Abstract
Low-frequency oscillation (LFO) is among the key factors that threaten interconnected power grids’ security and stability and restrict transfer capability. In particular, power systems incur now and then weak damping and forced oscillations. To monitor and control LFO, the principles of online calculation and analysis of two types of LFO are studied in this paper. The big data of wide area measurements is an important information source of LFO analysis. Hence, we should make sure it has access to online system continuously, accurately, and reliably. Nevertheless, the conventional linear data store model has difficulty to meet the processing requirements of high rate, multiple concurrency, and high reliability. To deal with it, a new model of double-set elastic store is proposed in this paper. It transforms the storage space linear model to plane model, realizes the management of power system substation group sets in vertical direction and the management of multiple Phase Measurement Units (PMU) uploading data sets in horizontal direction, and hence solves the problems in continuous and reliable access of the wide area measurements data, which is dense and of large scale and has quick update rate, providing technical support of accuracy and robustness of LFO analysis. The performance test and practical application of the proposed new model of double-set elastic store validate its accuracy.
Highlights
Chinese power network structure and operation/control characteristics have witnessed profound change, due to commission and operation of Ultra High Voltage (UHV) AC/DC power transmission, grid-connected massive new energy, and application of new types of devices of Flexible AC Transmission Systems (FACTS)
Low-Frequency Oscillation (LFO) is divided into three types: weak damping, forced, and nonlinear, among which weak damping and forced oscillation accidents have once happened in Henan, Yunnan, western Inner Mongolia, Xinjiang, and some other places in China [5,6,7]. erefore, it is necessary to utilize multiple information sources and advanced algorithms to analyze and control LFO, to deal with damage to power system that LFO brings
As Wide area measurement system (WAMS) is applied in real power systems, many advanced functions are hard to be practical due to the problems of devices, communication, master station maintaining and management, and so forth [16]. e main reason is that WAMS data accuracy, continuity, and stability are impaired by multiple influence factors, which cause the methods depending heavily on data accuracy and continuity to lose practical value
Summary
Chinese power network structure and operation/control characteristics have witnessed profound change, due to commission and operation of Ultra High Voltage (UHV) AC/DC power transmission, grid-connected massive new energy, and application of new types of devices of Flexible AC Transmission Systems (FACTS). To realize analysis and monitoring of LFO in power systems, on the one hand, forced oscillation source searching and positioning as well as modal analysis and model calculation are carried out, utilizing multiple information sources of WAMS data, Energy Management System (EMS) data, power system dynamic parameters, and so forth; on the other hand, frequency domain simulation analysis is carried out through integration of multiple information sources to search for the possible weak damping model and its control strategy. Tie line power trajectory is extracted form WAMS data, (7) is calculated through Prony algorithm, magnitude, initial phase angle, and attenuation factor, and frequency can be obtained from the complex exponential linear model:. All of the above three key technologies need to use WAMS information as data source, which speaks volumes for WAMS big data playing a key role in LFO online analysis
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