CN103166248B - Engineering configuration method of independent wind-diesel-storage micro grid system capacity - Google Patents

Abstract

The invention provides an engineering configuration method of independent wind-diesel-storage micro grid system capacity. The engineering configuration method includes the following steps: A, collecting local actual measurement loads and wind speed history data, and constructing a load and wind speed prediction curve of a whole life cycle according to a timing sequence mode; and B, performing preliminary model selection on a wind generation set, a diesel generation set and an energy storing device according to the curve obtained in the step A, and determining unit capacity and quantity limiting value of each distributed power source. The engineering configuration method of the independent wind-diesel-storage micro grid system capacity can accurately select configuration of the independent wind-diesel-storage micro grid system capacity, optimizes the capacity configuration, provides practical and effective scientific bases for planning and design of independent wind-diesel-storage micro grid system engineering, can reduce power supply cost of a system to the minimum on the premise of satisfying load requirements, and is simple in method and suitable for engineering calculation.

Description

A kind of engineering collocation method of independent wind-Chai-storage micro-grid system capacity

Technical field

The present invention relates to micro-power grid application technical field, particularly relate to a kind of engineering collocation method of independent wind-Chai-storage micro-grid system capacity.

Background technology

According to " planning of regenerative resource Long-and Medium-term Development " report, by 2012, China still had up to ten million population distributions at areas without electricity, because these areas are away from public electric wire net, while adopting conventional supply power mode, be faced with the problems such as the large and construction cost of remote conveying electrical loss is high.In the abundant remote mountain areas of wind resource, the area such as isolated island, micro-electrical network is with features such as its small investment, instant effect, flexible structures, just paid close attention to day by day widely, in these areas, can suit measures to local conditions to build the micro-mains supply system of an independent wind-Chai-store up, thereby solve local resident's electrical problem, in improving clean energy resource utilance, effectively reduce the pollution to environment, thereby further drive local economic development.

For the planning and designing of independent wind-Chai-storage micro-grid system, reasonably power supply type selecting and constant volume are that first it need the problem solving.At present, the research of this respect determines in situation mainly for wind turbine pool-size, smoothly to exert oneself or peak load shifting carries out stored energy capacitance optimization as object, the power supply of whole micro-grid system is not discussed and distributed rationally; Consider the ideal mathematics model of each distributed power source of the factors such as wind speed, ambient temperature, battery charging and discharging rate and service life by foundation, minimum as target function taking gross investment, taking power supply reliability as constraints, determine the allocation optimum of system power supply, but these researchs are more the advances that too stresses algorithm, thereby cause engineering practice not strong.

As can be seen here, the existing optimal configuration method capable for micro-grid system power supply, in use there is obvious deficiency and defect, urgently further improve, therefore, how to found a kind of guarantee on the reliable and stable basis of micro-grid system, can accurately choose micro-grid system capacity, the economy of the each distributed power source of comprehensive assessment, make every effort to micro-grid system life cycle management power supply cost minimum, calculate simply, be applicable to very much the engineering collocation method of independent wind-Chai-storage micro-grid system capacity of engineering calculation, one of real important topic that belongs to current research and development.

Summary of the invention

The object of this invention is to provide a kind of engineering collocation method of independent wind-Chai-storage micro-grid system capacity, it is being ensured on the reliable and stable basis of micro-grid system, can accurately choose micro-grid system capacity, economy that can the each distributed power source of comprehensive assessment, realize distributed power source allocation optimum, make micro-grid system life cycle management power supply cost minimum, thereby overcome the deficiencies in the prior art.

For solving the problems of the technologies described above, the engineering collocation method of a kind of independent wind-Chai-storage of the present invention micro-grid system capacity, comprise the following steps: A, collect local actual measurement load and wind speed historical data, according to time sequential mode structure life cycle management load and forecasting wind speed curve; B, the curve obtaining according to steps A are sent out unit and the preliminary type selecting of energy storage device to wind-powered electricity generation unit, bavin, determine cell capability and the quantity limit value of each distributed power source; C, the curve obtaining according to steps A are determined the peak-peak load of micro-grid system at life cycle management, send out single-machine capacity and the quantity limit value of unit, and calculate this present worth of system synthesis of initial micro-grid system life cycle management according to N-1 principle configuration bavin; D, wind turbine pool-size is initialized as to zero; E, stored energy capacitance is initialized as to zero; F, the curve obtaining according to steps A carry out the emulation of micro-grid system life cycle management; G, under the edge-restraint condition of micro-grid system and each distributed power source, calculate the total cost present worth of micro-grid system life cycle management system under current configuring condition; H, the total cost present worth that step G is obtained and the front total cost present worth comparison once obtaining, preserve smaller value wherein, and export the capacity configuration scheme under current minimum total cost present worth; I, judge whether the capacity of energy storage device reaches the definite quantity limit value of step B, performs step K if reach, if do not reach by setting capacity that step-length increases energy storage device until enter step J after meeting N-1 principle; J, judge whether the capacity of energy storage device exceeds the definite quantity limit value of step B, performs step in this way K, as otherwise return to step F; K, judge that whether wind turbine pool-size reaches the definite quantity limit value of step B, performs step L in this way; As otherwise increase wind turbine pool-size return to step e by setting step-length; L, judge that bavin sends out unit capacity and whether reach operation lower limit, perform step in this way N, as otherwise reduce bavin and send out unit capacity and enter step M by setting step-length; M, judge whether current configuration meets N-1 principle, if met, return to step D, if do not met, enter step N; N, process ends, send out unit and capacity of energy storing device allocation plan taking the allocation plan finally exported as optimum wind-powered electricity generation unit, bavin.

The target function of the total cost present worth in described step G is: wherein, the species number that N is distributed power source, n _irepresent the quantity of i kind distributed power source, C _pirepresent the first dress present value of cost of i kind distributed power source, C _mirepresent the life cycle management maintenance cost present worth of i kind distributed power source, C _firepresent the life cycle management fuel cost present worth of i kind distributed power source, C _rirepresent the life cycle management replacement cost present worth of i kind distributed power source.

Described C _pi=K _pi× P _i, wherein, K _pirepresent the power cost coefficient of i kind distributed power source, P _irepresent the specified single-machine capacity of i kind distributed power source.

Described $\begin{array}{c}{C}_{\mathrm{Mi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Mi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Mi}}\left(n\right){=K}_{\mathrm{Mi}}\left(n\right)\×C_{\mathrm{Pi}}\end{array},$

Wherein, C _mi(n) represent the maintenance cost of i kind distributed power source at n, K _mi(n) represent the maintenance cost coefficient of i kind distributed power source at n, y _pthe life cycle that represents micro-electrical network project, r represents interest rate.

Described $\begin{array}{c}{C}_{\mathrm{Fi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Fi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Fi}}\left(n\right)=K_{\mathrm{Fi}}\left(n\right)\×{\∫}_0^{8760}{P}_i(n,t)\mathrm{dt}\end{array},$

Wherein, C _fi(n) represent the fuel cost of i kind distributed power source at n, K _fi(n) represent the fuel cost coefficient of i kind distributed power source at n, P _i(n, t) represents the sequential operate power of i kind distributed power source at n, and r represents interest rate, y _prepresent the life cycle of micro-electrical network project.

Described $\begin{array}{c}{C}_{\mathrm{Ri}}=\underset{n=1}{\overset{m}{\mathrm{\Σ}}}{K}_{\mathrm{Ri}}\left(n\right)\×C_{\mathrm{Pi}}\×{(1+r)}^{-n}\\ m=\frac{y_P}{y_{\mathrm{Pi}}}-1\end{array},$

Wherein, m represents that i kind distributed power source needs the number of times of resetting and replacing, K in the project cycle _ri(n) represent the replacement cost coefficient of i kind distributed power source at n, y _prepresent the life cycle of micro-electrical network project, y _pirepresent the life cycle of i kind distributed power source, r represents interest rate.

Constraints in described step G comprises power supply units limits, specifically comprises:

$\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{n}_i{\×P}_i\left(t\right)=P_{\mathrm{Load}}\left(t\right),$

P _imin≤P _i(t)≤P _imax，

t _oni≥t _onimin，

t _offi≥t _offimin，

Wherein, P _i(t) the sequential operate power of expression i kind distributed power source, P _load(t) represent sequential load, P _iminrepresent the minimum stable operation power of i kind distributed power source, P _imaxrepresent the maximum stable operate power of i kind distributed power source, t _onirepresent the continuous operating time of i kind distributed power source, t _oniminrepresent the minimum continuous operating time of i kind distributed power source, t _offirepresent the continuous downtime of i kind distributed power source, t _offiminrepresent the continuous downtime of minimum of i kind distributed power source, n _irepresent the quantity of i kind distributed power source.

Described constraints also comprises that energy storage device discharges and recharges constraints

SOC _min≤SOC≤SOC _max，

Wherein, SOC represents the capacity status of energy storage device, SOC _minrepresent the lower bound of capacity of energy storage device, SOC _maxrepresent the maximum size of energy storage device.

Described constraints also comprises power supply reliability constraints

$R_{\mathrm{LPSP}}=\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{LPSP}}\left(t\right)/\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{Load}}\left(t\right)\≤R_{\mathrm{LPSP}\max },$

Wherein, R _lPSPthe ratio of expression system short of electricity time and total power-on time, P _lPSP(t) the sequential short of electricity power of expression system, P _load(t) represent sequential load, R _lPSPmaxthe maximum short of electricity rate that allows of expression system.

N-1 principle in described step C is at any time all must be higher than peak load demand according to the guarantee generate output in system, wherein, ensure generate output be defined as system installed capacity and maximum generation unit capacity difference 90%.

Adopt after above technical scheme, the present invention has following useful technique effect compared with the prior art:

1, the engineering collocation method of independence wind-Chai-storage micro-grid system capacity of the present invention, according to actual measurement wind speed and load time series data, taking the boundary constraint of micro-grid system and each distributed power source as basis, set up micro-grid system total cost present worth model based on life cycle management, can choose accurately the capacity configuration of independent wind-Chai-storage micro-grid system, optimizing capacity configuration, for the planning and designing of independent wind-Chai-storage micro-grid system engineering provide the scientific basis of practicability and effectiveness;

2, the engineering collocation method of independence wind-Chai-storage micro-grid system capacity of the present invention, under the prerequisite that meets workload demand, can drop to the power supply cost of system minimumly, and method is very simple, is applicable to very much engineering calculation.

Below by drawings and Examples, technical scheme of the present invention is described in further detail.

Brief description of the drawings

Above-mentioned is only the general introduction of technical solution of the present invention, and in order to better understand the present invention, below in conjunction with accompanying drawing and embodiment, the present invention is described in further detail.

Fig. 1 is the engineering collocation method flow chart of a kind of independent wind-Chai-storage of the present invention micro-grid system capacity.

Embodiment

Refer to shown in Fig. 1, the engineering collocation method flow process of independence wind-Chai-storage micro-grid system capacity of the present invention, propose maintenance cost present worth, fuel cost present worth and the replacement cost present worth of the first dress present value of cost of each distributed power source, life cycle management to count the target function of this present worth of system synthesis of life cycle management, meeting on the basis of the indexs such as power supply units limits, battery charging and discharging restriction and power supply reliability, make the system power supply cost of micro-grid system life cycle management minimum.

The engineering collocation method of a kind of independent wind-Chai-storage of the present invention micro-grid system capacity, comprises the following steps:

Step 1: collect local actual measurement load data and wind speed historical data, according to time sequential mode construct load and the forecasting wind speed curve of its life cycle management, and using this as design basis.

Step 2: the curve obtaining according to step 1, analyze a year equivalence for the average load of its life cycle management and peak load and wind-powered electricity generation unit and completely send out hourage, subsequent step will be based on this, wind-powered electricity generation unit, bavin are sent out to unit and energy storage device carries out type selecting, determine cell capability and the quantity limit value of each distributed power source.

Step 3: the curve obtaining according to step 1 is determined the peak-peak load of micro-grid system in life cycle management, send out single-machine capacity and the quantity limit value of unit according to N-1 principle configuration bavin, and calculate this present worth of system synthesis of the life cycle management of initial micro-grid system.

Wherein, this present worth of system synthesis of the micro-grid system life cycle management under the current configuration of target function is

$C_{\mathrm{CV}}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{n}_i\×(C_{\mathrm{Pi}}+C_{\mathrm{Mi}}+C_{\mathrm{Fi}}+C_{\mathrm{Ri}}),$

C _cVrepresent this present worth of system synthesis of micro-grid system life cycle management; N represents the kind of distributed power source; n _irepresent the quantity of i kind distributed power source; C _pirepresent the first dress present value of cost of i kind distributed power source; C _mirepresent the life cycle management maintenance cost present worth of i kind distributed power source; C _firepresent the life cycle management fuel cost present worth of i kind distributed power source; C _rirepresent the life cycle management replacement cost present worth of i kind distributed power source;

Further, just filling present value of cost is

C _Pi＝K _Pi×P _i

K _pirepresent the power cost coefficient of i kind distributed power source; P _irepresent the specified single-machine capacity of i kind distributed power source.

Life cycle management maintenance cost present worth is

$\begin{array}{c}{C}_{\mathrm{Mi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Mi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Mi}}\left(n\right){=K}_{\mathrm{Mi}}\left(n\right)\×C_{\mathrm{Pi}}\end{array}$

C _mi(n) represent the maintenance cost of i kind distributed power source at n; K _mi(n) represent the maintenance cost coefficient of i kind distributed power source at n; y _prepresent the life cycle of micro-electrical network project; R represents interest rate.

Life cycle management fuel cost present worth is

$\begin{array}{c}{C}_{\mathrm{Fi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Fi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Fi}}\left(n\right)=K_{\mathrm{Fi}}\left(n\right)\×{\∫}_0^{8760}{P}_i(n,t)\mathrm{dt}\end{array}$

C _fi(n) represent the fuel cost of i kind distributed power source at n; K _fi(n) represent the fuel cost coefficient of i kind distributed power source at n; P _i(n, t) represents the sequential operate power of i kind distributed power source at n.

Life cycle management replacement cost present worth refers in the project cycle time limit, as system inner assembly reaches its end-of-life time limit, needs its replacement of resetting.

Life cycle management replacement cost present worth is

$\begin{array}{c}{C}_{\mathrm{Ri}}=\underset{n=1}{\overset{m}{\mathrm{\Σ}}}{K}_{\mathrm{Ri}}\left(n\right)\×C_{\mathrm{Pi}}\×{(1+r)}^{-n}\\ m=\frac{y_P}{y_{\mathrm{Pi}}}-1\end{array}$

M represents that i kind distributed power source needs the number of times of resetting and replacing in the project cycle; K _ri(n) represent the replacement cost coefficient of i kind distributed power source at n; y _pirepresent the life cycle of i kind distributed power source, r represents interest rate.

N-1 principle refers at any time all must be higher than peak load demand according to the guarantee generate output in system, and ensure generate output be defined as system installed capacity and maximum generation unit capacity difference 90%.

Step 4: wind turbine pool-size is initialized as zero;

Step 5: stored energy capacitance is initialized as zero;

Step 6: carry out the emulation of micro-grid system life cycle management according to the prediction load curve of steps A;

Step 7: calculate respectively the first dress present value of cost under current configuration, maintenance cost present worth, fuel cost present worth and the replacement cost present worth of life cycle management under the edge-restraint condition of micro-grid system and each distributed power source, thereby obtain this present worth of system synthesis of micro-grid system life cycle management.

Wherein, constraints comprises power supply units limits, battery charging and discharging constraint, power supply reliability constraint.

Power supply units limits condition is:

Power-balance pi (t) represents the sequential operate power of i kind distributed power source; P _load(t) represent sequential load.

Unit power output restriction P _imin≤ P _i(t)≤P _imax, P _iminrepresent the minimum stable operation power of i kind distributed power source; P _imaxrepresent the maximum stable operate power of i kind distributed power source.

Unit limits t minimum running time _oni>=t _onimin; t _onirepresent the continuous operating time of i kind distributed power source; t _oniminrepresent the minimum continuous operating time of i kind distributed power source.

Unit limits t minimum downtime _offi>=t _offimin; t _offirepresent the continuous downtime of i kind distributed power source; t _offiminrepresent the continuous downtime of minimum of i kind distributed power source.

Battery charging and discharging constraints is, SOC _min≤ SOC≤SOC _max, SOC represents the state-of-charge (being residual capacity) of battery; SOC _minrepresent the lower limit of SOC; SOC _maxrepresent the upper limit of SOC.

Power supply reliability constraints is $R_{\mathrm{LPSP}}=\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{LPSP}}\left(t\right)/\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{Load}}\left(t\right)\≤R_{\mathrm{LPSP}\max },$ R _lPSPthe ratio of expression system short of electricity time and total power-on time; P _lPSP(t) the sequential short of electricity power of expression system; R _lPSPmaxmaximum short of electricity rate, the P of allowing of expression system _load(t) represent sequential load.

Step 8: the total cost present worth that step 7 is obtained and the total cost present worth of previous system life cycle management compare, and preserve wherein smaller value, and export the capacity configuration scheme under current minimum total cost limit value;

Step 9: judge that whether stored energy capacitance reaches the definite quantity limit value of step 2, if reach, proceeds to step 11; As no, increase stored energy capacitance by setting step-length, enter step 10 until meet N-1 principle;

Wherein, the cell capability of energy accumulation current converter is greater than the cell capability of energy-storage battery conventionally, organizes the corresponding separate unit energy accumulation current converter of energy-storage battery more, increases many group energy-storage batteries and just increases separate unit energy accumulation current converter;

Step 10: judge that whether stored energy capacitance exceeds the definite quantity limit value of step 2, as no, proceeds to step 6; In this way, proceed to step 11;

Step 11: judge that whether wind turbine pool-size arrives the definite quantity limit value of step 2, in this way, proceeds to step 12; As no, increase the capacity of wind-powered electricity generation unit according to setting step-length, proceed to step 5;

Step 12: judge that bavin sends out unit capacity and whether reach its lower limit, in this way, proceed to step 14; As no, send out the capacity of unit and proceed to step 13 according to setting step-length minimizing bavin;

Step 13: judge whether system configuration meets N-1 principle, if met, proceed to step 4; If do not met, enter step 14;

Step 14: process ends, send out unit and capacity of energy storing device allocation plan taking the allocation plan of finally exporting as optimum wind-powered electricity generation unit, bavin, be optimum wind-powered electricity generation unit, the bavin that this present worth of system synthesis is minimum and send out unit and stored energy capacitance allocation plan.

In order conveniently to understand the present invention program, below as an example of concrete quantity example, idiographic flow of the present invention is simply described: first suppose to determine that the upper limit of the quantity of wind-powered electricity generation unit, energy storage device and diesel generating set is all 5 after preliminary type selecting; Then first selecting 5 of diesel generating sets and wind-powered electricity generation unit is in the situation of 0, and energy storage device is progressively increased to 5 from 0, carries out this present value computation of system synthesis comparison of life cycle management; Increase subsequently by 1 typhoon group of motors, in the situation that 5 of diesel generating sets and wind-powered electricity generation unit are 1, energy storage device is progressively increased to 5 from 0, carry out this present value computation of system synthesis comparison of life cycle management; Until 5 of diesel generating sets and wind-powered electricity generation unit are in the situation of 5, energy storage device is progressively increased to 5 from 0, carry out this present value computation of system synthesis comparison of life cycle management, thereby the optimization that completes wind-powered electricity generation unit in 5 situations of diesel generating set and capacity of energy storing device is calculated; Again, reduce by 1 diesel generating set,, in the situation that diesel generating set is 4, repeat above-mentioned steps; Subsequently, then gradually reduce diesel generating set, one until the lower limit of arrival diesel generating set can complete this present value computation of system synthesis comparison of the life cycle management of all allocation plans.Wherein, N-1 principle, is mainly used in screening and falls irrational capacity configuration scheme.

The engineering collocation method of independence wind-Chai-storage micro-grid system capacity of the present invention, distributing principle rationally is: according to the sequential load data in life cycle management and sequential air speed data, the capacity that wind-powered electricity generation unit, bavin are sent out to unit and energy storage device is as optimized variable, and carries out preliminary type selecting and limit value is set, simultaneously based on micro-grid system life cycle management, each distributed power source is just filled to present value of cost, maintenance cost present worth, this present worth of system synthesis of fuel cost present worth and replacement cost present worth is as optimization aim, and consider power supply units limits, the constraintss such as battery charging and discharging constraint and system power supply reliability index, micro-operation of power networks control strategy of drafting according to engineering, by automatic optimal method, this present worth of system synthesis of different capabilities allocation plan is optimized to calculating, finally select and can meet user power utilization reliability by program Automatic sieve, can make again wind-Chai that this present worth of system synthesis is minimum-storage micro-grid system allocation plan.

The engineering collocation method of independence wind-Chai-storage micro-grid system capacity of the present invention also can be applicable to light-Chai-storage, wind-light-Chai-storage and other similar micro-grid system; The method has far-reaching realistic meaning to the fast development of wind-powered electricity generation, photovoltaic, energy storage distributed energy industry and micro-electric power network technique.

The above; it is only preferred embodiment of the present invention; not the present invention is done to any pro forma restriction, those skilled in the art utilize the technology contents of above-mentioned announcement to make a little simple modification, equivalent variations or modification, all drop in protection scope of the present invention.

Claims (10)

1. an engineering collocation method for independent wind-Chai-storage micro-grid system capacity, is characterized in that comprising the following steps:

A, collect local actual measurement load and wind speed historical data, according to time sequential mode structure life cycle management load and forecasting wind speed curve;

B, the curve obtaining according to steps A are sent out unit and the preliminary type selecting of energy storage device to wind-powered electricity generation unit, bavin, determine cell capability and the quantity limit value of each distributed power source;

C, the curve obtaining according to steps A are determined the peak-peak load of micro-grid system at life cycle management, send out single-machine capacity and the quantity limit value of unit, and calculate this present worth of system synthesis of initial micro-grid system life cycle management according to N-1 principle configuration bavin;

D, wind turbine pool-size is initialized as to zero;

E, stored energy capacitance is initialized as to zero;

F, the curve obtaining according to steps A carry out the emulation of micro-grid system life cycle management;

G, under the edge-restraint condition of micro-grid system and each distributed power source, calculate the total cost present worth of micro-grid system life cycle management system under current configuring condition;

H, the total cost present worth that step G is obtained and the front total cost present worth comparison once obtaining, preserve smaller value wherein, and export the capacity configuration scheme under current minimum total cost present worth;

I, judge whether the capacity of energy storage device reaches the definite quantity limit value of step B, performs step K if reach, if do not reach by setting capacity that step-length increases energy storage device until enter step J after meeting N-1 principle;

J, judge whether the capacity of energy storage device exceeds the definite quantity limit value of step B, performs step in this way K, as otherwise return to step F;

K, judge that whether wind turbine pool-size reaches the definite quantity limit value of step B, performs step L in this way; As otherwise increase wind turbine pool-size return to step e by setting step-length;

L, judge that bavin sends out unit capacity and whether reach operation lower limit, perform step in this way N, as otherwise reduce bavin and send out unit capacity and enter step M by setting step-length;

M, judge whether current configuration meets N-1 principle, if met, return to step D, if do not met, enter step N;

N, process ends, send out unit and capacity of energy storing device allocation plan taking the allocation plan finally exported as optimum wind-powered electricity generation unit, bavin.

2. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 1, is characterized in that:

The target function of the total cost present worth in described step G is:

$C_{\mathrm{CV}}=\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{n}_i\×(C_{\mathrm{Pi}}+C_{\mathrm{Mi}}+C_{\mathrm{Fi}}+C_{\mathrm{Ri}}),$

Wherein, the species number that N is distributed power source,

N _irepresent the quantity of i kind distributed power source,

C _pirepresent the first dress present value of cost of i kind distributed power source,

C _mirepresent the life cycle management maintenance cost present worth of i kind distributed power source,

C _firepresent the life cycle management fuel cost present worth of i kind distributed power source,

C _rirepresent the life cycle management replacement cost present worth of i kind distributed power source.

3. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 2, is characterized in that described C _pi=K _pi× P _i,

Wherein, K _pirepresent the power cost coefficient of i kind distributed power source,

P _irepresent the specified single-machine capacity of i kind distributed power source.

4. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 2, described in it is characterized in that:

$\begin{array}{c}{C}_{\mathrm{Mi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Mi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Mi}}\left(n\right){=K}_{\mathrm{Mi}}\left(n\right)\×C_{\mathrm{Pi}}\end{array},$

Wherein, C _mi(n) represent the maintenance cost of i kind distributed power source at n,

K _mi(n) represent the maintenance cost coefficient of i kind distributed power source at n,

Y _prepresent the life cycle of micro-electrical network project,

R represents interest rate.

5. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 2, described in it is characterized in that:

$\begin{array}{c}{C}_{\mathrm{Fi}}=\underset{n=1}{\overset{y_P}{\mathrm{\Σ}}}{C}_{\mathrm{Fi}}\left(n\right)\×{(1+r)}^{-n}\\ C_{\mathrm{Fi}}\left(n\right)=K_{\mathrm{Fi}}\left(n\right)\×{\∫}_0^{8760}{P}_i(n,t)\mathrm{dt}\end{array},$

Wherein, C _fi(n) represent the fuel cost of i kind distributed power source at n,

K _fi(n) represent the fuel cost coefficient of i kind distributed power source at n,

P _i(n, t) represents the sequential operate power of i kind distributed power source at n,

R represents interest rate,

Y _prepresent the life cycle of micro-electrical network project.

6. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 2, described in it is characterized in that:

$\begin{array}{c}{C}_{\mathrm{Ri}}=\underset{n=1}{\overset{m}{\mathrm{\Σ}}}{K}_{\mathrm{Ri}}\left(n\right)\×C_{\mathrm{Pi}}\×{(1+r)}^{-n}\\ m=\frac{y_P}{y_{\mathrm{Pi}}}-1\end{array},$

Wherein, m represents that i kind distributed power source needs the number of times of resetting and replacing in the project cycle,

K _ri(n) represent the replacement cost coefficient of i kind distributed power source at n,

Y _prepresent the life cycle of micro-electrical network project,

Y _pirepresent the life cycle of i kind distributed power source,

R represents interest rate.

7. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 1, is characterized in that the constraints in described step G comprises power supply units limits, specifically comprises:

$\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{n}_i{\×P}_i\left(t\right)=P_{\mathrm{Load}}\left(t\right),$

P _imin≤P _i(t)≤P _imax，

t _oni≥t _onimin，

t _offi≥t _offimin，

Wherein, P _i(t) the sequential operate power of expression i kind distributed power source,

P _load(t) represent sequential load,

P _iminrepresent the minimum stable operation power of i kind distributed power source,

P _imaxrepresent the maximum stable operate power of i kind distributed power source,

T _onirepresent the continuous operating time of i kind distributed power source,

T _oniminrepresent the minimum continuous operating time of i kind distributed power source,

T _offirepresent the continuous downtime of i kind distributed power source,

T _offiminrepresent the continuous downtime of minimum of i kind distributed power source,

N _irepresent the quantity of i kind distributed power source.

8. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 7, is characterized in that: described constraints also comprises that energy storage device discharges and recharges constraints

SOC _min≤SOC≤SOC _max，

Wherein, SOC represents the capacity status of energy storage device,

SOC _minrepresent the lower bound of capacity of energy storage device,

SOC _maxrepresent the maximum size of energy storage device.

9. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 7, is characterized in that: described constraints also comprises power supply reliability constraints

$R_{\mathrm{LPSP}}=\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{LPSP}}\left(t\right)/\underset{t=1}{\overset{8760}{\mathrm{\Σ}}}{P}_{\mathrm{Load}}\left(t\right)\≤R_{\mathrm{LPSP}\max },$

Wherein, R _lPSPthe ratio of expression system short of electricity time and total power-on time,

P _lPSP(t) the sequential short of electricity power of expression system,

P _load(t) represent sequential load,

R _lPSPmaxthe maximum short of electricity rate that allows of expression system.

10. the engineering collocation method of independent wind-Chai-storage micro-grid system capacity according to claim 1, is characterized in that:

N-1 principle in described step C is at any time all must be higher than peak load demand according to the guarantee generate output in system, wherein, ensure generate output be defined as system installed capacity and maximum generation unit capacity difference 90%.