Stochastic simulations and stability to determine maximum wind power penetration of an island network

Wendy Carolina Briceño Vicente (1) , Raphaël Caire (1) , Nouredine Hadjsaid (1)

1 G2ELab - Laboratoire de Génie Electrique de Grenoble

Wind power is the fastest developing renewable energy source in power networks. The maximization of wind power penetration depends on constraints imposed by network topology, electrical and mechanical limits, temporal variations of wind power injections and load consumption. In order to determine the maximum wind power penetration, uncertainties must be considered. The proposed method uses stability criterion (time domain simulations and) mixed with stochastic simulation, under different contingency scenarios. It determines the Probability Density Function (PDF) of unstable cases using small signal stability according to wind power penetration. The study case was IEEE 9-bus transmission network and two contingencies were considered: three phases short-circuit for Fault Ride Through (FRT) capability, and loss of a generation unit. The loss of a machine is the worst limiting operational condition which determines wind power penetration of the network within the operational limits of wind turbines (WTs).

Mots clés: Eigenvalue analysis; Maximum wind power penetration; Monte-Carlo Simulation (MCS); Probability Density Function (PDF); Small-signal stability; Wind Turbine (WT); grid code requirements; time domain simulation; uncertainty

Domaines: Sciences de l'ingénieur [physics]; Energie électrique

Wendy Carolina Briceño Vicente, Raphaël Caire, Nouredine Hadjsaid. Stochastic simulations and stability to determine maximum wind power penetration of an island network. 2017 IEEE Power & Energy Society General Meeting (PESGM), Jul 2017, Chicago, United States. ⟨10.1109/PESGM.2017.8273855⟩. ⟨hal-01809938⟩