Transient Stability Analysis Based On Sgeac Method

Transient stability analysis and control is one of the most severe problems in power system operation. Although many efforts have been taken to study the problem and plentiful and substantial results have been achieved in many respects. However, most transient stability analytical methods more or less make the strong assumptions. When the reality does not match these assumptions, these may result in very large analytical error.In this paper, the research work emphasis on the transient stability analysis and control in terms of accuracy, celerity and adaptability of different device model in the absence of any approximation or using hypothetical situations which meet transient stability analysis and control engineering application of the actual needs. Meanwhile, achievements in the research may be applied to WAMS.The difficulty of transient stability analysis and control is that the result must be got rapidly and accurately. The rapidity implies that it is able to meet the needs of real-time control; accuracy referring to the implementation of control measures should meet the needs of the economy and reliability. Both must be highly uniform.To meet the needs uniformly, the proposed transient stability analysis based on single generator equal area criterion (SGEAC) combines universality of the numerical integration method with quantity of the interpretation method in this paper. To improve the rapidity, this paper presents a new numerical integration method, which starts with Euler’s method, and ends with the convergence of state or/and algebraic variables each step. Meanwhile, the Jacobian matrix comes to invariable by deal with the generators’nodes and loads’nodes in the computing process. So, it combines the fast speed of the explicit integration method with the accuracy of the implicit integration method for solving the network equation iteratively. Therefore, the compute speed corresponds with the explicit integration method, but its precision and the numeric stability are the same as the implicit integration method. The actual large-scale system simulation shows that this method significantly improves the speed of implicit integration method, and has a good scalability and flexibility in the program design.Furthermore, the global transient stability margin based on dynamic single-equivalent machine is defined in the paper whose theoretical basis is on SGEAC. And it is compared with the stability margin based on the mutual motion of dynamic two groups of equivalent machine (OMIB). It is proved that single equivalent based stability margin is exactly identical with the stability margin based on one machine infinite bus (OMIB) equivalent in theory and nature. Compared with such methods as EEAC and SIME, detailed system model of steady state and transient can be considered in SGEAC. Therefore, it has the universality of the numerical integration method. Meanwhile, it is not necessary to identify the equivalent machines to avoid getting wrong stability evaluation. The accuracy of the algorithm is ensured without any assumptions or using hypothetical situations.In the guarantee algorithm model’s accurate situation, the power-angle curve fitting method is proposed to calculate the transient stability margin or the transient instability margin for further speeding transient stability analysis in this paper. The electromagnetic power of single equivalent is expressed by the polynomial function according to the proposed Taylor series expansion analysis in the COI frame by theoretical analysis. The curve between electric power of generator unit and rotor’s angle in relative to center of inertia is expanded by Taylor’s series based on single generation equivalent area criteria theory (SGEAC). By using SGEAC and combining with time domain simulation method, the disturbed system is simulated for a very short time period. According to the simulation result, the curve between electric power of generator unit and rotor’s angle in relative to center of inertia is fitted. Maximum deceleration area or maximum acceleration area of each unit is obtained according to the fitted curves and then the stability margin and instability margin for the system are obtained. This method has advantage of good accuracy and adaptability of time-domain simulation method and by using the method, the energy type stability margin is obtained. A fast transient stability prediction method based on the WAMS process measurement is proposed in this paper. It can quickly predict the system stability margin, the moment when the system loses stability and control devices’ response time by scrolling the measurement data which have been measured by the local PMU. Practical system analysis shows that the method is very efficient, and it should have wide engineering applications for on-line stability monitoring.In addition to evaluate the stability of the system, another important issue is that if the system will lose stability, how to apply the appropriate amount of control to prevent system instability or to achieve the intended target, which is another important part of this paper. It involves quantitative analysis of power system stability and quantitative indicators’ impact on control variables, even in the offline environment, this is a difficult, it will be more difficult in real-time environment that require fast given the appropriate amount of control. Fianally, a method is proposed for allocating generation so as to maximize power transfer between areas of interconnected systems under transient stability constraints. The proposed method is to specify how to give control or adjust strategy by SGEAC. This transient stability-constrained maximum allowable transfer method consists of screening a large number of contingencies, scrutinizing the dangerous ones, calculating the shifting active power generation of critical generators and suggesting generation rescheduling patterns to stabilize them by SGEAC. The method is accurate and adaptable as the time domain simulation method, but also stability margin based on single machine energy can be obtained. Compared with other energy function, it is not necessary to determine the correct two-group mode, can apply in multiply contingencies, multi-swing instability scenarios and different instability modes. It avoids exhaustive search. In addition, by controlling all dangerous contingencies simultaneously, the method succeeds in being fully compatible with requirements for real-time preventive monitoring and control. Lots of example analysis with different losing synchronism modes verified the proposed method.