CN103683326B - A kind of regional power grid wind-powered electricity generation multiple spot accesses the computational methods of best receiving ability - Google Patents

Abstract

Regional power grid wind-powered electricity generation multiple spot accesses computational methods for best receiving ability, belongs to power grid wind acceptance method technical field.Each wind energy turbine set installed capacity of initialization also gathers the data such as local wind speed; Calculate each output of wind electric field situation and carry out the Unit Combination optimization in each dispatching cycle, obtaining the annual Unit Combination mode of electric power system containing wind energy turbine set; Carry out Load flow calculation based on each period and verify whether meet system cloud gray model constraint, after simulation in 8760 hours is carried out to system, calculate final goal functional value; Upgrade wind energy turbine set installation and be optimized iteration to target function, in optimal solution, wind-powered electricity generation generate output is the best receiving ability of this power grid wind making system economy reach optimum while meeting safety and stability constraint.The present invention establishes the best wind-powered electricity generation being target to the maximum with the net profit of wind energy turbine set and electrical network (consideration environmental benefit) association system and receives capacity calculation model, suitably can build offer suggestions to Wind-Electric Power Stations installed capacity.

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 power grid wind acceptance method technical field.

Background technology

Along with day by day highlighting of energy security problem and environmental problem, China increases 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 excellent 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 fully must receive wind-powered electricity generation, this policy requirements electrical network must provide supporting grid-connected construction for this reason, increase and run for subsequent use and peak regulation cost, certain financial burden is brought to power grid enterprises, 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.It is on the one hand the regulation that the electrical network of Renewable Energy Law fully receives wind-powered electricity generation, the requirement of electrical network to fail safe, reliability, economy on the one hand, wind energy turbine set is made to abandon wind phenomenon serious, installation serious waste, existing research mainly concentrates on the technological layer considering ability to transmit electricity constraint and peak load regulation network capacity consistency, 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 meeting two aspects simultaneously and require, for Wind-Electric Power Stations construction is offered suggestions.

Summary of the invention

Whether can lose for receiving wind-powered electricity generation---economy carries out prediction and calculation, and at present Wind Power Development situation and existing research above shortcomings, under the object of this invention is to provide a kind of condition meeting system safety constraint, network transmission of electricity security constraint, the wind-powered electricity generation making the real receptible system net profit of electric power enterprise maximum receives capacity calculation method, and (economy is optimum, ask max), and based on improvement DE algorithm, analogue simulation is carried out to annual 8760 periods, 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 power unit installed capacity, yearly peak load data, each output of wind electric field situation P in planning year is drawn according to blower fan output calculation model _{w, j, h};

Described Wind turbines 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 power output situation in conjunction with load prediction level, carry out the Unit Combination optimization of first dispatching cycle of system, obtain each operating states of the units and the generated output of each period in one day according to economic dispatch model:

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

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 time in research cycle,

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

U _it: conventional power unit i in the start and stop state of period t, U _it=1 represents operation, U _it=0 represents shutdown,

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

F _it(P _it): the operating cost of conventional power 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 power unit i at the lower limit of exerting oneself of period t,

M: Wind turbines number of units,

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

P _{w, j, h}: Wind turbines 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}: the technology minimum load and the maximum output that represent conventional power unit respectively,

D _ri, U _ri: conventional power unit i at the meritorious output drop speed of period t and climbing speed,

β ₁: confidence level given in advance;

(2) carry out the calculating of wind-powered electricity generation annual energy output, obtain only relevant to wind power generation amount target function subconstiuent, described the target function subconstiuent relevant to wind power generation amount comprises electrical network sale of electricity income I _{g, s, j}, compensate income I _{g, co}, wind energy turbine set compensate 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}, the product of electrical network electricity sales amount and sale of electricity price can be expressed as, compensate income, comprise the compensation to wind energy turbine set self and the compensation to power grid enterprises;

Wind energy turbine set year compensates income:

I _w,co＝W _w×p _w,co，

Wherein,

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

W _w: wind energy turbine set annual energy output,

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

Electrical network year compensates income:

I _g,co＝W _w×p _g,co，

Wherein,

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

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

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: wind energy turbine set primary construction 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 regard 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, namely carry out Load flow calculation based on each period, and whether verification meets constraint, if meet, obtains each subconstiuent of this period association system and accumulates; Otherwise then need to carry out correcting property control and then the new operating point of certainty annuity and export the assistant service value at cost of this period and accumulate; Comprising degree of depth peak regulation cost and stand-by cost;

Degree of depth peak regulation cost: when conventional power unit carries out degree of depth peak regulation to ensure electricity net safety stable, just creates system 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;

Normal power supplies degree of depth peak regulation minimizing energy output and unit output exceed the part energy output of basic peak regulation:

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

Wherein,

K _b: degree of depth peak regulation coefficient,

P _gN: regulating units rated capacity,

P _{g, actual}: actual the gaining merit of unit is exerted oneself;

Get reserve capacity and meet the probability α ∈ (0,1) of system safety operation requirement as Reliability Index, then the minimum new forms of energy reserve capacity of system meeting 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: in order to receive, wind-powered electricity generation is required increases day reserve capacity newly to system,

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

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

α: system reliability level;

All conventional power unit of reserve capacity that provides all can obtain corresponding capacity compensation, and this part compensation is exactly electrical network is the stand-by cost 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) above-mentioned (1)-(3) process is repeated until simulation dispatching cycle terminates; With one day 24 hours for dispatching cycle, repeat step (1)-(3), the accumulated value of the continuous analog wind power output of 24 hours and the every value at cost of calculating;

(5) economic dispatch of next cycle is carried out, repeat said process until annual simulation terminates, 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 the electricity and the sale of electricity price that arrive user side through electrical network conveying,

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 Web-based exercise 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: Wind turbines number of units,

Constraints: system profitability constraint, the constraint of system active balance, conventional power unit units limits 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 finally obtain associating net profit maximum time each wind energy turbine set installed capacity, be best receiving scheme;

The expression form of the described constraint implementation method be 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: adjust F and C that individual relative is answered in population _rprobability.

Useful achievement of the present invention: the present invention is by the analysis of the wind energy turbine set that causes wind-electricity integration and electrical network cost benefit problem, propose a kind of with the maximum wind-powered electricity generation the best receiving capacity calculation method turning to target of association system net profit, the various costs and benefits caused after multianalysis wind-electricity integration, are then optimized based on the DE algorithm improved and calculate the best receiving ability of power grid wind.The present invention is directed to and receive wind-powered electricity generation whether can lose problem, establish the best wind-powered electricity generation being target to the maximum with the net profit of wind energy turbine set and electrical network (consideration environmental benefit) association system and receive capacity calculation model, comprise the environmental benefit that the construction cost of wind energy turbine set and electrical network, operating cost, compensation income, the assistant service cost of electrical network and wind-powered electricity generation cause in target function, meet system profitability, constraints such as generating active power and circuit overload etc. simultaneously.The wind-powered electricity generation that feasible region economic power system, safety and stability combine receives capability evaluation.The best receiving ability of the 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 both can not cause the problem that installation is wasted, utilance is low because of excessive, also can not produce the problem that can not make full use of wind-resources because installation is too small.

Accompanying drawing explanation

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

Fig. 2 is best receiving capacity calculation flow chart.

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, scheming (a) is wind energy turbine set Cost-benefit analysis schematic diagram.Figure (b) is electrical network cost effectiveness analysis schematic diagram.Fig. 2 is best receiving capacity calculation flow chart.Empty frame in Fig. 2 represents the time limit, is once period, dispatching cycle (a day), annual 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, for certain District power network planning, adopts RTS-79 standard example, carries out the analysis of the best receiving ability of wind-powered electricity generation.Plan 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 wind farm grid-connected two, 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 get 0.013 yuan/kWh and 0.1 yuan/kWh respectively; Equivalence year value coefficient gets 0.08.

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

1) based on the wind power integration point of 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, samples based on normal distribution to system loading situation.In the present invention, one day is divided into 24 operating points (operating point per hour), annual with the sampling of the time scale of 1h, form 8760 scenes.Under each scene, exert oneself P1, wind energy turbine set 2 of corresponding wind energy turbine set 1 is exerted oneself P2 and system loading PL.

Based on output of wind electric field sampling, with one day for dispatching cycle, carry out the Unit Combination optimization containing wind energy turbine set according to economic dispatch model and preserve;

2) carry out the calculating of wind-powered electricity generation annual energy output, obtain only relevant to wind power generation amount target function subconstiuent, comprise electrical network sale of electricity income I _{g, s, j}, compensate 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, namely carry out Load flow calculation based on each period, and whether verification meets constraint, if meet, obtains each subconstiuent of this period association system and accumulates; Otherwise then need to carry out correcting property control and then the new operating point of certainty annuity and export the assistant service value at cost of this period and accumulate.Comprising degree of depth peak regulation cost and stand-by cost.

4) said process is repeated until simulation dispatching cycle terminates; With one day 24h for dispatching cycle, repeat step 3), the wind power output of continuous analog 24h and the accumulated value of the every value at cost of calculating;

5) carry out the Unit Combination of next cycle, repeat said process until annual simulation terminates, 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 the electricity and the sale of electricity price that arrive user side through electrical network conveying,

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 Web-based exercise 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, conventional power unit units limits 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, according to the result that initial population calculates, initial population is carried out to differential according to differential evolution algorithm operation, selected operation, forms the population of a new generation.Then population of new generation is brought into adaptive value function calculate, and in like manner Population Regeneration until meet the end condition of iteration.Iterated conditional is the maximum iteration time that iterations arrives original setting, is 100 times in the present invention.Based on differential evolution algorithm be optimized finally obtain associating net profit maximum time each wind energy turbine set installed capacity, be best receiving scheme.Method terminates.

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

Table 2. program Output rusults

Can find out in table from iteration result and have the scheme not meeting constraints to exist, can see through iteration after rejecting infeasible scheme and iteration scheme, 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 capacity is in [360,410] scope, iteration result is more or less the same, and the maximum iteration time selected in this read-me is rational 100 times.

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

Table 3. optimal case

Result shows, the installed capacity of the some correspondence that associating net profit is maximum is respectively 264MW and 373.5MW, and the best wind-powered electricity generation of namely required electrical network receives ability, and now the net profit of association system is 3.649 hundred million yuan.In optimal case, wind power integration reduces via net loss cost, causes certain new forms of energy stand-by cost simultaneously, especially considerably increases peak regulation cost, and demonstrating the abundance problem of peak load regulation network is 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, establish the best wind-powered electricity generation being target to the maximum with the net profit of wind energy turbine set and electrical network (consideration environmental benefit) association system and receive capacity calculation model, comprise the environmental benefit that the construction cost of wind energy turbine set and electrical network, operating cost, compensation income, the assistant service cost of electrical network and wind-powered electricity generation cause in target function, meet system profitability, constraints such as generating active power and circuit overload etc. simultaneously.The wind-powered electricity generation that feasible region economic power system, safety and stability combine receives capability evaluation.The best receiving ability of the 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 both can not cause the problem that installation is wasted, utilance is low because of excessive, also can not produce the problem that can not make full use of wind-resources because installation is too small.

What finally illustrate is, above example is only in order to illustrate technical scheme of the present invention and unrestricted, although with reference to preferred embodiments to invention has been detailed description, those of ordinary skill in the art is to be understood that, can modify to technical scheme of the present invention 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 right 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 power unit installed capacity, yearly peak load data, each output of wind electric field situation P in planning year is drawn according to blower fan output calculation model _{w, j, h};

Described blower fan output calculation model:

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

Wherein,

P _wv () is wind power,

P _nfor 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 power output situation in conjunction with load prediction level, carry out the Unit Combination optimization of first dispatching cycle of system, obtain each operating states of the units and the generated output of each period in one day according to economic dispatch model:

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

Constraints:

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

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 time in research cycle,

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

U _it: conventional power unit i in the start and stop state of period t, U _it=1 represents operation, U _it=0 represents shutdown,

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

F _it(P _it): the operating cost of conventional power unit i, expression way is: $f_{it}\left(P_{it}\right)=a_i+b_i{P}_{it}+c_i{P}_{it}^2+|d_{i}sin\&lsqb;e_i(P_{it}^{min}-P_{it})\&rsqb;|,$ Wherein, a _i, b _i, c _i, d _i, e _i: the coefficient of cost function,

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

M: Wind turbines number of units,

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

P _{w, j, h}: Wind turbines 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}: the technology minimum load and the maximum output that represent conventional power unit respectively,

D _ri, U _ri: conventional power unit i at the meritorious output drop speed of period t and climbing speed,

β ₁: confidence level given in advance;

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

A. electrical network sale of electricity income, can be expressed as the product of electrical network electricity sales amount and sale of electricity price, and electrical network year compensates income I _{g, co}, comprise the compensation to wind energy turbine set self and the compensation to power grid enterprises;

Wind energy turbine set year compensates income:

I _w,co＝W _w×p _w,co，

Wherein,

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

W _w: wind energy turbine set annual energy output,

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

Electrical network year compensates income:

I _g,co＝W _w×p _g,co，

Wherein,

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

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

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:

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

Wherein,

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

C _w,c: wind energy turbine set primary construction 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 transmission line; The total cost of transmission line can regard 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, namely carry out Load flow calculation based on each period, and whether verification meets constraint, if meet, obtains each subconstiuent of this period association system and accumulates; Otherwise then need to carry out correcting property control and then the new operating point of certainty annuity and export the assistant service value at cost of this period and accumulate; Comprising degree of depth peak regulation cost and stand-by cost;

Degree of depth peak regulation cost: when conventional power unit carries out degree of depth peak regulation to ensure electricity net safety stable, just creates system 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;

Normal power supplies degree of depth peak regulation minimizing energy output and unit output exceed the part energy output of basic peak regulation:

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

Wherein,

K _b: degree of depth peak regulation coefficient,

P _gN: regulating units rated capacity,

P _{g, actual}: actual the gaining merit of unit is exerted oneself;

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

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

Wherein,

in order to receive, wind-powered electricity generation is required increases day reserve capacity newly to system,

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

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

α: system reliability level;

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

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

Wherein,

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

P _res: unit reserve capacity cost;

(4) above-mentioned (1)-(3) process is repeated until simulation dispatching cycle terminates; With one day 24 hours for dispatching cycle, repeat step (1)-(3), the accumulated value of the continuous analog wind power output of 24 hours and the every value at cost of calculating;

(5) economic dispatch of next cycle is carried out, repeat said process until annual simulation terminates, 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---:

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

Wherein,

I _g,s: the year sale of electricity income of electrical network, depend on the electricity and the sale of electricity price that arrive user side through electrical network conveying,

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 Web-based exercise herein,

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

N: Wind turbines number of units,

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

V>0，

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

P _G,i,h,min≤P _G,i,h≤P _G,i,h,max，

T _overload/T _total≤0.05；

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

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

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

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

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