A hybrid method for the dynamic parameter identification of generators via on-line measurements

Abstract

To maintain the reliability and security of power system, the Independent Power Producers (IPPs) are required to provide the accurate dynamic parameters of the generation facilities to the Independent System Operator (ISO) or Regional Transmission Organization (RTO). Dynamic parameter identification which aims at obtaining accurate dynamic parameters has been one of the central topics in power system studies for years. Sensitivity analysis is the most popular and traditional method in dynamic parameter identification of power system. However, its effectiveness is highly dependent on the preset initial guess. Some intelligent methods such as GA and ANN which can handle this problem usually require much more time and are complicated to be applied. This paper proposes a hybrid method combining particle swarm optimization and sensitivity analysis for dynamic parameter identification. The proposed hybrid method provides the right balance and trade-off between convergence and computation speed. Particle Swarm Optimization, a relatively new intelligent optimization method, is employed to find an approximate solution in the first step. Then the sensitivity analysis is run to achieve an accurate solution starting with the approximate solution obtained from PSO. This paper focuses on key parameters, pre-recognized by PSS/E simulation with historical data, to reduce the number of simulation cases. Also the parallel programming is used to take advantage of multiple core processors to significantly increase the computation speed. The simulation results show the validity and benefit of the hybrid method.

Dynamic parameter identification of generators for smart grid development

“…The exciter and governor models are EXAC1 and IEESGO respectively. The detailed parameters of the models are listed in Table 1 and Table 2 [15][16][17]. In the test case, the short-circuit fault event relating to the power plant is assumed.…”

Dynamic equivalent model development to improve the operation efficiency of wind farm

“…Field test is a direct method to get accurate parameter values for the tested device. However, frequent field tests, which require shutting down a unit for several days, would be impractical or even impossible considering unit unavailability impacts on the system and high costs [7]. In modern power system networks, on-line measurement technology such as Phasor Measurement Unit (PMU) or Digital Frequency Recorder (DFR) could provide system dynamic behavior information which enables dynamic equivalent model development via measured data.…”

PMU based generator parameter identification to improve the system planning and operation

“…Besides, the power plant usually lacks of expertise and experiences to perform these tests. In order to overcome the shortcomings of the field test method, online based identification methods have drawn attention in recent years, as in [1], [2], [3], [4].…”