CN104065168A - Dynamic variable-frequency data collection method for monitoring wind-PV-ES hybrid power generation status - Google Patents
Dynamic variable-frequency data collection method for monitoring wind-PV-ES hybrid power generation status Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention discloses a dynamic variable-frequency data collection method for monitoring wind-PV-ES hybrid power generation status. The method comprises the following steps: step 1, an inter-field scheduling monitoring work station in a monitoring layer obtains an operation combination mode of a hybrid power generation system and initializes task characteristic parameters at the same time; step 2, the monitoring layer monitors whether a data collection time is reached and sends a collection time instruction to a collection layer; step 3, the inter-field scheduling monitoring work station processes a received active power p and calculates a total active minute-level fluctuation rate; and step 4, the inter-field scheduling monitoring work station carries out analysis on each collection layer on the basis of the received active power p, adopts dual-threshold multi-level threshold frequency modulation mechanism to determine whether it is necessary to change the collection frequency, and determines the post-change collection frequency and sends the post-change collection frequency to each field-level work station if frequency change is needed. The method can recognize small data changes, achieves smooth switching between frequencies, and thus largely reduces the influence of threshold values to energy saving effects.
Description
Technical field
The present invention relates to a kind of collecting method of wind-solar-storage joint generating state monitoring, in particular, relate to a kind of dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring, belong to wind-light storage technical field of power generation.
Background technology
In recent years, in China, take the clean energy resource generation technology that wind power generation, photovoltaic generation be representative is developed rapidly.The feature for primary energy with randomness, fluctuation and indirect, wind-solar-storage joint generation technology is intended to utilize energy-storage system and photovoltaic generation and wind generator system to coordinate mutually, effectively reduce generation of electricity by new energy to the impact of safe operation of power system and impact, improve stability and the economy of power system operation.Collection and the supervision of wind-solar-storage joint generating real time execution information are the bases that guarantees its normal operation.Data acquisition system, as the important component part of control system basic platform, has realized the unified of production run information and has gathered and process, for combined generating system operation monitoring provides authentic data source.
Compare with traditional electrical network, containing the wind-solar-storage joint electricity generation system of distributed power source, all differences to some extent in the scale of power system capacity and collection point.Therefore, guarantee the real-time of data acquisition and seem particularly important with reliability.In wind-solar-storage joint electricity generation system, wind power system, photovoltaic system and energy-storage system are not only separate but also complement one another on topological structure, this has determined the diversity of wind-light storage system running pattern, as: wind power system is exerted oneself separately, photovoltaic system is exerted oneself separately, wind-powered electricity generation/photovoltaic system combine exert oneself, wind-powered electricity generation/energy-storage system combine exert oneself, photovoltaic/energy-storage system combine exert oneself, wind-powered electricity generation/photovoltaic/energy-storage system combines and exerts oneself.In above 6 kinds of configuration operational mode handoff procedures, service data variation characteristic also can produce respective change with the exert oneself adjustment of state of each system.Yet traditional data acquisition method adopts fixedly frequency acquisition conventionally, acquisition mode is " passive " comparatively, ignored the impact of data variation on acquisition tasks implementation.Be applied in Practical Project, can have following shortcoming: the data of (1) acquisition target change violent in district sometime, and times of collection is not enough, and the more difficult seizure of critical data, is easily left in the basket, variation tendency that cannot accurate response data; (2) data of acquisition target are changing gently in district sometime, and times of collection is too much, and data redudancy increases, and cause the wasting of resources and systematic function to decline; (3) along with electricity generation system dilatation, the load pressure of the network equipment and the transmission pressure of bandwidth can increase thereupon, have a strong impact on overall performance, and real-time property can not be guaranteed.
Summary of the invention
Goal of the invention: the object of the invention is for the deficiencies in the prior art, provides a kind of
Therefore for above-mentioned situation, need to set up a kind of wind-solar-storage joint generating set syntype that meets, can adjust data acquisition task status according to real system ruuning situation self adaptation, when meeting data integrity and real-time, make full use of the collecting method of Internet resources.
Technical scheme: the dynamic frequency-conversion collecting method of a kind of wind-solar-storage joint generating state monitoring of the present invention, combined generating system comprises mechanical floor, acquisition layer, network layer and supervisory layers, described mechanical floor comprises wind energy turbine set, photovoltaic DC field and energy storage device, described acquisition layer comprises the level work station, wind energy turbine set field with described wind energy turbine set communication connection, level work station, field, photovoltaic field with described photovoltaic DC field communication connection, level work station, energy storage device field with described energy storage device communication connection, described supervisory layers comprises dispatching and monitoring work station between field, between described, dispatching and monitoring work station communicates to connect by described network layer and described acquisition layer, carry out as follows:
Step1: between the field of supervisory layers, dispatching and monitoring work station obtains combined generating system operation integrated mode, while initialization task characteristic parameter, initialized task characteristic parameter comprises each rank frequency acquisition and at different levels total meritorious minute levels fluctuation threshold values corresponding to the granularity of dividing with described each rank frequency acquisition;
Step2: whether supervisory layers monitoring reaches the image data time, when arriving image data during the time, send acquisition time instruction to acquisition layer, each of acquisition layer level work station gathers the active power p of each on-site individuality that communicates with connection, the active power collecting is sent to dispatching and monitoring work station between the field of supervisory layers;
Step3: between, dispatching and monitoring work station is processed the active power p receiving, and extracts maximum active-power P in t minute
max, twith t minute in minimum active-power P
min, t, and calculate average active power P in t minute
avg, t, then calculate total meritorious minute level fluctuation ratio
, computational methods are
Step4: between, dispatching and monitoring work station is analyzed each acquisition layer according to the active power p receiving, for the acquisition layer in generation active power state, minute level fluctuation ratio of always gaining merit
compare with total meritorious minute level fluctuation threshold value, adopt double threshold multilevel threshold frequency modulation mechanism to judge whether to change frequency acquisition, if need to change frequency, determine frequency acquisition after changing and be sent to each level work station.
Being further defined to of technical solution of the present invention, the operation integrated mode described in Step1 comprises that wind energy turbine set is exerted oneself separately, exert oneself separately in photovoltaic field, wind-powered electricity generation/photovoltaic field combine exert oneself, wind-powered electricity generation/energy storage field combine exert oneself, photovoltaic/energy storage field combines and exerts oneself or one or more the combination in exerting oneself is combined in wind-powered electricity generation/photovoltaic/energy storage field.
Further, the concrete grammar of the employing double threshold multilevel threshold frequency modulation mechanism described in step Step4 is: first, during initialization initialization task characteristic parameter, initialized each rank frequency acquisition is F
i, the total meritorious minute level fluctuation threshold value corresponding with each rank frequency acquisition is 2n, wherein n low threshold value table is shown α
iL(1≤i≤n), n high threshold is expressed as α
iH(1≤i≤n), and meet α
iL< α
iH< α
(i+1) L(1≤i≤n); Then, when total meritorious minute level fluctuation ratio
time, between dispatching and monitoring work station by frequency acquisition by F
ibe down to F
i-1; When total meritorious minute level fluctuation ratio
time, between, dispatching and monitoring work station rises to F by frequency acquisition by Fi
i+1.
Further, in step Step4, in not producing the acquisition layer of active power state, under original frequency acquisition, the frequency acquisition minimum frequency acquisition to initial setting up step by step declines.
Beneficial effect: the dynamic frequency-conversion collecting method of a kind of wind-solar-storage joint generating state monitoring provided by the invention, in conjunction with wind-solar-storage joint electricity generation system combined running pattern and service data variation characteristic, adopt layered distribution type scheduling strategy, realize the execution frequency that self adaptation is dynamically adjusted acquisition tasks.Empirical tests, under identical frequency acquisition, the composes curve collecting than fixed frequency method according to self-adapting frequency conversion algorithm, precision improves an order of magnitude, effectively reduces the distortion factor of signal data acquisition; Under identical acquisition precision, the frequency acquisition of self-adapting frequency conversion acquisition method is lower more than 30% than fixed frequency acquisition method, and it is 1/3rd that the data volume of its transmission decreases, and has significantly improved Internet Transmission bandwidth availability ratio; The present invention builds data acquisition mission frequency apportion model, application simulation annealing algorithm obtains optimal solution and the suboptimal solution of system acquisition frequency set in finite time, realize the optimization that mission frequency distributes, obtain the dynamic frequency allocation scheme that task execution time is minimum, network energy consumption is minimum that makes; The present invention adopts double threshold multilevel threshold mechanism to realize frequency acquisition handoff procedure, solved the jitter problem while adopting single threshold frequency to switch, also be better than traditional double threshold method simultaneously, reduced the difference between side frequency, can identify data variation more by a small margin, realized between frequency and steadily having switched, greatly reduced the impact of threshold value value on energy-saving effect.
Accompanying drawing explanation
Fig. 1 is the structural representation of wind-solar-storage joint generating data acquisition system provided by the invention;
Fig. 2 is the flow chart of the dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring provided by the invention;
Fig. 3 is double threshold multilevel threshold frequency modulation schematic diagram of mechanism provided by the invention;
Fig. 4 is the dynamic frequency-conversion collecting method of wind-solar-storage joint generating state provided by the invention monitoring and the fixing simulated effect comparison diagram of frequency acquisition collecting method;
Fig. 5 is that the dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring provided by the invention is applied to the simulated effect figure in the monitoring of wind-solar-storage joint generating state.
Embodiment
Below by accompanying drawing, technical solution of the present invention is elaborated, but protection scope of the present invention is not limited to described embodiment.
Embodiment 1: a kind of dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring, the structural representation of combined generating system as shown in Figure 1, system adopts cross direction profiles, longitudinal layered thought, set up distributed network hardware platform, comprise mechanical floor, acquisition layer, network layer and supervisory layers, described mechanical floor comprises wind energy turbine set, photovoltaic DC field and energy storage device, described acquisition layer comprises the level work station, wind energy turbine set field with described wind energy turbine set communication connection, level work station, field, photovoltaic field with described photovoltaic DC field communication connection, level work station, energy storage device field with described energy storage device communication connection, described supervisory layers comprises dispatching and monitoring work station between field, between described, dispatching and monitoring work station communicates to connect by described network layer and described acquisition layer.
Described mechanical floor, according to generation mode, is divided into a plurality of regions by whole power plant zoning and carries out distributed capture, comprises wind energy turbine set, photovoltaic cell, and energy-storage system
Described acquisition layer, comprises level work station, field set in each region, and the acquisition tasks of generating field in region is carried out to dispatching and monitoring.
Described networking layer, adopts Ethernet mode to set up data acquisition system, and communication connects employing ICP/IP protocol.The unified telemechanical agreement based on TCP is followed in remote action data transmission in supervisory layers, guarantees compatibility, reliability and the opening of system communication.
Described supervisory layers, is responsible for the real-time monitoring and scheduling of system running state.Comprise dispatching and monitoring work station between field, failure warning management work station, system maintenance work station and database server.
Wind-solar-storage joint electricity generation system combined running pattern and service data variation characteristic, the present invention arranges Control and Schedule work station between field in supervisory layers and carries out self adaptation dynamic frequency-conversion data acquisition strategy, and the acquisition tasks of each place is carried out to dynamic adjustments.
The flow chart of the dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring as shown in Figure 2, carries out as follows:
Step1: between the field of supervisory layers, dispatching and monitoring work station obtains combined generating system operation integrated mode, while initialization task characteristic parameter, initialized task characteristic parameter comprises each rank frequency acquisition and at different levels total meritorious minute levels fluctuation threshold values corresponding to the granularity of dividing with described each rank frequency acquisition.
Described operation integrated mode comprises that wind energy turbine set is exerted oneself separately, exert oneself separately in photovoltaic field, wind-powered electricity generation/photovoltaic field combine exert oneself, wind-powered electricity generation/energy storage field combine exert oneself, photovoltaic/energy storage field combines and exerts oneself or one or more the combination in exerting oneself is combined in wind-powered electricity generation/photovoltaic/energy storage field.
Combining wind and light to generate electricity has natural complementarity to a certain degree, and by energy-storage system, it carries out smooth adjustment.Take one day 24 hours be example, retrained by environmental condition, wind power generation amount is many features at few night on daytime, and only has when wind speed is when minimum starts between wind speed, excision wind speed, wind power system just has output; And photovoltaic generation is subject to the factor impacts such as solar radiation, ambient temperature, while only having solar irradiation by day, just can exert oneself.Consider the factors of limit life of energy-storage battery, at the scene energy-storage system cannot reach grid-connected requirement time of exerting oneself, regulate, otherwise energy-storage system is failure to actuate.Wind-solar-storage joint power-generating control system, according to operation plan, scene prediction, carries out overall view monitoring to combined generating system, has realized 6 kinds of different configuration operational mode seamless switchings.As shown in table 1.P
pv, P
wd, P
batdifference photovoltaic module power stage value, wind-powered electricity generation unit power stage value, energy storage device power stage value.
Table 1 wind-light storage combined running modes relationships
| Operational mode | External environment factor | Energy storage regulates | Gross capability P |
| Wind is exerted oneself separately | Wind speed is in can range of operation and meet grid-connected condition, unglazed photograph | No | P wd |
| Wind/storage is combined and is exerted oneself | Wind speed is in can range of operation and do not meet grid-connected condition, unglazed photograph | Be | P wd+P bat |
| Light is exerted oneself separately | Have illumination and meet grid-connected condition, wind speed is outside can range of operation | No | P pv |
| Light/storage is combined and is exerted oneself | Have illumination and do not meet grid-connected condition, wind speed is outside can range of operation | Be | P pv+P bat |
| Wind/light is combined and is exerted oneself | Have illumination, wind speed in can range of operation, synthetic exerting oneself meets grid-connected condition | No | P pv+P wd |
| Wind-solar-storage joint is exerted oneself | There are illumination, wind speed in can range of operation, the synthetic grid-connected condition of discontented foot of exerting oneself | Be | P pv+P wd+P bat |
Step2: whether supervisory layers monitoring reaches the image data time, when arriving image data during the time, send acquisition time instruction to acquisition layer, each of acquisition layer level work station gathers the active power p of each on-site individuality that communicates with connection, the active power collecting is sent to dispatching and monitoring work station between the field of supervisory layers.
For each generating place, the present invention arranges respectively a level work station at wind energy turbine set, photovoltaic cell level and energy-storage system, to image data classification in region, and gathers by Location of requirement the task start mode that all types of data adopt.During beginning, define the characteristic parameter (as time of implementation, time limit, cycle etc.) of task, and determine each task priority; Then, selecting the highest task of dynamic priority is its Resources allocation, and responds task requests, and data acquisition thread starts to carry out this task.Timing carries out dynamic priority renewal to the task in task queue, at the task scheduling point of setting, regularly upgrades the dynamic priority that calculates all ready tasks, and task is sorted and selects to carry out head of the queue task.While having new task to arrive, calculate its priority, and insert the relevant position in task queue.When the priority value of a plurality of tasks equates, according to certain priority with reference to its characteristic parameter, as the priority of characteristic parameter is from high to low: time limit, time of implementation, cycle.
Step3: for the system that is in generating state, the situation of change according to its fluctuation ratio α that always gains merit in the recent period, judges whether to change frequency.If α surpasses or lower than the threshold value of closing on of setting, generate a frequency acquisition altering event frequency acquisition is adjusted accordingly, otherwise maintain original frequency acquisition.
Between, dispatching and monitoring work station is processed the active power p receiving, and extracts maximum active-power P in t minute
max, twith t minute in minimum active-power P
mtn, t, and calculate average active power P in t minute
avg, t, then calculate total meritorious minute level fluctuation ratio
, computational methods are
For the system that is in the state of not exerting oneself, under original acquisition state, be down to step by step minimum frequency acquisition F1.Definition frequency acquisition can only switch between adjacent frequency, the switching of can not bypassing the immediate leadership, and F1≤Fi≤Fn+1.Wherein, the minimum frequency acquisition that F1 is default, the maximum frequency acquisition that Fn+1 is default.
Step4: between, dispatching and monitoring work station is analyzed each acquisition layer according to the active power p receiving, for the acquisition layer in generation active power state, minute level fluctuation ratio of always gaining merit
compare with total meritorious minute level fluctuation threshold value, adopt double threshold multilevel threshold frequency modulation mechanism to judge whether to change frequency acquisition, if need to change frequency, determine frequency acquisition after changing and be sent to each level work station.
Described employing double threshold multilevel threshold frequency modulation mechanism, as shown in Figure 3, concrete grammar is its structural representation: first, during initialization initialization task characteristic parameter, initialized each rank frequency acquisition is F
i, the total meritorious minute level fluctuation threshold value corresponding with each rank frequency acquisition is 2n, wherein n low threshold value table is shown α
iL(1≤i≤n), n high threshold is expressed as α
iH(1≤i≤n), and meet α
iL< α
iH< α
(i+1) L(1≤i≤n); Then, when total meritorious minute level fluctuation ratio
time, between dispatching and monitoring work station by frequency acquisition by F
ibe down to F
i-1; When total meritorious minute level fluctuation ratio
time, between, dispatching and monitoring work station rises to F by frequency acquisition by Fi
i+1.For in not producing the acquisition layer of active power state, under original frequency acquisition, the frequency acquisition minimum frequency acquisition to initial setting up step by step declines.
For realizing each task of data acquisition system, carry out efficiently and in real time acquisition tasks, effectively promote network performance simultaneously, the present invention adopts simulated annealing, using time overhead and network overhead as evaluation model, in conjunction with wind-solar-storage joint electricity generation system combined running pattern and service data variation characteristic, formulating the target function E (x) of Model for Multi-Objective Optimization, is dynamically that frequency acquisition is distributed in each collection point, region.
One, dynamic frequency-conversion data acquisition mission frequency apportion model
1, mission frequency apportion model evaluation function
(1) time overhead, comprising: interaction time between a level acquisition time, field
Time is the time overhead of layered distribution type data acquisition; N is place quantity,
it is the acquisition node number of i place; Time
ijfor gathering each node required time, time
interthe mutual required time of control centre for work station between this place and field.
(2) network overhead, comprising: between a level communication energy consumption, field, communication energy consumption, acquisition node are processed energy consumption
C is the network overhead of layered distribution type data acquisition; N is place quantity,
with
be intra-area communication expense and the inter-domain communication expense of i place,
energy consumption for node processing task.
2, Model for Multi-Objective Optimization
For obtaining the dynamic frequency allocation scheme that meets data acquisition task real-time and network bandwidth requirement, the present invention, in conjunction with above-mentioned evaluation function, to every optimization index weighted comprehensive, obtains the target function of following Model for Multi-Objective Optimization:
E(x)＝w
1×min(time)+w
2×min (4)
W wherein
ifor can value being zero weight function.
Two, algorithm setting
If the frequency acquisition that data acquisition equipment can provide integrates as D={d1, d2 ..., dm}.Fixed Frequency Assignment is exactly in a fixing frequency set, to complete the sharing out the work of each device frequency, and makes that task execution time is minimum, network energy consumption is minimum.X represents frequency allocation plan, be expressed as X=(x1, x2 ..., xN), N represents collector quantity in system, xi arranges with priority rule.
New explanation production method: the present invention adopts the new explanation production method in two migrations field, produces new frequency and distributes solution: Xold and Xnew to represent that respectively the frequency before and after conversion distributes solution by changing two parameters at every turn.
State is accepted function: effectively avoid being absorbed in local suboptimal solution.The present invention adopts min{1, exp (△ E/t) } > random (0,1) is as accepting the condition of new state.
Control parametric t: control the process of whole annealing algorithm, determine at each " temperature " the lower iterations of separating.The present invention adopts Annealing Strategy how much, i.e. the decline of temperature is linear and declines, and the iterative steps in each temperature is identical.Temperature declines and meets following relation:
t
k+1＝α×t
k(0≤α≤1) (5)
Annealing scheme: establishing total temperature decline number of times is definite value K, when temperature iterations reaches K, stops computing.Further, the iterative steps of each temperature is by accepting rate control.Accept ratio index R (0.9) for given one, iteration step length upper limit U (100) and lower limit L (10), each temperature is iteration L time at least, and record total degree and the received number of times of same temperature iteration, when iterations surpasses L, if when accepting number of times and being not less than R with the ratio of total degree, in this temperature iteration and start temperature and reduce no longer, otherwise iterate to upper limit step number always.
Three, algorithm steps
Take generating place be allocation unit, according to priority orders, list all acquisition tasks.
According to priority order from high to low, be to distribute and carry out frequency to acquisition tasks, until all mission frequencys are assigned.
The task solution that is positioned at high priority is fixed, and other separate element as the initial solution of simulated annealing.
Carry out simulated annealing, find the solution that meets constraints, merge with the solution that high-priority task is distributed before, form the final set of separating, obtain final scheme.
Above-mentioned simulated annealing concrete steps:
Select the solution element i0 except high priority; I:=i0; K:=0; T0:=tmax (initial temperature).
If reach interior circulation stop condition changing temperature, arrive step3;
Otherwise, by current solution Xold, through conversion, producing Xnew, calculating target function Enew, by △ E=Enew-Eold; If △ E≤0, Eold:=Enew, Xold:=Xnew, if otherwise during exp (△ E/tk) > random (0,1), Eold:=Enew, Xold:=Xnew; Repeating step 2.
Tk+1:=d (tk); K:=k+1; If meet stop condition, stop calculating; Otherwise, get back to step 2.
By above-mentioned algorithm, the place that can obtain generating electricity is the frequency allocation plan of each level work station acquisition tasks of unit.For example there is allocative decision (2,3,1), represent that the frequency acquisition that a level work station is distributed is respectively d2, d3, d1.
As shown in Figure 4, by emulation experiment, self adaptation dynamic frequency-conversion collecting method and the fixing effect contrast figure of frequency acquisition collecting method have been simulated.
As shown in Figure 5, by emulation experiment, take one day 24 hours be example, simulated self adaptation dynamic frequency-conversion collecting method and be applied to the simulated effect figure in the monitoring of wind-solar-storage joint generating state.
Above-mentioned simulation result shows, a kind of self adaptation dynamic frequency-conversion collecting method that is applied to the monitoring of wind-solar-storage joint generating state of the present invention, can in time regulate frequency acquisition, compare with fixing frequency acquisition, meeting under the requirement of task execution time and network energy consumption, effectively reduce the distortion factor of sampling, improve the stability of a system.
As mentioned above, although represented and explained the present invention with reference to specific preferred embodiment, it shall not be construed as the restriction to the present invention self.Not departing under the spirit and scope of the present invention prerequisite of claims definition, can make in the form and details various variations to it.
Claims (4)
1. the dynamic frequency-conversion collecting method of wind-solar-storage joint generating state monitoring, combined generating system comprises mechanical floor, acquisition layer, network layer and supervisory layers, described mechanical floor comprises wind energy turbine set, photovoltaic DC field and energy storage device, described acquisition layer comprises the level work station, wind energy turbine set field with described wind energy turbine set communication connection, level work station, field, photovoltaic field with described photovoltaic DC field communication connection, level work station, energy storage device field with described energy storage device communication connection, described supervisory layers comprises dispatching and monitoring work station between field, between described, dispatching and monitoring work station communicates to connect by described network layer and described acquisition layer, it is characterized in that, carry out as follows:
Step1: between the field of supervisory layers, dispatching and monitoring work station obtains combined generating system operation integrated mode, while initialization task characteristic parameter, initialized task characteristic parameter comprises each rank frequency acquisition and at different levels total meritorious minute levels fluctuation threshold values corresponding to the granularity of dividing with described each rank frequency acquisition;
Step2: whether supervisory layers monitoring reaches the image data time, when arriving image data during the time, send acquisition time instruction to acquisition layer, each of acquisition layer level work station gathers the active power p of each on-site individuality that communicates with connection, the active power collecting is sent to dispatching and monitoring work station between the field of supervisory layers;
Step3: between, dispatching and monitoring work station is processed the active power p receiving, and extracts maximum active-power P in t minute
max, twith t minute in minimum active-power P
min, t, and calculate average active power P in t minute
avg, t, then calculate total meritorious minute level fluctuation ratio
, computational methods are
Step4: between, dispatching and monitoring work station is analyzed each acquisition layer according to the active power p receiving, for the acquisition layer in generation active power state, minute level fluctuation ratio of always gaining merit
compare with total meritorious minute level fluctuation threshold value, adopt double threshold multilevel threshold frequency modulation mechanism to judge whether to change frequency acquisition, if need to change frequency, determine frequency acquisition after changing and be sent to each level work station.
2. the dynamic frequency-conversion collecting method that a kind of wind-solar-storage joint generating state according to claim 1 is monitored, it is characterized in that, the operation integrated mode described in Step1 comprises that wind energy turbine set is exerted oneself separately, exert oneself separately in photovoltaic field, wind-powered electricity generation/photovoltaic field combine exert oneself, wind-powered electricity generation/energy storage field combine exert oneself, photovoltaic/energy storage field combines and exerts oneself or one or more the combination in exerting oneself is combined in wind-powered electricity generation/photovoltaic/energy storage field.
3. the dynamic frequency-conversion collecting method that a kind of wind-solar-storage joint generating state according to claim 1 is monitored, it is characterized in that, the concrete grammar of the employing double threshold multilevel threshold frequency modulation mechanism described in step Step4 is: first, during initialization initialization task characteristic parameter, initialized each rank frequency acquisition is F
i, the total meritorious minute level fluctuation threshold value corresponding with each rank frequency acquisition is 2n, wherein n low threshold value table is shown α
iL(1≤i≤n), n high threshold is expressed as α
iH(1≤i≤n), and meet α
iL< α
iH< α
(i+1) L(1≤i≤n); Then, when total meritorious minute level fluctuation ratio
time, between dispatching and monitoring work station by frequency acquisition by F
ibe down to F
i-l; When total meritorious minute level fluctuation ratio
time, between, dispatching and monitoring work station rises to F by frequency acquisition by Fi
i+l.
4. the dynamic frequency-conversion collecting method that a kind of wind-solar-storage joint generating state according to claim 1 is monitored, it is characterized in that, in step Step4, for in not producing the acquisition layer of active power state, under original frequency acquisition, the frequency acquisition minimum frequency acquisition to initial setting up step by step declines.
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| CN105305624A (en) * | 2015-10-28 | 2016-02-03 | 成都振中电气有限公司 | Intelligent power monitoring system |
| CN107864071A (en) * | 2017-11-02 | 2018-03-30 | 江苏物联网研究发展中心 | A kind of dynamic measuring method, apparatus and system towards active safety |
| CN109446023A (en) * | 2018-10-12 | 2019-03-08 | 上海东土远景工业科技有限公司 | A kind of determination method, apparatus, equipment and the storage medium of data collection cycle |
| CN109528175A (en) * | 2018-08-30 | 2019-03-29 | 吉林大学 | Monitoring early-warning system and method for early warning in a kind of gynecological tumor Internet-based nursing |
| CN111314801A (en) * | 2020-02-13 | 2020-06-19 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Data acquisition system and method supporting dynamic scheduling |
| CN112732738A (en) * | 2020-11-05 | 2021-04-30 | 北京邮电大学 | Adaptive network data acquisition method based on multi-objective optimization and related equipment |
| CN113341918A (en) * | 2021-05-28 | 2021-09-03 | 北京时域智控技术有限公司 | Railway wagon monitoring system and method |
| CN113631811A (en) * | 2019-03-28 | 2021-11-09 | Ntn株式会社 | Condition monitoring system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101144840A (en) * | 2007-10-24 | 2008-03-19 | 重庆大学 | Power network overvoltage signal frequency conversion sampling method |
| US7716567B1 (en) * | 2000-09-28 | 2010-05-11 | Rockwell Automation Technologies, Inc. | Multilinguistic industrial control and monitoring system |
| CN101900777A (en) * | 2009-05-27 | 2010-12-01 | 河南省电力勘测设计院 | Monitoring method and device of power system |
| CN102510286A (en) * | 2011-10-29 | 2012-06-20 | 中北大学 | Frequency conversion sampling method |
| WO2013020034A2 (en) * | 2011-08-03 | 2013-02-07 | Johnson Controls Technology Company | Variable frequency generator power supply for centrifugal chillers |
| CN203616000U (en) * | 2013-11-26 | 2014-05-28 | 东华大学 | Frequency conversion sampling device for hydraulic pump vibration signal |
-
2014
- 2014-06-30 CN CN201410307922.7A patent/CN104065168B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7716567B1 (en) * | 2000-09-28 | 2010-05-11 | Rockwell Automation Technologies, Inc. | Multilinguistic industrial control and monitoring system |
| CN101144840A (en) * | 2007-10-24 | 2008-03-19 | 重庆大学 | Power network overvoltage signal frequency conversion sampling method |
| CN101900777A (en) * | 2009-05-27 | 2010-12-01 | 河南省电力勘测设计院 | Monitoring method and device of power system |
| WO2013020034A2 (en) * | 2011-08-03 | 2013-02-07 | Johnson Controls Technology Company | Variable frequency generator power supply for centrifugal chillers |
| CN102510286A (en) * | 2011-10-29 | 2012-06-20 | 中北大学 | Frequency conversion sampling method |
| CN203616000U (en) * | 2013-11-26 | 2014-05-28 | 东华大学 | Frequency conversion sampling device for hydraulic pump vibration signal |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104599468A (en) * | 2014-12-18 | 2015-05-06 | 中国电子科技集团公司第五十研究所 | Multidevice information acquisition control method |
| CN104599468B (en) * | 2014-12-18 | 2018-01-30 | 中国电子科技集团公司第五十研究所 | The information gathering control method of more equipment |
| CN105305624A (en) * | 2015-10-28 | 2016-02-03 | 成都振中电气有限公司 | Intelligent power monitoring system |
| CN107864071A (en) * | 2017-11-02 | 2018-03-30 | 江苏物联网研究发展中心 | A kind of dynamic measuring method, apparatus and system towards active safety |
| CN107864071B (en) * | 2017-11-02 | 2021-06-22 | 江苏物联网研究发展中心 | Active safety-oriented dynamic data acquisition method, device and system |
| CN109528175A (en) * | 2018-08-30 | 2019-03-29 | 吉林大学 | Monitoring early-warning system and method for early warning in a kind of gynecological tumor Internet-based nursing |
| CN109446023A (en) * | 2018-10-12 | 2019-03-08 | 上海东土远景工业科技有限公司 | A kind of determination method, apparatus, equipment and the storage medium of data collection cycle |
| CN113631811A (en) * | 2019-03-28 | 2021-11-09 | Ntn株式会社 | Condition monitoring system |
| CN111314801A (en) * | 2020-02-13 | 2020-06-19 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Data acquisition system and method supporting dynamic scheduling |
| CN111314801B (en) * | 2020-02-13 | 2022-01-28 | 中国铁道科学研究院集团有限公司铁道建筑研究所 | Data acquisition system and method supporting dynamic scheduling |
| CN112732738A (en) * | 2020-11-05 | 2021-04-30 | 北京邮电大学 | Adaptive network data acquisition method based on multi-objective optimization and related equipment |
| CN113341918A (en) * | 2021-05-28 | 2021-09-03 | 北京时域智控技术有限公司 | Railway wagon monitoring system and method |
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