CN106384176A - Wind-photovoltaic-energy-storage power generation system capacity optimizing method based on wind-photovoltaic hybrid characteristic - Google Patents

Abstract

A wind-photovoltaic-energy-storage power generation system capacity optimizing method based on a wind-photovoltaic hybrid characteristic belongs to the technical field of a wind-photovoltaic-energy-storage power generation system. According to the wind-photovoltaic-energy-storage power generation system capacity optimizing method, through controlling the hybrid power generation system, island-mode operation and grid-connected-mode operation of the hybrid power generation system can be realized. According to the wind-photovoltaic-energy-storage power generation system capacity optimizing method, a capacity optimizing model which is suitable for the wind-photovoltaic-energy-storage power generation system is presented, wherein system cost minimizing is used as an optimizing target, and furthermore the wind-photovoltaic hybrid characteristic, a grid-connected power fluctuation condition and a system load loss rate are comprehensively considered. The wind-photovoltaic-energy-storage power generation system capacity optimizing method has advantages of sufficiently utilizing the wind-photovoltaic hybrid characteristic, ensuring high reliability in power supplying of the system just through a relatively low storage battery capacity, and reducing system cost.

Description

A kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic

Technical field

The invention belongs to wind-light storage hybrid power system technical field, especially relate to one kind and be based on wind light mutual complementing characteristic Wind-light storage hybrid power system capacity optimization method.

Background technology

Wind-light storage hybrid power system is by distributed power source, energy-storage units, local load cell and the grid-connected end of AC network Mouth composition.It is equivalent to a controllable for exchange bulk power grid, and can realize the multiple kinds of energy shape to local load The supply of the high-reliability of formula；It can run on grid-connect mode and off-network pattern：Under grid-connect mode, hybrid system is by system Superfluous energy passes through AC network grid-connected Port Translation device, is conveyed to exchange bulk power grid it is also possible to pass through to absorb bulk power grid Energy carrys out the power shortage in compensation system；Under off-network pattern, that is, bulk power grid breaks down needs the situation of the grid-connected port of locking Under, hybrid system is equivalent to an isolated node and carries out controlled operation.

Traditional wind-light storage capacity configuration mode, with the minimization of total system cost for unique optimization aim, according to floor space Constraint, least energy supply constraint etc. are as the restrictive condition of Optimized model.Due to not making full use of the complementation of wind light generation Characteristic, and to make the power supply reliability of system reach requirement only by the capacity configuration increasing energy storage.Thus considerably increasing Cost is so that the configuration of mixed energy storage system and operation lack economical and reasonability.

Therefore needing badly in the middle of prior art wants a kind of new technical scheme to solve this problem.

Content of the invention

The technical problem to be solved is：A kind of wind-light storage electricity generation system based on wind light mutual complementing characteristic is provided to hold Amount optimization method only makes system by increasing the capacity configuration of energy storage for solving traditional wind-light storage capacity configuration mode Power supply reliability reaches requirement, thus considerably increase cost so that the configuration of mixed energy storage system and operation lack economical With rational technical problem.

A kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic, is characterized in that：Walk including following Suddenly, and following steps are sequentially carried out,

The illumination of 8760 hours whole years of step one, collection typing wind-light storage electricity generation system Location, temperature and wind Fast data message；

Step 2, set up wind-light storage hybrid power system capacity Optimized model,

Wind-light storage hybrid power system capacity Optimized model includes the evaluation index of Optimized model and the constraint of Optimized model Condition,

Ith, evaluation index includes：

1. system power supply reliability

System power supply reliability is characterized with load short of electricity rate LPSP, it is defined as：

$f_{LPSP}=\frac{\underset{t=1}{\overset{N}{\Σ}}\[P_L\left(t\right)-\left(P_w\right(t)+P_v(t)+P_E(t\left)\right)\]}{\underset{t=1}{\overset{N}{\Σ}}{P}_L\left(t\right)}---\left(1\right)$

P in formula_vT () is period t photovoltaic, P_wT () is the power output of wind-powered electricity generation, P_ET () is the power output of battery, P_L T () is the power of load, N is the points of the sampling interval chosen；

2. wind light mutual complementing characteristic

Using wind-powered electricity generation and photovoltaic power output sum with respect to load power stability bandwidth D_LSpecial to characterize wind light mutual complementing Property, it is defined as：

$D_L=\frac{1}{{\stackrel{\‾}{P}}_L}\sqrt{\frac{1}{N}\underset{t=1}{\overset{N}{\Σ}}{\left(P_w\right(t)+P_v(t)-P_L(t\left)\right)}^2}---\left(2\right)$

In formula：Mean power for load；

3. the fluctuation of networking power

Using networking power standard difference D_STDWith power variation rate D_gsTwo indices characterizing the wave characteristic of networking power,

Networking power standard difference D_STDFor：

$D_{STD}=\sqrt{\frac{1}{N-1}\underset{t=1}{\overset{N}{\Σ}}{\left(P_{ac}\right(t)-{\stackrel{\‾}{P}}_{ac})}^2}---\left(3\right)$

In formula：P_acT () is the instantaneous value of networking power,For the mean value of networking power,

Power variation rate D_gsFor：

D_gs=(P_acmax-P_acmin)/Δt

(4) P in formula_acmaxRepresent the maximum of networking power in Δ t time interval, P_acminRepresent in Δ t time interval The minimum of a value of net power；

4. system cost

The cost of DC distribution net mainly includes following part：

A), intrinsic cost

Intrinsic cost is the buying expenses of wind-driven generator, photovoltaic cell and each generator unit of battery, and expression formula is：

$C_0=f_{cr}\underset{i=1}{\overset{3}{\Σ}}{N}_i{p}_i$

$f_{cr}=\frac{r{(1+r)}^l}{{(1+r)}^l-1}---\left(5\right)$

In formula：I represents power supply type, N_iRepresent the number of power supply, p_iRepresent the unit price of power supply；f_crFor coefficient of depreciation；R is Allowance for depreciation；L is the service life of power supply；

B), maintenance cost

Maintenance cost is in whole life cycle, generator unit is carried out safeguarding required expense, expression formula is

$C_m=l\underset{t=1}{\overset{8760}{\Σ}}\underset{i=1}{\overset{3}{\Σ}}{k}_i{N}_i{p}_i\left(t\right)\mathrm{\Δ}t---\left(6\right)$

In formula：T represents a certain sampling instant, k_iFor the maintenance cost coefficient of each power supply, p_iT () is the fortune of each power supply t Row power；

C), purchases strategies

Purchases strategies are the cost to AC distribution net purchase electricity for the DC distribution net, and expression formula is as follows：

$C_B=\underset{t=1}{\overset{8760}{\Σ}}p\left(t\right)\mathrm{sgn}\left(P_{ac}\right(t\left)\right)\mathrm{\Δ}t---\left(7\right)$

D), selling benefit

The electric energy sending is sold to the income that electrical network is obtained, expression formula by wind-light storage hybrid power system by selling benefit For：

$C_S=\underset{t=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}{p}_{const}sgn(-P_{ac}(t\left)\right)\mathrm{\Δ}t---\left(8\right)$

In formula：k_inFor electricity price, p_jT () is the sale of electricity power to AC network for the moment t；

E), generate electricity subsidy

The subsidy that generates electricity generates electricity to construction unit for government department and subsidizes, and expression formula is：

$C_a=k_a\underset{i=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{2}{\Σ}}{N}_j{p}_j\left(t\right)\mathrm{\Δ}t---\left(9\right)$

In formula, j refers to blower fan and photovoltaic cell, k_aFor subsidizing electricity price；

In sum, the integrated cost of DC distribution net is：

C=C₀+C_m+C_B-C_s+C_a(10)

IIth, the constraints of Optimized model includes：

1. the maximum installed capacity constraint of distributed power source DG

In DC distribution net, the total floor space of wind energy turbine set is S_w, long L_w, wide B_w, the floor space of photovoltaic plant is S₁, electric power storage The floor space in pond is S₂, then generator unit number constraint expression formula be：

$N_w\≤\[\frac{L_w}{8d_w}+1\]\[\frac{B_w}{4d_w}+1\]$

$N_v\≤\[\frac{S_1}{S_p}{\mathrm{\α}}_p\]$

$N_E\≤\[\frac{S_2}{S_b}\]---\left(11\right)$

In formula：[] is bracket function, d_wFor rotor diameter, S_pFor the floor space of single photovoltaic cell, α_pFor sheltering from heat or light it is Number, S_bFloor space for single battery；N_wFor the number of units of blower fan, N_vFor the block number of photovoltaic battery panel, N_EIndividual for battery Number；

2. the minimum power constraint of distributed power source DG

The minimum installation number expression formula of wind-powered electricity generation, photovoltaic and secondary battery unit is respectively：

$N_{wt}\≥\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_{wt}\left(t\right)dt---\left(12\right)$

$N_{PV}\≥\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_{pv}\left(t\right)dt---\left(13\right)$

$N_{bs}\≥\frac{{\mathrm{\λW}}_{Ld}}{{\mathrm{\ηC}}_{bs}{V}_{bs}{\mathrm{DOD}}_{max}}---\left(14\right)$

In formula：t_m0～t_m1Represent the effective time of night wind-driven generator, t_m2～t_m3Represent photovoltaic battery panel on daytime Effective time, W_LdRepresent daily load energy, unit is kWh, C_bsFor the capacity of single battery, V_bsFor battery list The voltage of body, DOD_maxFor the maximum depth of discharge of battery, η is the discharging efficiency of battery, N_wtMinimum erecting bed for blower fan Number, N_PVMinimum for photovoltaic battery panel installs block number, N_bsMinimum for battery installs number；

3. system reserve capacity constraint

The total peak power output of distributed power source must assure that the power supply of the load of μ % increasing in system, and system is standby With the expression formula of capacity-constrained it is：

ΣP_DG>=(1+ μ %) P_L(15)

In formula：P_DGFor the total power output of distributed power source, P_LFor the general power of system internal loading, μ % is system reserve Capacity Margin；

4. the discharge and recharge constraint of battery

SOC_min≤SOC≤SOC_max(16)

r_ch≤r_{ch_R},r_dch≤r_{dch_R}(17)

I_ch≤I_chmax,I_dch≤I_dchmax(18)

0≤P_{bs_ch}≤P_{bs_chmax},0≤P_{bs_dch}≤P_{bs_dchmax}(19)

N_c≤N_Cmax(20)

The state-of-charge SOC of battery meets formula (16),

Charge rate r of battery_chWith discharge rate r_dchMeet formula (17), r in formula_{ch_R}And r_{dch_R}For limit value,

The charging and discharging currents of battery meet formula (18), and the charging current of battery is less than its maximum I_chmax, electric power storage The discharge current I in pond_dchLess than its maximum I_dchmax,

The charge-discharge electric power P of battery_{bs_ch}With discharge power P_{bs_dch}Meet formula (19), wherein P_{bs_chmax}And P_{bs_dchmax} It is the KiBaM model acquisition according to battery,

The charge and discharge cycles times N of battery_cMeet formula (20), wherein N_CmaxFor allowing charge and discharge cycles number of times maximum；

5. exchange the constraint of power between system and power distribution network

The power P exchanging between system and power distribution network_gMeet formula be：

P_gmin≤P_g≤P_gmax(21)

In formula：P_gminAllow the minimum power exchanging, P for system and power distribution network_gmaxAllow exchange for system with power distribution network Peak power, P_gminAnd P_gmaxNumerical value determined according to the supply and demand agreement that system and power distribution network are reached；

6. performance indications constraint

A), power supply reliability constraint

Power supply reliability load short of electricity rate f_LPSPCharacterize, short of electricity rate f of load_LPSPMeet formula be：

f_LPSP≤λ_L(22)

Wherein λ_LThe short of electricity rate allowing for load；

B), wind light mutual complementing characteristic constraint

Photovoltaic and wind power output power are with respect to the stability bandwidth D of load power_LLess than reference value ε_L,

D_L≤ε_L(23)

C), the fluctuation constraint of networking power

Fluctuation power variation rate D of networking power_gsCharacterize,

The rate of change D of networking power_gsMeet formula be：

D_gs≤ε_g(24)

Wherein ε_gThe maximum power variation rate that can bear for electrical network, D_gsRate of change for networking power；

According to the constraints of Optimized model, screen and obtain power system capacity configuration sample space,

Screening conditions include obtaining distributed power source maximum installed capacity constraint by formula (10), by formula (12), formula (13) obtain distributed power source minimum power and constrain limit value with formula (14), system reserve capacity constraint is obtained by formula (15), leads to Cross formula (16) to formula (20) to obtain accumulator cell charging and discharging constraint and obtain exchange work(between system and power distribution network by formula (21) The constraint of rate；

Step 3, the data input that step one is obtained in the middle of HOMER simulation software, and by formula (10)～formula (21) Input to HOMER software, run HOMER simulation software and obtain each capacity configuration in power system capacity configuration sample space The power output of the distributed power source DG of combination；

Step 4, by the capacity configuration obtaining in step 3 combination pass through formula (2), obtain each capacity configuration combination under Wind-powered electricity generation and photovoltaic power output sum with respect to load power stability bandwidth D_L, and according to formula (23) to wind light mutual complementing characteristic Screened, meet formula (23) for meeting photovoltaic and wind power output power with respect to the stability bandwidth restrictive condition of load power Capacity configuration is combined；

Combine meeting photovoltaic with respect to the capacity configuration of the stability bandwidth restrictive condition of load power with wind power output power By formula (1), obtain load dead electricity rate f under described each capacity configuration combination_LPSP, and according to formula (22) to system power supply Reliability is screened, and the capacity configuration for meeting load dead electricity rate restrictive condition meeting formula (22) is combined；

Will meet load dead electricity rate restrictive condition capacity configuration combination pass through formula (3) and formula (4), obtain described in each Capacity configuration group is combined in power variation rate D under grid-connect mode_gs, and according to formula (24), networking power swing characteristic is sieved Choosing, the capacity configuration for meeting networking power fluctuation limit condition meeting formula (24) is combined；

Step 5, will the satisfaction that filter out in described step 4 networking power fluctuation limit condition capacity configuration combination logical Cross formula (10) and obtain this capacity configuration combined assembly originally, selection cost minimum programme is configuration scheme.

Power supply type in described step 2 is blower fan, photovoltaic cell or battery.

Maximum power variation rate ε that in described step 2, electrical network can bear_gMeet Q-GDW392-2009 and Q-GDW617- The regulation of Large Copacity wind-power electricity generation and photovoltaic power generation grid-connecting power variation rate in 2011 standards, Δ t=10min, ε_gLess than dress The 33% of machine capacity；Δ t=1min, ε_gLess than the 10% of installed capacity, wherein Δ t represents wind-power electricity generation and photovoltaic generation simultaneously The transformation period section of net power.

Screen and obtain power system capacity configuration sample space in described step 2, screening conditions include obtaining by formula (10) Distributed power source maximum installed capacity constraint, obtains distributed power source minimum power about by formula (12), formula (13) and formula (14) Bundle limit value, obtains system reserve capacity constraint by formula (15), obtains accumulator cell charging and discharging constraint by formula (16) to formula (20) And the constraint exchanging power between system and power distribution network is obtained by formula (21).

By above-mentioned design, the present invention can bring following beneficial effect：

The present invention is by the control to hybrid power system, it is possible to achieve the island mode of system and grid-connect mode run. The present invention proposes the capacity Optimized model being applied to wind-light storage hybrid power system, with the minimum optimization aim of system cost, And considered wind light mutual complementing characteristic, grid-connected power swing situation and system loading dead electricity rate.This invention takes full advantage of wind Light complementary characteristic, it is only necessary to less accumulator capacity can ensure the reliability of system power supply, reduces system cost.

Brief description

Below in conjunction with the drawings and specific embodiments, the present invention is further illustrated：

Fig. 1 is a kind of wind applied based on the wind-light storage electricity generation system capacity optimization method of wind light mutual complementing characteristic of the present invention Light stores up the Organization Chart of hybrid power system.

Fig. 2 is a kind of flow chart element of the wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic of the present invention Figure.

Specific embodiment

As illustrated, a kind of wind-light storage of the wind-light storage electricity generation system capacity optimization method application based on wind light mutual complementing characteristic Hybrid power system is it is characterised in that include：Wind-powered electricity generation unit, photovoltaic cells, batteries to store energy unit, load cell with exchange Electrical network network interface：

Wind-powered electricity generation unit, photovoltaic cells, battery are connected on dc bus by DC/DC interface converter；

Local load unit is connected to dc bus by DC/AC converter；

Dc bus is connected to AC network by DC/AC interface converter.

A kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic, is characterized in that：Walk including following Suddenly, and following steps are sequentially carried out,

The illumination of 8760 hours whole years of step one, collection typing wind-light storage electricity generation system Location, temperature and wind Fast data message；

Step 2, set up wind-light storage hybrid power system capacity Optimized model,

Wind-light storage hybrid power system capacity Optimized model includes the evaluation index of Optimized model and the constraint of Optimized model Condition,

Ith, evaluation index includes：

1. system power supply reliability

It is the ability that system provides load power demand due to consider, therefore with load short of electricity rate (Loss of Power Supply Probability, LPSP) characterize system power supply reliability, it is defined as：

$f_{LPSP}=\frac{\underset{t=1}{\overset{N}{\Σ}}\[P_L\left(t\right)-\left(P_w\right(t)+P_v(t)+P_E(t\left)\right)\]}{\underset{t=1}{\overset{N}{\Σ}}{P}_L\left(t\right)}---\left(1\right)$

P in formula_vT () is period t photovoltaic, P_wT () is the power output of wind-powered electricity generation, P_ET () is the power output of battery, P_L T () is the power of load, N is the points of the sampling interval chosen.Obviously f_LPSPLess, the power supply reliability of system is higher.

2. wind light mutual complementing characteristic

Using wind-powered electricity generation and photovoltaic power output sum with respect to load power stability bandwidth D_LSpecial to characterize wind light mutual complementing Property, it is defined as：

$D_L=\frac{1}{{\stackrel{\‾}{P}}_L}\sqrt{\frac{1}{N}\underset{t=1}{\overset{N}{\Σ}}{\left(P_w\right(t)+P_v(t)-P_L(t\left)\right)}^2}---\left(2\right)$

In formula：Mean power for load.Obviously, D_LLess, the curve of wind-powered electricity generation and photovoltaic power output sum and load Curve is closer to the capacity of so required battery is less, and the discharge and recharge number of times of battery and depth of discharge are also less, thus may be used Better with the complementary characteristic of thinking wind energy and solar energy.

3. the fluctuation of networking power

To characterize the wave characteristic of networking power using standard deviation and power variation rate two indices.Networking power standard is poor D_STDWith power variation rate D_gsDefinition be respectively：

$D_{STD}=\sqrt{\frac{1}{N-1}\underset{t=1}{\overset{N}{\Σ}}{\left(P_{ac}\right(t)-{\stackrel{\‾}{P}}_{ac})}^2}---\left(3\right)$

D_gs=(P_acmax-P_acmin)/Δt (4)

In formula：P_acT () is the instantaneous value of networking power,Mean value for networking power.When standard deviation gets over hour, enter The fluctuation of net power is less；P in formula (4)_acmaxRepresent the maximum of networking power in Δ t time interval, P_acminWhen representing Δ t Between interval in networking power minimum of a value.

Standard deviation is to characterize the fluctuation of networking power relative to the dispersion degree of its mean value with the power curve that networks, suitably Evaluation index as long duration wave characteristic；Power variation rate be with the peak valley difference degree of the power curve that networks to characterize into The fluctuation of net power, suitably as the evaluation index of short time interval wave characteristic.Comprehensive these two aspects, can reflect than more comprehensive The wave characteristic of networking power.

4. system cost

The cost of DC distribution net mainly includes following four part：

A), intrinsic cost

Intrinsic cost ignores construction and the maintenance cost of electrical changing station and circuit, because the expense of these electric power facilities and scene The capacity relationship of storage is little.The buying expenses of wind-driven generator, photovoltaic cell and each generator unit of battery is admittedly indispensable , these expenses are referred to as intrinsic cost, and expression formula is：

$C_0=f_{cr}\underset{i=1}{\overset{3}{\Σ}}{N}_i{p}_i$

$f_{cr}=\frac{r{(1+r)}^l}{{(1+r)}^l-1}---\left(5\right)$

In formula：I represents different power supply types, i.e. blower fan, photovoltaic cell and battery；N_iRepresent the number of each power supply, p_i Represent the unit price of each power supply；f_crFor coefficient of depreciation；R is allowance for depreciation；L is the service life of power supply.

B), maintenance cost

In whole life cycle, in order to keep the operation of electricity generation system normal table, be on time to each generator unit Safeguarded, required expense is referred to as maintenance cost, expression formula is

$C_m=l\underset{t=1}{\overset{8760}{\Σ}}\underset{i=1}{\overset{3}{\Σ}}{k}_i{N}_i{p}_i\left(t\right)\mathrm{\Δ}t---\left(6\right)$

In formula：T represents a certain sampling instant；k_iFor the maintenance cost coefficient of each power supply, p_iT () is the fortune of each power supply t Row power.

C), purchases strategies

DC distribution net is as follows to the cost expressions of AC distribution net purchase electricity：

$C_B=\underset{t=1}{\overset{8760}{\Σ}}p\left(t\right)\mathrm{sgn}\left(P_{ac}\right(t\left)\right)\mathrm{\Δ}t---\left(7\right)$

D), selling benefit

It is sale of electricity income that the electric energy sending is sold to the income that electrical network obtained by wind-light storage hybrid power system, and expression formula is

$C_S=\underset{t=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}{p}_{const}sgn(-P_{ac}(t\left)\right)\mathrm{\Δ}t---\left(8\right)$

In formula：k_inFor electricity price, p_jT () is the sale of electricity power to AC network for the moment t.

E), generate electricity subsidy

Wind light mutual complementing power generation is generation of electricity by new energy, there is presently no and is widely used, power plant construction cost is also very high, leads Causing to sell electricity price is higher than conventional power generation usage price.Government is to encourage generation of electricity by new energy, can generate electricity to construction unit and subsidize, expression formula For：

$C_a=k_a\underset{i=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{2}{\Σ}}{N}_j{p}_j\left(t\right)\mathrm{\Δ}t---\left(9\right)$

In formula；J refers to blower fan and photovoltaic cell, k_aFor subsidizing electricity price.

In sum, the integrated cost of DC distribution net is：

C=C₀+C_m+C_B-C_s+C_a(10)

IIth, the constraints of Optimized model includes：

1. the maximum installed capacity constraint of distributed power source DG

Distributed power source DG includes blower fan, photovoltaic cell and battery.For a certain specific wind light mutual complementing power generation engineering, The construction site area planned in advance is fixing, and systems organization installed capacity also can be given, therefore wind-light storage mixed power generation system In system, the number of blower fan, photovoltaic cell and battery has all limited, and according to system Construction place, system scale should be carried out about Bundle, specifically enters row constraint to the quantity of blower fan, photovoltaic cell and battery.Meeting between Wind turbines line space and row Away from the premise of, in planning place, the blower fan number of units that can install there will necessarily be a upper limit.Similarly it is contemplated that sunshine The place that coverage, acclive mountain region, installing blower fan etc. cannot use, the installation number of photovoltaic module there is also on one Limit.It is assumed that the total floor space of wind energy turbine set is S in DC distribution net_w, long L_w, wide B_w, the floor space of photovoltaic plant is S₁, electric power storage The floor space in pond is S₂, then each generator unit number constraint expression formula be：

$\begin{array}{c}{N}_w\≤\[\frac{L_w}{8d_w}+1\]\[\frac{B_w}{4d_w}+1\]\\ N_v\≤\[\frac{S_1}{S_p}{\mathrm{\α}}_p\]\\ N_E\≤\[\frac{S_2}{S_b}\]\end{array}---\left(11\right)$

In formula：[] is bracket function, d_wFor rotor diameter, S_pFor the floor space of single photovoltaic cell, α_pFor sheltering from heat or light it is Number, S_bFloor space for single battery.

Relevant design department, before building each wind-light storage hybrid power system, advises according to local load need for electricity Pull the total capacity of electricity generation system.The wind-light storage hybrid power system being for total capacity, wind-driven generator, photovoltaic cell and Certain restriction relation is there is between the quantity of battery.

2. the minimum power constraint of distributed power source DG

In order to make full use of wind energy and solar energy, reduce the discharge and recharge of energy-storage battery, night photovoltaic exert oneself be zero when, the phase Machine of keeping watch at least is provided that the mean power of load.Equally, on daytime, if calm or weak wind state it is desirable to photovoltaic cell extremely It is provided that the mean power of load less.When calm unglazed weather, the power of load is provided by energy-storage battery, then battery should At least ensure that based model for load duration works λ days, λ is determined by the importance of load.Thus, the minimum of wind-powered electricity generation, photovoltaic and secondary battery unit Installation number needs to meet：

$N_{wt}\≥\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_{wt}\left(t\right)dt---\left(12\right)$

$N_{PV}\≥\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_{pv}\left(t\right)dt---\left(13\right)$

$N_{bs}\≥\frac{{\mathrm{\λW}}_{Ld}}{{\mathrm{\ηC}}_{bs}{V}_{bs}{\mathrm{DOD}}_{max}}---\left(14\right)$

In formula：t_m0～t_m1Represent the effective time of night wind-driven generator, t_m2～t_m3Represent photovoltaic battery panel on daytime Effective time, W_LdRepresent daily load energy, unit is kWh, C_bsFor the capacity of single battery, V_bsFor battery list The voltage of body, DOD_maxFor the maximum depth of discharge of battery, η is the discharging efficiency of battery, N_wtMinimum erecting bed for blower fan Number, N_PVMinimum for photovoltaic battery panel installs block number, N_bsMinimum for battery installs number.

3. system reserve capacity constraint

May increase in view of load in system or unit, element are likely to occur fault, system need to leave certain The total peak power output of spare capacity, therefore DG allows for the power supply of possible the increased load of μ % in guarantee system, that is,

ΣP_DG>=(1+ μ %) P_L(15)

In formula：P_DGFor the total power output of distributed power source, P_LFor the general power of system internal loading, μ % is system reserve Capacity Margin.

4. the discharge and recharge constraint of battery

In order to optimize the charging and discharging state of battery, extend the service life of battery, herein in system operation Strict restriction has been made in the discharge and recharge of battery.The state-of-charge SOC of battery need to meet formula (16), its charge rate r_chAnd discharge rate r_dchFormula (17), r in formula need to be met_{ch_R}And r_{dch_R}For limit value.The charging and discharging currents I of battery_chAnd I_dchMaximum less than it Value I_chmaxAnd I_dchmax, that is, meet formula (18).The charge-discharge electric power P of battery_{bs_ch}And P_{bs_dch}Formula (19) need to be met, wherein P_{bs_chmax}And P_{bs_dchmax}It is to be calculated according to the KiBaM model of battery.The charge and discharge cycles times N of battery_cNeed to meet Formula (20), wherein N_CmaxFor the maximum charge and discharge cycles number of times allowing.

SOC_min≤SOC≤SOC_max(16)

r_ch≤r_{ch_R},r_dch≤r_{dch_R}(17)

I_ch≤I_chmax,I_dch≤I_dchmax(18)

0≤P_{bs_ch}≤P_{bs_chmax},0≤P_{bs_dch}≤P_{bs_dchmax}(19)

N_c≤N_Cmax(20)

5. exchange the constraint of power between system and power distribution network

The power P exchanging between system and power distribution network_gNeed to meet

P_gmin≤P_g≤P_gmax(21)

In formula：P_gminAnd P_gmaxThe system of being respectively and power distribution network allow minimum power and the peak power exchanging, and this value is root To determine according to the supply and demand agreement that system and power distribution network are reached.

6. performance indications constraint

A), power supply reliability constraint

Power supply reliability load short of electricity rate f_LPSPCharacterize it is generally the case that the short of electricity rate of load only need to can at one With the scope born, that is,

f_LPSP≤λ_L(22)

Wherein λ_LThe short of electricity rate allowing for load.

B), wind light mutual complementing characteristic constraint

System to be made makes full use of wind light mutual complementing characteristic, then photovoltaic and wind power output power are with respect to the ripple of load power Dynamic rate D_LIt is necessarily less than reference value ε_L, that is,

D_L≤ε_L(23)

C), the fluctuation constraint of networking power

Fluctuation power variation rate D of networking power_gsCharacterize.The rate of change of networking power only need to be in the tolerance range of electrical network Within, that is,

D_gs≤ε_g(24)

Wherein ε_gThe maximum power variation rate that can bear for electrical network.

According in Q-GDW392-2009 and Q-GDW617-2011 standard with regard to Large Copacity wind-power electricity generation and photovoltaic generation simultaneously The regulation of net power variation rate, as Δ t=10min, ε_gLess than installed capacity 33%；As Δ t=1min, ε_gDo not surpass Cross the 10% of installed capacity.

Step 3, the data input that step one is obtained in the middle of HOMER simulation software, and by formula (10)～formula (21) Input to HOMER software, each capacity configuration group in power system capacity configuration sample space after running emulation, can be obtained The power output of the distributed power source DG closing；

Step 4, by the capacity configuration obtaining in step 3 combination pass through formula (2), obtain each capacity configuration combination under Wind-powered electricity generation and photovoltaic power output sum with respect to load power stability bandwidth D_L, and according to formula (23) to wind light mutual complementing characteristic Screened, meet formula (23) for meeting photovoltaic and wind power output power with respect to the stability bandwidth restrictive condition of load power Capacity configuration is combined；

Combine meeting photovoltaic with respect to the capacity configuration of the stability bandwidth restrictive condition of load power with wind power output power By formula (1), obtain load dead electricity rate f under described each capacity configuration combination_LPSP, and according to formula (22) to system power supply Reliability is screened, and the capacity configuration for meeting load dead electricity rate restrictive condition meeting formula (22) is combined；

Will meet load dead electricity rate restrictive condition capacity configuration combination pass through formula (3) and formula (4), obtain described in each Capacity configuration group is combined in power variation rate D under grid-connect mode_gs, and according to formula (24), networking power swing characteristic is sieved Choosing, the capacity configuration for meeting networking power fluctuation limit condition meeting formula (24) is combined；

Step 5, will the satisfaction that filter out in described step 4 networking power fluctuation limit condition capacity configuration combination logical Cross formula (10) and obtain this capacity configuration combined assembly originally, selection cost minimum programme is configuration scheme.

The FB(flow block) of the wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic as a kind of in Fig. 2 present invention Can be summarized as：

First, the meteorology such as the illumination of 8760 hours whole years according to collection hybrid power system Location, temperature, wind speed Data, provides data basis for capacity optimization.

Then, the constraints according to wind-light storage each unit, filters out and meets the power system capacity configuration sample space requiring. Specific screening conditions include distributed power source maximum installed capacity constraint, as shown in formula (10), distributed power source minimum power To formula (14) Suo Shi, system reserve capacity constrains as shown in formula (15) constraint limit value such as formula (12), and accumulator cell charging and discharging constrains such as Formula (16), to formula (20) Suo Shi, exchanges between system and power distribution network shown in the constraint such as formula (21) of power.

Then, calculate each distributed power source output work of each capacity configuration combination in sample space obtained above Rate.

Then, according to each item data obtained above, calculate shown in wind light mutual complementing characterisitic parameter such as formula (2).And according to Constraints is screened as shown in formula (23).

Then, according to above-mentioned obtained each item data, calculate shown in load short of electricity rate such as formula (1).And according to constraint Condition is screened as shown in formula (22).

Then, each item data according to above-mentioned gained, calculate grid-connect mode under networking power swing rate such as formula (3) and Formula (4).And screened as shown in formula (24) according to constraints.

Then the sample that above several steps are screened is carried out totle drilling cost calculating, such as shown in formula (10).Select totle drilling cost Minimum combination, draws final distributing rationally.

Claims (4)

1. a kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic, is characterized in that：Comprise the following steps, And following steps are sequentially carried out,

The illumination of 8760 hours whole years of step one, collection typing wind-light storage electricity generation system Location, temperature and wind speed number It is believed that breath；

Step 2, set up wind-light storage hybrid power system capacity Optimized model,

Wind-light storage hybrid power system capacity Optimized model includes the evaluation index of Optimized model and the constraints of Optimized model,

Ith, evaluation index includes：

1. system power supply reliability

System power supply reliability is characterized with load short of electricity rate LPSP, it is defined as：

$f_{LPSP}=\frac{\underset{t=1}{\overset{N}{\Σ}}\[P_L\left(t\right)-\left(P_w\right(t)+P_v(t)+P_E(t\left)\right)\]}{\underset{t=1}{\overset{N}{\Σ}}{P}_L\left(t\right)}---\left(1\right)$

P in formula_vT () is period t photovoltaic, P_wT () is the power output of wind-powered electricity generation, P_ET () is the power output of battery, P_LT () is The power of load, N is the points of the sampling interval chosen；

2. wind light mutual complementing characteristic

Using wind-powered electricity generation and photovoltaic power output sum with respect to load power stability bandwidth D_LTo characterize wind light mutual complementing characteristic, its It is defined as：

$D_L=\frac{1}{{\stackrel{\‾}{P}}_L}\sqrt{\frac{1}{N}\underset{t=1}{\overset{N}{\Σ}}{\left(P_w\right(t)+P_v(t)-P_L(t\left)\right)}^2}---\left(2\right)$

In formula：Mean power for load；

3. the fluctuation of networking power

Using networking power standard difference D_STDWith power variation rate D_gsTwo indices characterizing the wave characteristic of networking power,

Networking power standard difference D_STDFor：

$D_{STD}=\sqrt{\frac{1}{N-1}\underset{t=1}{\overset{N}{\Σ}}{\left(P_{ac}\right(t)-{\stackrel{\‾}{P}}_{ac})}^2}---\left(3\right)$

In formula：P_acT () is the instantaneous value of networking power,For the mean value of networking power,

Power variation rate D_gsFor：

D_gs=(P_{ac max}-P_{ac min})/Δt

(4)

P in formula_{ac max}Represent the maximum of networking power in Δ t time interval, P_{ac min}Represent networking power in Δ t time interval Minimum of a value；

4. system cost

The cost of DC distribution net mainly includes following part：

A), intrinsic cost

Intrinsic cost is the buying expenses of wind-driven generator, photovoltaic cell and each generator unit of battery, and expression formula is：

$C_0=f_{cr}\underset{i=1}{\overset{3}{\Σ}}{N}_i{p}_i$

$f_{cr}=\frac{r{(1+r)}^l}{{(1+r)}^l-1}---\left(5\right)$

In formula：I represents power supply type, N_iRepresent the number of power supply, p_iRepresent the unit price of power supply；f_crFor coefficient of depreciation；R is depreciation Rate；L is the service life of power supply；

B), maintenance cost

Maintenance cost is in whole life cycle, generator unit is carried out safeguarding required expense, expression formula is

$C_m=l\underset{t=1}{\overset{8760}{\Σ}}\underset{i=1}{\overset{3}{\Σ}}{k}_i{N}_i{p}_i\left(t\right)\mathrm{\Δ}t---\left(6\right)$

In formula：T represents a certain sampling instant, k_iFor the maintenance cost coefficient of each power supply, p_iT () is the operation work(of each power supply t Rate；

C), purchases strategies

Purchases strategies are the cost to AC distribution net purchase electricity for the DC distribution net, and expression formula is as follows：

$C_B=\underset{t=1}{\overset{8760}{\Σ}}p\left(t\right)\mathrm{sgn}\left(P_{ac}\right(t\left)\right)\mathrm{\Δ}t---\left(7\right)$

D), selling benefit

The electric energy sending is sold to the income that electrical network is obtained by wind-light storage hybrid power system by selling benefit, and expression formula is：

$C_S=\underset{t=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{n}{\Σ}}{p}_{const}\mathrm{sgn}(-P_{ac}(t\left)\right)\mathrm{\Δ}t---\left(8\right)$

In formula：k_inFor electricity price, p_jT () is the sale of electricity power to AC network for the moment t；

E), generate electricity subsidy

The subsidy that generates electricity generates electricity to construction unit for government department and subsidizes, and expression formula is：

$C_a=k_a\underset{i=1}{\overset{8760}{\Σ}}\underset{j=1}{\overset{2}{\Σ}}{N}_j{p}_j\left(t\right)\mathrm{\Δ}t---\left(9\right)$

In formula, j refers to blower fan and photovoltaic cell, k_aFor subsidizing electricity price；

In sum, the integrated cost of DC distribution net is：

C=C₀+C_m+C_B-C_s+C_a(10)

IIth, the constraints of Optimized model includes：

1. the maximum installed capacity constraint of distributed power source DG

In DC distribution net, the total floor space of wind energy turbine set is S_w, long L_w, wide B_w, the floor space of photovoltaic plant is S₁, battery Floor space is S₂, then generator unit number constraint expression formula be：

$\begin{array}{c}{N}_w\≤\[\frac{L_w}{8d_w}+1\]\[\frac{B_w}{4d_w}+1\]\\ N_v\≤\[\frac{S_1}{S_p}{\mathrm{\α}}_p\]\\ N_E\≤\[\frac{S_2}{S_b}\]\end{array}---\left(11\right)$

In formula：[] is bracket function, d_wFor rotor diameter, S_pFor the floor space of single photovoltaic cell, α_pFor the coefficient that shelters from heat or light, S_b Floor space for single battery；N_wFor the number of units of blower fan, N_vFor the block number of photovoltaic battery panel, N_ENumber for battery；

2. the minimum power constraint of distributed power source DG

The minimum installation number expression formula of wind-powered electricity generation, photovoltaic and secondary battery unit is respectively：

$N_{wt}\≥\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m0}}{\overset{t_{m1}}{\∫}}{P}_{wt}\left(t\right)dt---\left(12\right)$

$N_{PV}\≥\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_L\left(t\right)dt/\underset{t_{m2}}{\overset{t_{m3}}{\∫}}{P}_{pv}\left(t\right)dt---\left(13\right)$

$N_{bs}\≥\frac{{\mathrm{\λW}}_{Ld}}{{\mathrm{\ηC}}_{bs}{V}_{bs}{\mathrm{DOD}}_{max}}---\left(14\right)$

In formula：t_m0～t_m1Represent the effective time of night wind-driven generator, t_m2～t_m3Represent having of photovoltaic battery panel on daytime The effect working time, W_LdRepresent daily load energy, unit is kWh, C_bsFor the capacity of single battery, V_bsFor single battery Voltage, DOD_maxFor the maximum depth of discharge of battery, η is the discharging efficiency of battery, N_wtFor blower fan minimum install number of units, N_PVMinimum for photovoltaic battery panel installs block number, N_bsMinimum for battery installs number；

3. system reserve capacity constraint

The total peak power output of distributed power source must assure that the power supply of the load of μ % increasing in system, and system reserve holds Measuring the expression formula constraining is：

∑P_DG>=(1+ μ %) P_L(15)

In formula：P_DGFor the total power output of distributed power source, P_LFor the general power of system internal loading, μ % is system reserve capacity Nargin；

4. the discharge and recharge constraint of battery

SOC_min≤SOC≤SOC_max(16)

r_ch≤r_{ch_R},r_dch≤r_{dch_R}(17)

I_ch≤I_{ch max}, I_dch≤I_{dch max}(18)

0≤P_{bs_ch}≤P_{bs_ch max},0≤P_{bs_dch}≤P_{bs_dch max}(19)

N_c≤N_{C max}(20)

The state-of-charge SOC of battery meets formula (16),

Charge rate r of battery_chWith discharge rate r_dchMeet formula (17), r in formula_{ch_R}And r_{dch_R}For limit value,

The charging and discharging currents of battery meet formula (18), and the charging current of battery is less than its maximum I_{ch max}, battery Discharge current I_dchLess than its maximum I_{dch max},

The charge-discharge electric power P of battery_{bs_ch}With discharge power P_{bs_dch}Meet formula (19), wherein P_{bs_chmax}And P_{bs_dch max}It is root KiBaM model according to battery obtains,

The charge and discharge cycles times N of battery_cMeet formula (20), wherein N_{C max}For allowing charge and discharge cycles number of times maximum；

5. exchange the constraint of power between system and power distribution network

The power P exchanging between system and power distribution network_gMeet formula be：

P_{g min}≤P_g≤P_{g max}(21)

In formula：P_{g min}Allow the minimum power exchanging, P for system and power distribution network_{g max}Allow to exchange for system and power distribution network High-power, P_{g min}And P_{g max}Numerical value determined according to the supply and demand agreement that system and power distribution network are reached；

6. performance indications constraint

A), power supply reliability constraint

Power supply reliability load short of electricity rate f_LPSPCharacterize, short of electricity rate f of load_LPSPMeet formula be：

f_LPSP≤λ_L(22)

Wherein λ_LThe short of electricity rate allowing for load；

B), wind light mutual complementing characteristic constraint

Photovoltaic and wind power output power are with respect to the stability bandwidth D of load power_LLess than reference value ε_L,

D_L≤ε_L(23)

C), the fluctuation constraint of networking power

Fluctuation power variation rate D of networking power_gsCharacterize,

The rate of change D of networking power_gsMeet formula be：

D_gs≤ε_g(24)

Wherein ε_gThe maximum power variation rate that can bear for electrical network, D_gsRate of change for networking power；

According to the constraints of Optimized model, screen and obtain power system capacity configuration sample space,

Screening conditions include by formula (10) obtain distributed power source maximum installed capacity constraint, by formula (12), formula (13) and Formula (14) obtains distributed power source minimum power constraint limit value, obtains system reserve capacity constraint by formula (15), by formula (16) obtain accumulator cell charging and discharging constraint and by exchanging power between formula (21) acquisition system and power distribution network to formula (20) Constraint；

Step 3, the data input that step one is obtained in the middle of HOMER simulation software, and by formula (10)～formula (21) input To HOMER software, run HOMER simulation software and obtain each capacity configuration combination in power system capacity configuration sample space Distributed power source DG power output；

Step 4, by the capacity configuration obtaining in step 3 combination pass through formula (2), obtain each capacity configuration combination under wind The power output sum of electricity and photovoltaic is with respect to the stability bandwidth D of load power_L, and according to formula (23), wind light mutual complementing characteristic is carried out Screening, meet formula (23) for meeting the capacity that photovoltaic and wind power output power are with respect to the stability bandwidth restrictive condition of load power Configuration combination；

Pass through meeting photovoltaic and combining with respect to the capacity configuration of the stability bandwidth restrictive condition of load power with wind power output power Formula (1), obtains load dead electricity rate f under described each capacity configuration combination_LPSP, and reliable to system power supply according to formula (22) Property screened, meet formula (22) for meet load dead electricity rate restrictive condition capacity configuration combine；

The capacity configuration meeting load dead electricity rate restrictive condition is combined and passes through formula (3) and formula (4), obtain each capacity described Configuration group is combined in power variation rate D under grid-connect mode_gs, and according to formula (24), networking power swing characteristic is screened, full The capacity configuration for meeting networking power fluctuation limit condition of sufficient formula (24) is combined；

Step 5, formula is passed through in the capacity configuration of the satisfaction filtering out in described step 4 networking power fluctuation limit condition combination (10) obtain this capacity configuration combined assembly originally, selection cost minimum programme is configuration scheme.

2. a kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic according to claim 1, its Feature is：Power supply type in described step 2 is blower fan, photovoltaic cell or battery.

3. a kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic according to claim 1, its Feature is：Maximum power variation rate ε that in described step 2, electrical network can bear_gMeet Q-GDW392-2009 and Q-GDW617- The regulation of Large Copacity wind-power electricity generation and photovoltaic power generation grid-connecting power variation rate in 2011 standards, Δ t=10min, ε_gLess than dress The 33% of machine capacity；Δ t=1min, ε_gLess than the 10% of installed capacity, wherein Δ t represents wind-power electricity generation and photovoltaic generation simultaneously The transformation period section of net power.

4. a kind of wind-light storage electricity generation system capacity optimization method based on wind light mutual complementing characteristic according to claim 1, its Feature is：Screen and obtain power system capacity configuration sample space in described step 2, screening conditions include obtaining by formula (10) Distributed power source maximum installed capacity constraint, obtains distributed power source minimum power about by formula (12), formula (13) and formula (14) Bundle limit value, obtains system reserve capacity constraint by formula (15), obtains accumulator cell charging and discharging constraint by formula (16) to formula (20) And the constraint exchanging power between system and power distribution network is obtained by formula (21).