Elektrik güç sistemlerinde durum kestirimi
Electrical power system state estimation
- Tez No: 39127
- Danışmanlar: PROF.DR. NESRİN TARKAN
- Tez Türü: Yüksek Lisans
- Konular: Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1993
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 73
Özet
ÖZET Güç sistemlerinin büyüklüğü ve karmaşıklığı nedeniyle kontrolün bir merkezden yapılması gerekmektedir. Böyle bir merkezin ilk hedefi sistemin güvenli çalışmasını sağlamaktır. Daha sonra ele alınması gereken hedef ise sistemin ekonomik işletimi olacaktır. Bu hedeflerin ışığında kontrol merkezinde gerçekleştirilen bilgisayar programlan iki bölümde incelenebilir. Bir bölüm programlar ölçümleri doğrudan doğruya kullanarak, şebekenin durumu hakkında bilgi vermekte, diğer bölüm ise bu programların sonucunu veri olarak kullanmaktadır. İlk gruptaki yazılım programlan genelde, incelenen sisteme ilişkin durum keslirimi adı altında toplanabilir. Durum kestirimi, modern kontrol merkezinin bir parçasıdır ve güvenilir bir veri tabanı oluşturmak için gereklidir. Çok sayıdaki ölçümden sistem durumunun kestirimi, çevrim içi bilgisayar kontrolü ve bilgi işlemede geniş kapsamlı bir problemdir. Eğer durum kestirimi tutarlı, güvenilir, yeterli doğrulukta ve az bir gecikme ile şebeke durumunu yorumlama imkanı verirse, güvenlik gözlemleme ve kontrol daha iyi yapılabilir. Kestirim işleminde şebekeden alınan ölçü değerlerinin önemi büyüktür. Bu nedenle, daha güvenilir sonuçlar elde etmek için kötü veri incelemesi yapılmalıdır. Bir durum kestirimi algoritmasında olması gereken özellikler güvenilirlik, hız ye hafızada az yer kaplamasıdır. Bu çalışmada belirtilen özellikleri sağlamaya çalışan çeşitli algoritmalar ele alınmış, üstünlük ve sakıncalan karşılaştırılarak hızh ayrıştıran durum kestirimi yöntemini kullanan yeni bir bilgisayar programı gerçeMeştirilmiştir. Program, bilinen bir test sistemine uygulamıştır.
Özet (Çeviri)
SUMMARY ELECTRICAL POWER SYSTEM STATE ESTIMATION The electrical power system, representing generation, transmission, distribution and consumption of electrical energy, is a very advanced and complex process in a modern society. The process is geographically distributed over large areas. The used control system is generally a full scale computerized control system. It consists of four parts : - Control center : There are many equipment such as color cathode-ray tube, mimic diagram, typewriters, computers, etc. Dual ports connect all hardware to both computers. The ports are switched under software control. - Computer system : Real time data acquisition and supervisory control require a computer with very fast context switching due to the frequent communication interruptions the application programs require computing power and efficient floating point arithmetic. - Front - End (FE ^ system : The FE system unloads the computers by taking care of the process data communications. It also gives easy adaptation to different types of RTUs. - Remote terminal units (RTUs ) : A basic RTU provides data acquisition for status points, momentary and accumulated digital values cyclically. The effectiveness of power system control and operation planning strongly depends on acquiring and securing the system data. In modern power control system, there are extremely large data volume and complex relationship among them. The complete and reliable knowledge of the system state during normal and disturbed operating conditions is an important prerequisite for the secure and economic supply of electrical energy. The large geographical size of most power systems makes the data acquisition dependent on communication links. General structure of the central computer concept for system operations can be summarized as follows: The information defining the present power system state is transmitted via- telemetry systems. The same system sends the control signals to the power system. The supervisory control and data acquisition ( SCAD A ) is the link between the VIincoming or outgoing informations and the data base. The operating personal has access to the control system through the man-machine communication. Security monitoring which is the complete monitoring in real time of the operating conditions of the power system entails the gathering of system data every few seconds and the presentations of operating information to the human operator. These process transform these data into a set of realible data using the following four steps : - The topology program, - The observability pragram, - The state estimation program, - The limit check program. The purpose of the topology program is to determine the actual network topology, on the basis of a static network connectivity description and a set of dynamic circuit breaker statues. The most common approach is to use a tree search algorithm, starting with the formation of the substation configuration and then proceed with the total network configuration. The objective of the observability analysis is to determine whether a sufficient set of measurements are available to perform the SE. If the network is classified as unobservable, the observability analysis should determine the observable sub-networks and propose pseudo-measurements to re-establish overall observability. The heart of the security monitoring functions is the state estimation program. It is the process of determining the bus voltage magnitudes and angles from a set of measurements which ordinarily consists of bus voltage magnitudes, real and reactive lineflow powers and real and reactive bus injection powers. If the state estimation can yield a consistent, reliable and sufficiently accurate on-line interpretation of network state within a reasonably short delay, security monitoring control dispatch can be considerably improved. State estimation consists of three different parts : - Calculation of state variables from on-line system measurement, - Detection of bad data in the measurements, - ^identification of bad data and model structure errors. The essential qualities required of a state estimation algorithm are : - Speed : to protect the real-time performance of the software, - Reliability : aptitude to converge under all circumstances ( state of load, topology of the system, configuration of measurements, etc. ) towards a plausible solution, vu- The accuracy of this solution with reference to the true state, - The lowest possible memory occupation. Besides this, it is desirable that the algorithm which process the data be insensitive to extraneous factors, such as rounding errors, resulting from the storage of system parameters and variables in a digital computers memory. In this method, the non-linear equation relating the measurements are : Z = f(x) + T1 (1) E[11t1t] = R (2) where Z : vector of measurements, x : state vector, r| : zero-mean random vector representing the measurement errors, f(.) : non-linear vector function relating the measured quantities and the states, E[.] : expectation operator, R : covarians matrix of the measurements errors. The WLS estimator finds the state estimate x based on the minimization of the cost function : J = [Z-f(x)]TR“i[Z-f(x)] (3) To avoid the non-linear equation which results from the necessary condition for a minimum of J, Eq. ( 1 ) is linearized with respect to current estimate xjj. The cost function is also modified accordingly. The necessary condition for a minimum : (4) (5) £x x = xk VfllAx = x - xjj Az=z-f(xfc) These can be solved by Cholesky factorization of G = H1”R"1 H and the solution of two triangular systems. But, the WLS algorithm is time consuming as regards computation for relatively large systems. To alleviate this potential problem, some promising methods have been proposed : Fast decoupled state estimator (FDSE) : This method is a combination of a 'constant gain ' and ' P-S, Q-V decoupling ' technique where furthermore, the solution is obtained by interlacing iterations for the active and reactive parts of the non-linear equations. Golub's method : This method is based on applications of Householder orthogonal transformations on the overdetermined system of equations. In such systems the quantity of data to be transmitted and the number of equations to be solved are such that processing them by a classic algorithm would oppose real time operation. The hierarchical state estimation method aims to avoid these problems. It consists of decomposing the system into subsytem and applying a two-level procedure them. The presence of bad data among the measurements processed by a power system state estimator may severely degrade the final estimates. To prevent bad data from reaching the estimator, pre-filters can be used which, when working properly, will reject the most flagrantly erroneous data. Nevertheless, it is to expect that some gross measurements may pass through the pre-filter. The reliable performance of the estimator then requires the use of a technique (detection ) to check whether any of such measurements have been processed; if so, an additional procedure (identification) is employed to determine which measurements are spurious. According to the usual bad data processing methods, these observations are removed from the measurement set and a new estimation has to be carried out. In conclusion, the state estimator program supports the operator by giving a correct network image. The state estimator : - Compensates the measurements and telemetry errors, - Detects and marks rough errors, - Eleminate rough errors, - Gives hints on errors of topology telemetry, - Gives warnings in case of flow threshold overflows, - Complete the set of variables for non-measured values, - Calculates the most likely power flow, mathematically based upon Newton 's least square deviation method combined with a Gaussian elimination in optimized order sparsity technique, IX- Calculates all losses, - Thus creates a safe, complete and consistent data set for the operator's decisions. The properties needed for a state estimation algorithm is given above. This thesis consists of a few algorithms which have these properties. These algorithms are compared by their advantage and disadvantage and a new computer program which uses fast decoupled state estimation method is written. It is applied to a known test system.
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