CN104300564A - Wind-sunlight storage contained micro grid system peak clipping and valley filling method based on random production simulating - Google Patents

Abstract

The invention provides a wind-sunlight storage contained micro grid system peak clipping and valley filling method based on random production simulating. The wind-sunlight storage contained micro grid system peak clipping and valley filling method includes the following steps: (1) reading original load data, a wind electricity contribution value and a photovoltaic contribution value which are predicated in future 24 hours; (2) determining equivalent load data, and obtaining an original equivalent load curve; (3) determining an ENNS and an LOLP; (4) according to the ENNS or the LOLP needing to be reduced, determining the charging-discharging power and the discharging quantity of an energy storage system, and generating a charging-discharging strategy; (5) verifying the reached peak clipping and valley filling effect. According to the wind-sunlight storage contained micro grid system peak clipping and valley filling method, the simple and clear equivalent continuous load curve in random production simulation is adopted for determining the charging-discharging power and the capacity of the energy storage system, the charging-discharging strategy is generated in combination with the curve, the whole process is simple and practicable, and the power supply reliability improvement and load peak clipping and valley filling of a micro grid system are effectively combined.

Description

A kind of based on Stochastic Production Simulation containing wind-light storage micro-grid system peak load shifting method

Technical field

The present invention relates to a kind of method of micro-grid system operation planning and wind-solar-storage joint technical field of power generation, be specifically related to a kind of micro-grid system peak load shifting method containing wind-solar-storage joint electricity generation system based on Stochastic Production Simulation.

Background technology

Along with the development of microgrid, distributed power source is more and more applied in microgrid, in distributed power source, the increase of wind-force Generate, Generation, Generator volt capacity of installed generator makes the possibility that in the change of microgrid load fluctuation and microgrid, conventional rack fault is stopped transport, these all can produce uncertain to load supply, the reliability of power supply can be subject to certain impact.

Microgrid due to its load little, the installed capacity be equipped with is also less, for ensureing that power supply improves the reliability of power supply, reply load fluctuation needs to be equipped with certain for subsequent use, coming from the point of common coupling be connected with bulk power grid for subsequent use more, namely, in the hypodynamic situation of electricity, supply of electric power is obtained from bulk power grid.Microgrid is divided into and is incorporated into the power networks and independent operating two kinds of operational modes, and when independent operating, cannot be connected with bulk power grid, when causing supply of electric power deficiency in microgrid, supply of electric power cannot meet.Now just need to install certain stand-by power supply additional, in case of need.

Reserve capacity mainly traditional fired power generating unit that can respond fast of tradition micro-grid system, powers when undercapacity.And install traditional regulating units in microgrid additional as there is certain deficiency, the regular hour of the start and stop needs of conventional rack, and when microgrid load is less, unit also can not be for subsequent use each other as bulk power grid, causes the waste of resource.

Along with the development of energy storage technology, energy-storage system also becomes one of selection of stand-by power supply in microgrid.Energy-storage system can utilize the characteristic of its fast charging and discharging, effectively oscillation suppression, and plays the effect of peak load shifting, thus improves the reliability of supply of electric power.

Because fired power generating unit is in different situations of exerting oneself, its economy run is different, equal consumed energy ratio is difference to some extent, the i.e. per unit fired power generating unit fuel consumption difference to some extent of exerting oneself, the use of energy-storage system, the operating point that original unit of exerting oneself can be enable to a certain extent comparatively economic runs, thus improves the economy of supply of electric power.

Energy-storage system, as the device of fast charging and discharging, is extremely adapted at carrying out in microgrid for subsequent use, can carries out peak load shifting in time, suppresses the fluctuation of wind speed.Meanwhile, also can play maintenance stable operation of unit, make it operate in economical operating point.

Energy-storage system joins in microgrid, when carries out discharge and recharge and also can have an impact to microgrid reliability, also can play the effect of peak load shifting simultaneously, and the use of energy-storage system should improve the reliability that microgrid is powered as much as possible, and reduces the peak-valley difference of microgrid load.

Stochastic Production Simulation is as a kind of in power system planning and power generation dispatching instrument of practicality, and it can be used to obtain the energy output of each unit and the reliability index of system, and reliability index comprises expected loss of energy EENS and loss of load probability LOLP.

Consider energy-storage system in prior art to join micro-grid system and carry out corresponding economy optimization, but do not consider while the reliability improving its power supply, realize peak load shifting.Therefore need to provide a kind of micro-grid system random production analog method containing wind-light storage, that is applied by Stochastic Production Simulation contains in the micro-grid system of wind-light storage, can obtain the reasonable disposition of how to carry out energy-storage system, to improve economy and reliability on the one hand; On the other hand, can draw and how reasonably should dispatch energy-storage system, to carry out peak load shifting, farthest reduce the peak-valley difference of load.

Summary of the invention

In order to overcome the defect of above-mentioned prior art, the invention provides a kind of based on Stochastic Production Simulation containing wind-light storage micro-grid system peak load shifting method.

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

Based on Stochastic Production Simulation containing a wind-light storage micro-grid system peak load shifting method, its improvements are: said method comprising the steps of:

I, the original loads data reading prediction in following 24 hours, wind power output value and photovoltaic go out force value;

II, determine equivalent load data, obtain original equivalent load curve;

III, determine expected loss of energy ENNS and loss of load probability LOLP;

IV, according to the expected loss of energy ENNS of required reduction or loss of load probability LOLP, determine charge-discharge electric power and the discharge electricity amount of energy-storage system, and formulate discharge and recharge strategy;

The peak load shifting effect that V, checking reach.

Further, described Step II comprises:

S201, by following formula determination equivalent load data:

P _eq＝P _org-P _wind-P _pv

Wherein, P _orgfor described original loads data, P _windfor described wind power output value, P _pvfor described photovoltaic goes out force value;

S202, form described original equivalent load curve f according to described equivalent load data ⁽⁰⁾.

Further, described Step II I comprises the following steps:

S301, by convolutional calculation, revise original lasting load curve;

S302, obtain revised equivalent load duration curve f ⁽ⁿ⁾(P), determine that maximum equivalent load is P _max+ C _s, wherein, C _sfor intrasystem total installation of generating capacity, P _maxfor the peak load in cycle T;

S303, determine expected loss of energy EENS and loss of load probability LOLP respectively by following formula:

$\mathrm{EENS}=T\underset{C_s}{\overset{P_{\max }+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

$\mathrm{LOLP}=\frac{t_L}{T}=f\left(C_s\right)$

Wherein, C _srepresent intrasystem total installation of generating capacity; P _max+ C _sfor maximum equivalent load; t _lfor the not enough duration of electric power.

Further, described step S301 comprises:

Determine that capacity is C _ithe availability factor of i-th generating set be p _i, determine the forced outage rate q of described generator _i=1-p _i;

After i-th generator on-load, determine that i-th generating set is loaded into the equivalent load duration curve after lasting load curve by following formula:

f ⁽ⁱ⁾(P)＝p _if ^(i-1)(P)+q _if ^(i-1)(P-C _i)

Wherein, C _irepresent the capacity of i-th generating set; p _irepresent the availability factor of i-th generating set; q _irepresent the forced outage rate of i-th generating set.

Further, described step IV comprises the following steps:

S401, according to reduction described loss of load probability LOLP determine energy storage system discharges power; Comprise the following steps:

According to the reducing amount of loss of load probability LOLP, determine the power length P of the correspondence of described reducing amount _disfor the maximum discharge power P of described energy-storage system _dis;

Determine that described energy-storage system needs the discharge electricity amount of release by following formula:

$E_{\mathrm{dis}}=T\underset{C_s}{\overset{P_{\mathrm{dis}}+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

In formula, P _disrepresent the maximum discharge power of energy-storage system, C _srepresent intrasystem total installation of generating capacity, f ⁽ⁿ⁾(P) equivalent load duration curve is represented; E _disrepresent the discharge electricity amount of energy-storage system, T represents simulation cycle;

S402, determine energy storage system discharges power according to reduction expected loss of energy EENS; Comprise the following steps:

To equivalent load duration curve f ⁽ⁿ⁾(P) carry out integral operation, obtain the function that following formula characterizes electric energy:

$E^n\left(P\right)=T\·{\∫}_0^P{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

Wherein, E ⁿ(P) electricity corresponding under equivalent load duration curve between load 0 to load P is represented; f ⁽ⁿ⁾(P) equivalent load duration curve is represented; T represents simulation cycle;

The maximum discharge power P of described energy-storage system is determined according to following formula _dis:

E ⁿ(P _dis)-E ⁿ(C _s)＝ΔEENS

Wherein, C _srepresent intrasystem total installation of generating capacity; Δ EENS represents the reducing amount of expected loss of energy EENS;

By following formula determination discharge electricity amount: $E_{\mathrm{dis}}=T\·\underset{0}{\overset{P_{\mathrm{dis}}}{\∫}}{f}^{\left(n\right)}\left(p\right)\mathrm{dP}$

In formula, P _disfor the maximum discharge power f of energy-storage system ⁽ⁿ⁾(P) equivalent load duration curve is represented; T represents simulation cycle;

S403, according to after the discharge power of the determination energy-storage system of step S401 or step S402 and discharge electricity amount, determine nominal discharge power and the rated capacity of described energy-storage system according to nargin coefficient;

S404, the discharge power determining energy-storage system and discharge electricity amount, formulate the discharge and recharge strategy of energy-storage system.

Further, described step S403 comprises the following steps:

S4031, according to discharge power P _dis, in conjunction with nargin coefficient as shown in the formula the nominal discharge power determining described energy-storage system:

P _dis,r＝P _dis/(1-α _dis)

Wherein, α _disfor electric discharge nargin coefficient;

S4032, in conjunction with electric energy loss as shown in the formula determining charge capacity:

E _ch＝E _dis/(1-γ)

Wherein, γ is electric energy loss rate;

S4033, Capacity Margin in conjunction with described energy-storage system, the rated capacity as shown in the formula determining energy-storage system:

E _dis,r＝E _ch/(1-β)

Wherein, β is nargin coefficient.

Further, in described step S404, discharge and recharge strategy comprises charge-discharge electric power sequence and discharge and recharge time series; Described step S404 comprises the following steps:

S4041, time interval according to load prediction, to the not enough duration segmentation of electric power;

The discharge power of S4042, acquisition day part;

S4043, acquisition Spike train, described Spike train comprises: the discharge power sequence of the discharge power of day part ${\stackrel{\‾}{P}}_{\mathrm{dis}}=[P_{\mathrm{dis}}^1,P_{\mathrm{dis}}^2,...P_{\mathrm{dis}}^k,...P_{\mathrm{dis}}^m,]$ With electric discharge duration sequence ${\stackrel{\‾}{t}}_{\mathrm{dis}}=[t_{\mathrm{dis}}^1,t_{\mathrm{dis}}^2,...t_{\mathrm{dis}}^k,...t_{\mathrm{dis}}^m,],$ i＝1,2,…,m；

From high to low whole Spike train is discharged according to load, realize peak clipping;

S4044, in conjunction with electric energy loss rate determination charge power P _ch=P _dis/ (1-γ), γ is electric energy loss rate;

Determine the charge power sequence formed when charging

Determine the duration sequence that charges:

The loaded portion not carrying out peak clipping is arranged from low to high, according to charge power distribution series charge from big to small, realize fill out paddy;

S4045, formulate described discharge and recharge strategy after, the specified charge power as shown in the formula in conjunction with nargin determination energy-storage system:

P _ch,r＝P _ch/(1-α _ch)

In formula, α _chfor the nargin coefficient of charging.

Further, in described step V, after adopting energy-storage system discharge and recharge operation to carry out peak load shifting according to step S404, the new sequential load curve obtained calculates peak-valley difference, and compare with the peak-valley difference of the sequential load curve not carrying out peak load shifting, determine that reduction loss of load probability or expected loss of energy are on the impact reducing peak-valley difference.

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

1, original Stochastic Production Simulation is mainly used in calculating power supply reliability index: expected loss of energy or loss of load probability and the energy output of each unit in simulation cycle, method of the present invention is then based on Stochastic Production Simulation technology, the reliability improved is needed according to micro-grid system, in conjunction with the equivalent load duration curve in Stochastic Production Simulation, determine in microgrid and need to be equipped with energy-storage system rated power and capacity, and formulated energy-storage system discharge and recharge strategy;

2, the power supply reliability index that obtains of original Stochastic Production Simulation: expected loss of energy or loss of load probability general only for assessment of power supply reliability, method of the present invention is by reducing this two indices: expected loss of energy or loss of load probability, determine the corresponding power and the capacity that need the energy-storage system be equipped with in micro-grid system, comprising: maximum charge-discharge electric power, specified charge-discharge electric power and rated capacity.

3, in original Stochastic Production Simulation, equivalent load duration curve is only for calculating expected loss of energy or loss of load probability and the energy output of each unit in simulation cycle.Method of the present invention formulates energy-storage system discharge and recharge strategy based on equivalent load duration curve, include power sequence and time series, power sequence and time series are size and the duration of the power of the discharge and recharge when, and equivalent load duration curve are not done this application in original Stochastic Production Simulation;

4, in prior art the raising of power supply reliability level and load peak load shifting relation little, method of the present invention improves the power supply reliability level of microgrid, and then has carried out peak load shifting to the load of micro-grid system.

Compared with prior art, present invention employs the determination that equivalent load duration curve simple and clear in Stochastic Production Simulation carries out energy-storage system charge-discharge electric power and capacity, and formulate discharge and recharge strategy in conjunction with this curve, whole process is simple, and together with raising power supply reliability is combined effectively with micro-grid system load peak load shifting, breach deficiency of the prior art.

Accompanying drawing explanation

Fig. 1 is the flow chart of the inventive method;

Fig. 2 is original temporal load curve;

Fig. 3 is that blower fan is exerted oneself timing curve;

Fig. 4 is that photovoltaic is exerted oneself timing curve;

Fig. 5 is equivalent sequential load curve;

Fig. 6 is the original lasting load curve formed after obtaining equivalent sequential load curve;

Fig. 7 is the schematic diagram forming final equivalent load duration curve;

Fig. 8 illustrates the schematic diagram calculating loss of load probability and expected loss of energy;

Fig. 9 is the schematic diagram determining discharge power;

Figure 10 is the schematic diagram formulating Spike train;

Figure 11 is the partial enlarged drawing of Figure 10;

Figure 12 is the partial enlarged drawing of MN section in Figure 11.

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described.

As shown in Figure 1, Fig. 1 is the flow chart of the inventive method; Method of the present invention be a kind of based on Stochastic Production Simulation containing wind-light storage micro-grid system peak load shifting method, the method comprises the following steps:

Step one, the original loads data reading prediction in following a day, wind power output value and photovoltaic go out force value;

Step 2, determine equivalent load data, obtain original equivalent load curve;

Step 3, determine expected loss of energy ENNS and loss of load probability LOLP;

Step 4, according to the expected loss of energy ENNS of required reduction and loss of load probability LOLP, determine charge-discharge electric power and the charge/discharge electricity amount of energy-storage system, and formulate discharge and recharge strategy further;

The peak load shifting effect that step 5, checking reach.

In step one, read original loads data, wind power output value and photovoltaic in following one day and go out the predicted value of force value, carry out micro-grid system Stochastic Production Simulation according to described predicted value.

In step 2, specifically comprise following:

S201, as shown in the formula determining equivalent load data:

P _eq＝P _org-P _wind-P _pv

Wherein, P _orgfor described original loads data, P _windfor described wind power output value, P _pvfor described photovoltaic goes out force value;

S202, form described original equivalent load curve f according to described equivalent load data ⁽⁰⁾.

As shown in Figure 6, Fig. 6 is the original lasting load curve formed after the equivalent sequential load curve obtained, for representing that load is greater than the duration of a certain value, as any point (P on curve, t) represent that load is more than or equal to the duration t of load P, i.e. t=F (P).Cycle T, divided by the duration, obtains Probability p=f (P)=F (P)/T that load is more than or equal to P.In figure, P _maxfor the peak load in simulation cycle T.

In step 3, determine expected loss of energy ENNS and loss of load probability LOLP; Step 3 specifically comprises the following steps:

S301, first, consider the random shut down condition of each generating set, by convolutional calculation, revise original lasting load curve, method is:

Determine that capacity is C _ithe availability factor of i-th generating set be p _i, determine the forced outage rate q of described generator _i=1-p _i;

After i-th generator on-load, determine i-th generating set be loaded into the equivalent load duration curve after lasting load curve as shown in the formula:

f ⁽ⁱ⁾(P)＝p _if ^(i-1)(P)+q _if ^(i-1)(P-C _i)

Wherein, C _irepresent the capacity of i-th generating set; p _irepresent the availability factor of i-th generating set; q _irepresent the forced outage rate of i-th generating set; After convolutional calculation, the equivalent load duration curve f being loaded with last generating set can be obtained ⁽ⁿ⁾(P), as shown in Figure 7.

S302, obtain final equivalent load duration curve f ⁽ⁿ⁾(P), now maximum equivalent load is P _max+ C _s, as shown in Figure 7, C _sfor intrasystem total installation of generating capacity, P _maxfor the peak load in cycle T;

S303, as shown in Figure 8, in Fig. 8, show original lasting load curve f ⁽⁰⁾and final equivalent load duration curve f (P) ⁽ⁿ⁾(P), in conjunction with this figure, as shown in the formula calculating expected loss of energy EENS and loss of load probability LOLP respectively:

$\mathrm{EENS}=T\underset{C_s}{\overset{P_{\max }+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

$\mathrm{LOLP}=\frac{t_L}{T}=f\left(C_s\right)$

Wherein, C _srepresent intrasystem total installation of generating capacity; P _max+ C _sfor maximum equivalent load; t _lfor intrasystem total installation of generating capacity C _sall after power supply, cannot duration of power pack, also claim electric power not enough duration.

Improve power supply reliability and comprise two reference indexs: loss of load probability LOLP, expected loss of energy EENS, method of the present invention is for by reducing above-mentioned two reliability indexs, one of them improves power supply reliability.In step 4, the method improving power supply reliability according to two indices is all described.

Step 4, according to described expected loss of energy ENNS or loss of load probability LOLP, determine the discharge measuring of energy-storage system.

In practice, which is decided according to the actual requirements in concrete employing, and reduces the target that any one index all can reach raising power supply reliability.

Step 4 specifically comprises the following steps:

S401, according to reduction described loss of load probability LOLP determine energy storage system discharges power; Comprise the following steps:

As shown in Figure 9, Fig. 9 is the schematic diagram determining energy-storage system power and capacity; When loss of load probability needs to be reduced to D point from B point, loss of load probability is now LOLP ¹, namely the former loss of load probability calculated is from LOLP ⁰be reduced to LOLP ¹; Now, the power length of corresponding energy-storage system is P _dis, according to this as the discharge power maximum of energy-storage system.And calculate the discharge electricity amount of energy-storage system needs release accordingly, be shown below:

$E_{\mathrm{dis}}=T\underset{C_s}{\overset{P_{\mathrm{dis}}+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

Wherein, P _disrepresent the maximum discharge power of energy-storage system, C _srepresent intrasystem total installation of generating capacity, f ⁽ⁿ⁾(P) equivalent load duration curve is represented; E _disrepresent the discharge electricity amount of energy-storage system, i.e. the area of ABDC in Figure 10, Δ EENS=E _dis.

Above-mentioned LOLP ¹can determine according to the needs improving power supply reliability.

S402, determine energy storage system discharges power according to reduction expected loss of energy EENS; Comprise the following steps:

Determine energy storage system discharges power according to reduction expected loss of energy EENS, first need equivalent load duration curve f ⁽ⁿ⁾(P) carry out integral operation and obtain F ⁽ⁿ⁾(P), thus obtain characterize electric energy function as shown in the formula:

$E^n\left(P\right)=T\·{\∫}_0^P{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

This formula represents electricity corresponding under equivalent load duration curve between 0 to P.

By solving equation E ⁿ(P _dis)-E ⁿ(C _s)=Δ EENS, can calculate the maximum discharge power P of energy-storage system _dis;

Wherein, C _srepresent intrasystem total installation of generating capacity; Δ EENS represents the expected loss of energy that needs reduce.

In practice, due to the discretization of the measurement of load, equivalent load duration curve can not be the function that can amass continuously, therefore obtain by enclosing area-method in practice, as shown in Figure 10, mobile line segment CD, with make ABCD the electricity surrounded representated by area equal the expected loss of energy Δ EENS that needs to reduce, thus maximum discharge power P can be determined _dis.

Above-mentioned Δ EENS can determine according to the needs improving power supply reliability.

S403, respectively by after the discharge power of two kinds of situation determination energy-storage systems of step S401 or step S402 and discharge electricity amount, consider certain nargin coefficient and then nominal discharge power and the capacity of energy-storage system can be determined; Comprise the following steps:

S4031, according to determining maximum discharge power P _dis, in conjunction with nargin coefficient as shown in the formula the nominal discharge power determining described energy-storage system:

P _dis,r＝P _dis/(1-α _dis)

Wherein, α _disfor electric discharge nargin coefficient;

S4032, in conjunction with electric energy loss as shown in the formula determining charge capacity:

E _ch＝E _dis/(1-γ)

Wherein, γ is electric energy loss rate;

S4033, Capacity Margin in conjunction with described energy-storage system, as shown in the formula determining energy-storage system rated capacity:

E _dis,r＝E _ch/(1-β)

Wherein, β is nargin coefficient.

S404, the charge-discharge electric power determining energy-storage system and electricity, formulate the discharge and recharge strategy of energy-storage system.

Consider that sequential load curve and equivalent load duration curve are discretization distribution in practice, therefore when formulating electric discharge strategy, discharge power is also discretization distribution; As shown in Figure 10, Figure 10 is the schematic diagram formulating energy-storage system discharge and recharge strategy.

In step S404, formulate discharge and recharge strategy, described discharge and recharge strategy comprises corresponding charge-discharge electric power sequence and discharge and recharge time series; Specifically comprise the following steps:

After the charge-discharge electric power determining energy-storage system and electricity, next step can according to the schematic diagram of charge-discharge electric power determining energy-storage system, and namely Figure 10 formulates the discharge and recharge strategy of energy-storage system.

Sequential load curve and equivalent load duration curve are discretization distribution in practice, and therefore when formulating electric discharge strategy, the power of electric discharge is also discretization distribution.As shown in Figure 10, according to the time interval of load prediction, AB section is divided into:

k＝[t _AB/t _c]

In formula, t _aBfor the time span of AB section correspondence, the total installation of generating capacity C namely in said system _sall after power supply, cannot duration of power pack, also claim electric power not enough duration.T _cfor predicting the time interval of load, the integer be more than or equal to is got in [] expression.

In order to further illustrate the process formulating electric discharge strategy, by Figure 10 partial enlargement, as shown in figure 11.In order to illustrate Spike train form in power sequence and time series, being described especially exemplified by routine EF section, is the time span t of EF section correspondence for electric discharge duration _eF, discharge power is P _fH, discharge power often a bit of in A to B and electric discharge duration can be determined accordingly, for duration to two and above discharge power, then carry out segment processing, MN section is as shown in figure 11 corresponding two different power, its electric discharge duration t _mNalso be divided into corresponding two sections, namely as shown in enlarged drawing Figure 12 of Figure 11, duration divides in order to two sections of t _mUand t _uN, and discharge power corresponds to P respectively _mRand P _nU.

The rest may be inferred, can form a discharge power sequence i=1,2 ..., m, also correspond to an electric discharge duration sequence therewith both together constitute a Spike train, are then discharged by whole Spike train from high to low according to load, thus realize peak clipping.

Because the electric energy stored in charge and discharge process has loss, therefore the determination of charge power needs to consider electric energy loss rate, and charge power is determined as follows:

P _ch=P _dis/ (1-γ), wherein, γ is electric energy loss rate, determines charge power with this, effectively can simplify charging strategy.

The charge power sequence formed during charging draw according to the following formula:

${\stackrel{\‾}{P}}_{\mathrm{ch}}={\stackrel{\‾}{P}}_{\mathrm{dis}}/(1-\mathrm{\γ})$

And the duration sequence that charges is identical with electric discharge duration sequence:

${\stackrel{\‾}{t}}_{\mathrm{ch}}={\stackrel{\‾}{t}}_{\mathrm{dis}}$

The loaded portion not carrying out peak clipping is arranged from low to high, according to charge power distribution series charge from big to small, namely fill out paddy.

After formulating charging strategy, also need the specified charge power determining energy-storage system, in order to meet certain nargin, the specified charge power of energy-storage system is determined as follows:

P _ch,r＝P _ch/(1-α _ch)

In formula, α _chfor the nargin coefficient of charging.

In step 5, after adopting energy-storage system discharge and recharge operation to carry out peak load shifting according to step S404, the new sequential load curve obtained calculates peak-valley difference, and compare with the peak-valley difference of the sequential load curve not carrying out peak load shifting, determine that reduction loss of load probability or expected loss of energy are on the impact reducing peak-valley difference.

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. based on Stochastic Production Simulation containing a wind-light storage micro-grid system peak load shifting method, it is characterized in that: said method comprising the steps of:

I, the original loads data reading prediction in following 24 hours, wind power output value and photovoltaic go out force value;

II, determine equivalent load data, obtain original equivalent load curve;

III, determine expected loss of energy ENNS and loss of load probability LOLP;

IV, according to the expected loss of energy ENNS of required reduction or loss of load probability LOLP, determine charge-discharge electric power and the discharge electricity amount of energy-storage system, and formulate discharge and recharge strategy;

The peak load shifting effect that V, checking reach.

2. the method for claim 1, is characterized in that: described Step II comprises:

S201, by following formula determination equivalent load data:

P _eq＝P _org-P _wind-P _pv

Wherein, P _orgfor described original loads data, P _windfor described wind power output value, P _pvfor described photovoltaic goes out force value;

S202, form described original equivalent load curve f according to described equivalent load data ⁽⁰⁾.

3. the method for claim 1, is characterized in that: described Step II I comprises the following steps:

S301, by convolutional calculation, revise original lasting load curve;

S302, obtain revised equivalent load duration curve f ⁽ⁿ⁾(P), determine that maximum equivalent load is P _max+ C _s, wherein, C _sfor intrasystem total installation of generating capacity, P _maxfor the peak load in cycle T;

S303, determine expected loss of energy EENS and loss of load probability LOLP respectively by following formula:

$\mathrm{EENS}=T\underset{C_s}{\overset{P_{\max }+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

$\mathrm{LOLP}=\frac{t_L}{T}=f\left(C_s\right)$

Wherein, C _srepresent intrasystem total installation of generating capacity; P _max+ C _sfor maximum equivalent load; t _lfor the not enough duration of electric power.

4. method as claimed in claim 3, is characterized in that: described step S301 comprises:

Determine that capacity is C _ithe availability factor of i-th generating set be p _i, determine the forced outage rate q of described generator _i=1-p _i;

After i-th generator on-load, determine that i-th generating set is loaded into the equivalent load duration curve after lasting load curve by following formula:

f ⁽ⁱ⁾(P)＝p _if ^(i-1)(P)+q _if ^(i-1)(P-C _i)

Wherein, C _irepresent the capacity of i-th generating set; p _irepresent the availability factor of i-th generating set; q _irepresent the forced outage rate of i-th generating set.

5. the method for claim 1, is characterized in that: described step IV comprises the following steps:

S401, according to reduction described loss of load probability LOLP determine energy storage system discharges power; Comprise the following steps:

According to the reducing amount of loss of load probability LOLP, determine the power length P of the correspondence of described reducing amount _disfor the maximum discharge power P of described energy-storage system _dis;

Determine that described energy-storage system needs the discharge electricity amount of release by following formula:

$E_{\mathrm{dis}}=T\underset{C_s}{\overset{P_{\mathrm{dis}}+C_s}{\∫}}{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

In formula, P _disrepresent the maximum discharge power of energy-storage system, C _srepresent intrasystem total installation of generating capacity, f ⁽ⁿ⁾(P) equivalent load duration curve is represented; E _disrepresent the discharge electricity amount of energy-storage system, T represents simulation cycle;

S402, determine energy storage system discharges power according to reduction expected loss of energy EENS; Comprise the following steps:

To equivalent load duration curve f ⁽ⁿ⁾(P) carry out integral operation, obtain the function that following formula characterizes electric energy:

$E^n\left(P\right)=T\·{\∫}_0^P{f}^{\left(n\right)}\left(P\right)\mathrm{dP}$

Wherein, E ⁿ(P) electricity corresponding under equivalent load duration curve between load 0 to load P is represented; f ⁽ⁿ⁾(P) equivalent load duration curve is represented; T represents simulation cycle;

The maximum discharge power P of described energy-storage system is determined according to following formula _dis:

E ⁿ(P _dis)-E ⁿ(C _s)＝ΔEENS

Wherein, C _srepresent intrasystem total installation of generating capacity; Δ EENS represents the reducing amount of expected loss of energy EENS;

By following formula determination discharge electricity amount: $E_{\mathrm{dis}}=T\·\underset{0}{\overset{P_{\mathrm{dis}}}{\∫}}{f}^{\left(n\right)}\left(p\right)\mathrm{dP}$

In formula, P _disfor the maximum discharge power f of energy-storage system ⁽ⁿ⁾(P) equivalent load duration curve is represented; T represents simulation cycle;

S403, according to after the discharge power of the determination energy-storage system of step S401 or step S402 and discharge electricity amount, determine nominal discharge power and the rated capacity of described energy-storage system according to nargin coefficient;

S404, the discharge power determining energy-storage system and discharge electricity amount, formulate the discharge and recharge strategy of energy-storage system.

6. method as claimed in claim 5, is characterized in that: described step S403 comprises the following steps:

S4031, according to discharge power P _dis, in conjunction with nargin coefficient as shown in the formula the nominal discharge power determining described energy-storage system:

P _dis,r＝P _dis/(1-α _dis)

Wherein, α _disfor electric discharge nargin coefficient;

S4032, in conjunction with electric energy loss as shown in the formula determining charge capacity:

E _ch＝E _dis/(1-γ)

Wherein, γ is electric energy loss rate;

S4033, Capacity Margin in conjunction with described energy-storage system, the rated capacity as shown in the formula determining energy-storage system:

E _dis,r＝E _ch/(1-β)

Wherein, β is nargin coefficient.

7. method as claimed in claim 5, is characterized in that: in described step S404, discharge and recharge strategy comprises charge-discharge electric power sequence and discharge and recharge time series; Described step S404 comprises the following steps:

S4041, time interval according to load prediction, to the not enough duration segmentation of electric power;

The discharge power of S4042, acquisition day part;

S4043, acquisition Spike train, described Spike train comprises: the discharge power sequence of the discharge power of day part ${\stackrel{\‾}{P}}_{\mathrm{dis}}=[P_{\mathrm{dis}}^1,P_{\mathrm{dis}}^2,...P_{\mathrm{dis}}^k,...P_{\mathrm{dis}}^m,]$ With electric discharge duration sequence ${\stackrel{\‾}{t}}_{\mathrm{dis}}=[t_{\mathrm{dis}}^1,t_{\mathrm{dis}}^2,...t_{\mathrm{dis}}^k,...t_{\mathrm{dis}}^m,],$ i＝1,2,…,m；

From high to low whole Spike train is discharged according to load, realize peak clipping;

S4044, in conjunction with electric energy loss rate determination charge power P _ch=P _dis/ (1-γ), γ is electric energy loss rate;

Determine the charge power sequence formed when charging

Determine the duration sequence that charges:

The loaded portion not carrying out peak clipping is arranged from low to high, according to charge power distribution series charge from big to small, realize fill out paddy;

S4045, formulate described discharge and recharge strategy after, the specified charge power as shown in the formula in conjunction with nargin determination energy-storage system:

P _ch,r＝P _ch/(1-α _ch)

In formula, α _chfor the nargin coefficient of charging.

8. the method for claim 1, it is characterized in that: in described step V, after adopting energy-storage system discharge and recharge operation to carry out peak load shifting according to step S404, the new sequential load curve obtained calculates peak-valley difference, and compare with the peak-valley difference of the sequential load curve not carrying out peak load shifting, determine that reduction loss of load probability or expected loss of energy are on the impact reducing peak-valley difference.