On the Estimation of Power System Inertia accounting for Renewable Generation Penetration

Abstract

Large-scale penetration of renewable energy sources in power systems is essentially related to the need of reducing the environmental impact caused by the fossil-fuel. As well known, the interface between the power grid and this kind of energy resource is achieved by power converters, with a consequent dynamic behavior quite different from the synchronous generators. This matter involves negative impacts on the operating conditions of power systems. In this context, it is crucial to individuate estimation techniques able to predict promptly critical conditions which could, in extreme cases, compromise the stability of whole system. In this paper the authors employ an auto-regressive model which can describe the dynamic evolution of the power system inertia. The core of the procedure relies on an inertia model conceived as the sum of a periodic component and a noise stochastic process distributed according a Logistic model. The robustness of a novel estimation procedure, able to capture the dynamic evolution of the inertia, is investigated by testing two scenarios of Italian Transmission Network. The assumptions in terms of the obtained numerical results show the validity of the estimation technique and of the probabilistic characterization of the noise.