Novel Decentralized Control of Power Systems With Penetration of Renewable Energy Sources in Small-Scale Power Systems

Abstract

In this paper, the power grid with penetration of renewable energy sources is modeled as a multigenerator interconnected power network. The power grid includes distributed energy resources including conventional synchronous generators and renewable energy sources; here called renewable generators that are connected to the grid via grid-tie inverters (GTIs). With the proposed modeling, the GTI resembles a synchronous generator with excitation control. The modeling takes into account the dc-link capacitor stored energy as a dynamical state, in contrast with the available methods, and through an appropriate controller assures the stability of the dc link and the entire grid without needing an abundant-energy dc link. Next, the power grid comprising the synchronous and renewable generators is converted to decentralized control form with subsystems in Brunovsky canonical form whose interactions with the rest of the grid are unknown. A decentralized adaptive neural network (NN) feedback controller is proposed with quadratic update law to stabilize the rotor speed and dc-link voltage oscillations in asymptotic fashion in the presence of grid disturbances. The proposed controller is then simplified. Though the solar power interacting with conventional synchronous generators is considered in this paper, the proposed modeling and controller design can be applied to many other renewable energy systems. Simulation results on the IEEE 14-bus power system with penetration of solar power are provided to show the effectiveness of the approach in damping oscillations that occur after disturbances.