CN105529728A - Adjustable capacity prediction method for energy storage system of considering multi-source information fusion and planned power output - Google Patents

Abstract

The invention provides an adjustable capacity prediction method for an energy storage system of considering multi-source information fusion and planned power output. The method comprises the following steps: (1) obtaining real-time data; (2) calculating a day-ahead predictive power and an ultra short-term predictive power of a new energy power plant at a present moment and a charged state of the energy storage system; (3) calculating a power output value of the energy storage system at the present moment on the basis of an operating state of the new energy power plant and a charged state interval of the energy storage system; (4) distributing the power output value of the energy storage system to various energy storage units, and calculating charged state values of the energy storage units at the end of the present moment; (5) calculating the charged state value of the energy storage system at the end of the next four hours of the present moment; and (6) calculating the adjustable charge-discharge capacity of the energy storage system in the next four hours. The adjustable capacity prediction method is suitable for prediction of the adjustable capacity of the energy storage system during new energy of stored wind, stored light, stored wind and light and the like and stored energy combined generation tracking and generation planning application.

Description

Consider the energy storage schedulable capacity prediction methods that Multi-source Information Fusion and plan are exerted oneself

Technical field

The invention belongs to intelligent grid and stored energy and switch technology field, be specifically related to a kind of energy storage schedulable capacity prediction methods that Multi-source Information Fusion and plan are exerted oneself of considering, be particularly useful for energy-storage system to participate in following the tracks of generation schedule when exerting oneself, the prediction of energy-storage system future time instance schedulable capacity and energy-storage system energy management.

Background technology

In the last few years, the generation of electricity by new energy such as wind-powered electricity generation, photovoltaic scale constantly expanded, but its intrinsic randomness and fluctuation make new forms of energy large-scale grid connection may jeopardize the safety and stability of electrical network.Usually there is the larger situation of error in the generating actual power such as wind-powered electricity generation, photovoltaic and a few days ago planned value, in order to reduce error between the two, utilizing the discharge and recharge bidirectional characteristic of energy storage participation tracking generation schedule to exert oneself becomes a kind of feasible program gradually.

Carry out prediction to the schedulable capacity of energy-storage system effectively to improve the utilization ratio of energy storage and make better decision-making etc. to the charge and discharge control of energy storage, patent, document, technical report etc. at present about energy-storage system schedulable capacity predict aspect are little, need to study further.

Summary of the invention

In order to overcome above-mentioned the deficiencies in the prior art, the invention provides a kind of energy storage schedulable capacity prediction methods that Multi-source Information Fusion and plan are exerted oneself of considering, the present invention proposes the Forecasting Methodology that new forms of energy and energy storage combined generating system follow the tracks of energy-storage system schedulable capacity when generation schedule is exerted oneself, be applicable to the prediction that the new forms of energy such as wind storage, light storage and wind-light storage and energy storage cogeneration follow the tracks of energy-storage system schedulable capacity when generation schedule is applied.

In order to realize foregoing invention object, the present invention takes following technical scheme:

Consider the energy storage schedulable capacity prediction methods that Multi-source Information Fusion and plan are exerted oneself, described method comprises as follows

Step:

(1) real time data is obtained;

(2) state-of-charge of the predicted power a few days ago of generation of electricity by new energy field current time, ultra-short term predicted power and energy-storage system is calculated;

(3) based on generation of electricity by new energy field running status and described energy-storage system state-of-charge interval, what calculate current time energy-storage system goes out force value;

(4) force value that goes out of described energy-storage system is distributed to each energy-storage units, and calculate the SOC of each energy-storage units in current time end;

(5) SOC of described energy-storage system at current time following four hours ends is calculated;

(6) following four hours described energy-storage system schedulable charge/discharge capacities are calculated.

Preferably, in described step (1), described real time data comprises: the real time data obtaining each Wind turbine of current time from generation of electricity by new energy farm monitoring system, obtain wind-powered electricity generation predicted power, ultra-short term predicted power a few days ago from wind power prediction system, from energy-accumulating power station supervisory control system, obtain the current related data of each energy-storage units.

Preferably, described step (2) comprises the steps:

Step 2-1, the predicted power a few days ago calculating generation of electricity by new energy field current time and ultra-short term predicted power:

The power of generation of electricity by new energy field is the performance number sum of each new forms of energy unit:

$P_f=\underset{i=1}{\overset{N}{\Σ}}{P}_{fi}$

$P_{uf}=\underset{i=1}{\overset{N}{\Σ}}{P}_{ufi}$

In formula, P _f, P _ufbe respectively predicted power a few days ago and the ultra-short term predicted power of generation of electricity by new energy field; P _fi, P _ufibe respectively predicted power a few days ago and the ultra-short term predicted power of Wind turbines i, N is the sum of Wind turbines;

The SOC of step 2-2, calculating energy-storage system:

$SOC=\frac{\underset{i=1}{\overset{M}{\Σ}}{\mathrm{SOC}}_i\×E_{Ni}}{\underset{i=1}{\overset{M}{\Σ}}{E}_{Ni}}$

In formula, SOC is the SOC of energy-storage system; SOC _ifor the SOC of energy-storage units i; E _nifor the capacity of energy-storage units i, M is energy-storage units sum.

Preferably, described step (3) comprises the steps:

Step 3-1, based on the wind-powered electricity generation ultra-short term predicted power of current time and wind-powered electricity generation a few days ago predicted power data determine current wind-powered electricity generation state;

Three generated power forecasting characteristic values are set, comprise: generated power forecasting upper limit characteristic value P _fb(t), current generated power forecasting value P _f(t), generated power forecasting lower limit characteristic value P _fs(t),

Predicted power higher limit: P _fb(t)=P _f(t)+P _limit

Predicted power lower limit: P _fs(t)=P _f(t)-P _limit

Wherein: P _limit=α × Cap, α gets the installed capacity that 0.25, Cap is generation of electricity by new energy unit;

(0, ∞) is divided into three interval: P by above-mentioned three generated power forecasting characteristic values _uf(t) < P _fs(t), P _fs(t)≤P _uf(t)≤P _fb(t), P _uf(t) > P _fb(t), the corresponding a kind of generating state in each interval, respectively called after generating state A, B, C, wherein P _uft wind-powered electricity generation ultra-short term predicted power value that () is t;

Step 3-2, four control coefrficient SOC are set _low, a ₁, a ₂, and SOC _high, and meet SOC _low< a ₁< a ₂< SOC _high, according to four control coefrficients, the current SOC SOC of energy-storage system is divided into five intervals successively between [0,1], 0≤SOC (t) < SOC _low, SOC _low≤ SOC (t) < a ₁, a ₁≤ SOC (t) < a ₂, a ₂≤ SOC (t) < SOC _high, SOC _high≤ SOC (t) < 1, respectively called after Interval I, II, III, IV, V;

Step 3-3, interval based on current time generating state and state-of-charge, according to computation rule, that determines current time energy-storage system goes out force value.

Preferably, in described step 3-3, described computation rule is:

When generating state is A and SOC is in Interval I, the force value that goes out of energy-storage system is 0;

When generating state is A and SOC is in interval II, III, the force value that goes out of energy-storage system is P _fs(t)-P _uf(t);

When generating state is A and SOC is in interval IV, V, the force value that goes out of energy-storage system is (P _fs(t)-P _uf(t), P _fb(t)-P _uf(t));

When generating state is B and SOC is in Interval I, the force value that goes out of energy-storage system is-(P _uf(t)-P _fs(t));

When generating state is B and SOC is in interval II, the force value that goes out of energy-storage system is-(0, P _uf(t)-P _fs(t));

When generating state is B and SOC is in interval III, the force value that goes out of energy-storage system is 0;

When generating state is B and SOC is in interval IV, the force value that goes out of energy-storage system is (0, P _fb(t)-P _uf(t));

When generating state is B and SOC is in interval V, the force value that goes out of energy-storage system is P _fb(t)-P _uf(t);

When generating state be C and SOC be in Interval I, II time, energy-storage system go out force value for-(P _uf(t)-P _fb(t), P _uf(t)-P _fs(t));

When generating state is C and SOC is in interval III, IV, the force value that goes out of energy-storage system is-(P _uf(t)-P _fb(t));

When generating state is C and SOC is in interval IV, the force value that goes out of energy-storage system is 0;

The determination that above energy-storage system goes out force value will meet following constraints simultaneously:

-P _max≤P _ES≤P _max

SOC _low≤SOC(t)≤SOC _high

Wherein P _eSbe energy-storage system go out force value; P _maxit is energy-storage system peak power output.

Preferably, described step (4) comprises the steps:

Step 4-1, energy-storage system gone out force value distribute to each energy-storage units,

If P _eS> 0:

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{M}{\&Sigma;}}({\mathrm{SOC}}_i-{\mathrm{SOC}}_{low})}{P}_{ES}$

Wherein P _batiforce value is gone out for energy-storage units i;

Checking P _batiwhether at [0, P _maxi] in scope, wherein P _maxifor the maximum output of energy-storage units i limits, determined by the self character of energy-storage units; If do not meet, setting P _bati=P _maxi, all the other points in scope are done following renewal:

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_i-{\mathrm{SOC}}_{low})}{P}_{ES}$

In formula, W is P _batimeet [0, P _maxi] counting in scope;

If P _eS< 0:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

Checking P _batiwhether at [-P _maxi, 0] and in scope, if do not meet, setting P _bati=-P _maxi, all the other points in scope are done following renewal:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{H}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

In formula, H is P _batimeet [-P _maxi, 0] and counting in scope;

The SOC of step 4-2, each energy-storage units in calculating current time end,

T end SOC value is calculated: work as P by following recurrence relation _batiduring (t)≤0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δtη _C/E _Ni

Work as P _batiduring (t) > 0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δt/η _DE _Ni

In formula: SOC _it () is the SOC at the end of energy-storage units t; σ _sdrfor the self-discharge rate of energy-storage system; η _cand η _dbe respectively the charging and discharging efficiency of energy-storage system; Δ t is calculation window duration, min; E _nifor the rated capacity of energy-storage units.

Preferably, described step (5) comprises the steps:

Step 5-1, calculating energy-storage system are at the SOC of current time:

$SOC\left(t\right)=\frac{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}\&times;{\mathrm{SOC}}_i\left(t\right)}{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}}$

In formula, SOC (t) is for energy-storage system is at the SOC of t; SOC _it () is for energy-storage units i is at the SOC of t; E _nifor the capacity of energy-storage units i;

Step 5-2, t=t+1, the energy-storage system calculating following four hours according to above step cycle goes out force value with the SOC of each moment Mo energy-storage system, and finally calculates at the last SOC of following four hours of current time.

Preferably, in described step (6), the formula of the following four hours described energy-storage system schedulable charging capacitys of described calculating is as follows:

E _disC(t)＝SOC _af(t)*E _N

The formula of the following four hours described energy-storage system schedulable discharge capacities of described calculating is as follows:

E _disD(t)＝(1-SOC _af(t))*E _N

E in formula _disCt () is this moment following four hours schedulable charging capacitys of energy-storage system, unit: MW; E _disDt () is this moment following four hours schedulable discharge capacities of energy-storage system, unit: MW; SOC _aft () is the SOC of this moment following four hours last energy-storage systems, E _nfor the capability value of energy-storage system.

Compared with prior art, beneficial effect of the present invention is:

The present invention utilizes the multi-source information of generation of electricity by new energy (wind-powered electricity generation, photovoltaic generation) and energy-storage system, consider the state-of-charge etc. of ultra-short term predicted power, short-term forecast power, power prediction characteristic value, energy-storage system, take into account analysis and the fusion of above-mentioned multi-source information, propose the Forecasting Methodology that new forms of energy and energy storage combined generating system follow the tracks of energy-storage system schedulable capacity when generation schedule is exerted oneself.The present invention is applicable to the prediction that wind storage, light storage and the new forms of energy such as wind-light storage and energy storage cogeneration follow the tracks of energy-storage system schedulable capacity when generation schedule is applied, and can provide reference frame for the optimal control of energy-storage system and energy management.

Accompanying drawing explanation

Fig. 1 is the system diagram of generation of electricity by new energy unit provided by the invention and energy-storage units,

Fig. 2 is a kind of flow chart considered Multi-source Information Fusion and plan the energy storage schedulable capacity prediction methods of exerting oneself provided by the invention,

Fig. 3 is the curve chart of energy-storage system schedulable discharge capacity institute provided by the invention accounting,

Fig. 4 is the curve chart of energy-storage system schedulable charging capacity institute provided by the invention accounting.

Embodiment

Below in conjunction with accompanying drawing, the present invention is described in further detail.

As shown in Figure 1, for the system diagram of generation of electricity by new energy unit and energy-storage system, generation of electricity by new energy unit comprises wind turbine generator and photovoltaic generation unit, wind turbine generator is connected with wind farm monitoring system and wind power prediction system, photovoltaic generation unit is connected with photovoltaic power station monitoring system and photo-voltaic power generation station prognoses system, energy-storage system comprises M energy-storage units, and each energy-storage units is connected with two way convertor, and energy-storage system is connected with energy-accumulating power station supervisory control system.

As shown in Figure 2, improve the polymorphic type energy storage system control method of following the tracks of generation schedule capacity in this example, mainly comprise the steps:

The wind-powered electricity generation related data that predicted power, ultra-short term predicted power and each energy-storage units are current a few days ago of steps A, each Wind turbine of acquisition current time;

The related data of step B, the predicted power a few days ago calculating generation of electricity by new energy field current time, ultra-short term predicted power and energy-storage system;

Step C, interval based on wind-powered electricity generation state and energy-storage system state-of-charge, what calculate current time energy-storage system goes out force value;

Step D, energy-storage system is gone out force value distribute between each energy-storage units, and calculate the SOC of each energy-storage units in current time end;

Step e, the SOC of calculating energy-storage system at current time following four hours ends;

Step F, the following four hours energy-storage system schedulable discharge capacities of calculating and schedulable charging capacity.

In stepb, the related data method of described calculating current wind generating field and energy-storage system is as follows:

First, predicted power a few days ago and the ultra-short term predicted power of wind power plant current time is calculated:

The power of wind power plant is the performance number sum of each Wind turbine:

$P_f=\underset{i=1}{\overset{N}{\&Sigma;}}{P}_{fi}$

$P_{uf}=\underset{i=1}{\overset{N}{\&Sigma;}}{P}_{ufi}$

In formula, P _f, P _ufbe respectively predicted power a few days ago and the ultra-short term predicted power of wind energy turbine set; P _fi, P _ufibe respectively predicted power a few days ago and the ultra-short term predicted power of Wind turbines i, N is the sum of Wind turbines.

Then, the SOC of energy-storage system is calculated:

$SOC=\frac{\underset{i=1}{\overset{M}{\&Sigma;}}{\mathrm{SOC}}_i\&times;E_{Ni}}{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}}$

In formula, SOC is the SOC of energy-storage system; SOC _ifor the SOC of energy-storage units i; E _nifor the capacity of energy-storage units i, M is energy-storage units sum.

In step C, the computational methods that described energy-storage system goes out force value are as follows:

First, based on the wind-powered electricity generation ultra-short term predicted power of current time and wind-powered electricity generation a few days ago predicted power data determine current wind-powered electricity generation state;

Three generated power forecasting characteristic values are set, comprise: generated power forecasting upper limit characteristic value P _fb(t), current generated power forecasting value P _f(t), generated power forecasting lower limit characteristic value P _fs(t).

Predicted power higher limit: P _fb(t)=P _f(t)+P _limit

Predicted power lower limit: P _fs(t)=P _f(t)-P _limit

Wherein: P _limit=α × Cap, α gets 0.25; Cap is the installed capacity of generation of electricity by new energy unit.

(0, ∞) is divided into three interval: P by above-mentioned three generated power forecasting characteristic values _uf(t) < P _fs(t), P _fs(t)≤P _uf(t)≤P _fb(t), P _uf(t) > P _fb(t), the corresponding a kind of generating state in each interval, respectively called after generating state A, B, C, wherein P _uft wind-powered electricity generation ultra-short term predicted power value that () is t;

Secondly, the SOC based on current energy-storage system determines that current state-of-charge is interval;

Four control coefrficient SOC are set _low, a ₁, a ₂, and SOC _high, and meet SOC _low< a ₁< a ₂< SOC _high, wherein SOC _lowand SOC _highdetermined by the self character of energy-storage system.According to four control coefrficients, the current SOC SOC of energy-storage system is divided into five intervals successively between [0,1], 0≤SOC (t) < SOC _low, SOC _low≤ SOC (t) < a ₁, a ₁≤ SOC (t) < a ₂, a ₂≤ SOC (t) < SOC _high, SOC _high≤ SOC (t) < 1, respectively called after Interval I, II, III, IV, V;

Again, based on current time generating state and state-of-charge interval, according to computation rule as follows, that determines current time energy-storage system goes out force value;

Finally, the determination that above energy-storage system goes out force value will meet following constraints simultaneously:

-P _max≤P _ES≤P _max

SOC _low≤SOC(t)≤SOC _high

Wherein P _eSbe energy-storage system go out force value; P _maxit is energy-storage system peak power output.

In step D, describedly energy-storage system gone out force value and distribute between each energy-storage units, and the computational methods calculating the SOC of each energy-storage units in current time end are as follows:

First, energy-storage system is gone out force value to distribute between each energy-storage units:

If P _eS> 0, i.e. energy storage system discharges:

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{M}{\&Sigma;}}({\mathrm{SOC}}_1-{\mathrm{SOC}}_{low})}{P}_{ES}$

Wherein P _batiforce value is gone out for energy-storage units i.

Checking P _batiwhether at [0, P _maxi] in scope, if do not meet, setting P _bati=P _maxi.All the other points in scope are done following renewal, wherein P _maxifor the maximum output of energy-storage units i limits, determined by the self character of energy-storage units.

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_1-{\mathrm{SOC}}_{low})}{P}_{ES}$

Wherein W is P _batimeet [0, P _maxi] counting in scope.

If P _eS< 0, i.e. energy-storage system charging:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

Checking P _batiwhether at [-P _maxi, 0] and in scope, if do not meet, setting P _bati=-P _maxi.All the other points in scope are done following renewal:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{H}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

Wherein H is P _batimeet [-P _maxi, 0] and counting in scope.

Afterwards, the SOC of each energy-storage units in current time end is calculated:

T end SOC value is calculated: work as P by following recurrence relation _batiduring (t)≤0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δtη _C/E _Ni

Work as P _batiduring (t) > 0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δt/η _DE _Ni

In formula: SOC _it () is the SOC at the end of energy-storage units t; σ _sdrfor the self-discharge rate of energy-storage system; η _cand η _dbe respectively the charging and discharging efficiency of energy-storage system; Δ t is calculation window duration, min; E _nifor the rated capacity of energy-storage units.

In step e, described calculating energy-storage system is as follows in the method for the SOC at current time following four hours ends:

First, the SOC of energy-storage system at current time is calculated:

$SOC\left(t\right)=\frac{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}\&times;{\mathrm{SOC}}_i\left(t\right)}{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}}$

In formula, SOC (t) is for energy-storage system is at the SOC of t; SOC _it () is for energy-storage units i is at the SOC of t; E _nifor the capacity of energy-storage units i.

Then, t=t+1, the energy-storage system calculating following four hours according to above step cycle goes out force value with the SOC of each moment Mo energy-storage system, and finally calculates at the last SOC of following four hours of current time;

In step F, the method for the following four hours energy-storage system schedulable discharge capacities of described calculating and schedulable charging capacity is as follows:

E _disC(t)＝SOC _af(t)*E _N

E _disD(t)＝(1-SOC _af(t))*E _N

In formula, E _disCt () is this moment following four hours schedulable charging capacitys of energy-storage system, MW; E _disDt () is this moment following four hours schedulable discharge capacities of energy-storage system, MW; SOC _aft () is the SOC at this moment following four hours ends; E _nfor the capability value of energy-storage system.

As shown in Figure 3, being the curve chart of 20 hours schedulable discharge capacity proportions of energy-storage system, as indicated at 4, is the curve chart of 20 hours schedulable charging capacity proportions of energy-storage system.

Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit, although with reference to above-described embodiment to invention has been detailed description, those of ordinary skill in the field are to be understood that: still can modify to the specific embodiment of the present invention or equivalent replacement, and not departing from any amendment of spirit and scope of the invention or equivalent replacement, it all should be encompassed in the middle of right of the present invention.

Claims (8)

1. consider the energy storage schedulable capacity prediction methods that Multi-source Information Fusion and plan are exerted oneself, it is characterized in that, described method comprises the steps:

(1) real time data is obtained;

(2) state-of-charge of the predicted power a few days ago of generation of electricity by new energy field current time, ultra-short term predicted power and energy-storage system is calculated;

(3) based on generation of electricity by new energy field running status and described energy-storage system state-of-charge interval, what calculate current time energy-storage system goes out force value;

(4) force value that goes out of described energy-storage system is distributed to each energy-storage units, and calculate the SOC of each energy-storage units in current time end;

(5) SOC of described energy-storage system at current time following four hours ends is calculated;

(6) following four hours described energy-storage system schedulable charge/discharge capacities are calculated.

2. Forecasting Methodology according to claim 1, it is characterized in that, in described step (1), described real time data comprises: the real time data obtaining each Wind turbine of current time from generation of electricity by new energy farm monitoring system, obtain wind-powered electricity generation predicted power, ultra-short term predicted power a few days ago from wind power prediction system, from energy-accumulating power station supervisory control system, obtain the current related data of each energy-storage units.

3. Forecasting Methodology according to claim 1, it is characterized in that, described step (2) comprises the steps:

Step 2-1, the predicted power a few days ago calculating generation of electricity by new energy field current time and ultra-short term predicted power:

The power of generation of electricity by new energy field is the performance number sum of each new forms of energy unit:

$P_f=\underset{i=1}{\overset{N}{\&Sigma;}}{P}_{fi}$

$P_{uf}=\underset{i=1}{\overset{N}{\&Sigma;}}{P}_{ufi}$

In formula, P _f, P _ufbe respectively predicted power a few days ago and the ultra-short term predicted power of generation of electricity by new energy field; P _fi, P _ufibe respectively predicted power a few days ago and the ultra-short term predicted power of Wind turbines i, N is the sum of Wind turbines;

The SOC of step 2-2, calculating energy-storage system:

$SOC=\frac{\underset{i=1}{\overset{M}{\&Sigma;}}{\mathrm{SOC}}_i\&times;E_{Ni}}{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}}$

In formula, SOC is the SOC of energy-storage system; SOC _ifor the SOC of energy-storage units i, M is energy-storage units sum; E _nifor the capacity of energy-storage units i.

4. Forecasting Methodology according to claim 3, it is characterized in that, described step (3) comprises the steps:

Step 3-1, based on the wind-powered electricity generation ultra-short term predicted power of current time and wind-powered electricity generation a few days ago predicted power data determine current wind-powered electricity generation state;

Three generated power forecasting characteristic values are set, comprise: generated power forecasting upper limit characteristic value P _fb(t), current generated power forecasting value P _f(t), generated power forecasting lower limit characteristic value P _fs(t),

Predicted power higher limit: P _fb(t)=P _f(t)+P _limit

Predicted power lower limit: P _fs(t)=P _f(t)-P _limit

Wherein: P _limit=α × Cap, α gets the installed capacity that 0.25, Cap is generation of electricity by new energy unit;

(0, ∞) is divided into three interval: P by above-mentioned three generated power forecasting characteristic values _uf(t) < P _fs(t), P _fs(t)≤P _uf(t)≤P _fb(t), P _uf(t) > P _fb(t), the corresponding a kind of generating state in each interval, respectively called after generating state A, B, C, wherein P _uft wind-powered electricity generation ultra-short term predicted power value that () is t;

Step 3-2, four control coefrficient SOC are set _low, a ₁, a ₂, and SOC _high, and meet SOC _low< a ₁< a ₂< SOC _high, according to four control coefrficients, the current SOC SOC of energy-storage system is divided into five intervals successively between [0,1], 0≤SOC (t) < SOC _low, SOC _low≤ SOC (t) < a ₁, a ₁≤ SOC (t) < a ₂, a ₂≤ SOC (t) < SOC _high, SOC _high≤ SOC (t) < 1, respectively called after Interval I, II, III, IV, V;

Step 3-3, interval based on current time generating state and state-of-charge, according to computation rule, that determines current time energy-storage system goes out force value.

5. Forecasting Methodology according to claim 4, it is characterized in that, in described step 3-3, described computation rule is:

When generating state is A and SOC is in Interval I, the force value that goes out of energy-storage system is 0;

When generating state is A and SOC is in interval II, III, the force value that goes out of energy-storage system is P _fs(t)-P _uf(t);

When generating state is A and SOC is in interval IV, V, the force value that goes out of energy-storage system is (P _fs(t)-P _uf(t), P _fb(t)-P _uf(t));

When generating state is B and SOC is in Interval I, the force value that goes out of energy-storage system is-(P _uf(t)-P _fs(t));

When generating state is B and SOC is in interval II, the force value that goes out of energy-storage system is-(0, P _uf(t)-P _fs(t));

When generating state is B and SOC is in interval III, the force value that goes out of energy-storage system is 0;

When generating state is B and SOC is in interval IV, the force value that goes out of energy-storage system is (0, P _fb(t)-P _uf(t));

When generating state is B and SOC is in interval V, the force value that goes out of energy-storage system is P _fb(t)-P _uf(t);

When generating state be C and SOC be in Interval I, II time, energy-storage system go out force value for-(P _uf(t)-P _fb(t), P _uf(t)-P _fs(t));

When generating state is C and SOC is in interval III, IV, the force value that goes out of energy-storage system is-(P _uf(t)-P _fb(t));

When generating state is C and SOC is in interval IV, the force value that goes out of energy-storage system is 0;

The determination that above energy-storage system goes out force value will meet following constraints simultaneously:

-P _max≤P _ES≤P _max

SOC _low≤SOC(t)≤SOC _high

Wherein P _eSbe energy-storage system go out force value; P _maxit is energy-storage system peak power output.

6. Forecasting Methodology according to claim 5, it is characterized in that, described step (4) comprises the steps:

Step 4-1, energy-storage system gone out force value distribute to each energy-storage units,

If P _eS> 0:

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{M}{\&Sigma;}}({\mathrm{SOC}}_i-{\mathrm{SOC}}_{low})}{P}_{ES}$

Wherein P _batiforce value is gone out for energy-storage units i;

Checking P _batiwhether at [0, P _maxi] in scope, wherein P _maxifor the maximum output of energy-storage units i limits, determined by the self character of energy-storage units; If do not meet, setting P _bati=P _maxi, all the other points in scope are done following renewal:

$P_{bati}=\frac{{\mathrm{SOC}}_i-{\mathrm{SOC}}_{low}}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_i-{\mathrm{SOC}}_{low})}{P}_{ES}$

In formula, W is P _batimeet [0, P _maxi] counting in scope;

If P _eS< 0:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{W}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

Checking P _batiwhether at [-P _maxi, 0] and in scope, if do not meet, setting P _bati=-P _maxi, all the other points in scope are done following renewal:

$P_{bati}=\frac{{\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i}{\underset{i=1}{\overset{H}{\&Sigma;}}({\mathrm{SOC}}_{high}-{\mathrm{SOC}}_i)}{P}_{ES}$

In formula, H is P _batimeet [-P _maxi, 0] and counting in scope;

The SOC of step 4-2, each energy-storage units in calculating current time end,

T end SOC value is calculated: work as P by following recurrence relation _batiduring (t)≤0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δtη _C/E _Ni

Work as P _batiduring (t) > 0:

SOC _i(t)＝(1-σ _sdr)SOC _i(t-1)-P _bati(t)Δt/η _DE _Ni

In formula: SOC _it () is the SOC at the end of energy-storage units t; σ _sdrfor the self-discharge rate of energy-storage system; η _cand η _dbe respectively the charging and discharging efficiency of energy-storage system; Δ t is calculation window duration, min; E _nifor the rated capacity of energy-storage units.

7. Forecasting Methodology according to claim 1, it is characterized in that, described step (5) comprises the steps:

Step 5-1, calculating energy-storage system are at the SOC of current time:

$SOC\left(t\right)=\frac{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}\&times;{\mathrm{SOC}}_i\left(t\right)}{\underset{i=1}{\overset{M}{\&Sigma;}}{E}_{Ni}}$

In formula, SOC (t) is for energy-storage system is at the SOC of t; SOC _it () is for energy-storage units i is at the SOC of t; E _nifor the capacity of energy-storage units i;

Step 5-2, t=t+1, the energy-storage system calculating following four hours according to above step cycle goes out force value with the SOC of each moment Mo energy-storage system, and finally calculates at the last SOC of following four hours of current time.

8. Forecasting Methodology according to claim 1, is characterized in that, in described step (6), the described formula calculating following four hours described energy-storage system schedulable charging capacitys is as follows:

E _disC(t)＝SOC _af(t)*E _N

The formula of the following four hours described energy-storage system schedulable discharge capacities of described calculating is as follows:

E _disD(t)＝(1-SOC _af(t))*E _N

E in formula _disCt () is this moment following four hours schedulable charging capacitys of energy-storage system, unit: MW; E _disDt () is this moment following four hours schedulable discharge capacities of energy-storage system, unit: MW; SOC _aft () is the SOC of this moment following four hours last energy-storage systems, E _nfor the capability value of energy-storage system.