no code implementations • 19 Apr 2024 • Rahul K. Gupta, Sherif Fahmy, Max Chevron, Riccardo Vasapollo, Enea Figini, Mario Paolone
The framework consists of two stages.
no code implementations • 19 Apr 2024 • Rahul K. Gupta, Sherif Fahmy, Max Chevron, Enea Figini, Mario Paolone
MPC accounts for the uncertainty of the power injections from stochastic resources (such as demand and generation from photovoltaic - PV plants) by short-term forecasts.
no code implementations • 19 Mar 2024 • Antonio Di Pasquale, Johanna Kristin Maria Becker, Andreas Martin Kettner, Mario Paolone
Notably, the effectiveness of the fixed-point formulation and the uniqueness of the solution are evaluated through numerical analyses conducted on a modified version of the CIGRE low-voltage benchmark microgrid.
no code implementations • 15 Mar 2024 • Vladimir Sovljanski, Mario Paolone
The paper proposes a novel algorithm for designing the EIS experiments by applying the theory on Cramer-Rao Lower Bound (CRLB) and Fisher Information Matrix (FIM) to the identification problem.
no code implementations • 1 Nov 2023 • Willem Lambrichts, Jules Mace, Mario Paolone
The SCs are based on the unified power flow model for hybrid AC/DC grids that accounts for the AC grid, DC grid, and the Interfacing Converters (IC), which can operate in different control modes, e. g. voltage or power control.
no code implementations • 5 Oct 2023 • Pål Forr Austnes, Celia García-Pareja, Fabio Nobile, Mario Paolone
Accurate and reliable electricity load forecasts are becoming increasingly important as the share of intermittent resources in the system increases.
no code implementations • 28 Sep 2023 • Willem Lambrichts, Mario Paolone
In this paper, we present a closed-form model for the analytical computation of the power flow sensitivity coefficients (SCs) for hybrid AC/DC networks.
no code implementations • 28 Sep 2023 • Willem Lambrichts, Mario Paolone
Compared to other recent works, the proposed method allows multiple ICs to regulate the DC voltage simultaneously.
no code implementations • 27 Sep 2023 • Francesco Gerini, Elena Vagnoni, Martin Seydoux, Rachid Cherkaoui, Mario Paolone
This paper presents a solution to address wear and tear of Run-of-River (RoR) Hydropower Plants (HPPs) providing enhanced Frequency Containment Reserve (FCR).
no code implementations • 19 Sep 2023 • Plouton Grammatikos, Fabrizio Sossan, Jean-Yves Le Boudec, Mario Paolone
Microgrids and, in general, active distribution networks require ultra-short-term prediction, i. e., for sub-second time scales, for specific control decisions.
no code implementations • 26 Apr 2023 • Rahul Gupta, Mario Paolone
The estimated voltage sensitivity coefficients are used to model the nodal voltages, and the control robustness is achieved by accounting for their uncertainties.
no code implementations • 15 Apr 2023 • César García Veloso, Mario Paolone, José María Maza Ortega
The main feature of the method is its ability to detect interfering tones with an amplitude lower than that adopted by the IEC/IEEE Std.
no code implementations • 6 Feb 2023 • Johanna Kristin Maria Becker, Andreas Martin Kettner, Yihui Zuo, Mario Paolone
This paper updates the HPF method to model hybrid AC/DC grids interconnected through NICs.
no code implementations • 15 Jun 2022 • Johanna Kristin Maria Becker, Andreas Martin Kettner, Yihui Zuo, Federico Cecati, Sante Pugliese, Marco Liserre, Mario Paolone
Power distribution systems experience a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs).
no code implementations • 11 Jan 2022 • Rahul Gupta, Fabrizio Sossan, Mario Paolone
This formulation is applied to control distributed controllable photovoltaic (PV) generation in a distribution network to restrict the voltage within prescribed limits.
no code implementations • 10 Jan 2022 • Rahul Gupta, Sherif Fahmy, Mario Paolone
Specifically, the proposed framework optimizes the dispatch plan of an upstream medium voltage (MV) grid accounting for the flexibility offered by downstream low voltage (LV) grids and the knowledge of the uncertainties of the stochastic resources.
no code implementations • 19 Oct 2021 • Francesco Gerini, Yihui Zuo, Rahul Gupta, Elena Vagnoni, Rachid Cherkaoui, Mario Paolone
This paper proposes and experimentally validates a joint control and scheduling framework for a grid-forming converter-interfaced BESS providing multiple services to the electrical grid.
no code implementations • 11 Oct 2021 • Antonio Zecchino, Francesco Gerini, Yihui Zuo, Rachid Cherkaoui, Mario Paolone, Elena Vagnoni
The progressive displacing of conventional generation in favour of renewable energy sources requires restoring an adequate capacity of regulating power to ensure reliable operation of power systems.
no code implementations • 23 Jun 2021 • Johanna Kristin Maria Becker, Andreas Martin Kettner, Lorenzo Reyes-Chamorro, Zhixiang Zou, Marco Liserre, Mario Paolone
the number of CIDERs and the maximum harmonic order ($\leqslant$25).
no code implementations • 23 Jun 2021 • Andreas Martin Kettner, Lorenzo Reyes-Chamorro, Johanna Kristin Maria Becker, Zhixiang Zou, Marco Liserre, Mario Paolone
In this paper, a method for the calculation of the so-called Harmonic Power-Flow (HPF) in three-phase grids with CIDERs is proposed.
no code implementations • 7 Jun 2021 • Dorsan Lepour, Mario Paolone, Guillaume Denis, Carmen Cardozo, Thibault Prevost, Emeline Guiu
This work presents a comparison between two technologies with grid-forming capability: the VSC with a grid-forming control coupled with an adequate energy storage system, and the synchronous condensers (SC).
no code implementations • 10 Aug 2020 • Mathias Dorier, Guglielmo Frigo, Ali Abur, Mario Paolone
The state estimation problem can be solved through different methods.
no code implementations • 23 Jun 2020 • Zhao Yuan, Antonio Zecchino, Rachid Cherkaoui, Mario Paolone
To guarantee the feasibility of the power set-points with respect to both the converter capability and BESS security constraints, the final power set-points calculation is formulated as a nonconvex optimization problem.