CN107565585B - Energy storage device peak regulation report-back time prediction technique and its model creation method - Google Patents
Energy storage device peak regulation report-back time prediction technique and its model creation method Download PDFInfo
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Abstract
The invention discloses a kind of energy storage device peak regulation report-back time prediction technique and its model creation methods, first multiple groups historical load data of the acquisition from multiple users, and establish electricity model, earnings pattern and the charge-discharge electric power constraint of energy storage device；Go out the operation reserve of energy storage device time acquired in each group historical load data by energy storage algorithm simulation；Simulation calculation goes out the energy storage device peak regulation report-back time under each group historical load data；The energy storage device peak regulation report-back time being finally directed under each group historical load data and each user's history load data is fitted calculating, gets energy storage device peak regulation report-back time prediction model；The method of the present invention can fast and accurately get energy storage device peak regulation report-back time prediction model, and creation obtains energy storage device peak regulation report-back time prediction model and can be realized the accurate prediction of energy storage device peak regulation report-back time, play the role of encouraging people using energy storage device, improves electric energy social benefit.
Description
Technical field
The present invention relates to a kind of power peak regulation technical field, in particular to a kind of energy storage device peak regulation report-back time prediction side
Method and its model creation method.
Background technique
Currently, China's electricity market carries out time-of-use tariffs system, i.e. Utilities Electric Co. determines peak valley according to network load characteristic
Period carries out the electricity price regulation of different electricity prices in peak of power consumption and low ebb period.In low ebb and improving electricity price in peak period
Phase lowers the means of electricity price to promote user to take corresponding measure, alleviates peak phase shortage of electric power situation, improves society's effect of electric energy
Benefit.
Battery energy storage device can realize demand side management in user side, and pass through Load Regulation effectively smooth load, subtract
Small peak load is poor, lowers user's purchases strategies, changes but also as emergency standby power in enhancing customer power supply reliability
The scheduling of electricity consumption is horizontal, improves power quality etc. and is of great significance.But since the development of current energy storage technology is limited,
Cost is higher, and in the case where unknown energy storage device return benefit clearly can not return the time limit, most of user is not take into account that
Use energy storage device.These factors are unfavorable for the application and popularization of energy storage technology at home.
Therefore, it is necessary in conjunction with domestic electricity price regulation, provide one in the case where fully considering battery energy storage device economy
The effective energy storage peak shaving of kind returns time limit prediction technique, and the people that encourages investment attempts to use energy storage device, promotes the hair of energy storage technology
The developing of exhibition and energy storage market.
Summary of the invention
The first object of the present invention is the shortcomings that overcoming the prior art and deficiency, provides a kind of fast and accurately energy storage
Device peak regulation report-back time prediction model creation method is predicted by the energy storage device peak regulation report-back time that this method creates
Model can be realized the accurate prediction of energy storage device peak regulation report-back time, plays and encourages people using energy storage device, is effectively relieved
Power grid peak time Voltage force, and improve the effect of electric energy social benefit.
The second object of the present invention is to provide a kind of energy storage device peak regulation report-back time prediction technique, and this method passes through upper
Energy storage device peak regulation report-back time prediction model is stated to predict energy storage device peak regulation report-back time fast and accurately.
The first object of the present invention is achieved through the following technical solutions: a kind of energy storage device peak regulation report-back time prediction model
Creation method, steps are as follows:
Step S1, multiple user sides are directed to, obtain multiple groups historical load data respectively；The electricity of energy storage device is established simultaneously
Measure model, earnings pattern and charge-discharge electric power constraint；
Step S2, according to the electricity model of the step S1 each group historical load data and energy storage device got and charge and discharge
Electrical power constraint, the operation reserve of energy storage device time acquired in each group historical load data is gone out by energy storage algorithm simulation；
Step S3, the time acquired in each group historical load data in conjunction with the earnings pattern of energy storage device and energy storage device
Operation reserve, simulation calculation goes out the energy storage device peak regulation report-back time under each group historical load data；
Step S4, it is directed under each group historical load data and the calculated each user's history load data of step S3
Energy storage device peak regulation report-back time is fitted calculating, obtains between historical load data and energy storage device peak regulation report-back time
Fitting function relationship gets energy storage device peak regulation report-back time prediction model:
Y=β1x1+β2x2+β3x3+...+βnxn+u；
Wherein x1To xnFor the 1st to the n kind data for including in historical load data, y is energy storage device peak regulation report-back time,
β1To βnFor fitting coefficient, u is distracter.
It preferably, include following several data: user side in every group of historical load data of acquisition in the step S1
The peak-to-average ratio of the load factor of daily load, the peak-to-valley ratio of user side daily load and user side daily load；Every group of historical load data
Continue test in more days by user side to acquire.
Preferably, the electricity model for the energy storage device established in the step S1 refers to the electricity model of any moment；
Wherein when energy storage device charges, the electricity model of any moment are as follows:
Et+1=Et-ηCPt+1(Pt<0)；
Wherein when energy storage device discharges, the electricity model of any moment are as follows:
Et+1=Et-1/ηDPt+1(Pt>0)；
Wherein:
Et+1For the energy storage amount of t+1 moment energy storage device；
EtFor the energy storage amount of t moment energy storage device；
Work as Pt+1When < 0, i.e., when energy storage device charges, then Pt+1For t moment to the average input work of t+1 moment energy storage device
Rate；
Work as Pt+1When > 0, i.e., when energy storage device discharges, then Pt+1For t moment to the average output work of t+1 moment energy storage device
Rate；
ηCFor the charge efficiency of energy storage device；
ηDFor the discharging efficiency of energy storage device.
Preferably, the earnings pattern for the energy storage device established in the step S1 are as follows:
Wherein
V is the day income that energy storage device carries out peak load shifting；
Work as PtWhen > 0, PtFor the t-1 moment to the average output power of t moment energy storage device；
Work as PtWhen < 0, PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；
etFor the average electricity price at t-1 moment to t moment, the time wherein differed between t-1 moment and t moment is 1 small
When.
Preferably, the charge-discharge electric power constraint of energy storage device is as follows in the step S1:
-Pmax≤Pt≤Pmax；
Wherein:
Work as PtWhen < 0, i.e., when energy storage device charges, then PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；
Work as PtWhen > 0, i.e., when energy storage device discharges, then PtFor the t-1 moment to the average output power of t moment energy storage device；
PmaxIt is the greatest physical transimission power of energy storage device.
Preferably, in the step S2, it is directed to every group of historical load data, energy storage device is gone out by energy storage algorithm simulation
The operation reserve of the time acquired in this group of historical load data are as follows: simulation energy storage device is acquired in this group of historical load data
Each period of each electricity peak period of time discharges by certain power, simulates energy storage device in this group of historical load
Each period in each low power consumption period of time acquired in data charges by certain power；
Wherein, it is directed to each period of each electricity peak period, the energy storage device of simulation is in the electricity peak period
The discharge power determination process of the period is as follows:
The electricity consumption of user's period in the electricity peak period, while basis are obtained according to this group of historical load data
The electricity model of energy storage device obtains electricity of the energy storage device of simulation when entering the electricity peak period, then calculates depanning
Electricity when it is entered the electricity peak period by quasi- energy storage device discharges required mean power in the electricity peak period
P；Finally the electricity consumption of user's period in the electricity peak period is compared with above-mentioned mean power P respectively；
If the former is greater than the latter, the energy storage device simulated discharge power of the period and flat in the electricity peak period
Equal power P is identical；I.e.Wherein it isFor simulation energy storage device i-th in j-th of electricity peak period
The discharge power of a period；
If the former is less than or equal to the latter, the discharge power of the energy storage device simulated period in the electricity peak period
It is identical as the electricity consumption of user's period in the electricity peak period, i.e.,WhereinFor according to historical load
The electricity consumption of the user that data acquisition arrives i-th of period in j-th of electricity peak period, that is, the energy storage device simulated is in jth
The discharge power of i-th of period in a electricity peak periodWith the user that is got according to historical load data at j-th
The electricity consumption of i-th of period in electricity peak periodIt is identical；
Wherein, it is directed to each period in each low power consumption period, the energy storage device of simulation is in the low power consumption period
The charge power determination process of the period is as follows:
The electricity consumption of user's period within the low power consumption period, while basis are obtained according to this group of historical load data
The electricity model of energy storage device obtains electricity of the energy storage device of simulation when entering the low power consumption period, then calculates depanning
Electricity when it is entered the low ebb period by quasi- energy storage device is full of required mean power P ' in the low power consumption period；Most
The electricity consumption of user's period within the low power consumption period is subjected to following compare afterwards；
If the electricity consumption of user's period within the low power consumption period is more than or equal to maximum electricity consumption threshold value S, simulate
Energy storage device within the low power consumption period charge power of the period be zero, i.e.,WhereinFor
The charge power of energy storage device i-th period within j-th of low power consumption period；
If user is more than or equal to maximum electricity consumption threshold after the electricity consumption of the period is added with P ' within the low power consumption period
Value S, the then charge power of the energy storage device simulated period within the low power consumption period are that S subtracts user in the low power consumption
The electricity consumption of the period in period, i.e.,WhereinFor the use got according to historical load data
The electricity consumption of family i-th of period within j-th of low power consumption period, that is, the energy storage device simulated is j-th of low power consumption period
The charge power of interior i-th of periodFor the electricity consumption of S i-th of period that subtract user within j-th of low power consumption period
If user is less than maximum electricity consumption threshold value S after the electricity consumption of the period is added with P ' within the low power consumption period,
The charge power of the energy storage device then simulated period within the low power consumption period is identical as mean power P '.
Preferably, in the step S3, the energy storage device peak regulation report-back time under each group historical load data is calculated
Detailed process is as follows:
Step S31, first against in every group of historical load data, the time acquired in this group of historical load data is subjected to week
Phase divides, and then according to the operation reserve of the energy storage device of simulation time acquired in this group of historical load data, passes through energy storage
Successively simulation calculation goes out net profit of the energy storage device in each period under this group of historical load data to the earnings pattern of device, wherein
The net profit in each period are as follows:
Net profit of the energy storage device k-th of period under this group of historical load data that wherein V (k) goes out for simulation calculation；
Vn(k) m day net profit of the energy storage device k-th of period under this group of historical load data gone out for simulation calculation；C (k) is
The punitive electricity charge of the energy storage device k-th of period under this group of historical load data that simulation calculation goes out；M be each period include
Number of days；X is the total number of cycles being divided into the time acquired in this group of historical load data；
Wherein Vm(k) are as follows:
Wherein
WhenWhen,For this group of historical load data Imitating energy storage device at m days of k-th of period
The t-1 moment to t moment average output power；
WhenWhen,For this group of historical load data Imitating energy storage device at m days of k-th of period
The t-1 moment to t moment Mean Input Power；
For this group of historical load data Imitating energy storage device k-th of period m days t-1 moment extremely
The average electricity price of t moment；
Wherein C (k) is obtained in the following manner:
Maximum electricity consumption of the energy storage device of this group of historical load data Imitating within k-th of period is obtained firstThen it is compared with maximum electricity consumption threshold value S；IfThenS)*2*；IfThen C (k)=0；
Step S32, the net profit by energy storage device under this group of historical load data in the preceding x period is added, and is obtained
Net profit summation Sumx, subsequently into step S33；Wherein:
Step S33, the net profit summation Sum that judgment step S32 is gotxWhether the cost of energy storage device is more than or equal to
Cost；
If it is not, returning to step S32 after the current value of x is then added 1；
If so, the number of days that the current value of x is recorded, and is obtained after the current value of x is multiplied with M as
Energy storage device peak regulation report-back time under historical load data.
Further, 30 M.
The second object of the present invention is achieved through the following technical solutions: a kind of energy storage device peak regulation report-back time prediction side
Method, steps are as follows:
Step B1, first against installing energy storage device in plan or having installed the user side of energy storage device, obtaining should
One group of historical load data of user side；
Step B2, it according to the one group of historical load data got in step B1, is obtained by the step S4 of claim 1
Following energy storage device peak regulation report-back time prediction model, the peak regulation report-back time of energy storage device is calculated；
Y=β1x1+β2x2+β3x3+...+βnxn+u；
Wherein x1To xnThe the 1st to the n kind data in one group of historical load data got for step B1, y is energy storage device
Peak regulation report-back time, β1To βnFor fitting coefficient, u is distracter.
It preferably, include following several data: load factor, the user side of user side daily load in the historical load data
The peak-to-valley ratio of daily load and the peak-to-average ratio of user side daily load；Every group of historical load data is continued to test for more days by user side
It acquires.
The present invention has the following advantages and effects with respect to the prior art:
(1) energy storage device peak regulation report-back time prediction model creation method of the present invention is obtained from multiple users' first
Multiple groups historical load data, and establish electricity model, earnings pattern and the charge-discharge electric power constraint of energy storage device；Then root
It is constrained according to the electricity model and charge-discharge electric power of each group historical load data and energy storage device, goes out to store up by energy storage algorithm simulation
The operation reserve of energy device time acquired in each group historical load data；Then in conjunction with the earnings pattern of energy storage device and storage
The operation reserve of energy device time acquired in each group historical load data, simulation calculation go out the storage under each group historical load data
It can device peak regulation report-back time；Finally it is directed to each group historical load data and the above-mentioned each user's history load number simulated
Energy storage device peak regulation report-back time under is fitted calculating, gets energy storage device peak regulation report-back time prediction model；This
Inventive method can fast and accurately get energy storage device peak regulation report-back time prediction model, and the present invention creates to obtain
Energy storage device peak regulation report-back time prediction model can be realized the accurate prediction of energy storage device peak regulation report-back time, play encouragement
People use energy storage device, power grid peak time Voltage force are effectively relieved, and improve the effect of electric energy social benefit.
(2) energy storage device peak regulation report-back time prediction technique of the present invention is first against in plan installation energy storage device or
Through installing the user side of energy storage device, one group of historical load data of the user side is obtained；Then by this group of historical load data
The energy storage device peak regulation created for the above-mentioned energy storage device peak regulation report-back time prediction model creation method of the people present invention returns
Call time prediction model, and the method for the present invention can predict fast and accurately energy storage device peak regulation report-back time.
Detailed description of the invention
Fig. 1 is energy storage device peak regulation report-back time prediction model creation method of the present invention.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited
In this.
Embodiment 1
A kind of energy storage device peak regulation report-back time prediction model creation method is also disclosed in the present embodiment, as shown in Figure 1, step
It is as follows:
Step S1, multiple user sides are directed to, obtain multiple groups historical load data respectively；The electricity of energy storage device is established simultaneously
Measure model, earnings pattern and charge-discharge electric power constraint；Wherein every group of historical load data is continued to test for more days by user side
It acquires, and includes a variety of factor datas for influencing energy storage device peak regulation report-back time in every group of historical load data.?
It include following several factors for influencing energy storage device peak regulation report-back time in the present embodiment, in every group of historical load data of acquisition
Data: the peak-to-average ratio of the load factor of user side daily load, the peak-to-valley ratio of user side daily load and user side daily load；
In the present embodiment, the electricity model of the energy storage device of above-mentioned foundation refers to the electricity model of any moment；
Wherein when energy storage device charges, the electricity model of any moment are as follows:
Et+1=Et-ηCPt+1(Pt<0)；
Wherein when energy storage device discharges, the electricity model of any moment are as follows:
Et+1=Et-1/ηDPt+1(Pt>0)；
Wherein:
Et+1For the energy storage amount of t+1 moment energy storage device；
EtFor the energy storage amount of t moment energy storage device；
Work as Pt+1When < 0, i.e., when energy storage device charges, then Pt+1For t moment to the average input work of t+1 moment energy storage device
Rate；
Work as Pt+1When > 0, i.e., when energy storage device discharges, then Pt+1For t moment to the average output work of t+1 moment energy storage device
Rate；
ηCFor the charge efficiency of energy storage device；
ηDFor the discharging efficiency of energy storage device.
In the present embodiment, the earnings pattern of the energy storage device of above-mentioned foundation are as follows:
Wherein
V is the day income that energy storage device carries out peak load shifting；
Work as PtWhen > 0, i.e., when energy storage device discharges, then PtFor the t-1 moment to the average output power of t moment energy storage device；
Work as PtWhen < 0, i.e., when energy storage device charges, then PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；
etFor the average electricity price at t-1 moment to t moment, the time wherein differed between t-1 moment and t moment is 1 small
When.
In the present embodiment, the charge-discharge electric power constraint of above-mentioned energy storage device is as follows:
-Pmax≤Pt≤Pmax；
Wherein:
Work as PtWhen < 0, i.e., when energy storage device charges, then PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；
Work as PtWhen > 0, i.e., when energy storage device discharges, then PtFor the t-1 moment to the average output power of t moment energy storage device；
PmaxIt is the greatest physical transimission power of energy storage device.
Step S2, according to the electricity model of the step S1 each group historical load data and energy storage device got and charge and discharge
Electrical power constraint, the operation reserve of energy storage device time acquired in each group historical load data is gone out by energy storage algorithm simulation；
Detailed process is as follows: being directed to every group of historical load data, goes out energy storage device in this group of historical load by energy storage algorithm simulation
The operation reserve of time acquired in data are as follows: each electricity consumption of simulation energy storage device time acquired in this group of historical load data
Each period of peak time discharges by certain power, simulates energy storage device time acquired in this group of historical load data
Each period in each low power consumption period charge by certain power；
Wherein, it is directed to each period of each electricity peak period, the energy storage device of simulation is in the electricity peak period
The discharge power determination process of the period is as follows:
The electricity consumption of user's period in the electricity peak period, while basis are obtained according to this group of historical load data
The electricity model of energy storage device obtains electricity of the energy storage device of simulation when entering the electricity peak period, then calculates depanning
Electricity when it is entered the electricity peak period by quasi- energy storage device discharges required mean power in the electricity peak period
P；Finally the electricity consumption of user's period in the electricity peak period is compared with above-mentioned mean power P respectively；
If the former is greater than the latter, the energy storage device simulated discharge power of the period and flat in the electricity peak period
Equal power P is identical；I.e.Wherein it isFor simulation energy storage device i-th in j-th of electricity peak period
The discharge power of a period；
If the former is less than or equal to the latter, the discharge power of the energy storage device simulated period in the electricity peak period
It is identical as the electricity consumption of user's period in the electricity peak period, i.e.,WhereinFor according to historical load number
According to the electricity consumption of the user got i-th of period in j-th of electricity peak period, i.e., energy storage device is in j-th of electricity consumption height
The discharge power of i-th of period in peak periodWith the user that is got according to historical load data in j-th of peak of power consumption
The electricity consumption of i-th of period in periodIt is identical；
Wherein, it is directed to each period in each low power consumption period, the energy storage device of simulation is in the low power consumption period
The charge power determination process of the period is as follows:
The electricity consumption of user's period within the low power consumption period, while basis are obtained according to this group of historical load data
The electricity model of energy storage device obtains electricity of the energy storage device of simulation when entering the low power consumption period, then calculates depanning
Electricity when it is entered the low ebb period by quasi- energy storage device is full of required mean power P ' in the low power consumption period；Most
By user, the electricity consumption of the period is compared within the low power consumption period afterwards；
If the electricity consumption of user's period within the low power consumption period is more than or equal to maximum electricity consumption threshold value S, simulate
Energy storage device within the low power consumption period charge power of the period be zero, i.e.,WhereinFor
The charge power of energy storage device i-th period within j-th of low power consumption period；
If user is more than or equal to maximum electricity consumption threshold after the electricity consumption of the period is added with P ' within the low power consumption period
Value S, the then charge power of the energy storage device simulated period within the low power consumption period are that S subtracts user in the low power consumption
The electricity consumption of the period in period, i.e.,WhereinFor the user got according to historical load data
The electricity consumption of i-th of period within j-th of low power consumption period, that is, the energy storage device simulated is within j-th of low power consumption period
The charge power of i-th of periodFor the electricity consumption of S i-th of period that subtract user within j-th of low power consumption period
If user is less than maximum electricity consumption threshold value S after the electricity consumption of the period is added with P ' within the low power consumption period,
The charge power of the energy storage device then simulated period within the low power consumption period is identical as mean power P '.
Step S3, the time acquired in each group historical load data in conjunction with the earnings pattern of energy storage device and energy storage device
Operation reserve, simulation calculation goes out the energy storage device peak regulation report-back time under each group historical load data；Wherein in this step, meter
Detailed process is as follows for energy storage device peak regulation report-back time under calculating each group historical load data:
Step S31, first against in every group of historical load data, the time acquired in this group of historical load data is subjected to week
Phase divides, and then according to the operation reserve of the energy storage device of simulation time acquired in this group of historical load data, passes through energy storage
Successively simulation calculation goes out net profit of the energy storage device in each period under this group of historical load data to the earnings pattern of device, wherein
The net profit in each period are as follows:
Net profit of the energy storage device k-th of period under this group of historical load data that wherein V (k) goes out for simulation calculation；
Vn(k) m day net profit of the energy storage device k-th of period under this group of historical load data gone out for simulation calculation；C (k) is
The punitive electricity charge of the energy storage device k-th of period under this group of historical load data that simulation calculation goes out；M be each period include
Number of days, it is 30 that M is arranged in the present embodiment, i.e., the time span in each period is 30；X is this group of historical load data institute
The total number of cycles that acquisition time is divided into；
Wherein Vm(k) are as follows:
Wherein
WhenWhen,For this group of historical load data Imitating energy storage device at m days of k-th of period
The t-1 moment to t moment average output power；WhenWhen,For the storage of this group of historical load data Imitating
Can device k-th of period m days t-1 moment to t moment Mean Input Power；WhereinAccording to what is simulated
The operation reserve of energy storage device time acquired in this group of historical load data is got, specifically: first search out this group of history
This group of history at k-th of period m days t-1 moment to t moments of the energy storage device of load data Imitating is negative
The electricity peak period of time acquired in lotus data or the period in low power consumption period,The energy storage device as simulated is at this
The discharge power of the electricity peak period period or charge power in the low power consumption period in period.
For this group of historical load data Imitating energy storage device k-th of period m days t-1 moment to t
The average electricity price at moment；
Wherein C (k) is obtained in the following manner:
Maximum electricity consumption of the energy storage device of this group of historical load data Imitating within k-th of period is obtained firstThen it is compared with maximum electricity consumption threshold value S；IfThen IfThen C (k)=0；
Step S32, the net profit by energy storage device under this group of historical load data in the preceding x period is added, and is obtained
Net profit summation Sumx, subsequently into step S33；Wherein:
Step S33, the net profit summation Sum that judgment step S32 is gotxWhether the cost of energy storage device is more than or equal to
Cost；
If it is not, returning to step S32 after the current value of x is then added 1；
If so, the number of days that the current value of x is recorded, and is obtained after the current value of x is multiplied with M as
Energy storage device peak regulation report-back time under historical load data.
Step S4, it is directed under each group historical load data and the calculated each user's history load data of step S3
Energy storage device peak regulation report-back time is fitted calculating, obtains between historical load data and energy storage device peak regulation report-back time
Fitting function relationship gets energy storage device peak regulation report-back time prediction model:
Y=β1x1+β2x2+β3x3+...+βnxn+u；
Wherein x1To xnFor the 1st to n kind data in historical load data, n is 3, x in the present embodiment1To x3Respectively
The peak-to-average ratio of the load factor of user side daily load, the peak-to-valley ratio of user side daily load and user side daily load；Y is energy storage device
Peak regulation report-back time, β1To βnFor fitting coefficient.Wherein u is distracter, indicates to remove data x1To xnOuter other influences energy storage device
Factor of peak regulation report-back time, such as user side transformer capacity etc..
The present embodiment 2
Present embodiment discloses a kind of energy storage device peak regulation report-back time prediction techniques, and steps are as follows:
Step B1, first against installing energy storage device in plan or having installed the user side of energy storage device, obtaining should
One group of historical load data of user side；
Step B2, it according to the one group of historical load data got in step B1, is obtained by step S4 in embodiment 1
Following energy storage device peak regulation report-back time prediction model, is calculated the peak regulation report-back time of energy storage device；
Y=β1x1+β2x2+β3x3+...+βnxn+u；
Wherein x1To xnThe the 1st to the n kind data in one group of historical load data got for step B1, y is energy storage device
Peak regulation report-back time, β1To βnFor fitting coefficient, u is distracter.
It in the present embodiment, include following several data: the load factor x of user side daily load in historical load data1, use
The peak-to-valley ratio x of family side daily load2And the peak-to-average ratio x of user side daily load3；Every group of historical load data is continued by user side
Test in more days acquires.
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention,
It should be equivalent substitute mode, be included within the scope of the present invention.
Claims (10)
1. a kind of energy storage device peak regulation report-back time prediction model creation method, which is characterized in that steps are as follows:
Step S1, multiple user sides are directed to, obtain multiple groups historical load data respectively；The electricity mould of energy storage device is established simultaneously
Type, earnings pattern and charge-discharge electric power constraint；
Step S2, according to the electricity model and charge and discharge electric work of the step S1 each group historical load data and energy storage device got
Rate constraint, the operation reserve of energy storage device time acquired in each group historical load data is gone out by energy storage algorithm simulation；
Step S3, the fortune of the time acquired in each group historical load data in conjunction with the earnings pattern of energy storage device and energy storage device
Row strategy, simulation calculation go out the energy storage device peak regulation report-back time under each group historical load data；
Step S4, the energy storage being directed under each group historical load data and the calculated each user's history load data of step S3
Device peak regulation report-back time is fitted calculating, obtains the fitting between historical load data and energy storage device peak regulation report-back time
Functional relation gets energy storage device peak regulation report-back time prediction model:
Y=β1x1+β2x2+β3x3+…+βnxn+u；
Wherein x1To xnFor the 1st to the n kind data for including in historical load data, y is energy storage device peak regulation report-back time, β1To βn
For fitting coefficient, u is distracter.
2. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
It include following several data: the load factor of user side daily load, user in every group of historical load data of acquisition in step S1
The peak-to-valley ratio of side daily load and the peak-to-average ratio of user side daily load；Every group of historical load data is continued to survey for more days by user side
Examination acquires.
3. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
The electricity model for the energy storage device established in step S1 refers to the electricity model of any moment；
Wherein when energy storage device charges, the electricity model of any moment are as follows:
Et+1=Et-ηCPt+1(Pt< 0)；
Wherein when energy storage device discharges, the electricity model of any moment are as follows:
Et+1=Et-1/ηDPt+1(Pt> 0)；
Wherein:
Et+1For the energy storage amount of t+1 moment energy storage device；
EtFor the energy storage amount of t moment energy storage device；
Work as Pt+1When < 0, i.e., when energy storage device charges, then Pt+1For t moment to the Mean Input Power of t+1 moment energy storage device；
Work as Pt+1When > 0, i.e., when energy storage device discharges, then Pt+1For t moment to the average output power of t+1 moment energy storage device；
ηCFor the charge efficiency of energy storage device；
ηDFor the discharging efficiency of energy storage device.
4. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
The earnings pattern for the energy storage device established in step S1 are as follows:
Wherein
V is the day income that energy storage device carries out peak load shifting；
Work as PtWhen > 0, PtFor the t-1 moment to the average output power of t moment energy storage device；
Work as PtWhen < 0, PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；
etFor the average electricity price at t-1 moment to t moment, the time wherein differed between t-1 moment and t moment is 1 hour.
5. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
The charge-discharge electric power constraint of energy storage device is as follows in step S1:
-Pmax≤Pt≤Pmax；
Wherein:
Work as PtWhen < 0, i.e., when energy storage device charges, then PtFor the t-1 moment to the Mean Input Power of t moment energy storage device；Work as Pt
When > 0, i.e., when energy storage device discharges, then PtFor the t-1 moment to the average output power of t moment energy storage device；
PmaxIt is the greatest physical transimission power of energy storage device.
6. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
In step S2, it is directed to every group of historical load data, energy storage device is gone out in this group of historical load data by energy storage algorithm simulation
The operation reserve of acquired time are as follows: each peak of power consumption of simulation energy storage device time acquired in this group of historical load data
Each period in period discharges by certain power, simulates the every of energy storage device time acquired in this group of historical load data
Each period in a low power consumption period charges by certain power；
Wherein, be directed to each period of each electricity peak period, the energy storage device of simulation the electricity peak period this when
The discharge power determination process of section is as follows:
The electricity consumption of user's period in the electricity peak period is obtained according to this group of historical load data, while according to energy storage
The electricity model of device obtains electricity of the energy storage device of simulation when entering the electricity peak period, then calculates simulation
Electricity when it is entered the electricity peak period by energy storage device discharges required mean power P in the electricity peak period；Most
The electricity consumption of user's period in the electricity peak period is compared with above-mentioned mean power P respectively afterwards；
If the former is greater than the latter, the energy storage device the simulated discharge power of the period and average function in the electricity peak period
Rate P is identical；I.e.Wherein it isFor simulation energy storage device i-th in j-th of electricity peak period when
The discharge power of section；
If the former is less than or equal to the latter, the discharge power and use of the energy storage device simulated period in the electricity peak period
The electricity consumption of family period in the electricity peak period is identical, i.e.,WhereinFor according to historical load data
The electricity consumption of the user got i-th of period in j-th of electricity peak period, that is, the energy storage device simulated are used at j-th
The discharge power of i-th of period in electric peak timeWith the user that is got according to historical load data in j-th of electricity consumption
The electricity consumption of i-th of period in peak timeIt is identical；
Wherein, be directed to each period in each low power consumption period, the energy storage device of simulation the low power consumption period this when
The charge power determination process of section is as follows:
The electricity consumption of user's period within the low power consumption period is obtained according to this group of historical load data, while according to energy storage
The electricity model of device obtains electricity of the energy storage device of simulation when entering the low power consumption period, then calculates simulation
Electricity when it is entered the low ebb period by energy storage device is full of required mean power P ' in the low power consumption period；Finally will
The electricity consumption of user's period within the low power consumption period carries out following compare；
If the electricity consumption of user's period within the low power consumption period is more than or equal to maximum electricity consumption threshold value S, the storage simulated
Energy device charge power of the period within the low power consumption period is zero, i.e.,WhereinFor the storage of simulation
The charge power of energy device i-th period within j-th of low power consumption period；
If user is more than or equal to maximum electricity consumption threshold value S after the electricity consumption of the period is added with P ' within the low power consumption period,
The charge power of the energy storage device then simulated period within the low power consumption period is that S subtracts user in the low power consumption period
The electricity consumption of the interior period, i.e.,WhereinUser to be got according to historical load data exists
The electricity consumption of i-th of period in j-th of low power consumption period, that is, the energy storage device simulated is i-th within j-th of low power consumption period
The charge power of a periodFor the electricity consumption of S i-th of period that subtract user within j-th of low power consumption period
If user is less than maximum electricity consumption threshold value S, mould after the electricity consumption of the period is added with P ' within the low power consumption period
The charge power of quasi- energy storage device period within the low power consumption period is identical as mean power P '.
7. energy storage device peak regulation report-back time prediction model creation method according to claim 1, which is characterized in that described
In step S3, detailed process is as follows for the energy storage device peak regulation report-back time for calculating under each group historical load data:
Step S31, first against in every group of historical load data, the time acquired in this group of historical load data is subjected to the period stroke
Point, then according to the operation reserve of the energy storage device of simulation time acquired in this group of historical load data, pass through energy storage device
Earnings pattern successively simulation calculation goes out net profit of the energy storage device in each period under this group of historical load data, wherein each
The net profit in period are as follows:
Net profit of the energy storage device k-th of period under this group of historical load data that wherein V (k) goes out for simulation calculation；Vm(k)
M day net profit of the energy storage device k-th of period under this group of historical load data gone out for simulation calculation；C (k) is emulation meter
The punitive electricity charge of the energy storage device k-th of period under this group of historical load data calculated；M is the day for each period including
Number；X is the total number of cycles being divided into the time acquired in this group of historical load data；
Wherein Vm(k) are as follows:
Wherein
WhenWhen,For this group of historical load data Imitating energy storage device m days of k-th of period
The t-1 moment to t moment average output power；
WhenWhen,For this group of historical load data Imitating energy storage device m days of k-th of period
The t-1 moment to t moment Mean Input Power；
For this group of historical load data Imitating energy storage device k-th of period m days t-1 moment to t moment
Average electricity price；
Wherein C (k) is obtained in the following manner:
Maximum electricity consumption of the energy storage device of this group of historical load data Imitating within k-th of period is obtained firstSo
It is compared with maximum electricity consumption threshold value S afterwards；IfThen If Dmaxk
≤ S, then C (k)=0；
Step S32, the net profit by energy storage device under this group of historical load data in the preceding x period is added, and is received only
Beneficial summation Sumx, subsequently into step S33；Wherein:
Step S33, the net profit summation Sum that judgment step S32 is gotxWhether the cost Cost of energy storage device is more than or equal to；
If it is not, returning to step S32 after the current value of x is then added 1；
If so, the current value of x is recorded, and the number of days obtained after the current value of x is multiplied with M is as history
Energy storage device peak regulation report-back time under load data.
8. energy storage device peak regulation report-back time prediction model creation method according to claim 7, which is characterized in that M is
30。
9. a kind of energy storage device peak regulation report-back time prediction technique, which is characterized in that steps are as follows:
Step B1, first against installing energy storage device in plan or having installed the user side of energy storage device, the user is obtained
One group of historical load data of side；
Step B2, according to the one group of historical load data got in step B1, by the step S4 of claim 1 obtain with
Lower energy storage device peak regulation report-back time prediction model, is calculated the peak regulation report-back time of energy storage device；
Y=β1x1+β2x2+β3x3+…+βnxn+u；
Wherein x1To xnThe the 1st to the n kind data in one group of historical load data got for step B1, y are energy storage device peak regulation
Report-back time, β1To βnFor fitting coefficient, u is distracter.
10. energy storage device peak regulation report-back time prediction technique according to claim 9, which is characterized in that the history is negative
It include following several data: load factor, the peak-to-valley ratio and user side of user side daily load of user side daily load in lotus data
The peak-to-average ratio of daily load；Every group of historical load data continues test in more days by user side and acquires.
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