CN107017625A - The method and apparatus that energy dynamics for independent micro-capacitance sensor are dispatched - Google Patents
The method and apparatus that energy dynamics for independent micro-capacitance sensor are dispatched Download PDFInfo
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- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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Abstract
The present invention provides the method and apparatus that a kind of energy dynamics for independent micro-capacitance sensor are dispatched, the independent micro-capacitance sensor includes a variety of distributed power generation sources and energy-storage system, a variety of distributed power generation sources include regenerative resource and tradition can dispatch unit, the method for the dynamic dispatching of independent micro-capacitance sensor comprises the following steps：S1：Obtain the prediction data for dynamic dispatching and obtain the tradition can dispatch unit and the energy-storage system essential information；S2：The dynamic dispatching Optimized model based on a variety of distributed power generation sources is set up based on the essential information and using intelligent optimization algorithm；S3：The prediction data is input to the dynamic dispatching Optimized model；S4：The energy dynamics scheduling of the independent micro-capacitance sensor is carried out according to the output result of the dynamic dispatching Optimized model.
Description
Technical field
The present invention relates to a kind of method and apparatus dispatched for micro-capacitance sensor, more particularly, it is related to a kind of be used for independently
The method and apparatus of the energy dynamics scheduling of micro-capacitance sensor.
Background technology
The mininet that micro-capacitance sensor is made up of distributed power source, load and energy storage device.Micro-capacitance sensor can be incorporated into the power networks,
Can also islet operation.Scattered electricity generation system and energy storage units are combined together as micro-capacitance sensor in an independent way
Advanced Control Techniques providing the user in the local chance for obtaining reliable and safety electric power.As main renewable
The wind-force (WT) and photovoltaic solar (PV) and such as miniature gas turbine, fuel cell (FC) and Diesel engine (DE) of the energy
It is the main distributed power generation source used in micro-capacitance sensor Deng energy source, these energy can mutually be supported with energy-storage system, to mend
The intermittence of regenerative resource is repaid, so as to improve the reliability and energy sustainability of system as much as possible.In intelligent grid
Under background, the load dispatch of micro-capacitance sensor is for ensuring that energy utilization rate and reduction operating cost are particularly important.
However, the research for optimizing distribution to micro-grid load at present is less, existing load optimized distribution model is base
Set up in the analysis result of historical data.That is, these modeling methods are merely by statistics or Probability
Method is analyzed historical data (energy characteristicses and micro-capacitance sensor demand), and the rule drawn according to analysis sets up optimization mould
Type.These methods had not both accounted for the influence that the change of outside environmental elements is exported to the energy, did not accounted for micro-capacitance sensor itself yet
The dynamic change of energy requirements, waste and the cost in turn resulting in resource is high.
The content of the invention
An object of the present invention is to provide a kind of energy dynamics dispatching party of the independent micro-capacitance sensor based on genetic algorithm
Method and equipment.
Another object of the present invention is to provide one kind to minimize production of energy cost, maximization energy storage system
Economic benefit and enhancing are to the independent micro-capacitance sensor dynamic dispatching method utilized of regenerative resource in independent micro-capacitance sensor.
According to an aspect of the present invention there is provided a kind of energy dynamics dispatching method of independent micro-capacitance sensor, independent micro-capacitance sensor can
Including a variety of distributed power generation sources and energy-storage system, a variety of distributed power generation sources may include that regenerative resource and tradition can assign list
Member, dynamic dispatching method may include following steps：S1：List can be assigned by obtaining the prediction data for dynamic dispatching and obtaining tradition
The essential information of member and energy-storage system；S2：Set up based on essential information and using intelligent optimization algorithm based on a variety of distributed hairs
The dynamic dispatching Optimized model of power supply；S3：Prediction data is input to dynamic dispatching Optimized model；S4：It is excellent according to dynamic dispatching
The output result for changing model carries out the energy dynamics scheduling of independent micro-capacitance sensor.
Embodiments in accordance with the present invention, the step of obtaining the prediction data for dynamic dispatching may include：Prediction is independent micro-
The load requirements data of power network at preset time intervals；Predict the generating data of regenerative resource at preset time intervals.
Embodiments in accordance with the present invention, obtain tradition can dispatch unit and energy-storage system essential information the step of can wrap
Include：Obtain tradition can dispatch unit cost function, power limit and start-up cost function；The charging of acquisition energy-storage system/put
Electrical power limit value and charged state.
Embodiments in accordance with the present invention, the step of predicting the load requirements data of independent micro-capacitance sensor at preset time intervals can
Including：Obtain history load requirements data, historical weather data and meteorological prediction data and be based on history load requirements data, go through
History weather data predicts the load requirements data of independent micro-capacitance sensor at preset time intervals with meteorological prediction data；Prediction can be again
The step of giving birth to the generating data of the energy at preset time intervals may include：Obtain history generating data, the history of regenerative resource
Weather data and meteorological prediction data simultaneously can be again to predict based on history generating data, historical weather data and meteorological prediction data
The generating data of the raw energy at preset time intervals.
Embodiments in accordance with the present invention, the energy of independent micro-capacitance sensor is carried out according to the output result of dynamic dispatching Optimized model
The step of dynamic dispatching, may include：To control tradition can the instruction of power output of dispatch unit and energy-storage system be separately sent to
Tradition can dispatch unit and energy-storage system.
Embodiments in accordance with the present invention, will control tradition can the instruction of power output of dispatch unit and energy-storage system distinguish
Being sent to tradition dispatch unit and can may include the step of energy-storage system：Continue to control tradition can dispatch unit and energy-storage system
The instruction of power output at preset time intervals be separately sent to tradition can dispatch unit and energy-storage system, with real time dynamic adjust
Whole tradition can dispatch unit and energy-storage system power output.
There is provided a kind of energy dynamics controlling equipment of independent micro-capacitance sensor, independent micro-capacitance sensor according to another aspect of the present invention
It may include a variety of distributed power generation sources and energy-storage system, a variety of distributed power generation sources may include that regenerative resource and tradition can assign
Unit, dynamic dispatching equipment may include：Information acquiring program module, obtains the prediction data for dynamic dispatching and obtains tradition
Can dispatch unit and energy-storage system essential information；Modeling program module, essential information simultaneously sets up base using intelligent optimization algorithm
Dynamic dispatching Optimized model in a variety of distributed power generation sources；Program module is inputted, prediction data dynamic dispatching is input to excellent
Change model；Scheduler module, is adjusted according to the energy dynamics that the output result of dynamic dispatching Optimized model carries out independent micro-capacitance sensor
Degree.
Embodiments in accordance with the present invention, information acquiring program module may include Prediction program module, and Prediction program module can
Predict the load requirements data of independent micro-capacitance sensor at preset time intervals, and predictable regenerative resource is at preset time intervals
Generating data.
Embodiments in accordance with the present invention, information acquiring program module may also include parameter retrieval process module, parameter acquiring
Program module can obtain tradition can dispatch unit cost function, power limit and start-up cost function, and energy storage system can be obtained
The charge/discharge power limit and charged state of system.
Embodiments in accordance with the present invention, Prediction program module can obtain history load requirements data, historical weather data and
Weather prognosis data simultaneously predict independent micro-capacitance sensor based on history load requirements data, historical weather data and meteorological prediction data
Load requirements data at preset time intervals；Prediction program module can obtain history generating data, the history of regenerative resource
Weather data and meteorological prediction data simultaneously can be again to predict based on history generating data, historical weather data and meteorological prediction data
The generating data of the raw energy at preset time intervals.
Embodiments in accordance with the present invention, scheduler module can by control tradition can dispatch unit and energy-storage system output
The instruction of power is separately sent to tradition can dispatch unit and energy-storage system.
Embodiments in accordance with the present invention, scheduler module it is sustainable will control tradition can dispatch unit and energy-storage system exist
The instruction of the power output of predetermined time interval be separately sent to tradition can dispatch unit and energy-storage system, with real time dynamic adjust
Tradition can dispatch unit and energy-storage system power output.
According to another aspect of the present invention there is provided a kind of computer-readable recording medium, on computer-readable recording medium
Have program stored therein or instruct, program or instruct by computing device when realize the above method.
According to another aspect of the present invention there is provided a kind of computer equipment, the computer equipment may include processor and deposit
Have program stored therein or instruct in reservoir, memory, described program or instruct by computing device when realize the above method.
Embodiments in accordance with the present invention, can quickly be received using the energy dynamics dispatching method of the independent micro-capacitance sensor of genetic algorithm
Hold back and obtain overall optimal solution.
Embodiments in accordance with the present invention, the daily energy in independent micro-capacitance sensor is realized by the foundation of dynamic dispatching Optimized model
Source production cost minimizes and strengthens the utilization rate of regenerative resource.
Brief description of the drawings
By the description with reference to accompanying drawing to the following examples, these and/or other side of the present invention and advantage will become
It must understand, and it is more readily appreciated that wherein：
Fig. 1 is the structural map of micro-capacitance sensor independent according to an embodiment of the invention；
Fig. 2 is the flow chart of the energy dynamics dispatching method of micro-capacitance sensor independent according to an embodiment of the invention；
Fig. 3 is the block diagram of the energy dynamics controlling equipment of micro-capacitance sensor independent according to an embodiment of the invention；
Fig. 4 is to show load requirements prediction according to an embodiment of the invention；
Fig. 5 is the generating prediction for showing wind-driven generator according to an embodiment of the invention；
Fig. 6 is the generating prediction for showing photovoltaic solar according to an embodiment of the invention；
Fig. 7 is the energy dynamics scheduling for being shown with genetic algorithm (GA)；
Fig. 8 is the charged state (SOC) for the lithium ion battery for being shown with genetic algorithm；
Fig. 9 is the energy dynamics scheduling for being shown with pattern search (PS)；
Figure 10 is the SOC for the lithium ion battery for being shown with pattern search (PS) acquisition；
Figure 11 is the contrast diagram of the production of energy cost for the dynamic dispatching for being shown with GA and PS.
Embodiment
Embodiments of the invention are described with reference to the accompanying drawings, in the accompanying drawings identical label indicates identical portion all the time
Part.
Micro-capacitance sensor is independent micro-capacitance sensor according to an embodiment of the invention, and it can not send electric power to main power network, can not
Electric power is received from main power network, therefore the load requirements of independent micro-capacitance sensor are met by local generate electricity.
During all working of independent micro-capacitance sensor, independent micro-capacitance sensor is estimated will to minimize production of energy cost and ensure can
The maximum utilization of the renewable sources of energy.
Fig. 1 is the structural map of micro-capacitance sensor independent according to an embodiment of the invention.
A variety of distributed power generation sources and energy-storage system (ESS) may include according to the independent micro-capacitance sensor of the present invention.
As shown in figure 1, may include a variety of distributed power generation sources (for example, renewable according to the independent micro-capacitance sensor 10 of the present invention
The energy 11 and tradition can dispatch units 12) and energy-storage system 17, regenerative resource 11 may include wind-driven generator (WT) 13 and light
Lie prostrate solar energy (PV) 14, tradition can dispatch unit 12 may include fuel cell (FC) 15 and diesel-driven generator (DE) 16.Energy storage system
System (ESS) can be lithium ion battery (Li-Icon).
Fig. 2 is the flow chart for the energy dynamics dispatching method for showing micro-capacitance sensor independent according to an embodiment of the invention.
As shown in Fig. 2 the energy dynamics dispatching method of micro-capacitance sensor independent according to an embodiment of the invention may include step
S1 to step S4.However, those skilled in the art knows multiple steps therein can be merged into a step, or it can omit
Part steps therein.For example, step S1 and step S2 can be merged, or step S3 and S4 can be merged.
In step sl, obtaining the prediction data for dynamic dispatching and obtain tradition can dispatch unit 12 and energy-storage system
17 essential information.Here, obtain for the prediction data of dynamic dispatching can prevent independent micro-capacitance sensor load requirements and can be again
Influence of the fluctuation of the generated energy of the raw energy to dynamic dispatching.
Specifically, the step of obtaining the prediction data for dynamic dispatching may include to predict independent micro-capacitance sensor in the scheduled time
The generating data of the load requirements data and/or prediction regenerative resource at interval at preset time intervals.
For example, can predict and (hereinafter referred to as predict) independent micro-capacitance sensor in particular schedule day (for example, one day) in advance a few days ago
Predetermined time interval (for example, per hour) load requirements data, regenerative resource also can be predicted in particular schedule day (example
Such as, one day) in predetermined time interval (for example, per hour) generating data.
Specifically, can be predicted the load requirements per hour a few days ago of independent micro-capacitance sensor, predictable tradition can dispatch unit day
Preceding generated energy per hour, for example, generated energy and the photovoltaic solar per hour a few days ago of predictable wind-driven generator is a few days ago every
Hour generated energy.
Embodiments in accordance with the present invention, can carry out above-mentioned prediction to overcome regenerative resource based on neural network algorithm
Influence of the fluctuation of generated energy and load requirements to scheduling.
Embodiments in accordance with the present invention, the step of predicting the load requirements data of independent micro-capacitance sensor at preset time intervals can
Including：Obtain history load requirements data, historical weather data and meteorological prediction data and be based on history load requirements data, go through
History weather data predicts the load requirements of independent micro-capacitance sensor at preset time intervals with meteorological prediction data.To make precision of prediction
It is higher, it will also can such as influence other data factors of the factor of industrial load distribution to take the above-mentioned prediction of progress into account.
For example, predetermined time interval (example of the independent micro-capacitance sensor in history in some scheduling day (for example, one day) can be obtained
Such as, 1h) load requirements data and the historical weather data and particular schedule to be scheduled day in some scheduling days
The meteorological data of (for example, one day), and predict the independent micro-capacitance sensor in the particular schedule to be scheduled day based on these data
Predetermined time interval load requirements data.
As described above, embodiments in accordance with the present invention, can be predicted independent micro-capacitance sensor in particular schedule to be scheduled day
The load requirements of predetermined time interval, so as to prevent load requirements fluctuation from causing the energy dissipation of independent micro-capacitance sensor.
In addition, independent micro-capacitance sensor includes regenerative resource, the energy dynamics dispatching method of embodiments of the invention can be maximum
Regenerative resource is utilized with limiting, to reduce the energy into production cost.
, can be to renewable energy in order to prevent the supply variation of regenerative resource from influenceing the energy dynamic dispatching of independent micro-capacitance sensor
The generating data in source are predicted.
Specifically, the step of predicting the generating data of regenerative resource at preset time intervals may include：Obtain renewable
History generating data, historical weather data and the meteorological prediction data of the energy are simultaneously based on history generating data, historical weather data
The generating data of regenerative resource at preset time intervals are predicted with meteorological prediction data.
For example, the regenerative resource that can obtain independent micro-capacitance sensor is pre- in some scheduling day (for example, one day) in history
Fix time interval (for example, 1h) generating data and it is described some scheduling days historical weather data and spy to be scheduled
The meteorological data of degree of setting the tone day (for example, one day), and predict that independent micro-capacitance sensor is to be scheduled specific at this based on these data
Dispatch the generating data of the predetermined time interval in day.
Although the application is using 1 hour (h) as time interval, it should be understood by those skilled in the art that may be selected other
Predetermined time interval as the application time interval.For example, 2h, 0.5h or 1.5h etc. may be selected as time interval, so that
In the specific day 24h (one day) dispatch of prediction often 2h, 0.5h or 1.5h load requirements, every 2h, 0.5h of regenerative resource or
1.5h generated energy.
In addition, obtained in step S1 the tradition can dispatch unit and the energy-storage system essential information the step of can wrap
Include obtain tradition can dispatch unit 12 cost function, power limit and start-up cost function and/or obtain the energy-storage system
17 charge/discharge power limit and charged state.
In step s 2, it can be set up based on above-mentioned essential information and using intelligent optimization algorithm based on a variety of distributed power generations
The dynamic dispatching Optimized model in source.
Here, the intelligent optimization algorithm can be genetic algorithm (GA), simulated annealing (SA), pattern search algorithm
(PS) etc., genetic algorithm has faster convergence rate and results in globally optimal solution, and utilization is detailed below
Genetic algorithm is set up dynamic optimization model and is compared with the scheduling result of pattern search algorithm.
In step s3, prediction data can be input to dynamic dispatching Optimized model.As described above, prediction data may include
Load requirements data, the generating data per hour of regenerative resource per hour.
In step s 4, the energy dynamics that independent micro-capacitance sensor can be carried out according to the output result of dynamic dispatching Optimized model are adjusted
Degree.
Below will using tradition can dispatch unit as fuel cell (FC) and diesel-driven generator (DE), regenerative resource is wind-force
Exemplified by generator (WT) and photovoltaic solar (PV), the energy dynamics dispatching method of the present invention is described in detail, but ability
The technical staff in domain knows, tradition can dispatch unit and regenerative resource may include other kinds of energy source.
For example, distributed power generation source and energy-storage system (for example, lithium ion battery (Li-Ion)) in independent micro-capacitance sensor
Power limit (essential information) can be as shown in table 1, and power unit is kW in table 1：
Table 1：DG initial capacity
In table 1, the power threshold of each distributed power generation source and energy-storage system (lithium ion battery) can be according to model
Difference and change, therefore it is contemplated that different factors and arbitrarily choose the capacity in distributed power generation source, power limit etc..Separately
Outside, the power of the Li-Icon batteries in table 1 is -200, and the Li-Icon battery charge power limit for representing this type are
200KW。
Embodiments in accordance with the present invention, can be predicted wind-driven generator and photovoltaic solar in particular schedule to be scheduled day
Predetermined time interval generating data.
For example, can be predicted according to history photovoltaic solar generating data, historical weather data and digital weather prediction model
Meteorological data predict the generated energy per hour a few days ago of photovoltaic solar.In addition, also can according to history wind-power electricity generation data, go through
History weather data and the meteorological data of digital weather prediction model prediction predict the generated energy per hour a few days ago of wind-driven generator.
During dynamic dispatching Optimized model is set up, mainly so that the production of energy cost minimization of independent micro-capacitance sensor
Change, the maximization of economic benefit of energy-storage system in micro-capacitance sensor and enhancing to such as wind-driven generator and photovoltaic solar can
The utilization rate of the renewable sources of energy is main purpose.In addition, it is also contemplated that service life of energy-storage system etc. sets up dynamic dispatching optimization
Model.
The object function of dynamic dispatching Optimized model is as follows according to an embodiment of the invention：
In formula 1.1, n is the quantity of the time interval in a scheduling day, and m represents that the tradition in micro-capacitance sensor can assign list
The quantity of first (for example, fuel cell (FC) and diesel-driven generator (DE)).
As shown in table 1, micro-capacitance sensor independent according to an embodiment of the invention may include a wind-driven generator (WT), three
Photovoltaic solar (PV), a fuel cell (FC), two diesel-driven generators (DE) and a lithium ion battery, wherein, wind
Power generator (WT) and photovoltaic solar (PC) are regenerative resource, and fuel cell (FC) and diesel-driven generator (DE) are that tradition can
Send subdivision.
However, various types of regenerative resources and tradition in embodiments of the invention not limited to this, independent micro-capacitance sensor
The quantity and species of subdivision can be sent to be needed to carry out any change according to the power supply of independent micro-capacitance sensor.
As described above, in an embodiment of the present invention, using 1h as time interval, and it is only according to an embodiment of the invention
Vertical micro-capacitance sensor includes a fuel cell (FC) and two diesel-driven generators (DE).In this case, n can be with for 24, m
For 3.
In addition, in formula 1.1, if i-th tradition can dispatch unit be in running status, τ in time ti(t)=1；
If for example, as tradition can dispatch unit the 1st diesel-driven generator (DE) in time t=3, in operation
State, then in τ1(3)=1.
If i-th tradition can dispatch unit be closed in time t, τi(t)=0；
Embodiments in accordance with the present invention, the cost function of fuel cell (FC) can be：
Fi(Pi(t))=bi.Pi(t)2+ciFormula 1.2
The cost function of diesel-driven generator (DE) can be：
Fi(Pi(t))=ai.Pi(t)2+bi.P(t)+ciFormula 1.3
Wherein, ai、biAnd ciCan be i-th of tradition in independent micro-capacitance sensor can dispatch unit cost function parameters,
SCi(t) can be i-th of tradition in independent micro-capacitance sensor can dispatch unit start-up cost function.
As an example, the cost function of fuel cell (FC) and diesel-driven generator (DE) is joined according to an embodiment of the invention
Number and start-up cost can be as shown in table 2：
Table 2 can assign DG cost function
Similarly, tradition can dispatch unit (for example, fuel cell (FC) and diesel-driven generator (DE)) cost function ginseng
Number and its start-up cost can change according to factors such as models, and the present invention only shows the selected tool of the present invention in an illustrative manner
Body tradition can dispatch unit design parameter, provide necessary condition for the data comparison that hereinafter carries out.
In formula 1.1, if τi(t)-τi(t-1)=1, then SCi(t)=sci；
Otherwise, SCi(t)=0,
Wherein, sciBe i-th tradition can dispatch unit start-up cost.For example, as shown in table 2, fuel cell (FC)
Start-up cost can be 18 dollars, and the cost of diesel-driven generator (DE) can be 23 dollars.
In other words, if i-th tradition can dispatch unit run in time t, and the off-duty in time t-1 then should
I-th tradition can dispatch unit need to consider its start-up cost in time t.In other words, if tradition can dispatch unit in list
From stopping being changed into starting in position time interval (for example, 1h), then need to consider the tradition can dispatch unit start-up cost.If
In unit interval, the tradition can the running status of dispatch unit do not change, then do not consider that the tradition can assign list
The start-up cost of member.
In addition, it is necessary to, it is noted that in view of regenerative resource and the cost of energy-storage system (for example, cost of electricity-generating) and startup
Cost (for example, maintenance cost) is relatively small, therefore in an embodiment of the present invention, does not consider regenerative resource and energy-storage system
Relevant cost.On the contrary, embodiments in accordance with the present invention, consider the energy storage economic benefit and energy-storage system of energy-storage system in addition
Service life etc..
Following constraints can be had according to the object function of the dynamic dispatching Optimized model of the present invention：
For example, i-th tradition can dispatch unit can meet following condition in time t power output：
Pi min≤Pi(t)≤Pi maxFormula 1.4
Wherein, Pi(t) be i-th tradition can dispatch unit in time t power output, Pi min、Pi maxRespectively i-th
Tradition can dispatch unit time t power output minimum value and maximum.Above-mentioned minimum value and maximum can be according to advance
The essential information (as shown in table 1) of acquisition and obtain.
In addition, following condition is met between load requirements and generated output according to an embodiment of the invention：
By above-mentioned constraints, the utilization rate of the wind-driven generator and photovoltaic solar as regenerative resource can be made
Farthest utilized.
The power output P of energy-storage system (for example, lithium ion battery) charge/discharge according to an embodiment of the inventioness
(t) following condition can be met：
Wherein, Pess(t) ＞ 0, represents energy-storage system in electric discharge；
Pess(t) ＜ 0, represents energy-storage system in charging；
Pess(t) energy-storage system un-activation or off-duty=0, are represented,
Wherein, Pload(t)、PwindAnd P (t)pv(t) load requirements in time t, the wind-driven generator of prediction are represented respectively
Generated output and photovoltaic solar generated output.
In the case where energy-storage system is lithium ion battery,The 20% of maximum energy storage can be approximately equal to.That is, energy storage system
The minimum value of the charged state of system can be 20%.
To ensure the service life of energy-storage system, the dynamic operation performance of the energy-storage system can also meet following two bars
Part：
SOCmin≤SOC(t+1)≤SOCmaxFormula 1.8
Wherein, ηtIt is the charge or discharge efficiency of energy-storage system (for example, lithium ion battery), CessRepresent energy-storage system
Rated capacity, SOC (t) represents charged state of the energy-storage system in time t.SOCmaxRepresent the charged state of energy-storage system most
Big value, SOCminRepresent the minimum value of the charged state of energy-storage system.For example, SOCminCan be 20%, SOCmaxCan be
100%.
When prediction data is input to dynamic dispatching Optimized model by step S3, the dynamic dispatching Optimized model is exportable more
Individual result, the result may include tradition can dispatch unit exert oneself (for example, power output) and energy-storage system (ESS) output work
Rate and its charged state, i.e. the P of exportable fuel cell (FC) and diesel-driven generator (DE)i(t), the output work of energy-storage system
Rate PessAnd SOC (t) (t).
The energy dynamics for carrying out independent micro-capacitance sensor according to the output result of dynamic dispatching Optimized model in step S4 are dispatched
The step of may include：To control tradition can the instruction of power output of dispatch unit and energy-storage system be separately sent to tradition and can divide
Distribute leaflets member and energy-storage system.
Specifically, by control tradition can dispatch unit and energy-storage system power output instruction be separately sent to tradition can
The step of dispatch unit and energy-storage system, may include：Continue will control tradition can dispatch unit and energy-storage system between the scheduled time
Every power output instruction be separately sent to tradition can dispatch unit and energy-storage system, with real time dynamic adjustment tradition can assign
The power output of unit and energy-storage system.
For example, sustainably will with tradition can dispatch unit and energy-storage system to be scheduled intraday hourly defeated
Go out the corresponding instruction of power be separately sent to the tradition can dispatch unit and energy-storage system.
Embodiments in accordance with the present invention, can be based between the scheduled time in particular schedule to be scheduled day (for example, one day)
Realized every the load requirements prediction data of (for example, per hour) and the generating prediction data of regenerative resource in independent micro-capacitance sensor
Energy dynamic dispatching.
For example, can be based on loading prediction data hourly, the generating prediction data of regenerative resource come constantly to only
Vertical micro-capacitance sensor carries out energy dynamic dispatching (for example, dispatching per hour once) to reach the mesh of production of energy cost minimization
's.
Fig. 3 is the block diagram for the energy dynamics controlling equipment for showing micro-capacitance sensor independent according to an embodiment of the invention.
As shown in figure 3, the dynamic dispatching equipment 30 of the independent micro-capacitance sensor of micro-capacitance sensor can be wrapped according to an embodiment of the invention
Include information acquiring program module 40, modeling program module 50, input program module 60 and scheduler module 70.Acquisition of information journey
Sequence module 40 can obtain the prediction data for dynamic dispatching and obtain tradition can dispatch unit and energy-storage system essential information,
Modeling program module 50 can set up the dynamic based on a variety of distributed power generation sources based on essential information and using intelligent optimization algorithm
Prediction data can be input to dynamic dispatching Optimized model, scheduler module 70 by Scheduling Optimization Model, input program module 60
The energy dynamics that independent micro-capacitance sensor can be carried out according to the output result of dynamic dispatching Optimized model are dispatched.
In addition, as shown in figure 3, information acquiring program module 40 may include Prediction program module 41 and parameter retrieval process mould
The load requirements data of independent micro-capacitance sensor at preset time intervals can be predicted in block 42, Prediction program module 41, and predict renewable
The generating data of the energy at preset time intervals, parameter retrieval process module 42 can obtain tradition can dispatch unit cost letter
Number, power limit and start-up cost function, and the charge/discharge power limit and charged state of energy-storage system can be obtained.
Prediction program module 41 can obtain history load requirements data, historical weather data and meteorological prediction data and be based on
History load requirements data, historical weather data and meteorological prediction data predict the load of independent micro-capacitance sensor at preset time intervals
Lotus demand data.
Prediction program module 41 can obtain history generating data, historical weather data and the weather prognosis number of regenerative resource
Predict regenerative resource at preset time intervals according to and based on history generating data, historical weather data and meteorological prediction data
Generating data.
In addition, scheduler module 70 can by control tradition can dispatch unit and energy-storage system power output instruction point
Not being sent to tradition can dispatch unit and energy-storage system.Specifically, scheduler module is sustainable can assign list by control tradition
Member and the power output of energy-storage system at preset time intervals instruction be separately sent to tradition can dispatch unit and energy-storage system,
With the tradition of dynamic adjustment in real time can dispatch unit and energy-storage system power output.
In addition, the dynamic dispatching Optimized model of the energy dynamics controlling equipment of independent micro-capacitance sensor and above-mentioned dynamic dispatching method
Described in Optimized model it is identical, will not be repeated here.
Load requirements prediction, wind-power electricity generation prediction and photovoltaic solar are described below in conjunction with Fig. 4 to Fig. 6 to generate electricity and predict.
Fig. 4 is to show load requirements prediction according to an embodiment of the invention, and Fig. 5 is to show embodiments in accordance with the present invention
Wind-power electricity generation prediction, Fig. 6 be show photovoltaic solar according to an embodiment of the invention generating prediction.
As described above, embodiments in accordance with the present invention, can be based on history load requirements data, historical weather data, meteorology
Prediction data (can be predicted by digital weather prediction model) and/or other data factors of the industrial load distribution of influence utilize nerve
Network algorithm predicts a few days ago load requirements per hour.Embodiments in accordance with the present invention, can be predicted the load per hour in future 24h
Lotus demand, can disposably predict the load requirements per hour in following 24h, also with the passage of time, one is predicted per hour
Secondary load requirements.
As shown in figure 4, in micro-capacitance sensor independent according to an embodiment of the invention, within 1am-7am period, per small
When load requirements it is of a relatively high, and within 7am-24pm period, load requirements are relatively low per hour.
Specifically, as 3≤t≤4, the load requirements in independent micro-capacitance sensor are maximum, are approximately equal to 1300KW, when 7≤t≤
When 8, the load requirements of independent micro-capacitance sensor are minimum, are approximately equal to 300KW.
As shown in figure 5, in the region residing for micro-capacitance sensor independent according to an embodiment of the invention, in 1am-7am time
Wind energy is more sufficient in section, within 7am to 24pm period, wind energy relative deficiency.
When wind energy is more sufficient, wind energy is stored for the confession of the period of wind energy relative deficiency using energy-storage system
Electricity, if energy-storage system is fully charged in time t and wind energy still has surplus, can be such that charging dumps and test load.
As shown in figure 5, as 3≤t≤4, the wind-power electricity generation amount of independent micro-capacitance sensor is maximum, is approximately equal to 1400KW, in 7≤t
In≤24 period, wind-power electricity generation amount is substantially zeroed.
In the region residing for micro-capacitance sensor independent according to an embodiment of the invention, photovoltaic solar in 1am-7am period
Can be not enough, within 13pm to 16pm period, photovoltaic solar is more sufficient.
As shown in fig. 6, in the case of 1≤t≤7 and 19≤t≤24, the generated output that photovoltaic solar generates electricity is (i.e.,
Power output) it is substantially zeroed, when the generated output that in the period of 13≤t≤14, photovoltaic solar generates electricity is maximum.
Fig. 7 is the energy dynamics scheduling for being shown with genetic algorithm, and Fig. 8 is that the lithium battery for being shown with genetic algorithm fills
Electricity condition (SOC).
As shown in figure 8, in the case of 1≤t≤7, the power of lithium ion battery is less than zero, shows that lithium ion battery is in
Charged state, the power supply of regenerative resource is enough to provide the load requirements in independent micro-capacitance sensor, and unnecessary rechargeable energy can quilt
It is stored in energy-storage system (for example, lithium ion battery).
In 12≤t, lithium ion battery is stopped power supply, within the period of 7≤t≤8, fuel cell (FC) and diesel oil hair
Motor (DE) startup optimization, and as tradition can dispatch unit be whole micro-capacitance sensor power.
Specifically, as shown in figure 8, in the first six hour, mostly wind turbine power generation, being generated electricity without photovoltaic solar,
In this period, wind-driven generator fully supplies load requirements, and the lithium ion battery in minimum SOC (20%) is filled
Electricity, and all tradition can dispatch unit (zero energy) is closed to minimize fuel cost.
Energy-storage system (lithium ion battery) persistently charging (negative power as shown in Figure 7), and as shown in FIG. 8,
6am reaches its maximum storage capacity (maximums of 800kwh or 100% SOC), and it charge power vanishing (off-duty or
Un-activation).
In order to which the energy dynamics dispatching method to the application is compared analysis, to be moved using PS (searching for generally) energy
State dispatching method is used as comparison other.
Fig. 9 is the energy dynamics scheduling for being shown with pattern search (PS), and Figure 10 is the lithium ion for being shown with PS acquisitions
The SOC of battery.Figure 11 is the contrast diagram of the production of energy cost for the dynamic dispatching for being shown with GA and PS.
As shown in figure 9, using the dynamic dispatching for searching for (PS) generally, within the period of 12≤t≤24, fuel cell
(FC) power output is substantially zeroed, within the period, is powered by diesel-driven generator (DE).
As shown in Figure 10, using the SOC minimum values for the lithium ion battery for searching for (PS) acquisition generally 30% or so, it is impossible to
Make the energy storage maximization of economic benefit of lithium ion battery.
In addition, as shown in figure 11, using GA dynamic dispatching almost in production of energy cost interior per hour all than using
The production of energy cost of PS scheduling is low.
Specifically, can be as shown in table 3 using GA and PS production of energy cost：
Table 3 using GA and PS the energy into production Cost comparisons
As shown in table 3, PS production of energy cost per hour is used using the GA cost of production of energy per hour average specific
Low 7 dollars or so.
Also, the time spent by the dynamic dispatching calculated using GA and PS is also different.Specifically, table 4 gives
Matlab/Simulink simulated environment (uses Intel (R) core (TM i5-5200 CPU, 2.20GHz processors, 4GB
RAM, 64 bit manipulation component computers) use the total evaluation time spent by two kinds of method for optimizing scheduling.
The GA of the table 4 and PS calculating time (for 24 hours scheduling simulations in advance)
| Optimized algorithm | Amount to evaluation time (second) |
| GA | 1.6824 |
| PS | 3.9452 |
As shown in superincumbent table 4, compared with the scheduling based on PS, the dynamic dispatching based on GA is in a short period of time
Just have been carried out distribution, the dynamic dispatching fast convergence rate based on GA.That is, the dynamic dispatching based on GA can be realized more
The good dynamic dispatching become more meticulous, disclosure satisfy that the prediction dynamic dispatching of hour level, ensures the pre- timing in setting to greatest extent
Between be spaced in obtain optimal solution in global scope, and then the energy dynamics adjustment to independent micro-capacitance sensor is completed, to cause independence
Production of energy cost minimization in micro-capacitance sensor, strengthens the utilization rate of regenerative resource.
In addition, above-mentioned dynamic dispatching method can be written as computer program or instruction, the program or instruction can be stored
In computer-readable recording medium, the program or instruct by computing device when can realize the dynamic dispatching method.
Embodiments in accordance with the present invention, may also provide above computer readable storage medium storing program for executing and computer equipment, the meter
Calculating machine equipment includes to have program stored therein or instructing in processor and memory, memory, and described program or instruction are by processor
The above method is realized during execution.
Embodiments in accordance with the present invention, using genetic algorithm independent micro-capacitance sensor dynamic dispatching method can Fast Convergent simultaneously
Obtain overall optimal solution.
Embodiments in accordance with the present invention, for the prediction of data a few days ago, it is possible to decrease the supply variation of regenerative resource and load
The fluctuation of lotus demand and the influence produced.
Embodiments in accordance with the present invention, the daily energy in independent micro-capacitance sensor is realized by the foundation of dynamic dispatching Optimized model
Source production cost is minimized, energy-storage system economic benefit maximizes and strengthens the utilization rate of regenerative resource.
The preferred embodiment of the present invention is the foregoing is only, but protection scope of the present invention is not limited thereto, it is any
Those familiar with the art the invention discloses technical scope in the change or replacement that are readily apparent that, should all cover
Within protection scope of the present invention.Therefore, protection scope of the present invention should be based on the protection scope of the described claims.
Claims (14)
1. a kind of energy dynamics dispatching method of independent micro-capacitance sensor, it is characterised in that the independent micro-capacitance sensor includes a variety of distributions
Formula energy source and energy-storage system, a variety of distributed power generation sources include regenerative resource and tradition can dispatch unit, it is described dynamic
State dispatching method comprises the following steps：
S1：Obtain the prediction data for dynamic dispatching and obtain the tradition can dispatch unit and the energy-storage system it is basic
Information；
S2：Based on the essential information and the dynamic based on a variety of distributed power generation sources is set up using intelligent optimization algorithm to adjust
Spend Optimized model；
S3：The prediction data is input to the dynamic dispatching Optimized model；
S4：The energy dynamics scheduling of the independent micro-capacitance sensor is carried out according to the output result of the dynamic dispatching Optimized model.
2. energy dynamics dispatching method according to claim 1, it is characterised in that
It is described obtain for dynamic dispatching prediction data the step of include：Predict the independent micro-capacitance sensor at preset time intervals
Load requirements data；Predict the generating data of the regenerative resource at preset time intervals.
3. energy dynamics dispatching method according to claim 2, it is characterised in that
It is described obtain the tradition can dispatch unit and the energy-storage system essential information the step of include：Obtain the tradition
Can dispatch unit cost function, power limit and start-up cost function；Obtain the charge/discharge power limit of the energy-storage system
Value and charged state.
4. energy dynamics dispatching method according to claim 2, it is characterised in that
The step of prediction independent micro-capacitance sensor load requirements data at preset time intervals, includes：Obtain history load
Demand data, historical weather data and meteorological prediction data are simultaneously based on the history load requirements data, the weather history number
Load requirements data of the independent micro-capacitance sensor in the predetermined time interval are predicted according to the weather prognosis data；
The step of prediction regenerative resource generating data at preset time intervals, includes：Obtain the renewable energy
History generating data, historical weather data and the meteorological prediction data in source are simultaneously based on the history generating data, weather history number
Generating data of the regenerative resource in the predetermined time interval are predicted according to the weather prognosis data.
5. the energy dynamics dispatching method according to any one of claim 1-4, it is characterised in that
What the energy dynamics for carrying out the independent micro-capacitance sensor according to the output result of the dynamic dispatching Optimized model were dispatched
Step includes：By control the tradition can dispatch unit and the energy-storage system power output instruction be separately sent to it is described
Tradition can dispatch unit and the energy-storage system.
6. energy dynamics dispatching method according to claim 5, it is characterised in that
It is described by control the tradition can dispatch unit and the energy-storage system power output instruction be separately sent to it is described
Tradition dispatch unit and can include the step of the energy-storage system：It will persistently control the tradition can dispatch unit and the energy storage
The instruction of the power output of system at preset time intervals be separately sent to the tradition can dispatch unit and the energy-storage system,
With dynamic in real time adjust the tradition can dispatch unit and the energy-storage system power output.
7. a kind of energy dynamics controlling equipment of independent micro-capacitance sensor, it is characterised in that the independent micro-capacitance sensor includes a variety of distributions
Formula energy source and energy-storage system, a variety of distributed power generation sources include regenerative resource and tradition can dispatch unit, it is described dynamic
State controlling equipment includes：
Information acquiring program module, obtaining the prediction data for dynamic dispatching and obtain the tradition can dispatch unit and described
The essential information of energy-storage system；
Modeling program module, is set up based on the essential information and using intelligent optimization algorithm and is based on a variety of distributed power generations
The dynamic dispatching Optimized model in source；
Program module is inputted, the prediction data is input to the dynamic dispatching Optimized model；
Scheduler module, is moved according to the energy that the output result of the dynamic dispatching Optimized model carries out the independent micro-capacitance sensor
State is dispatched.
8. energy dynamics controlling equipment according to claim 7, it is characterised in that
Described information, which obtains program module, includes Prediction program module, and the Prediction program module predicts that the independent micro-capacitance sensor exists
The load requirements data of predetermined time interval, and predict the generating data of the regenerative resource at preset time intervals.
9. energy dynamics controlling equipment according to claim 8, it is characterised in that
Described information, which obtains program module, also includes parameter retrieval process module, and the parameter retrieval process module obtains described pass
System can dispatch unit cost function, power limit and start-up cost function, and obtain the charge/discharge work(of the energy-storage system
Rate limit value and charged state.
10. energy dynamics controlling equipment according to claim 8, it is characterised in that
The Prediction program module obtains history load requirements data, historical weather data and meteorological prediction data and based on described
History load requirements data, the historical weather data and the weather prognosis data predict the independent micro-capacitance sensor described
The load requirements data of predetermined time interval；
The Prediction program module obtains history generating data, historical weather data and the weather prognosis number of the regenerative resource
Predict that the regenerative resource exists according to and based on the history generating data, historical weather data and the weather prognosis data
The generating data of the predetermined time interval.
11. the energy dynamics controlling equipment according to any one of claim 7 to 10, it is characterised in that
The scheduler module by control the tradition can dispatch unit and the energy-storage system power output instruction point
Not being sent to the tradition can dispatch unit and the energy-storage system.
12. energy dynamics controlling equipment according to claim 11, it is characterised in that
The scheduler module will persistently control the tradition can dispatch unit and the energy-storage system at preset time intervals
Power output instruction be separately sent to the tradition can dispatch unit and the energy-storage system, it is described with dynamic adjustment in real time
Tradition can dispatch unit and the energy-storage system power output.
13. have program stored therein or instruct on a kind of computer-readable recording medium, the computer-readable recording medium, its feature
It is, the method according to claim any one of 1-6 is realized when described program or instruction are as computing device.
14. have program stored therein or instruct in a kind of computer equipment, including processor and memory, memory, it is characterised in that
The method according to claim any one of 1-6 is realized when described program or instruction are as computing device.
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