7 Iteratioal Coferece o Eergy, Power ad Evirometal Egieerig (ICEPEE 7) ISBN: 978--6595-456- Study of the Power Quality Comprehesive Evaluatio Method Zhi-mi ZHAN, Peg-fei CHAI, Bi LUO, Xig-bo LIU, Yua-li LI, Lei YE ad Ge-yog CHEN 3,* Hubei Cetral Chia Tech. Developmet of Electric Power CO.LTD, Wuha, 4377, Chia Luoyag Power Supply Compay, Hea Luoyag, 47, Chia 3 School of Electrical Egieerig, Zhegzhou Uiversity, Zhegzhou 45, Chia *Correspodig author Keywords: Power quality, Assessmet system, Harmoic evaluatio, Comprehesive evaluatio. Abstract. The scietific evaluatio of power quality is the basic coditio for the treatmet of electric eergy pollutio. I this paper, the relevat cocepts ad various idexes of power quality are aalyzed based o the iteral ad exteral power quality stadards. The evaluatio method of power quality is divided ito the specific aalysis of sigle idex evaluatio ad comprehesive evaluatio. This paper proposes four evaluatio methods of sigle idex, icludig based o fuzzy mathematical sigle idex evaluatio method, based o fuzzy mathematics i various eergy idex commoly used membership fuctio method, based o probability ad statistics of the sigle idex evaluatio method ad based o the mai use of power grid plaig, power grid costructio ad iterferece load before access to the simulatio of the idividual idicators to predict the assessmet method. The weight selectio method used i the comprehesive evaluatio of power quality is aalyzed from the subective weight to the obective weight. Itroductio I recet years, more ad more attetio has bee paid to power quality of power grid, ad may methods have bee used i power quality assessmet at home ad abroad. Accordig to the basic requiremets of power quality assessmet, it ca be divided ito sigle idex evaluatio ad comprehesive evaluatio. Accordig to the differet evaluatio obects, it also ca be divided ito test poit evaluatio ad power system comprehesive evaluatio. The evaluatio of power quality ivolves may factors ad differet stadards. Thus there is o accepted defiitio of a authoritative assessmet, at preset, the mai basis for the evaluatio of power quality is whether or ot the power grid or the user's harmoic is over stadard []. The mai evaluatio methods of power quality iclude the evaluatio method based o fuzzy mathematics, the evaluatio method based o probability statistics, the evaluatio method based o itelliget algorithm, ad the method of determiig the subective weight, the method of determiig the obective weight, ad the method of weighted combiatio selectio method. These methods have their ow advatages, disadvatages ad the scope of use []. Overview of Power Quality Assessmet Methods Power quality assessmet is a multi-idex comprehesive evaluatio problem, which has bee studied at home ad abroad. Accordig to the differet idexes of power quality assessmet, it ca be divided ito sigle idex evaluatio ad comprehesive evaluatio. Accordig to the differet forms of the results, it ca be divided ito quatitative evaluatio ad idex grade evaluatio. Accordig to the evaluatio obect, it ca be divided ito test poit evaluatio ad power system comprehesive evaluatio. Accordig to the purpose of evaluatio, it ca be divided ito custom assessmet ad public assessmet. The evaluatio of power quality is so complex that there is o uiversally accepted defiitio of complete evaluatio[3,4]. 3
Sigle Evaluatio of Power Quality The sigle evaluatio of power quality refers to the evaluatio of a certai idex of power quality, or a certai characteristic parameter. For example, i order to evaluate the detectio poit of harmoic coditio or voltage sag coditio, the harmoic ad voltage sag of power quality are evaluated separately. The evaluatio results ca be the umerical idicators quatized or the power quality grade. Sigle idex evaluatio is the basis of comprehesive evaluatio of power quality, ad may comprehesive evaluatio methods are based o the evaluatio of power quality idexes. Sigle Idex Evaluatio Method Based o Fuzzy Mathematics The idex of power quality is ofte fuzzy whe describig the power quality ad fuzzy mathematics theory ca deal with this id of fuzzy problem effectively. Firstly, the fuzzy mathematics evaluatio of power quality should be established membership fuctio power quality idexes. Secodly, the measured data of each idex are obtaied the membership of each idex. Lastly, the classificatio of membership grades for differet idex levels. It is ecessary to select proper membership fuctio for fuzzy mathematics evaluatio, ad the membership fuctio ca be divided ito two categories: cotiuous membership fuctio ad discrete membership fuctio. I order to esure the accuracy of the fuzzy model, we must choose a reasoable membership fuctio. It ca be see from the method of determiig membership degree that the choice of membership is subective. But as log as the modelig obect ca be described accurately, the membership fuctio is reasoable. The membership fuctio used i power quality evaluatio is itroduced as follows: () The membership fuctio of voltage deviatio is show i equatio () ad () U U U U.5.5si ( U ) U U U U U ( U ). () U U.5.5si ( U ) U U U U U U U U U U ( U ) e else. () U U Formula: U is the voltage deviatio, the other is based o the actual situatio of costat determiatio. () Membership fuctio of duratio of voltage deviatio ) e U U T T U ( T U ( TU TU ). T T U Formula: T U represets the duratio of the voltage deviatio, ad T U are costats. (3) The voltage fluctuatio ad flicer, harmoic distortio, three-phase ubalace, etc. (3) 33
au U3 U3 U 4 ( au ) si au U3 au U 4. (4) U 4 U3 au U 4 (4) Cout idex The reliability of power supply, voltage sag, short-time iterruptio is usually used as the membership fuctio of type ( x) x. For the reliability idex x t r tt, t r is used to evaluate the time of iterruptio of power supply i the period of time, t T is the total time. The voltage swell or voltage sag, x N i NT, N i is the umber of users i the evaluatio regio of the voltage sag or swell, N T to assess the total umber of users i the regio. Sigle Idex Evaluatio Method Based o Probability ad Statistics For the deviatio of voltage ad frequecy deviatio, we should pay attetio to the magitude ad duratio of the deviatio. Scietists commoly used methods of mathematical statistics to do cotiuous moitorig o voltage ad frequecy i the assessmet period, record umerical ad time of the variable voltage ad frequecy, ad mae aalysis of the moitorig data. So the correspodig idex ca be calculated. Averagig the atioal stadard limit accordig to the atioal stadards ad the actual situatio ad establishig evaluatio level. The, measurig the power quality idex which belogs to the time of each grade ad obtaiig the variace ad stadard deviatio. The aalysig the expected value ad stadard deviatio which accord to the give expected value ad stadard deviatio [5]. Sigle Idex Evaluatio Method Based o Predictio This evaluatio method is used to evaluate the potetial quality problems by usig the method of simulatio calculatio before the power grid plaig, power grid costructio or iterferece load access. First of all, the power supply departmet should be familiar with the special load data ad the ca evaluate by the predictio method. Details of the load iclude: power supply capacity, load worig mode, load worig time, grid locatio ad so o. The grid parameters ad the above details are aalyzed ad simulated. The the power quality problems are aalyzed. The steps of predictive aalysis are: the equivalet circuit diagram is determied ad the simulatio calculatio is carried out by the characteristics of power grid ad load. If calculatig harmoic or three-phase sequece. The etwor parameters are the correspodig harmoic parameters ad three phase sequece parameters. Pourig ito harmoic curret by calculatig the harmoic curret ad the voltage fluctuatio of the coectio poit is calculated accordig to the load curret, the gettig the various idicators by simulatio calculatio [6]. Comprehesive Evaluatio of Power Quality Sigle Power Quality Comprehesive Evaluatio Evaluatio of harmoic quality belogs to the evaluatio of sigle power quality ad it is ot comprehesive evaluatio whe the total harmoic distortio rate or the harmoic frequecy (as 3 times) ad characteristic harmoics are separate evaluated. However, because of may characteristics of harmoic measuremet parameters, for example, Chia's atioal stadard GB/T4549-993 fixes the total harmoic distortio rate ad the harmoic cotais rate from to 9 ad Europea EN56 stadard also fixes harmoic rate from to 4. A large umber of characteristic idexes ad their limits determie that the complete evaluatio of harmoics should be a sigle idex. There are two methods of fuzzy comprehesive evaluatio, such as fuzzy clusterig [7] ad geetic proectio pursuit [8]. Fuzzy clusterig method is a id of multivariate aalysis method that assorts samples with fuzzy boudaries by mathematical methods. Determiig quatified the similarity ad differece i samples. Geetic proectio method is a id of obective data aalysis method, which is used to trasform 34
the high dimesioal data through the proectio fuctio, covert the high dimesioal data to the low dimesio, ad aalyze the structural characteristics of the high dimesioal data accordig to the proectio value. The method uses the proectio fuctio to describe the similarity ad the differece of the aalysis data, ad uses the geetic algorithm to calculate the proectio value of the optimal proectio fuctio to aalyze the structural characteristics of the high dimesioal data [7]. The harmoic evaluatio idex geerally cotais the harmoic ad the harmoic curret. Accordig to our coutry's harmoic limit stadard, the harmoic idex such as the oil cotet of each harmoic voltage, the harmoic curret value ad the total distortio rate of harmoic voltage are classified ad subect proectio idex. The proectio fuctio is the mathematical relatioship betwee the M data ad the N evaluatio level (i=,...; =,...m)x(i,). The proectio pursuit method itegrates the -dimesioal data ito a oe-dimesioal proectio value Z (I) i the directio of a=: m z(i) a( ) x( i,), The proectio idex fuctio is i,;,m. (6) f ( a) SZ Rzy. Proectio value Z(i) should be as large as possible to extract x (i,) i the variatio of iformatio. Z (i) s stadard deviatio SZ should be as large as possible ad requirig Z (i) ad Y (i) correlatio coefficiet R Rzy ZY absolute value of as much as possible. The best proectio directio is: max f ( a) S R z zy. (8) p a( ), a( ). (9) By solvig the equatio (8) ad (9), the best proectio directio ca be obtaied. A Comprehesive Evaluatio Method of Correlatio Probability Theory Because of the power quality idex, the probability statistics method ca be used to grasp the mai characteristics of the power quality idexes ad to evaluate the power quality. The applicatio of probability theory to power quality assessmet, first of all, it is ecessary to combie the atioal limit stadards to divide power quality idicators ito several levels. ad the accordig to the probability theory to calculate probability distributio fuctio f x of the assessmet period of the power idex for each grade, ad use expectatios ad cotrast of the distributio fuctio to reflect the data characteristics of idex i the assessmet period. That is to get the stadard deviatio R (x) ad expected value E (x) of the probability fuctio f (x), ad use give the stadard value of R (x) ad E (x) to ormalize the results of the idicators, which is coveiet for the subsequet comprehesive aalysis. Comprehesive Evaluatio Method Based o Itelliget Algorithm I additio to the applicatio of sigle idex evaluatio of geetic algorithms, as well as eural etwor methods. Neural etwor method is a id of artificial itelligece method through (7) 35
simulatig the worig priciple of biological eural system. It has good self-orgaizatio ad fault tolerace. A typical BP eural etwor cotais iput layer, hidde layer ad output layer. Through iputtig the traiig samples, each ode of each layer is traied, whe the traiig error accuracy meets the requiremets, it ca be used to aalyze the test data [7]. Comprehesive Evaluatio Method Based o Fuzzy Mathematics Some idexes of power quality are fuzzy, They ca be evaluated by fuzzy mathematics ad ca be classified ito fuzzy patter recogitio method ad fuzzy comprehesive evaluatio method. The evaluatio procedure of fuzzy patter recogitio method: () Accordig to the atioal stadard, the power quality is divided ito several grades; Fially, the sample set of idex membership degree is formed; () Establish the fuzzy model of power quality idexes; (3) the measured data are substituted ito the fuzzy model to get the fuzzy sets of each idex; (4) tae the arithmetic mea of fuzzy set to get the membership degree of each idex, ad use the membership set to express it; (5) use the mathematical method to calculate the degree of closeess of the membership degree to the each grade of power quality idex; (6) determie the grade of power quality. Fuzzy comprehesive evaluatio method: () Establish the membership fuctio of each idex of power quality; () the measured data of each idex are brought to obtai the membership of each idex; (3) gradig of each idex; (4) fid out the percetage of each idex data i each grade; (5) use the fuzzy comprehesive method to udge the grade of the two grade udgmet matrix. Power Quality Comprehesive Evaluatio Weight Selectio Method Subective Weightig Method Subective weightig method is a qualitative aalysis method, the core of which is based o the owledge ad experiece of experts, the subective udgmet of the importat degree betwee the idexes through the comprehesive idex weight. AHP (Aalytic hierarchy process) is the most widely used, which maes the complex evaluatio problem hierarchical, ad compares the qualitative compariso of the idexes with the scale quatizatio, it s suitable for multi obective decisio maig problem with multi hierarchy. Firstly, the hierarchy of the idex system should be determied, ad the hierarchy of the idex system ca be divided ito the target layer, the criterio layer ad the solutio layer. The udgmet matrix is obtaied accordig to the 5 scale or the 9 scale method s mutual compariso for idex, the we ca get idex weight by calculatig the eigevector of the maximum eigevalue of the udgemet matrix ad ormalized processig. The cosistecy test is eeded to solve the feature vector, ad the udgmet matrix is ot adusted by the cosistecy test util satisfyig cosistecy chec[8]. Superiority chart compares idexes i pairs ad establishes ( ) ico matrix for evaluatio idex. If the idex i is more importat tha the idex, the the idex is, equal to the xi x ( ) importace of.5, otherwise for the, score as ad form matrix i. Fially, i is calculated by the formula () as the weight of the idex i. i X i.5( ). 5. () For example, as show i table. Accordig to the formula (), the weight of the idex a to g ca be obtaied as(.4,.4,.,.4,.4,.8,.4). The advatage of subective weightig method is that it ca give full play to the role of expert owledge, ad ca determie the weight of each idex accordig to differet practical problems. The weight of each idex ca ot be accurate by the subective weightig method, but i ormal circumstaces, the order of weight give by the subective weightig method should be accurate. Ad through the subective weight ca be defied to limit the weight of the idex, to avoid the obective weight method i the idex weight divorce from the actual. 36
Table. Istace of superiority chart. Idexes a b c d e f g A.5 B.5 C.5 D.5 E.5 F.5 G.5 Subective advatage is also the disadvatage. Expert opiio has a decisive effect o the results, differet experts opiios will get differet weights. By icreasig the umber of experts, the use of a more comprehesive method of expert opiio to improve the accuracy of subective weight. Differet methods of improvemet ca weae its disadvatages but ot elimiate it. Obective Weightig Method The core idea of obective weightig method is to determie the idex weight by excavatig dates based o the structural characteristics of the data. There are maily weighted etropy edow etropy model, pricipal compoet aalysis weightig method, variatio coefficiet weightig method, ope grade weightig method, multi-obective programmig weightig method, Correlatio fuctio weightig method, stadard variace weightig method, etc. The etropy weight method ad the pricipal compoet aalysis method are applied more[7]. Etropy weightig method derived from iformatio theory, i iformatio theory, etropy is used to measure the degree of disorder of the system. For the multi idex evaluatio, the weight of the idexes depeds o the iformatio provided by each idex, the greater the impact of idicators o the evaluatio, the greater the value of the idex weight. Firstly, the origial data matrix is Y. The matrix is ormalized, the ratio of the colum vectors of the matrix ad the sum of all the elemets i the matrix is tae as the ormalizatio result, the formula is as follows (): z E i y i i Y i (,,, m). () i i, i Where: whe l z lz,, m z i, regulatig z l i z i m E E,, m,. (). The:.. (3) Obective weight vector:,,, T m Pricipal compoet aalysis weightig method is a id of obective weightig method. Assume that there are idicators: F,F,,F, Data collected for each idicator: X,X, X. We first compute the covariace matrix, the the eige values,,, of the covariace 37
matrix ad the variace cotributio rate are calculated ad the weight is determied. a (4) i i Obective weightig method is based o the iformatio cotaied i the data to determie the weight, do ot have subective arbitrariess, the structure of a good eough mathematical theory. It is the advatage of the obective weightig method, but the data processig method depeds o the actual problem, it may be because the data is too large to mae the calculatio loc. Comprehesive Weight Calculatio While determiig the weight of the evaluatio idex, the subective weightig method ad the obective weightig method have their ow advatages ad disadvatages. It is difficult for a sigle weightig method to achieve satisfactory weightig effect, ad therefore may papers use two or more methods to determie the fial weight. The followig two algorithms are commoly used to sythesize various weightig methods to obtai comprehesive weights. () Multiplicatio m m /,,, (5) Where m is the umber of methods which is used to weight, is the weight of item J of the first weightig method. This comprehesive approach cosiders that there is o differece amog the various weightig methods, ad weights obtaied by various methods are equally importat. While sythesizig various weightig methods, this approach virtually is a tacit admissio that various weightig methods are equally importat. () Additio m /,,, ( m Where m is the umber of methods which is used to weight, is the weight of item J of the first weightig method ad is the "importace" coefficiet for the weights which is obtaied by various weightig methods. This comprehesive approach cosiders that there are advatages ad disadvatages amog the various weightig methods, ad weights obtaied by various weightig methods have differet importace. By calculatig the weights of differet methods, importat weightig methods mae a greater impact o the fial weight. Coclusio I this paper, the existig evaluatio methods of power quality are aalyzed ad compared. The evaluatio method of power quality ca be divided ito the scietific aalysis of sigle idex evaluatio ad comprehesive evaluatio, ad the comprehesive evaluatio ca be divided ito sigle idex comprehesive evaluatio ad multi idex comprehesive evaluatio. Sigle idex evaluatio maily aalyzes four evaluatio methods, icludig based o fuzzy mathematical sigle idex evaluatio method, based o fuzzy mathematics i various eergy idex commoly used membership fuctio method, based o probability ad statistics of the sigle idex evaluatio method ad based o the mai use of power grid plaig, power grid costructio ad iterferece load before access to the simulatio of the idividual idicators to predict the assessmet method, ad proposes other idicators such as evaluatio method of service idex. The weight selectio method used i the comprehesive evaluatio of power quality is aalyzed from the subective weight to the obective weight. 38 6)
Refereces [] Jiag Hui, Peg Jia-Chu, Ou Ya-pig et al. Power Quality Uitary Quatificatio ad Evaluatio Based o Probability ad Vector Algebra [J]. Joural of Hua Uiversity (Natural Scieces), 3, (): 66-77. [] Che Lei, Xu Yog-hai. Discussio about the Methods of Evaluatig Power Quality [J]. Electrotechical Applicatio, 5, ():58-6+65. [3] Li Qiu-Hua, Zhou Li, Liu Hua-yog et al. Evaluatio of Power Quality by Acceleratig Geetic Algorithm ad Shepard Iterpolatio [J]. High Voltage Egieerig, 7, (7): 39-43. [4] Zhou Li, Li Qiu-Hua, Zhag Feg. Applicatio of Geetic Proectio Pursuit Iterpolatio Model o Power Quality Sythetic Evaluatio [J]. Power System Techology, 7, (7): 3-35. [5] Li Qiu-Hua, Zhou Li, Liu Hua-yog et al. Evaluatio of Power Quality by Fuzzy Artificial Neural Networ [J]. High Voltage Egieerig, 7, (9): 66-69. [6] Yao Meg, Jiag De-Log, Che Ge-yog. Applicatio of Fuzzy Clusterig o Power Grid Harmoic ComprehesiveEvaluatio [J]. Electrical Measuremet & Istrumetatio,, (): -4. [7] Dig Li, Jia Xiu- Fag, Zhao Cheg-yog et al. Sythetic evaluatio of power quality based o exteics [J]. Electric Power Automatio Equipmet, 7, ():44-47+5. [8] Li Qiu-Hua, Zhou Li, Liu Hua-yog et al. Evaluatio of Power Quality by Acceleratig Geetic Algorithm ad Shepard Iterpolatio [J]. High Voltage Egieerig, 7, (7): 39-43. 39