The paper introduces a technical-economic methodology to estimate the additional inertia required in a Transmission Network for future scenarios and presents an algorithm to optimally dispatch it among different sources and interwork busbars. First, the amount of inertia is calculated to constrain the Rate of Change of Frequency (RoCoF) within sustainable limits. Then, such inertia is allocated accounting for the contributions from Renewable Energy Sources (RESs) and Battery Energy Storage Systems (BESSs), complemented by the deployment of Synchronous Compensators (SCs) across various nodes of a Transmission Network. The methodology underwent testing within the Italian Transmission Network, utilizing the informational support furnished by the Italian Transmission System Operator (TSO). Despite its simplicity, the results exhibit notable accuracy, validated through rigorous comparisons with detailed time-domain simulations. Moreover, the low computational cost of the method, allowed a statistical analysis considering all the hours of year 2030, to get information on the distributions of the quantities of interest.
Optimal inertia allocation in future transmission networks: A case study on the Italian grid
Minetti M.;Fresia M.;Procopio R.;Bonfiglio A.;
2025-01-01
Abstract
The paper introduces a technical-economic methodology to estimate the additional inertia required in a Transmission Network for future scenarios and presents an algorithm to optimally dispatch it among different sources and interwork busbars. First, the amount of inertia is calculated to constrain the Rate of Change of Frequency (RoCoF) within sustainable limits. Then, such inertia is allocated accounting for the contributions from Renewable Energy Sources (RESs) and Battery Energy Storage Systems (BESSs), complemented by the deployment of Synchronous Compensators (SCs) across various nodes of a Transmission Network. The methodology underwent testing within the Italian Transmission Network, utilizing the informational support furnished by the Italian Transmission System Operator (TSO). Despite its simplicity, the results exhibit notable accuracy, validated through rigorous comparisons with detailed time-domain simulations. Moreover, the low computational cost of the method, allowed a statistical analysis considering all the hours of year 2030, to get information on the distributions of the quantities of interest.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



