Xie Chang

Quantitative evaluation for influence factors of calculation deviations of schedule power flow for large power grid

With the increase of the scale of the power grid and the improvement of the intelligence degree, the rationality and accuracy of the schedule power flow (the schedule) are becoming more and more serious. In this paper, by analyzing the relationship between input and output in the process of power flow calculation, the five main factors influencing the line active power deviation and the main cause of node voltage deviation are obtained. Furthermore, the influence of these factors on the line active power and node voltage are analyzed and the corresponding contribution indexes are calculated with the flexible use of sensitivity analysis and power flow distribution factors. The analysis and synthesis of these indexes lead to a set of methods for quantitative evaluation of the schedule, which can realize the rapid evaluation of the calculation precision. The rationality and practicability of this method are verified by the sample application, based on the schedule data from Central China State Grid.

Study on huge power grid online operation trend assessment system

Online dynamic security analysis conclusion is lagging power grid operation mode changes, and contradictions with the timeliness of power grid real-time scheduling and operation control have become increasingly prominent. To solve the problem, framework of power grid online operation trend analysis system is constructed, and three advanced technologies are researched, including future power flow algorithm based on controlling power of multi transmission section simultaneously, operation trend analysis method based on stability assessment index and multiple fault coordination control method. Huge power grid online operation trend analysis system is developed, and timeliness problem of the online security analysis is solved. The system has realized the change from the accident alarm, emergency control to accident early warning, prevention and control. It can predict future operation state of power system, and pre-control operation risk of power system.

Paralleled optimal power flow algorithm based on subarea division of the power system

With the continuous expansion of the grid scale, the traditional centralized optimal power flow calculation has the difficulties of long computing time and higher dimension matrix. This paper presents a paralleled optimal power flow algorithm based on subarea division, which divides the actual grid into several independent subareas geographically according to the decomposition and coordination method, and uses the auxiliary problem principle (APP) in parallel computing. In each subarea, the multicenter-correction interior point method is used to solve the optimization problem of the subarea system. The example shows that the algorithm has good convergence and faster computing speed.

Research on active power control analysis method of transmission interfaces for online TTC calculation

Total Transfer Capability(TTC) play an important role on anlysis and control of power system stability. This paper proposes an method about active power control strategy analysis of transmission interfaces, which identifies the most sensitive generator for transmission interfaces and decides control strategy of transmission interfaces active power automatically. It can improve accuracy of online TTC which dependent on off-line simulation knowledge, also could not automatically adapt the real-time operation mode of power system. In this paper, a varible of integrative sensitivity of transmission interfaces is defined for reflecting the control effect of different generator for total power of transmission interface. Based on this varible, the method can calculate the adjustment margin and priority of generator in power network, and search adjustable electric equipments for controlling transmission interfaces power, and provide control strategy for transmission interfaces active power. Finally the simulation analysis of actual exapmle verifies the effectiveness of the method.

Operation rule extracting based on time series association analysis in transient stability study

A robust operation rule extracting algorithm is proposed based on adaptive time series association analysis here. It is applied to extract association knowledge among the accumulating massive operation data. A data model describing the system state and topological structure before/after fault happening is built up at first. The initial abstract features are independent of the scale of a power system. A recursive principal component analysis method is employed to yield the reduced-size feature space. The extract features are then fed into the associative analysis. For considering temporal constraint, the generated associative rules not only reflect the relationship between power system operating condition and transient stability, but also reveal some valuable information about operating characteristics. Simulation results on on IEEE 39-bus test system demonstrate the feasibility and efficiency of the proposed method.