CN103683326A - Method for calculating optimal admitting ability for wind power multipoint access of regional power grid - Google Patents

Abstract

The invention discloses a method for calculating the optimal admitting ability for wind power multipoint access of a regional power grid and belongs to the technical field of wind power penetration methods of the power grid. The method for calculating the optimal admitting ability for the wind power multipoint access of the regional power grid comprises the steps that the installed capacity of all wind power plants is initialized, and data such as the local wind speed are acquired; the output condition of all the wind power plants is calculated, and unit commitment and optimization within all dispatching cycles are conducted, so that an annual unit commitment mode of an electric power system comprising the wind power plants is obtained; power flow calculation is conducted based on each period of time, whether an operation constraint condition of the system is met is verified, and a final objective function value is calculated after simulation is conducted on the system for more than 8760 hours; the installed capacity of the wind power plants is updated, optimized iteration is conducted on an objective function, and optimal solution of the wind power generating capacity is achieved, namely the optimal admitting ability of the power grid which enables the economical efficiency of the system to be optimized on the premise that the safety and stability constraint conditions are met is achieved. According to the method for calculating the optimal admitting ability for the wind power multipoint access of the regional power grid, an optimal wind power admitting capacity calculation model with the largest net earning of a wind power plant and power grid combination system (with the environmental benefit considered) as the purpose is established, and suggestions can be provided for the proper establishment of the installed capacity of the regional wind power plants.

Description

A kind of regional power grid wind-powered electricity generation multiple spot accesses the computational methods of best receiving ability

Technical field

The present invention relates to the computational methods that a kind of regional power grid wind-powered electricity generation multiple spot accesses best receiving ability, belong to electrical network wind-powered electricity generation acceptance method technical field.

Background technology

Along with day by day highlighting of energy security problem and environmental problem, China has strengthened the exploitation dynamics to renewable energy power generation, and wherein wind-powered electricity generation is with fastest developing speed.Although wind-powered electricity generation has good reduction of discharging benefit, due to its randomness of exerting oneself, fluctuation, wind-electricity integration brings challenges to the security and stability of electrical network, and this also makes its economics of power generation lower than conventional thermal power generation.China's regenerative resource law regulation: electrical network must fully be received wind-powered electricity generation, this policy requirements electrical network must provide supporting grid-connected construction, the standby and peak regulation cost of increase operation for this reason, to power grid enterprises, brought certain financial burden, make power grid enterprises receive the enthusiasm of wind-powered electricity generation not high, cause the problems such as installed capacity of wind-driven power is superfluous, utilance is low.One side is the regulation that the electrical network of Renewable Energy Law is fully received wind-powered electricity generation, the requirement of electrical network to fail safe, reliability, economy on the one hand, make wind energy turbine set abandon wind phenomenon serious, installation serious waste, existing research mainly concentrates on the technological layer of considering ability to transmit electricity constraint and the constraint of peak load regulation network ability, what generally obtain is the receptive maximum wind capacity of electrical network under existing power supply structure, cannot meet the requirement of system economy, security and stability simultaneously.The present invention is intended to seek a kind of best installed capacity of wind-powered electricity generation that two aspects require that simultaneously meets, for Wind-Electric Power Stations construction is offered suggestions.

Summary of the invention

For receiving wind-powered electricity generation whether can lose---economy is carried out prediction and calculation, and current Wind Power Development situation and existing research above shortcomings, the object of this invention is to provide and a kind ofly meeting under the condition of system safety constraint, network transmission of electricity security constraint, make the wind-powered electricity generation of the real receptible system net profit maximum of electric power enterprise receive capacity calculation method (economy optimum, ask max), and based on improving DE algorithm, annual 8760 periods are carried out to analogue simulation, prove validity and the practicality of invention.

Technical scheme provided by the invention is,

Regional power grid wind-powered electricity generation multiple spot accesses computational methods for best receiving ability, and the method step is:

(1) each wind energy turbine set installed capacity of initialization P _n, and gather local air speed data, conventional unit installed capacity, yearly peak load data, according to blower fan output calculation model, draw planning each output of wind electric field situation P in year _{w, j, h};

Described wind-powered electricity generation unit output calculation model:

$p_w\left(v\right)=\left\{\begin{array}{c}0,0\&le;v<v_{\mathrm{ci}}\\ p_N\frac{v_i-v_{\mathrm{ci}}}{v_R-v_{\mathrm{ci}}},v_{\mathrm{ci}}\&le;v<v_R\\ P_N,v_R\&le;v<v_{\mathrm{co}}\end{array}\right.,$

Wherein,

P _w(v): wind power,

P _n: blower fan rated power,

V _ci: the incision wind speed of blower fan,

V _r: the rated wind speed of blower fan,

V _co: the cut-out wind speed of blower fan;

By year wind-powered electricity generation exert oneself situation in conjunction with load prediction level, carry out the system Unit Combination optimization of first dispatching cycle, according to economic dispatch model, obtain each operating states of the units and the generated output of each period in one day:

$\min E=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{U}_{\mathrm{it}}{f}_{\mathrm{it}}\left(P_{\mathrm{it}}\right),$

Constraints:

$\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{G,i,h}+\underset{j=1}{\overset{M}{\mathrm{\&Sigma;}}}{P}_{w,j,h}=P_{\mathrm{Load},h}+{\mathrm{\&Delta;P}}_{\mathrm{Loss},h},$

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

P{D _Ri≤P _it-P _it-1≤U _Ri}≥β ₁，

Wherein,

E: system total power production cost,

T: hop count in the time of in research cycle,

N: the number of units of conventional power generation usage unit in system,

U _it: conventional unit i is at the start and stop state of period t, U _it=1 represents operation, U _it=0 represents to shut down,

P _it: conventional unit i is at the active power of output of period t,

F _it(P _it): the operating cost of conventional unit i, expression way is:

$f_{\mathrm{it}}\left(P_{\mathrm{it}}\right)=a_i+b_i{P}_{\mathrm{it}}+c_i{P}_{\mathrm{it}}^2+\left|d_i\sin \right[e_i(P_{\mathrm{it}}^{\min }-P_{\mathrm{it}})\left]\right|,$ Wherein, a _i, b _i, c _i, d _i, e _i: the coefficient of cost function,

: conventional unit i is at the lower limit of exerting oneself of period t,

M: the wind turbine number of organizing a performance,

P _{g, i, h}: conventional unit is meritorious exerts oneself,

P _{w, j, h}: wind-powered electricity generation unit is meritorious exerts oneself,

P _{load, h}: burden with power size,

Δ P _{loss, h}: active power loss,

P _{g, i, h, min}, P _{g, i, h, max}: represent respectively technology minimum load and the maximum output of conventional unit,

D _ri, U _ri: conventional unit i is at meritorious fall off rate and the climbing speed of exerting oneself of period t,

β ₁: prior given confidence level;

(2) carry out the calculating of wind-powered electricity generation annual energy output, only obtain the target function subconstiuent relevant to wind power generation amount, described the target function subconstiuent relevant to wind power generation amount comprises electrical network sale of electricity income I _{g, s, j}, compensation income I _{g, co}, wind energy turbine set compensation income I _{w, co}, Construction of Wind Power cost C _w,c, wind energy turbine set year operation expense C _{w, op}with power grid construction cost C _{g, tr};

A. electrical network sale of electricity income I _{g, s, j}, can be expressed as the product of electrical network electricity sales amount and sale of electricity price, compensation income, comprises the compensation to the compensation He Dui power grid enterprises of wind energy turbine set self;

Wind energy turbine set year compensation income:

I _w,co＝W _w×p _w,co，

Wherein,

I _{w, co}: wind energy turbine set year compensation income,

W _w: wind energy turbine set annual energy output,

P _{w, co}: the compensation of wind power generation annual energy output unit,

Electrical network year compensation income:

I _g,co＝W _w×p _g,co，

Wherein,

I _{g, co}: electrical network year compensation income,

P _{g, co}: electrical network is received the compensation of wind-powered electricity generation annual energy output unit,

B. wind-powered electricity generation cost of investment comprise wind energy turbine set year construction cost and wind energy turbine set year operation expense;

Wind energy turbine set year construction cost:

$C_{w,c,\mathrm{actual}}=C_{w,c}\&times;i/[1-{(1+i)}^{-T_w}],$

Wherein,

C _{w, c, actual}: wind energy turbine set year construction cost,

C _w,c: the wind energy turbine set initial stage is built total cost,

I: bank's Annual Percentage Rate,

T _w: the life-span time limit of wind energy turbine set,

: fund equivalence year value coefficient,

Wind energy turbine set year operation expense:

C _w,op＝W _w×p _w,co，

Wherein,

C _{w, op}: wind energy turbine set year operation expense,

P _{w, co}: year unit operation expense,

C. the power grid construction cost that wind-electricity integration causes mainly refers to the construction cost of above-mentioned transmission line; The total cost of transmission line can be regarded the linear function of line length as; That is, power grid construction cost C _{g, tr}it is a linear function;

(3) proceed to real time execution simulation, based on each period, carry out trend calculating, and the whether satisfied constraint of verification, each subconstiuent the accumulation of this period association system if meet, obtained; Otherwise need to carry out the operating point that correcting property control and then definite system are new and export assistant service value at cost the accumulation of this period; Comprising degree of depth peak regulation cost and stand-by cost;

Degree of depth peak regulation cost: when conventional unit carries out degree of depth peak regulation while guaranteeing electricity net safety stable, just produced system degree of depth peak regulation cost:

C _g,dl＝W _G,dl×p _dl，

Wherein,

C _{g, dl}: degree of depth peak regulation cost,

W _{g, dl}: normal power supplies participates in the energy output that degree of depth peak regulation reduces,

P _dl: unit peak regulation cost;

It is the part energy output that unit output exceeds basic peak regulation that normal power supplies degree of depth peak regulation reduces energy output:

$W_{G,\mathrm{dl}}={\&Integral;}_{K_B{P}_{\mathrm{GN}}\&GreaterEqual;P_{G,\mathrm{actual}}}(K_B{P}_{\mathrm{GN}}-P_{G,\mathrm{actual}})$

Wherein,

K _b: degree of depth peak regulation coefficient,

P _gN: peak regulation unit rated capacity,

P _{g, actual}: actual meritorious the exerting oneself of unit;

Get probability α ∈ (0,1) that reserve capacity meets system safety operation requirement as Reliability Index, the minimum new forms of energy reserve capacity of system that meets confidence level α is:

${\&Integral;}_{-\&infin;}^{{\mathrm{<figure-callout\; id="1"\; label="Res\; d"\; filenames="HDA0000431096110000031.png"\; state="\{\{state\}\}">Res</figure-callout>}}_d}\frac{1}{\sqrt{2\mathrm{\&pi;}}{\mathrm{\&sigma;}}_{\mathrm{wind},d}}\exp (-\frac{{(\mathrm{\&xi;}-{\mathrm{\&mu;}}_{\mathrm{wind},d})}^2}{2{{\mathrm{\&sigma;}}^2}_{\mathrm{wind},d}})\mathrm{d\&xi;}=\mathrm{\&alpha;},$

Wherein,

Res _d: system is required newly-increased day reserve capacity of receiving wind-powered electricity generation,

μ _{wind, d}: the average of predicated error,

σ ² _{wind, d}: the variance of predicated error,

α: system reliability level;

All conventional units of reserve capacity that provide all can obtain corresponding capacity compensation, and this part compensation is exactly the stand-by cost of electrical network for receiving wind-powered electricity generation to produce:

$C_{\mathrm{res}}={\mathrm{\&Sigma;}}_{d=1}^{365}{\mathrm{Res}}_d\&times;p_{\mathrm{res}},$

Wherein,

C _res: year wind-powered electricity generation stand-by cost,

P _res: unit reserve capacity cost;

(4) repeat above-mentioned (1)-(3) process until simulation dispatching cycle finishes; Take one day 24 hours be dispatching cycle, repeating step (1)-(3), the continuous analog wind-powered electricity generation of 24 hours is exerted oneself and is calculated the accumulated value of every value at cost;

(5) carry out the economic dispatch of next cycle, repeat said process until annual simulation finishes, obtain the target function value based on simulation in annual 8760 hours, i.e. the net profit maxV of association system---described association system comprises wind energy turbine set, electrical network and social environment---:

$\max V=\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}(I_{w,\mathrm{co},j}+I_{g,s,j}+I_{g,\mathrm{co},j}+I_{\mathrm{emi},j})-\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[C_{w,c,j}\frac{i}{1-{(1+i)}^{-T_w}}+C_{g,\mathrm{tr},j}\frac{i}{1-{(1+i)}^{-T_l}}+C_{w,o,j}+C_{g,\mathrm{op},j}+C_{g,\mathrm{an},j}],$

Wherein,

I _g,s: the year sale of electricity income of electrical network, depend on through electrical network and carry electric weight and the sale of electricity price that arrives user's side,

I _emi: wind-powered electricity generation environmental benefit,

K: the kind of pollutant emission,

C _{g, tr}: connection charge, be expressed as herein receive wind-powered electricity generation newly-built connect net track cost,

T _l: the operation time limit of newly-built circuit,

C _{g, op}: electrical network annual operating and maintenance cost, only consider network loss cost herein,

C _{g, an}: electrical network year assistant service cost, the assistant service that in the present invention, wind-electricity integration causes comprises stand-by cost and peak regulation cost;

N: the wind turbine number of organizing a performance,

Constraints: system profitability constraint, the constraint of system active balance, the constraint of conventional unit output and circuit overload time-constrain;

V＞0，

$\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{P}_{G,i,h}+\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{w,j,h}=P_{\mathrm{Load},h}+{\mathrm{\&Delta;P}}_{\mathrm{Loss},h},$

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

T _overload/T _total≤0.05；

(6) upgrade wind energy turbine set installed capacity, repeat (1)-(5) process, based on differential evolution algorithm (DE), be optimized and finally obtain each wind energy turbine set installed capacity when maximum of associating net profit, be best receiving scheme;

The expression form of the described constraint implementation method being optimized based on differential evolution algorithm (DE) is:

$F_{i,G+1}=\left\{\begin{array}{c}{F}_{\min }+r_1{F}_{\max },r_2{<\mathrm{\&tau;}}_1\\ F_{i,},\mathrm{else}\end{array}\right.$

$C_{\mathrm{Ri},G+1}=\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="3"\; label="r"\; filenames="HDA0000431096110000031.png"\; state="\{\{state\}\}">r</figure-callout>}}_3,r_4<{\mathrm{\&tau;}}_2\\ C_{\mathrm{Ri},G},\mathrm{else}\end{array}\right.$

Wherein, r ₁, r ₂, r ₃, r ₄: the uniform random number between [0,1], τ ₁, τ ₂: in population, adjust F and C that individual relative is answered _rprobability.

Useful achievement of the present invention: the present invention is by wind energy turbine set that wind-electricity integration is caused and the analysis of electrical network cost benefit problem, a kind of best capacity calculation method of receiving of wind-powered electricity generation that turns to target with association system net profit maximum has been proposed, multianalysis the various costs and benefits that cause after wind-electricity integration, then based on improved DE algorithm, be optimized the best receiving ability of electrical network wind-powered electricity generation that calculates.The present invention is directed to and receive wind-powered electricity generation whether can lose problem, set up the best wind-powered electricity generation receiving capacity calculation model that is target with the net profit of wind energy turbine set and electrical network (consideration environmental benefit) association system to the maximum, the construction cost, operating cost, compensation income, the assistant service cost of electrical network and the environmental benefit that wind-powered electricity generation causes that in target function, comprise wind energy turbine set and electrical network have met the constraintss such as system profitability, generating active power and circuit overload simultaneously.The wind-powered electricity generation that feasible region electrical network economy, safety and stability combine is received capability evaluation.The best receiving ability of wind-powered electricity generation that the present invention finally obtains can be offered suggestions to regional Construction of Wind Power, make Wind-Electric Power Stations installed capacity neither can, because of excessive and cause installation waste, problem that utilance is low, also can not produce because installation is too small the problem that can not make full use of wind-resources.

Accompanying drawing explanation

Fig. 1 is pool cost effectiveness analysis schematic diagram figure of the present invention.Wherein, figure (a) is wind energy turbine set Cost-benefit analysis schematic diagram.Figure (b) is electrical network cost effectiveness analysis schematic diagram.

Fig. 2 is the best capacity calculation flow chart of receiving.

Fig. 3 is RTS79 electric power system topological structure schematic diagram.

Fig. 4 is the population location drawing in the last reign of a dynasty based on improving after DE algorithm optimization.

Embodiment

Below in conjunction with the drawings and specific embodiments, the present invention is described in further detail.

Fig. 1 is pool cost effectiveness analysis schematic diagram of the present invention.Wherein, figure (a) is wind energy turbine set Cost-benefit analysis schematic diagram.Figure (b) is electrical network cost effectiveness analysis schematic diagram.Fig. 2 is the best capacity calculation flow chart of receiving.Empty frame in Fig. 2 represents the time limit, is once a period, a dispatching cycle (one day), the whole year from inside to outside.Fig. 3 is RTS79 electric power system topological structure schematic diagram, and Fig. 4 is the population location drawing in the last reign of a dynasty based on improving after DE algorithm optimization.

The present invention be take certain District power network planning as example, adopts RTS-79 standard example, carries out the analysis of the best receiving ability of wind-powered electricity generation.Intending access point is Bus7 and Bus14, and wind-electricity integration adopts the control mode of PQ power factor to carry out, and power factor gets 0.95, and load prediction error adopts normal distribution model; Wind speed adopts Weibull distribution model.Wherein, accompanying drawing 3 is shown in by RTS79 standard example topological structure,, fan parameter arranges as follows:

Table 1 wind energy turbine set parameter

Somewhere wind park construction cost is 9000 yuan/kW; Average sales rate of electricity is 0.48 yuan/kWh inside the province; For receiving two, two wind farm grid-connected newly-increased circuits, specification is LGJ-185, and total length is 15km, and unit price is 1,300,000 yuan/km; Wind energy turbine set and power network compensation income are respectively 0.12 yuan/kWh and 0.1 yuan/kWh; Peak regulation COEFFICIENT K B gets 55%; Unit stand-by cost and unit peak regulation cost are got respectively 0.013 yuan/kWh and 0.1 yuan/kWh; An equivalence year value coefficient gets 0.08.

A kind of regional power grid wind-powered electricity generation multiple spot of realizing economy optimum accesses the computational methods of best receiving ability, and the method step is as follows:

1) the wind-powered electricity generation access point based on example and setting, the installed capacity of initialization wind energy turbine set 1 and wind energy turbine set 2, samples to two output of wind electric field in conjunction with Weibull distribution, based on normal distribution, system loading situation is sampled.In the present invention, will within one day, be divided into 24 operating points (operating point per hour), annual with the time scale sampling of 1h, form 8760 scenes.Corresponding wind energy turbine set 1 exert oneself P1, wind energy turbine set 2 exert oneself P2 and system loading PL under each scene.

Based on output of wind electric field sampling, take one day as dispatching cycle, according to economic dispatch model, contain Unit Combination optimization the preservation of wind energy turbine set;

2) carry out the calculating of wind-powered electricity generation annual energy output, only obtain the target function subconstiuent relevant to wind power generation amount, comprise electrical network sale of electricity income I _{g, s, j}, compensation income I _{w, co}, Construction of Wind Power cost C _w,c, year operation expense C _{w, op}with power grid construction cost C _{g, tr}.

3) proceed to real time execution simulation, based on each period, carry out trend calculating, and the whether satisfied constraint of verification, each subconstiuent the accumulation of this period association system if meet, obtained; Otherwise need to carry out the operating point that correcting property control and then definite system are new and export assistant service value at cost the accumulation of this period.Comprising degree of depth peak regulation cost and stand-by cost.

4) repeat said process until simulation dispatching cycle finishes; The one day 24h of take is dispatching cycle, repeating step 3), the wind-powered electricity generation of continuous analog 24h is exerted oneself and is calculated the accumulated value of every value at cost;

5) carry out the Unit Combination of next cycle, repeat said process until annual simulation finishes, obtain the target function value based on simulation in annual 8760 hours, i.e. the net profit maxV of association system;

$\max V=\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}(I_{w,\mathrm{co},j}+I_{g,s,j}+I_{g,\mathrm{co},j}+I_{\mathrm{emi},j})-\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[C_{w,c,j}\frac{i}{1-{(1+i)}^{-T_w}}+C_{g,\mathrm{tr},j}\frac{i}{1-{(1+i)}^{-T_l}}+C_{w,o,j}+C_{g,\mathrm{op},j}+C_{g,\mathrm{an},j}],$

Wherein,

I _g,s: the year sale of electricity income of electrical network, depend on through electrical network and carry electric weight and the sale of electricity price that arrives user's side,

I _emi: wind-powered electricity generation environmental benefit,

K: the kind of pollutant emission,

C _{g, tr}: connection charge, be expressed as herein receive wind-powered electricity generation newly-built connect net track cost,

T _l: the operation time limit of newly-built circuit,

C _{g, op}: electrical network annual operating and maintenance cost, only consider network loss cost herein,

C _{g, an}: electrical network year assistant service cost, the assistant service that in the present invention, wind-electricity integration causes comprises stand-by cost and peak regulation cost;

Constraints: system profitability constraint, the constraint of system active balance, the constraint of conventional unit output and circuit overload time-constrain;

V＞0，

$\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{P}_{G,i,h}+\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{w,j,h}=P_{\mathrm{Load},h}+{\mathrm{\&Delta;P}}_{\mathrm{Loss},h},$

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

T _overload/T _total≤0.05；

6) upgrade wind energy turbine set installed capacity, repeat said process, the result of calculating according to initial population, carries out differential, selects operation according to differential evolution algorithm operation initial population, forms population of new generation.Then population of new generation is brought into adaptive value function and calculates, and in like manner Population Regeneration until meet the end condition of iteration.Iterated conditional is that iterations arrives original maximum iteration time of setting, and is 100 times in the present invention.Based on differential evolution algorithm, be optimized and finally obtain each wind energy turbine set installed capacity when maximum of associating net profit, be best receiving scheme.Method finishes.

The present invention selects Output rusults to be the installed capacity of wind energy turbine set 1 and wind energy turbine set 2, whether to meet constraint and association system net profit.The simulation result that iteration is 100 times is as follows: (wherein, for constraint, whether meet one, 1 representative meets constraints, and 0 representative does not meet constraints, in follow-up processing, can be rejected).

Table 2. program Output rusults

From iteration result, can find out in table has the scheme that does not meet constraints to exist, after rejecting infeasible scheme and iteration scheme, can see through iteration, the optimum results of each population is more or less the same, the installed capacity of wind energy turbine set 1 is [262.5,264], in scope, wind energy turbine set 2 installed capacitys are in [360,410] scope, iteration result is more or less the same, and the maximum iteration time of selecting in this read-me is for 100 times rational.

In order more clearly to analyze every cost (benefit) proportion, in table 3, shown optimal case result:

Table 3. optimal case

Result shows, the installed capacity corresponding to point of associating net profit maximum is respectively 264MW and 373.5MW, and the best wind-powered electricity generation of required electrical network is received ability, and now the net profit of association system is 3.649 hundred million yuan.In optimal case, wind-powered electricity generation access has reduced via net loss cost, has caused certain new forms of energy stand-by cost simultaneously, has especially greatly increased peak regulation cost, has proved that the abundant property of peak load regulation network problem is to affect one of grid-connected main factor of large-scale wind power.In addition, wind-electricity integration must bring huge environmental benefit to society, this be also the new forms of energy such as wind-powered electricity generation can develop major reason rapidly.

The present invention is directed to and receive wind-powered electricity generation whether can lose problem, set up the best wind-powered electricity generation receiving capacity calculation model that is target with the net profit of wind energy turbine set and electrical network (consideration environmental benefit) association system to the maximum, the construction cost, operating cost, compensation income, the assistant service cost of electrical network and the environmental benefit that wind-powered electricity generation causes that in target function, comprise wind energy turbine set and electrical network have met the constraintss such as system profitability, generating active power and circuit overload simultaneously.The wind-powered electricity generation that feasible region electrical network economy, safety and stability combine is received capability evaluation.The best receiving ability of wind-powered electricity generation that the present invention finally obtains can be offered suggestions to regional Construction of Wind Power, make Wind-Electric Power Stations installed capacity neither can, because of excessive and cause installation waste, problem that utilance is low, also can not produce because installation is too small the problem that can not make full use of wind-resources.

Finally explanation is, above example is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiments, those of ordinary skill in the art is to be understood that, can to technical scheme of the present invention modify or etc. between replace, and not departing from aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of claim scope of the present invention.

Claims (2)

1. regional power grid wind-powered electricity generation multiple spot accesses computational methods for best receiving ability, it is characterized in that, the method step is as follows:

(1) each wind energy turbine set installed capacity of initialization P _n, and gather local air speed data, conventional unit installed capacity, yearly peak load data, according to blower fan output calculation model, draw planning each output of wind electric field situation P in year _{w, j, h};

Described wind-powered electricity generation unit output calculation model:

$p_w\left(v\right)=\left\{\begin{array}{c}0,0\&le;v<v_{\mathrm{ci}}\\ p_N\frac{v_i-v_{\mathrm{ci}}}{v_R-v_{\mathrm{ci}}},v_{\mathrm{ci}}\&le;v<v_R\\ P_N,v_R\&le;v<v_{\mathrm{co}}\end{array}\right.,$

Wherein,

P _w(v): wind power,

P _n: blower fan rated power,

V _ci: the incision wind speed of blower fan,

V _r: the rated wind speed of blower fan,

V _co: the cut-out wind speed of blower fan;

By year wind-powered electricity generation exert oneself situation in conjunction with load prediction level, carry out the system Unit Combination optimization of first dispatching cycle, according to economic dispatch model, obtain each operating states of the units and the generated output of each period in one day:

$\min E=\underset{t=1}{\overset{T}{\mathrm{\&Sigma;}}}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{U}_{\mathrm{it}}{f}_{\mathrm{it}}\left(P_{\mathrm{it}}\right),$

Constraints:

$\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{G,i,h}+\underset{j=1}{\overset{M}{\mathrm{\&Sigma;}}}{P}_{w,j,h}=P_{\mathrm{Load},h}+{\mathrm{\&Delta;P}}_{\mathrm{Loss},h},$

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

P{D _Ri≤P _it-P _it-1≤U _Ri}≥β ₁，

Wherein,

E: system total power production cost,

T: hop count in the time of in research cycle,

N: the number of units of conventional power generation usage unit in system,

U _it: conventional unit i is at the start and stop state of period t, U _it=1 represents operation, U _it=0 represents to shut down,

P _it: conventional unit i is at the active power of output of period t,

F _it(P _it): the operating cost of conventional unit i, expression way is:

$f_{\mathrm{it}}\left(P_{\mathrm{it}}\right)=a_i+b_i{P}_{\mathrm{it}}+c_i{P}_{\mathrm{it}}^2+\left|d_i\sin \right[e_i(P_{\mathrm{it}}^{\min }-P_{\mathrm{it}})\left]\right|,$ Wherein, a _i, b _i, c _i, d _i, e _i: the coefficient of cost function,

: conventional unit i is at the lower limit of exerting oneself of period t,

M: the wind turbine number of organizing a performance,

P _{g, i, h}: conventional unit is meritorious exerts oneself,

P _{w, j, h}: wind-powered electricity generation unit is meritorious exerts oneself,

P _{load, h}: burden with power size,

Δ P _{loss, h}: active power loss,

P _{g, i, h, min}, P _{g, i, h, max}: represent respectively technology minimum load and the maximum output of conventional unit,

D _ri, U _ri: conventional unit i is at meritorious fall off rate and the climbing speed of exerting oneself of period t,

β ₁: prior given confidence level;

(2) carry out the calculating of wind-powered electricity generation annual energy output, only obtain the target function subconstiuent relevant to wind power generation amount, described the target function subconstiuent relevant to wind power generation amount comprises electrical network sale of electricity income I _{g, s, j}, compensation income I _{g, co}, wind energy turbine set compensation income I _{w, co}, Construction of Wind Power cost C _w,c, wind energy turbine set year operation expense C _{w, op}with power grid construction cost C _{g, tr};

A. electrical network sale of electricity income I _{g, s, j}, be expressed as the product of electrical network electricity sales amount and sale of electricity price; Compensation income, comprises the compensation to the compensation He Dui power grid enterprises of wind energy turbine set self;

Wind energy turbine set year compensation income:

I _w,co＝W _w×p _w,co，

Wherein,

I _{w, co}: wind energy turbine set year compensation income,

W _w: wind energy turbine set annual energy output,

P _{w, co}: the compensation of wind power generation annual energy output unit,

Electrical network year compensation income:

I _g,co＝W _w×p _g,co，

Wherein,

I _{g, co}: electrical network year compensation income,

P _{g, co}: electrical network is received the compensation of wind-powered electricity generation annual energy output unit,

B. wind-powered electricity generation cost of investment comprise wind energy turbine set year construction cost and wind energy turbine set year operation expense;

Wind energy turbine set year construction cost:

$C_{w,c,\mathrm{actual}}=C_{w,c}\&times;i/[1-{(1+i)}^{-T_w}],$

Wherein,

C _{w, c, actual}: wind energy turbine set year construction cost,

C _w,c: the wind energy turbine set initial stage is built total cost,

I: bank's Annual Percentage Rate,

T _w: the life-span time limit of wind energy turbine set,

: fund equivalence year value coefficient,

Wind energy turbine set year operation expense:

C _w,op＝W _w×p _w,co，

Wherein,

C _{w, op}: wind energy turbine set year operation expense,

P _{w, co}: year unit operation expense,

C. the power grid construction cost that wind-electricity integration causes mainly refers to the construction cost of above-mentioned transmission line; The total cost of transmission line can be regarded the linear function of line length as; That is, power grid construction cost C _{g, tr}it is a linear function;

(3) proceed to real time execution simulation, based on each period, carry out trend calculating, and the whether satisfied constraint of verification, each subconstiuent the accumulation of this period association system if meet, obtained; Otherwise need to carry out the operating point that correcting property control and then definite system are new and export assistant service value at cost the accumulation of this period; Comprising degree of depth peak regulation cost and stand-by cost;

Degree of depth peak regulation cost: when conventional unit carries out degree of depth peak regulation while guaranteeing electricity net safety stable, just produced system degree of depth peak regulation cost:

C _g,dl＝W _G,dl×p _dl，

Wherein,

C _{g, dl}: degree of depth peak regulation cost,

W _{g, dl}: normal power supplies participates in the energy output that degree of depth peak regulation reduces,

P _dl: unit peak regulation cost;

It is the part energy output that unit output exceeds basic peak regulation that normal power supplies degree of depth peak regulation reduces energy output:

$W_{G,\mathrm{dl}}={\&Integral;}_{K_B{P}_{\mathrm{GN}}\&GreaterEqual;P_{G,\mathrm{actual}}}(K_B{P}_{\mathrm{GN}}-P_{G,\mathrm{actual}})$

Wherein,

K _b: degree of depth peak regulation coefficient,

P _gN: peak regulation unit rated capacity,

P _{g, actual}: actual meritorious the exerting oneself of unit;

Get probability α ∈ (0,1) that reserve capacity meets system safety operation requirement as Reliability Index, the minimum new forms of energy reserve capacity of system that meets confidence level α is:

${\&Integral;}_{-\&infin;}^{{\mathrm{Res}}_d}\frac{1}{\sqrt{2\mathrm{\&pi;}}{\mathrm{\&sigma;}}_{\mathrm{wind},d}}\exp (-\frac{{(\mathrm{\&xi;}-{\mathrm{\&mu;}}_{\mathrm{wind},d})}^2}{2{{\mathrm{\&sigma;}}^2}_{\mathrm{wind},d}})\mathrm{d\&xi;}=\mathrm{\&alpha;},$

Wherein,

Res _d: system is required newly-increased day reserve capacity of receiving wind-powered electricity generation,

μ _{wind, d}: the average of predicated error,

σ ² _{wind, d}: the variance of predicated error,

α: system reliability level;

All conventional units of reserve capacity that provide all can obtain corresponding capacity compensation, and this part compensation is exactly the stand-by cost of electrical network for receiving wind-powered electricity generation to produce:

$C_{\mathrm{res}}={\mathrm{\&Sigma;}}_{d=1}^{365}{\mathrm{Res}}_d\&times;p_{\mathrm{res}},$

Wherein,

C _res: year wind-powered electricity generation stand-by cost,

P _res: unit reserve capacity cost;

(4) repeat above-mentioned (1)-(3) process until simulation dispatching cycle finishes; Take one day 24 hours be dispatching cycle, repeating step (1)-(3), the continuous analog wind-powered electricity generation of 24 hours is exerted oneself and is calculated the accumulated value of every value at cost;

(5) carry out the economic dispatch of next cycle, repeat said process until annual simulation finishes, obtain the target function value based on simulation in annual 8760 hours, association system-described association system comprise wind energy turbine set, electrical network and social environment-net profit maxV:

$\max V=\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}(I_{w,\mathrm{co},j}+I_{g,s,j}+I_{g,\mathrm{co},j}+I_{\mathrm{emi},j})-\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}[C_{w,c,j}\frac{i}{1-{(1+i)}^{-T_w}}+C_{g,\mathrm{tr},j}\frac{i}{1-{(1+i)}^{-T_l}}+C_{w,o,j}+C_{g,\mathrm{op},j}+C_{g,\mathrm{an},j}],$

Wherein,

I _g,s: the year sale of electricity income of electrical network, depend on through electrical network and carry electric weight and the sale of electricity price that arrives user's side,

I _emi: wind-powered electricity generation environmental benefit,

K: the kind of pollutant emission,

C _{g, tr}: connection charge, be expressed as herein receive wind-powered electricity generation newly-built connect net track cost,

T _l: the operation time limit of newly-built circuit,

C _{g, op}: electrical network annual operating and maintenance cost, only consider network loss cost herein,

C _{g, an}: electrical network year assistant service cost, the assistant service that in the present invention, wind-electricity integration causes comprises stand-by cost and peak regulation cost;

N: the wind turbine number of organizing a performance,

Constraints: system profitability constraint, the constraint of system active balance, the constraint of conventional unit output and circuit overload time-constrain;

V＞0，

$\underset{i=1}{\overset{M}{\mathrm{\&Sigma;}}}{P}_{G,i,h}+\underset{j=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{w,j,h}=P_{\mathrm{Load},h}+{\mathrm{\&Delta;P}}_{\mathrm{Loss},h},$

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

T _overload/T _total≤0.05；

(6) upgrade wind energy turbine set installed capacity, repeat (1)-(5) process, based on differential evolution algorithm (DE), be optimized and finally obtain each wind energy turbine set installed capacity when maximum of associating net profit, be best receiving scheme;

The expression form of the described constraint implementation method being optimized based on differential evolution algorithm (DE) is:

$F_{i,G+1}=\left\{\begin{array}{c}{F}_{\min }+r_1{F}_{\max },r_2{<\mathrm{\&tau;}}_1\\ F_{i,},\mathrm{else}\end{array}\right.$

$C_{\mathrm{Ri},G+1}=\left\{\begin{array}{c}{r}_3,r_4<{\mathrm{\&tau;}}_2\\ C_{\mathrm{Ri},G},\mathrm{else}\end{array}\right.$

Wherein, r ₁, r ₂, r ₃, r ₄: the uniform random number between [0,1], τ ₁, τ ₂: in population, adjust F and C that individual relative is answered _rprobability.

2. a kind of regional power grid wind-powered electricity generation multiple spot according to claim 1 accesses the computational methods of best receiving ability, it is characterized in that described degree of depth peak regulation COEFFICIENT K _bget 50%-60%.

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