
doi: 10.1049/cps2.12051
Abstract The massive perception data based on efficient analysis and intelligent decision have put forward higher requirements for high‐precision time synchronisation with the construction and development of smart power grid. However, multi‐reference source time‐frequency synchronisation of power system only selects the best method after comparison, which cannot make the most efficient use of the existing resources. It also cannot meet the need for high‐precision time synchronisation of future power system. The existing multi‐reference source synthesis algorithms cannot take into account both long‐term stability and high‐precision synchronous output. This article presents a multi‐reference source weighted improved noise model and the high‐precision output method. The multi‐reference source error after classification is eliminated by leading into classification vector and classification coefficient. The synthesised frequency offset or the time precision of output can be optimised as the objective function by weighted classification algorithm and genetic algorithm. A simulation example based on the synthesis of two satellite system clock sources and three local caesium reference sources shows that the peak value of long‐term output accuracy is controlled within 10 ns after classification weighted synthesis and optimisation, which is better than that of any single reference source.
TK7885-7895, Computer engineering. Computer hardware, power electronics, global positioning system, Electronic computers. Computer science, synchronisation, QA75.5-76.95, genetic algorithms
TK7885-7895, Computer engineering. Computer hardware, power electronics, global positioning system, Electronic computers. Computer science, synchronisation, QA75.5-76.95, genetic algorithms
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
