Abstract Ib qho kev faib ua feem ntau ntawm photovoltaic fais fab tuag yuav muaj kev cuam tshuam tsis zoo rau kev ruaj ntseg ntawm lub zog hluav taws xob, thiab lub zog cia yog suav tias yog ib qho txiaj ntsig zoo los tshem tawm cov teebmeem no. Daim ntawv no txheeb xyuas qhov cuam tshuam ntawm kev tsim hluav taws xob photovoltaic ntawm lub zog hluav taws xob los ntawm qhov kev xav ntawm lub zog ntws, thiab tom qab ntawd txheeb xyuas cov txiaj ntsig ntawm lub zog cia ntawm kev txwv lub zog. Ua ntej, cov qauv kev faib tawm qhov tshwm sim thiab lub zog cia qauv ntawm cov khoom hauv lub zog hluav taws xob tau qhia, thiab Latin hypercube sampling method thiab gram-Schmidt sequence normalization method tau qhia. Thib ob, ntau lub hom phiaj optimization qauv tau tsim, uas suav tias yog tus nqi ntawm lub zog cia khoom, qhov tsis muaj peev xwm ntawm cov ceg fais fab ntws thiab lub network poob ntawm daim phiaj hluav taws xob. Qhov kev daws teeb meem zoo tshaj plaws ntawm lub hom phiaj muaj nuj nqi tau txais los ntawm kev tshuaj ntsuam genetic algorithm. Thaum kawg, qhov simulation tau ua tiav hauv IEEE24 node xeem system los txheeb xyuas qhov cuam tshuam ntawm qhov sib txawv photovoltaic muaj peev xwm nkag mus tau thiab nkag mus rau qhov chaw ntawm lub zog hluav taws xob thiab cov txiaj ntsig ntawm lub zog cia ntawm lub zog hluav taws xob, thiab qhov kev pom zoo ntawm lub zog khaws cia sib xws rau qhov sib txawv photovoltaic muaj peev xwm. yog tau.

Cov lus tseem ceeb photovoltaic zog tsim; Lub zog cia system; Optimized configuration; Yam yuav muaj zog txaus; Genetic algorithm (ga)

Kev tsim hluav taws xob photovoltaic muaj qhov zoo ntawm kev tiv thaiv ib puag ncig ntsuab thiab rov ua dua tshiab, thiab suav tias yog ib qho ntawm cov muaj peev xwm txuas ntxiv mus ntxiv. Los ntawm 2020, Tuam Tshoj tus tsim tsim muaj peev xwm ntawm photovoltaic fais fab tuag tau mus txog 253 lab kw. Kev sib cuam tshuam thiab tsis paub meej ntawm cov hluav taws xob loj PV cuam tshuam rau lub zog hluav taws xob, suav nrog cov teeb meem ntawm qhov siab tshaj plaws shaving, ruaj khov thiab lub teeb pov tseg, thiab daim phiaj yuav tsum tau txais kev hloov pauv ntau dua los daws cov teeb meem no. Lub zog cia tau suav tias yog ib txoj hauv kev zoo los daws cov teeb meem no. Daim ntawv thov ntawm lub zog cia qhov system coj cov kev daws teeb meem tshiab rau kev sib txuas loj loj photovoltaic kab sib chaws.

Tam sim no, muaj ntau yam kev tshawb fawb txog kev tsim hluav taws xob photovoltaic, lub zog khaws cia thiab qhov yuav muaj zog txaus hauv tsev thiab txawv teb chaws. Ntau cov ntaub ntawv kev tshawb fawb qhia tau hais tias lub zog cia tuaj yeem txhim kho qhov kev siv ntawm photovoltaic thiab daws qhov ruaj khov ntawm photovoltaic daim phiaj sib txuas. Nyob rau hauv lub configuration ntawm lub zog cia system nyob rau hauv lub tshiab lub zog fais fab chaw nres tsheb yuav tsum tau them nyiaj mloog tsis tsuas yog rau kev tswj lub tswv yim ntawm optical cia thiab cua cia, tab sis kuj rau kev lag luam ntawm lub zog cia system. Nyob rau hauv tas li ntawd, rau optimization ntawm ntau lub zog cia chaw nres tsheb nyob rau hauv lub hwj chim system, nws yog tsim nyog los kawm txog cov economic qauv ntawm kev ua hauj lwm ntawm lub zog cia fais fab chaw nres tsheb, qhov chaw xaiv ntawm qhov chaw pib thiab qhov kawg taw tes ntawm photovoltaic kis tau tus mob channel thiab lub site. qhov chaw xaiv ntawm lub zog cia. Txawm li cas los xij, cov kev tshawb fawb uas twb muaj lawm ntawm kev pom kev teeb tsa ntawm lub zog khaws cia tsis xav txog qhov cuam tshuam tshwj xeeb ntawm lub zog hluav taws xob, thiab kev tshawb fawb ntawm ntau qhov system tsis koom nrog cov khoom siv kho qhov muag loj loj.

Nrog rau qhov loj-loj kev loj hlob ntawm tsis paub tseeb lub zog tshiab zog xws li cua zog thiab photovoltaic, nws yog ib qhov tsim nyog los xam lub zog khiav ntawm lub hwj chim system nyob rau hauv lub lag luam kev npaj ntawm lub hwj chim system. Piv txwv li, cov ntaub ntawv kawm txog qhov chaw zoo tshaj plaws thiab kev faib peev xwm ntawm lub zog cia hauv lub zog hluav taws xob nrog lub zog cua. Tsis tas li ntawd, kev sib raug zoo ntawm ntau lub zog tshiab yuav tsum tau txiav txim siab hauv kev suav ntawm lub zog ntws. Txawm li cas los xij, tag nrho cov kev tshawb fawb saum toj no yog ua raws li kev txiav txim siab lub zog ntws, uas tsis xav txog qhov tsis paub tseeb ntawm lub zog tshiab. Cov ntaub ntawv txiav txim siab txog qhov tsis paub tseeb ntawm lub zog cua thiab siv txoj hauv kev zoo tshaj plaws kom pom lub zog ntws los ua kom zoo dua qhov chaw xaiv ntawm lub zog cia, uas txhim kho kev lag luam kev lag luam.

Tam sim no, qhov sib txawv probabilistic zog txaus algorithms tau npaj los ntawm cov kws tshawb fawb, thiab cov ntaub ntawv mining txoj kev ntawm nonlinear probabilistic fais fab txaus raws li Monte Carlo simulation txoj kev tau raug npaj nyob rau hauv cov ntaub ntawv, tab sis lub sij hawm ntawm Monte Carlo txoj kev tsis zoo heev. Nws tau thov nyob rau hauv cov ntaub ntawv siv cov probabilistic pom lub zog txaus los kawm txog qhov chaw ntawm lub zog cia, thiab 2 m point method yog siv, tab sis kev xam raug ntawm txoj kev no tsis zoo tagnrho. Daim ntawv thov ntawm Latin hypercube sampling method nyob rau hauv lub hwj chim txaus xam yog kawm nyob rau hauv daim ntawv no, thiab lub superiority ntawm Latin hypercube sampling txoj kev yog illustrated los ntawm cov zauv piv txwv.

Raws li cov kev tshawb fawb saum toj no, daim ntawv no siv txoj hauv kev ua kom muaj zog txaus los kawm txog kev pom zoo ntawm kev faib hluav taws xob hauv lub zog hluav taws xob nrog lub zog loj photovoltaic. Ua ntej, cov qauv kev faib tawm qhov tshwm sim thiab Latin hypercube sampling txoj kev ntawm cov khoom hauv lub zog tau qhia. Thib ob, ntau lub hom phiaj optimization qauv yog tsim los txiav txim siab lub zog cia tus nqi, lub zog ntws dhau qhov txwv tsis pub muaj peev xwm thiab kev poob hauv lub network. Thaum kawg, simulation tsom xam yog ua nyob rau hauv IEEE24 node xeem system.

1. Probabilistic zog txaus qauv

1.1 Cov qauv tsis paub meej ntawm cov khoom

Photovoltaic, load thiab lub tshuab hluav taws xob yog txhua qhov sib txawv ntawm qhov tsis paub meej. Nyob rau hauv kev xam ntawm probabilistic hwj chim khiav ntawm tis network, probabilistic qauv yog piav nyob rau hauv cov ntaub ntawv. Los ntawm kev txheeb xyuas cov ntaub ntawv keeb kwm, cov khoom siv hluav taws xob tsim hluav taws xob photovoltaic ua raws li BETA faib. Los ntawm kev haum rau qhov tshwm sim ntawm kev faib tawm ntawm lub zog thauj khoom, nws xav tias cov khoom ua raws li qhov kev faib tawm ib txwm muaj, thiab nws qhov tshwm sim qhov ntom ntom faib ua haujlwm yog

Picture (1)

Qhov twg, Pl yog lub zog load; μ L thiab σ L yog qhov kev cia siab thiab qhov sib txawv ntawm qhov sib txawv.

Tus qauv tsim nyog ntawm lub tshuab hluav taws xob feem ntau yog siv ob lub ntsiab lus faib, thiab nws qhov tshwm sim qhov ntom ntom ntom ntom yog

(2)

Qhov twg, P yog qhov tshwm sim ntawm kev ua haujlwm ntawm lub tshuab hluav taws xob; PG yog lub zog tso zis ntawm lub tshuab hluav taws xob.

When the light is sufficient at noon, the active power of the photovoltaic power station is large, and the power that is difficult to use in time will be stored in the energy storage battery. When the load power is high, the energy storage battery will release the stored energy. The instantaneous energy balance equation of the energy storage system is

Thaum them nyiaj

(3)

Thaum tso tawm

(4)

Qhov txwv

Duab,

Duab,

Picture, picture

Qhov twg, St yog lub zog khaws cia rau lub sijhawm T; Pt yog tus nqi thiab tso tawm lub zog ntawm lub zog cia; SL thiab SG yog lub zog ntawm kev them nyiaj thiab tso tawm raws. η C thiab η D yog them thiab tso tawm efficiency feem. Ds yog tus kheej tawm tus nqi ntawm lub zog cia.

1.2 Latin hypercube sampling method

Muaj cov txheej txheem simulation, kwv yees txoj hauv kev thiab cov txheej txheem tshuaj ntsuam xyuas uas tuaj yeem siv los txheeb xyuas qhov system fais fab ntws raws li qhov tsis paub tseeb. Monte Carlo simulation yog ib txoj hauv kev zoo tshaj plaws nyob rau hauv probabilistic zog txaus algorithms, tab sis nws lub sij hawm yog tsawg piv nrog high precision. Nyob rau hauv cov ntaub ntawv ntawm lub sij hawm tsawg sampling, txoj kev no feem ntau ignores tus Tsov tus tw ntawm qhov tshwm sim faib nkhaus, tab sis nyob rau hauv thiaj li yuav txhim kho qhov raug, nws yuav tsum tau nce lub sij hawm sampling. Latin hypercube sampling method zam qhov teeb meem no. Nws yog ib txoj hauv kev hierarchical sampling, uas tuaj yeem ua kom ntseeg tau tias cov ntsiab lus piv txwv muaj kev cuam tshuam qhov tshwm sim ntawm kev faib tawm tau zoo thiab txo cov sijhawm ua piv txwv zoo.

Daim duab 1 qhia tau hais tias qhov kev cia siab thiab qhov txawv ntawm Latin hypercube sampling method thiab Monte Carlo simulation txoj kev nrog cov sij hawm piv txwv li ntawm 10 mus rau 200. Tag nrho cov qauv ntawm cov txiaj ntsig tau los ntawm ob txoj kev yog txo qis. Txawm li cas los xij, qhov kev cia siab thiab qhov sib txawv tau los ntawm monte Carlo txoj kev tsis ruaj khov, thiab cov txiaj ntsig tau los ntawm ntau qhov simulations tsis zoo ib yam nrog tib lub sijhawm piv txwv. Qhov sib txawv ntawm Latin hypercube sampling txoj kev txo qis tsis tu ncua nrog qhov nce ntawm lub sij hawm sampling, thiab cov txheeb ze yuam kev poob qis dua 5% thaum lub sij hawm sampling ntau tshaj 150. Nws yog tsim nyog sau cia tias qhov piv txwv ntawm Latin hypercube sampling txoj kev yog. symmetrical ntawm Y-axis, yog li nws qhov kev xav tau yuam kev yog 0, uas kuj yog nws qhov zoo dua.

Daim duab

FIG. 1 Kev sib piv ntawm cov sijhawm piv txwv sib txawv ntawm MC thiab LHS

Latin hypercube sampling method yog txheej txheej sampling. Los ntawm kev txhim kho cov qauv tsim cov txheej txheem ntawm cov tswv yim random variables, tus nqi piv txwv tuaj yeem cuam tshuam qhov kev faib tawm tag nrho ntawm random variables. Cov txheej txheem kuaj tau muab faib ua ob kauj ruam.

(1) Sampling

Xi (I = 1, 2,… ,m) yog m random variables, thiab lub sij hawm sampling yog N, raws li qhia nyob rau hauv FIG. 2. Qhov sib npaug ntawm qhov kev faib tawm ntawm Xi tau muab faib ua N ntu nrog qhov sib npaug thiab tsis sib tshooj, qhov nruab nrab ntawm txhua lub sijhawm raug xaiv raws li tus lej piv txwv ntawm qhov tshwm sim Y, thiab tom qab ntawd tus nqi piv txwv Xi = p-1 (Yi) yog xam los ntawm kev siv inverse muaj nuj nqi, thiab xam Xi yog tus nqi piv txwv ntawm random sib txawv.

Daim duab

Daim duab 2 schematic daim duab ntawm LHS

(2) Kev hloov pauv

Qhov ntsuas qhov ntsuas ntawm qhov sib txawv ntawm qhov sib txawv tau txais los ntawm (1) yog sib txuas ua ke, yog li kev sib txheeb ntawm m random variables yog 1, uas tsis tuaj yeem xam. gram-Schmidt ib theem zuj zus orthogonalization txoj kev tuaj yeem raug coj los txo qhov kev sib raug zoo ntawm cov qauv piv txwv ntawm qhov sib txawv ntawm qhov sib txawv. Ua ntej, lub matrix ntawm K × M xaj I = [I1, I2…, IK]T yog generated. Cov ntsiab lus nyob rau hauv txhua kab yog randomly teem los ntawm 1 mus rau M, thiab lawv sawv cev rau txoj hauj lwm ntawm tus nqi piv txwv ntawm tus thawj random sib txawv.

Positive iteration

Daim duab

Ib tug rov qab iteration

Daim duab

“Daim duab” sawv cev rau txoj haujlwm, nqa tawm (Ik, Ij) sawv cev rau kev suav ntawm cov nqi seem hauv cov kab rov ua dua Ik = a + bIj, qib (Ik) sawv cev rau cov vector tshiab tsim los ntawm cov lej ntawm cov ntsiab lus hauv kev taw qhia Ik los ntawm me mus rau loj.

Tom qab bidirectional iteration kom txog rau thaum RMS tus nqi ρ, uas sawv cev rau kev sib raug zoo, tsis txo qis, txoj hauj lwm matrix ntawm txhua qhov sib txawv random tom qab permutation yog tau, thiab ces cov permutation matrix ntawm random variables nrog tsawg correlation tau.

(5)

Qhov twg, daim duab yog sib txheeb coefficient ntawm Ik thiab Ij, cov yog covariance, thiab VAR yog variance.

2. Multi-objective optimization configuration of energy storage system

2.1 Objective function

Txhawm rau txhawm rau txhim kho lub zog thiab lub peev xwm ntawm lub zog khaws cia, ntau lub hom phiaj kev ua kom zoo tshaj plaws yog tsim los txiav txim siab tus nqi ntawm lub zog cia, lub zog tawm ntawm qhov tshwm sim thiab kev poob hauv lub network. Vim qhov txawv qhov ntev ntawm txhua qhov ntsuas, qhov sib txawv ntawm cov qauv ntsuas tau ua tiav rau txhua qhov ntsuas. Tom qab deviation standardization, tus nqi ntau ntawm cov txiaj ntsig ntawm ntau qhov sib txawv yuav nyob nruab nrab ntawm (0,1), thiab cov ntaub ntawv txheem yog cov ntshiab tsis muaj units. Hauv qhov xwm txheej tiag tiag, tej zaum yuav muaj qhov sib txawv ntawm qhov tseem ceeb ntawm txhua qhov ntsuas. Yog tias txhua qhov ntsuas tau muab qhov hnyav, qhov tseem ceeb sib txawv tuaj yeem txheeb xyuas thiab kawm.

(6)

Qhov twg, w yog qhov ntsuas kom zoo; Wmin thiab wmax yog qhov tsawg kawg nkaus thiab qhov siab tshaj plaws ntawm kev ua haujlwm qub yam tsis muaj tus qauv tsim.

Lub hom phiaj ua haujlwm yog

(7)

Nyob rau hauv cov mis, λ1 ~ λ3 yog hnyav coefficients, Eloss, PE thiab CESS yog standardized ceg network poob, ceg active zog hla qhov tshwm sim thiab lub zog cia peev nqi feem.

2.2 Genetic algorithm

Genetic algorithm is a kind of optimization algorithm established by imitating the genetic and evolutionary laws of survival of the fittest and survival of the fittest in nature. It first to coding, initial population each coding on behalf of an individual (a feasible solution of the problem), so each feasible solution is from for genotype phenotype transformation, to undertake choosing according to the laws of nature for each individual, and selected in each generation to the next generation of computing environment to adapt to the strong individual, until the most adaptable to the environment of the individual, After decoding, it is the approximate optimal solution of the problem.

Hauv daim ntawv no, lub zog hluav taws xob suav nrog photovoltaic thiab lub zog khaws cia yog thawj zaug suav los ntawm qhov ua tau zoo ntawm lub zog ntws algorithm, thiab cov ntaub ntawv tau txais yog siv los ua cov tswv yim sib txawv ntawm cov genetic algorithm los daws qhov teeb meem. Cov txheej txheem suav yog qhia hauv daim duab 3, uas feem ntau muab faib ua cov kauj ruam hauv qab no:

Daim duab

FIG. 3 Algorithm ntws

(1) Cov khoom siv hluav taws xob, cov ntaub ntawv photovoltaic thiab lub zog khaws cia, thiab ua Latin hypercube sampling thiab Gram-Schmidt sequence orthogonalization;

(2) Input the sampled data into the power flow calculation model and record the calculation results;

(3) The output results were encoded by chromosome to generate the initial population corresponding to the sampling value;

(4) Calculate the fitness of each individual in the population;

(5) select, cross and mutate to produce a new generation of population;

(6) Txiav txim seb qhov yuav tsum tau ua, yog tias tsis yog, rov qab kauj ruam (4); Yog tias muaj, qhov kev daws teeb meem zoo tshaj plaws yog cov zis tom qab txiav txim siab.

3. Piv txwv tsom xam

Txoj kev ua kom muaj zog txaus yog simulated thiab tshuaj xyuas hauv IEEE24-node test system qhia hauv FIG. 4, qhov voltage ntawm 1-10 nodes yog 138 kV, thiab ntawm 11-24 nodes yog 230 kV.

Daim duab

Daim duab 4 IEEE24 node test system

3.1 Kev cuam tshuam ntawm photovoltaic fais fab chaw nres tsheb ntawm lub zog hluav taws xob

Photovoltaic fais fab chaw nres tsheb nyob rau hauv lub hwj chim system, qhov chaw thiab lub peev xwm ntawm lub hwj chim system yuav muaj feem xyuam rau lub node voltage thiab ceg hwj chim, yog li ntawd, ua ntej kev soj ntsuam ntawm lub hwj chim cia system rau lub hwj chim daim phiaj, seem no thawj zaug tsom xam lub hwj chim ntawm photovoltaic zog. chaw nres tsheb ntawm qhov system, photovoltaic nkag mus rau qhov system hauv daim ntawv no, qhov sib txawv ntawm qhov txwv ntawm qhov yuav tshwm sim, lub network poob thiab lwm yam tau nqa mus rau qhov simulation tsom xam.

Raws li tau pom los ntawm FIG. 5 (a), tom qab photovoltaic fais fab chaw nres tsheb txuas, cov nodes nrog cov ceg me me fais fab ntws overlimit yog raws li hauv qab no: 11, 12, 13, 23, 13 kom sib npaug ntawm node ntawm, qhov node voltage thiab theem lub kaum sab xis muab, muaj cov Cov nyhuv ntawm cov hluav taws xob ruaj khov hluav taws xob sib npaug, 11, 12 thiab 23 es tsis txhob txuas ncaj qha, vim li ntawd, ntau qhov txuas nrog rau qhov txwv qhov tshwm sim ntawm lub zog me thiab ntau dua, qhov chaw nres tsheb fais fab photovoltaic yuav nkag mus rau ntawm qhov sib npaug ntawm qhov cuam tshuam tsawg dua. cuam ​​tshuam ntawm lub zog system.

Daim duab

Daim duab 5. (a) sum ntawm lub hwj chim khiav off-limit probability (b) node voltage fluctuation (c) tag nrho system network poob ntawm txawv PV access point

In addition to the exceedance of power flow, this paper also analyzes the influence of photovoltaic on node voltage, as shown in FIG. 5(b). The standard deviations of voltage amplitudes of nodes 1, 3, 8, 13, 14, 15 and 19 are selected for comparison. On the whole, the connection of photovoltaic power stations to the power grid does not have a great influence on the voltage of nodes, but the photovoltaic power stations have a great influence on the voltage of a-Nodes and their nearby nodes. In addition, in the system adopted by the calculation example, through comparison, it is found that photovoltaic power station is more suitable for access to the node types: ① nodes with higher voltage grade, such as 14, 15, 16, etc., the voltage almost does not change; (2) nodes supported by generators or adjusting cameras, such as 1, 2, 7, etc.; (3) in the line resistance is large at the end of the node.

In order to analyze the influence of PV access point on the total network loss of power system, this paper makes a comparison as shown in Figure 5(c). It can be seen that if some nodes with large load power and no power supply are connected to pv power station, the network loss of the system will be reduced. On the contrary, nodes 21, 22 and 23 are the power supply end, which is responsible for centralized power transmission. The photovoltaic power station connected to these nodes will cause large network loss. Therefore, the pv power station access point should be selected at the receiving end of power or the node with large load. This access mode can make the power flow distribution of the system more balanced and reduce the network loss of the system.

Raws li peb yam hauv kev txheeb xyuas ntawm cov txiaj ntsig saum toj no, node 14 raug coj los ua qhov chaw nkag ntawm qhov chaw nres tsheb photovoltaic fais fab hauv daim ntawv no, thiab tom qab ntawd qhov kev cuam tshuam ntawm lub peev xwm ntawm cov chaw nres tsheb photovoltaic sib txawv ntawm lub zog hluav taws xob tau kawm.

Daim duab 6(a) txheeb xyuas qhov cuam tshuam ntawm photovoltaic muaj peev xwm ntawm qhov system. Nws tuaj yeem pom tau tias tus qauv sib txawv ntawm lub zog nquag ntawm txhua ceg nce nrog qhov nce ntawm photovoltaic muaj peev xwm, thiab muaj kev sib raug zoo linear ntawm ob. Tsuas yog rau ob peb ceg qhia hauv daim duab, tus qauv sib txawv ntawm lwm cov ceg yog tag nrho tsawg dua 5 thiab qhia txog kev sib raug zoo, uas tsis quav ntsej rau qhov yooj yim ntawm kev kos duab. Nws tuaj yeem pom tau tias photovoltaic daim phiaj kev sib txuas muaj kev cuam tshuam zoo rau lub zog ntawm kev sib txuas ncaj qha nrog photovoltaic nkag point lossis cov ceg ntoo uas nyob ib sab. Vim tias muaj kev txwv tsis pub siv hluav taws xob sib txuas, cov kab sib txuas ntawm qhov ntau ntawm kev tsim kho thiab kev nqis peev yog qhov loj, yog li kev txhim kho lub chaw nres tsheb photovoltaic, yuav tsum xav txog qhov txwv tsis pub muaj peev xwm thauj mus los, xaiv qhov tsawg tshaj plaws ntawm cov kab nkag mus rau qhov chaw zoo tshaj plaws, ntxiv rau, xaiv qhov zoo tshaj plaws muaj peev xwm ntawm photovoltaic fais fab chaw nres tsheb yuav ua si ib feem tseem ceeb los txo cov nyhuv no.

Daim duab

Daim duab 6. (a) Ceg active hwj chim standard deviation (b) ceg hwj chim ntws tawm-of-limit probability (c) tag nrho system network poob nyob rau hauv txawv photovoltaic peev xwm

FIG. 6(b) compares the probability of active power exceeding the limit of each branch under different pv power station capacities. Except for the branches shown in the figure, the other branches did not exceed the limit or the probability was very small. Compared with FIG. 6(a), it can be seen that the probability of off-limit and standard deviation are not necessarily related. The active power of a line with large standard deviation fluctuation does not necessarily off-limit, and the reason is related to the transmission direction of photovoltaic output power. If it is in the same direction as the original branch power flow, small photovoltaic power may also cause off-limit. When the pv power is very large, the power flow may not exceed the limit.

Hauv FIG. 6 (c), tag nrho lub network poob ntawm lub kaw lus nce nrog qhov nce ntawm lub peev xwm photovoltaic, tab sis qhov txiaj ntsig no tsis pom tseeb. Thaum lub peev xwm photovoltaic nce 60 MW, tag nrho cov network poob tsuas yog nce 0.5%, piv txwv li 0.75 MW. Yog li ntawd, thaum txhim kho pv fais fab chaw nres tsheb, network poob yuav tsum raug coj los ua qhov tseem ceeb thib ob, thiab cov yam ntxwv uas muaj kev cuam tshuam ntau dua rau kev ua haujlwm ruaj khov ntawm lub kaw lus yuav tsum raug txiav txim siab ua ntej, xws li cov kab hluav taws xob hloov pauv thiab qhov tshwm sim tsis txaus. .

3.2 Kev cuam tshuam ntawm lub zog cia nkag rau hauv qhov system

Tshooj 3.1 Txoj haujlwm nkag mus thiab lub peev xwm ntawm qhov chaw nres tsheb photovoltaic yog nyob ntawm lub zog hluav taws xob