Decoupling of voltage magnitude and phase in genetic algorithms for smart transmission network state estimation - Tran, Thanh-Son; Kieu, Thi-Thanh-Hoa; Le, Duc-Tung (Frontiers in Energy Research, 2023)
A large amount of renewable energies is integrated into electricity transmission networks. To properly operate, the transmission networks should be smart. In which, it is necessary to have the function of estimating the state of the power system. This function determines bus voltage magnitude and phase which are used for monitoring, operating, and controlling transmission networks. Transmission network state estimation is developed to estimate bus voltage magnitude and phase by many methods which include genetic algorithm. Published articles have not mentioned in detail how to apply genetic algorithm to estimate the state of large transmission networks or the application is limited for small networks. Therefore, this work seeks to estimate the state of large transmission networks by genetic algorithm. Observing a strong decoupling between active power and voltage phase, as well as between reactive power and voltage magnitude, while a weak coupling between active power and voltage magnitude, as well as between reactive power and voltage phase; voltage magnitude has value around 1.0 p.u and voltage phase has value around 0.0, this paper proposes a novel approach of genetic algorithm for estimating the state of smart transmission networks. In this novel approach, voltage magnitude and phase are separately estimated at each iteration of genetic algorithm. The approach is validated on IEEE 14, 30, and 118 bus networks. Results show that our approach can use phasor measurement unit data to estimate the state of large smart transmission networks by genetic algorithm.