, all should belong to the scope of protection of the invention.
Embodiment
It arranges in pairs or groups and schemes for the device of sensor node in the present embodiment as shown in Figure 1 comprising data acquisition module;At data Module, communication module, energy storage module, energy collection module and energy management module are managed, wherein data acquisition module includes Sensor module and A D converter, data processing module specifically includes micro process and memory, and communication module includes channel radio Letter.
It is illustrated in figure 2 internal energy and management module interaction mode schematic diagram in the present embodiment, from the external sun The super capacitor energy-storage in wireless sensor network can first be made and deliver power to energy distribution module, energy predicting device is according to energy The real-time parameter of amount distribution module control and back regulation super capacitor is made a response.
It is illustrated in figure 3 the specific method flow diagram of the corresponding embodiment of the present invention, comprising the following steps:
Step 1) determines existing power type.By dormancy mechanism, two or more working efficiencies, Zhi Houzai are obtained Step 2 is required to be allocated according to such power in 3.Assuming that its there are two types of operating power and by certain model into Row simple analysis calculates, and is P respectivelymaxAnd Pmin。PmaxFor the power consumption that all sensing elements of sensor work simultaneously, P with all strengthminFor Dormancy time and working time cross one another average power consumption of the sensor node in the case where maximum permissible time delay.Pass through Constraint output power of each of which the available node in different delay is calculated, when another constraint condition is transmission Prolong, it is as follows to specifically describe formula:
In formula, PZigBeeIt is about beam power, DZigBeeTo constrain propagation delay time, TC、TDWhen respectively node is powered and discharges Between, TSFor the sleeping time of transceiver, TTThe time mutually converted between state, T are sended and received for transceiverWFor transceiver The time mutually converted between sleep and idle state, PSFor the power that node is lost in a sleep state, PRXFor reception state The mean power of lower loss, PTXFor the mean power being lost under emission state, L is retrieval length, T1When working for maximum power Between, T2For the minimum power working time.
The minimum power under suitable case propagation delays is solved using sensor node parameters.Solution can obtain maximum delay situation Under: PminFor 130mW, PmaxFor 650mW.
Step 2) collects data.Date (year, month, day) comprising measuring and calculating since no light, next to there is illumination Interlude is up to T according to (1) All Through The NightnTime and En> Tn*Pmax+Eemonth, then node is kept to export always at night Pmax
(2) if All Through The Night is up to TnTime and Tn*Pmax+Eemonth> En> Tn*Pmin+Eemonth, then according to following calculation The high and low Power operation of method progress night hours:
Max T1 n
In formula, T1 nFor the maximum high-power operation time in n-th day evening,For the low-power operation time in n-th day evening.
Simultaneously because the realization of algorithm depends on capacity of self-regulation, what is drawn oneself up with enabling sensor node " greed " makes With the high-power operation time --- the high-power operation time is first carried out, then starts the low-power operation time.Time i.e. at the beginning It is worked using maximum power.Decision condition are as follows:
E > EPrevioust-(T-Δtall)*Pmin
E=EPrevioust-Δtall*Pmax
If E≤Eprevioust-(T-Δtall)*Pmin, then P is used alwaysminIt works, thereby realizes at night More time high-power operation, i.e. transinformation is relatively more, and wherein E is
Above-mentioned two situations are outstanding situation and only carry out real-time control to it on daytime.
(3) if All Through The Night is up to TnTime and Tn*Pmin+Eemonth> En> Tn*Pmin, then P is keptminWork, but this The case where being exactly dangerous tendency, needs timely to be corrected at the time of daytime.
(4) if Tn*Pmin> En, then since the remaining tangible deficiency of energy must use human intervention, charging is intelligently submitted to mend It helps.
Step 3), for the first two situation in step 1:
It is controlled with the following conditions, selects its node operating power, by this treating method to ensure that energy is increasing In the case where it is as much as possible used, and the use that energy is fewer in the case where increasing insufficient situation, this is also greedy algorithm A kind of embodiment.In order to realize the reversion of situation, under light conditions, sensor node be must continue to using Pmin, until residue ENERGY En> Eemonth, its purpose is to make the energy content of battery possess most solar month of 30 days guarantee electricity once again, later further according to photovoltaic energy Amount carries out self selective power consumption compared with operating power, in conclusion the operating power scheme on daytime is described as follows:
In formula, EE is photovoltaic energy.
Photovoltaic energy amendment;
This correction time be step 2 terminate, i.e., by night at the time of, carry out the supplement of a modified operators, reduce Energy error.Due to it is considered herein that " daytime " and " night " and actual day and night have certain difference, i.e. EE < PminPortion The time divided is interpreted as the night of no illumination supplement, so the energy error certain with physical presence, however due to its mistake Poor very little, approximation are ignored, therefore fixing tentatively does not influence daily power distribution.However when the supplement accumulation of a large amount of small-power photovoltaics also can be right Gross energy generates certain deviation, so the present invention is by daily EE > PminTime energy by modifying factor into The daily improvement of row, has thus ensured the error small as far as possible of energy, the description formula of modifying factor are as follows:
In formula, AnFor modifying factor.
The energy of sensor node can excessively using and cause it that can not spend longest night, so be provided with the moon it is excellent Change --- of that month minimum guarantee energy describes formula are as follows:
Eemonth=Pmin*Tmonthmax
In formula, TmonthmaxFor monthly night duration maximum value.
According to long-term observation test discovery, annual each moon longest no light time, approximation substantially was (due to the recurrence of the sun Property it is basic annual constant), as long as therefore thinking that the sensor residual energy can satisfy the every month longest unglazed time is safety Range.So having set of that month minimum guarantee energy, minimum peace is determined according to the time T at the prior year same moon at longest night Full energy datum is to ensure to spend most difficult that day every month.
The present invention realizes the distribution of energy in the case where energy supplement amount is unknown in advance for maximum system performance: It will consider energy-optimised strategy in real time, since the short time will not excessively be mutated photovoltaic energy supplement under normal circumstances, so It is considered that the photovoltaic energy EE output power of a upper timing node is similar with the output power of next timing node.In reality The size between energy output and photovoltaic energy supply is obtained under the requirement of when property, when photovoltaic energy supply is completely defeated greater than maximum When out, sensor output power reaches peak value;When photovoltaic energy is less than maximum output, for the sustainable use of sensor, Using minimum output power, it thus ensure that the survival of node and system performance are more excellent to a certain extent, as shown in figure 4, phase Than with normal operation algorithm, the present invention designed by scheme corresponding energy control has been carried out according to the characteristic of different time, With good control effect.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right It is required that protection scope subject to.

Claims (8)

1. a kind of wireless sensor network node energy optimizing method based on self adaptive control, which is characterized in that this method is logical The sequence that self perception solar panel dump energy changes over time is crossed, self selective change is carried out to output power, including following Step:
S1: dormancy time and work of the sensor node in the case where maximum permissible time delay are obtained using sensor node parameters Make the power consumption that time cross one another average power consumption and all sensing elements of sensor work with all strength simultaneously;
S2: the weather forecasting data of next consecutive days and the consumption parameter of self power are collected;
S3: the Power operation in different time is carried out according to the dump energy at the current time in data and is judged;
S4: the final Power operation judging result of different time is combined into final energy optimization operation result.
2. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 1, It is characterized in that, the step S3 include it is following step by step:
S301: the interval judgement that makes a decision is carried out for moment at night dump energy;
S302: night Power operation scheme is determined according to different judging results.
3. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 2, It is characterized in that, the step S301, describes formula are as follows:
En> Tn*Pmax+Eemonth
Tn*Pmax+Eemonth> En> Tn*Pmin+Eemonth
Tn*Pmin+Eemonth> En> Tn*Pmin
Tn*Pmin> En
In formula, EnFor moment at night dump energy, EemonthEnergy, T are ensured to be monthly minimumnFor All Through The Night duration, PmaxTo pass The power consumption that all sensing elements of sensor work with all strength simultaneously, PminFor sensor node in the case where maximum permissible time delay Dormancy time and working time cross one another average power consumption.
4. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 2, It is characterized in that, the step 302, specifically includes:
Work as En> Tn*Pmax+EemonthWhen, keep node to export P always at nightmax
Work as Tn*Pmax+Eemonth> En> Tn*Pmin+EemonthWhen, keep node in night dynamic operation;
Work as Tn*Pmin+Eemonth> En> Tn*PminWhen, keep node to export P always at nightmin
Work as Tn*Pmin> EnWhen, carry out artificial charging supplement energy.
5. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 1, The step S4 further include by night node output scheme result with daytime node output scheme result combine, the daytime Point output scheme, describes formula are as follows:
In formula, EE is photovoltaic energy.
6. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 3, The monthly minimum guarantee energy, describes formula are as follows:
Eemonth=Pmin*Tmonthmax
In formula, TmonthmaxFor monthly night duration maximum value.
7. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 1, The calculation constraint condition of the step S1 are as follows:
In formula, PZigBeeIt is about beam power, DZigBeeTo constrain propagation delay time, TC、TDRespectively node energization and discharge time, TS For the sleeping time of transceiver, TTThe time mutually converted between state, T are sended and received for transceiverWFor transceiver sleep with The time mutually converted between idle state, PSFor the power that node is lost in a sleep state, PRXTo be lost under reception state Mean power, PTXFor the mean power being lost under emission state, L is retrieval length, T1For maximum power working time, T2For The minimum power working time.
8. a kind of wireless sensor network node energy optimizing method based on self adaptive control according to claim 5, It is additionally provided with the modifying factor for correcting daytime and the output of night node in the step S4, describes formula are as follows:
In formula, AnFor modifying factor.
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