arXiv subjects

Samuele Grillo

Publications and source records attributed to Samuele Grillo.

18 recordsLinked to original sources

arXiv2026

Stability Analysis of Grid-Following and Grid-Forming Converters Connected to Generators

This work presents an examination of the main interactions between grid-following (GFL) and grid-forming (GFM) voltage source converters (VSCs) and synchronous generators (SGs), capturing the dynamics of a real power grid and pointing out the limitations of considering an ideal one for stability studies. Eigenvalue trajectories and participation factors are studied to perform in-depth small-signal analyses. Specifically, the GFL and GFM converters are compared in different grid strength scenarios by varying their rating powers and the grid short circuit ratio. Then, time-domain simulations of the non-linear and the developed linear systems are run to validate the mathematical findings from the stability analysis. The results reveal that the stability of VSCs-dominated grids, either in GFL or GFM mode, is strongly affected by both the grid strength and the VSC power, due to the coupling between the VSC control and the SGs.

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arXiv2026

Small-Signal Stability Manifolds in Converter-Dominated Power Systems

This paper proposes a systematic framework to assess the small-signal stability of power systems with high shares of grid-following inverter-based resources (IBRs) under varying controller parameters and operating conditions. Stability manifolds are introduced to identify controller-parameter regions that ensure stability across multiple scenarios. Full-network linearization and eigenvalue analysis are combined with adaptive sampling based on probabilistic support vector machine classification to approximate stability boundaries efficiently, while surrogate optimization identifies feasible initial controller settings meeting bandwidth and phase-margin constraints. The approach is validated on a modified Cigr\'e European HV network benchmark with 50 operating scenarios and increasing inverter penetration. Results show that stability sensitivity grows with inverter share, interactions among IBRs reshape admissible parameter regions, and simplified equivalent-network models may overlook critical system-level limitations. The framework supports stability-oriented controller design and interconnection studies in converter-dominated systems.

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arXiv2025

A Principled Framework to Evaluate Quality of AC-OPF Datasets for Machine Learning: Benchmarking a Novel, Scalable Generation Method

Several methods have been proposed in the literature to improve the quality of AC optimal power flow (AC-OPF) datasets used in machine learning (ML) models. Yet, scalability to large power systems remains unaddressed and comparing generation approaches is still hindered by the absence of widely accepted metrics quantifying AC-OPF dataset quality. In this work, we tackle both these limitations. We provide a simple heuristic that samples load setpoints uniformly in total load active power, rather than maximizing volume coverage, and solves an AC-OPF formulation with load slack variables to improve convergence. For quality assessment, we formulate a multi-criteria framework based on three metrics, measuring variability in the marginal distributions of AC-OPF primal variables, diversity in constraint activation patterns among AC-OPF instances and activation frequency of variable bounds. By comparing four open-source methods based on these metrics, we show that our heuristic consistently outperforms uniform random sampling, whether independent or constrained to a convex polytope, scoring as best in terms of balance between dataset quality and scalability.

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arXiv2025

Detailed Small-Signal Stability Analysis of the Cigr\'e High-Voltage Network Penetrated by Grid-Following Inverter-Based Resources

This paper presents a detailed small-signal stability analysis of a modified version of the Cigr\'e European high-voltage network, where one of the synchronous generators is replaced by a grid-following inverter-based resource (IBR). The analysis focuses on the influence of the parameters defining the grid-following IBR control scheme on the stability of the system. Given a set of potential grid configurations and the value of the IBR control parameters, stability is verified by the direct eigenvalue analysis of a high-detailed linearized model of the overall Cigr\'e network. Starting from this procedure, we propose an adaptive sampling method for training a support vector machine classifier able to estimate the probability of stability of the power system over a domain defined by candidate intervals of the considered parameters. The training of the classifier is refined to identify with more accuracy the boundaries of the parameters' stability regions. The obtained results are then compared with those obtained by representing the grid with the classical Th\'evenin equivalent. Results suggest that, when the Th\'evenin equivalent is accurate, the predicted stability region is conservative yet contained within that of the full network.

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arXiv2023

Definition of Static and Dynamic Load Models for Grid Studies of Electric Vehicles Connected to Fast Charging Stations

The growing deployment of electric mobility calls for power system analyses to investigate to what extent the simultaneous charging of electric vehicles leads to degraded network operation and to validate the efficiency of countermeasures. To reduce complexity and CPU time, a common approach while performing these analyses consists in replacing electric vehicles and their charging stations with constant PQ loads. However, this approach is inaccurate, as the power absorbed by these elements actually depends not only on voltage but also on the state of charge, charging method, cathode chemistry of the battery pack, and converter controls in the electric vehicle and charging station. By considering all these aspects, this article develops a novel static load model and a vector fitting-based dynamic load model for electric vehicles connected to fast charging stations. These computationally efficient representations can replace the standard constant PQ load model of electric vehicles to assess more accurately their impact in static and dynamic grid studies. Simulation results of the IEEE14 system modified by adding fleets of electric vehicles prove the accuracy of the proposed models and highlight the shortcomings of the standard electric vehicle representation as a constant PQ load in some cases.

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arXiv2022

On the Calculation of the Variance of Algebraic Variables in Power System Dynamic Models with Stochastic Processes

This letter presents a technique to calculate the variance of algebraic variables of power system models represented as a set of stochastic differential-algebraic equations. The technique utilizes the solution of a Lyapunov equation and requires the calculation of the state matrix of the system. The IEEE 14-bus system serves to demonstrate the accuracy of the proposed technique over a wide range of variances of stochastic processes. The accuracy is evaluated by comparing the results with those obtained with Monte Carlo time domain simulations. Finally, a case study based on a 1479-bus dynamic model of the all-island Irish transmission system shows the computational efficiency of the proposed approach compared to the Monte Carlo method.

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arXiv2022

Inertia Estimation Through Covariance Matrix

This work presents a technique to estimate on-line the inertia of a power system based on ambient measurements. The proposed technique utilizes the covariance matrix of these measurements and solves an optimization problem that fits such measurements to the synchronous machine classical model. We show that the proposed technique is adequate to accurately estimate the actual inertia of synchronous machines and also the virtual inertia provided by the controllers of converter-interfaced generators that emulate the behavior of synchronous machines. We also show that the proposed approach is able to estimate the equivalent damping of the classical synchronous machine model. This feature is exploited to estimate the droop of grid-following converters, which has a similar effect of the swing equation equivalent damping. The technique is comprehensively tested on a modified version of the IEEE 39-bus system as well as on a dynamic 1479-bus model of the all-island Irish transmission system.

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arXiv2022

Characterization of electric consumers through an automated clustering pipeline

Clustering analysis of daily load profiles represents an effective technique to classify and aggregate electric users based on their actual consumption patterns. Among other purposes, it may be exploited as a preliminary stage for load forecasting, which is applied in the same way to consumers in the same cluster. Several clustering algorithms have been proposed and developed in the literature, and the choice of the most appropriate set of clustering parameters is crucial for ensuring reliable results. In this paper, an automated service, suited for repeated clustering analysis, is presented. The pipeline is able to process a generic time series dataset and is easily adjustable to test other clustering input parameters; therefore, it may be utilized to find the best set of parameters with the specific dataset. Moreover, it facilitates repeated characterization on real-time load profiles with the aim of detecting sudden changes of consumers behaviors and variable external conditions, which influence the real power forecasting activity on a short temporal scale.

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arXiv2022

Lessons learned from Milan electric power distribution networks data analysis during COVID-19 pandemic

COVID-19 pandemic has been a disruptive event from health, social, and economic points of view. Besides that, changes in people's lifestyles, especially during the 2020 lockdowns, also affected energy networks. COVID-19 pandemic has resulted in a significant decline in electricity demand. The lockdown measures applied to handle the health crisis have caused the most relevant energy impact of the last years. In this paper, the local experiences of the distribution network of Milano, a city in northern Italy, are reported. The analysis starts with a summary of the restrictions imposed during 2020 and focuses on both active and reactive power flows, and faults. To this end, a comparison with 2019 data has been performed, highlighting the main differences with 2020. The outcome of the analysis is a valuable tool to predict urban distribution networks behavior during times of disruption, helping distribution system operators to prepare feasible short-term and long-term resilience plans.

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arXiv2022

An Efficiency-Based Power Management Strategy for an Isolated Microgrid Project

The microgrids design for remote locations represents one of the most important and critical applications of the microgrid concept. It requires the correct sizing and the proper utilization of the different sources to guarantee the economical feasibility and the reliability of the supply. This study illustrates an efficiency-based power management strategy, designed for an undergoing microgrid project, where the sizing process of the resources (diesel generators, battery energy storage system, and PV plant) is obtained using a mixed-integer optimization algorithm. The proposed power management strategy guarantees the efficient exploitation of the power sources, which is one of the key elements of the optimal sizing process, being naturally included in the definition of the energy cost functions. The effectiveness of the power control strategy is validated by means of quasi-dynamic simulations on the complete microgrid model, where sources are defined by the optimal problem solution, while the cabling (size and length) and the main switchboards location reflect the expected system layout. Results obtained from the simulation of the microgrid electrical system include losses, and allow to verify and to highlight the desired quantities, such as the quality of supply at each busbar (voltage magnitude), and the state of charge of the energy storage system.

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arXiv2021

High Voltage Shore Connection Systems: Grounding Resistance Selection and Short Circuit Currents Evaluation

Cold ironing represents an effective solution to remove air polluting emissions from ports. The high voltage shore connection system is the key enabling facility that allows to provide power from the shore side electrical system to the ship. The design of the shore connection needs a comprehensive assessment of the fault currents in different operating scenarios. International standards require the neutral point of the shore connection transformer be equipped with a neutral grounding resistor. Its value has to be defined to guarantee safety and protection of equipment and personnel in case of single phase-to-ground faults. Moreover, three-phase short circuits need to be considered to size equipment and protection devices. A crucial role is played by the frequency converter control system, required to adapt the mains frequency to the frequency of the ship. In this work, a complete electro-magnetic dynamic model of the high voltage shore connection and of the on-board power system has been developed, including frequency converter, shore-side transformer, connection MV cables and power system of the ship, to analyze in detail the behavior of the system in case of single phase-to-ground fault and three-phase short circuit, taking into account relevant standards and best practices.

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arXiv2021

Development and Validation of a Scalable Fast Load Shedding Technique for Industrial Power Systems

The work aims to improve the existing fast load shedding algorithm for industrial power system to increase performance, reliability, and scalability for future expansions. The paper illustrates the development of a scalable algorithm to compute the shedding matrix, and the test performed on a model of the electric grid of an offshore platform. From this model it is possible to study the impact on the transients of various parameters, such as spinning reserve and delay time. Subsequently, the code is converted into Structured Text and implemented on an ABB PLC. The scalability of the load shedding algorithm is thus verified, confirming its performance with respect to the computation of the shedding matrix and the usefulness of the dynamic simulations during the design phase of the plant.

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arXiv2021

Post-Metering Value-Added Services for Low Voltage Electricity Users: Lessons Learned From the Italian Experience of CHAIN 2

Electrical energy consumption data accessibility for low voltage end users is one of the pillars of smart grids. In some countries, despite the presence of smart meters, a fragmentary data availability and/or the lack of standardization hinders the creation of post-metering value-added services and confines such innovative solutions to the prototypal and experimental level. We take inspiration from the technology adopted in Italy, where the national regulatory authority actively supported the definition of a solution agreed upon by all the involved stakeholders. In this context, smart meters are enabled to convey data to low voltage end users through a power line communication channel (CHAIN 2) in near real-time. The aim of this paper is twofold. On the one hand, it describes the proof of concept that the channel underwent and its subsequent validation (with performances nearing 99% success rate). On the other hand, it defines a classification framework (I2MA) for post-metering value-added services, in order to categorize each use case based on both level of service and expected benefits, and understand its maturity level. As an example, we apply the methodology to the 16 use cases defined in Italy. The lessons learned from the regulatory, technological, and functional approach of the Italian experience bring us to the provision of recommendations for researchers and industry experts. In particular, we argue that a well-functioning post-metering value-added services' market can flourish when: i) distribution system operators certify the measurements coming from smart meters; ii) national regulatory authorities support the technological innovation needed for setting up this market; and iii) service providers create customer-oriented solutions based on smart meters' data.

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arXiv2021

Impact of EV Charging Stations in Power Grids in Italy and its Mitigation Mechanisms

Global warming leads the world to think of a different way of transportation: avoiding internal combustion engines and electrifying the transportation sector. With a high penetration of electric vehicle (EV) charging stations on an existing power distribution network, the impact may be consistent. The loads of the fast-charging stations would potentially result in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. The degrading performance of the power system due to the negative impact of the EV charging stations can even lead to penalties to be paid by the distribution system operator (DSO). This paper: i) investigates the impact of the \ac{ev} charging station on the distribution network for what concerns voltage drop on MV feeders and loading of transformers in primary substations, and ii) proposes a mitigation mechanism. A realistic typical Italian grid has been used to assess the impact of EV charging stations and to validate the mitigation mechanism.

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arXiv2021

Small-Signal Stability Analysis of a DC Shipboard Microgrid With Droop-Controlled Batteries and Constant Power Resources

The presence of constant power loads (CPLs) in dc shipboard microgrids may lead to unstable conditions. The present work investigates the stability properties of dc microgrids where CPLs are fed by fuel cells (FCs), and energy storage systems (ESSs) equipped with voltage droop control. With respect to the previous literature, the dynamics of the duty cycles of the dc-dc converters implementing the droop regulation are considered. A mathematical model has been derived, and tuned to best mimic the behavior of the electrical representation implemented in DIgSILENT. Then the model is used to find the sufficient conditions for stability with respect to the droop coefficient, the dc-bus capacitor, and the inductances of the dc-dc converters.

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arXiv2020

An Optimization Problem for Day-Ahead Planning of Electrical Energy Aggregators

The widespread diffusion of distributed energy resources, especially those based on renewable energy, and energy storage devices has deeply modified power systems. As a consequence, demand response, the ability of customers to respond to regulating signals, has moved from large high-voltage and medium-voltage end-users to small, low-voltage, customers. In order to be effective, the participation to demand response of such small players must be gathered by aggregators. The role and the business models of these new entities have been studied in literature from a variety of viewpoints. Demand response can be clearly applied by sending a dedicated price signal to customers, but this methodology cannot obtain a diverse, punctual, predictable, and reliable response. These characteristics can be achieved by directly controlling the loads units. This approach involves communication problems and technological readiness. This paper proposes a fully decentralized mixed integer linear programming approach for demand response. In this framework, each load unit performs an optimization, subject to technical and user-based constraints, and gives to the aggregator a desired profile along with a reserve, which is guaranteed to comply with the constraints. In this way, the aggregator can trade the reserve coming from several load units, being the only interface to the market. Upon request, then, the aggregator communicates to the load units the modifications to their desired profiles without either knowing or caring how this modification would be accomplished. The effectiveness is simulated on 200 realistic load units.

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arXiv2020

Functional Principal Component Analysis as a Versatile Technique to Understand and Predict the Electric Consumption Patterns

Understanding and predicting the electric consumption patterns in the short-, mid- and long-term, at the distribution and transmission level, is a fundamental asset for smart grids infrastructure planning, dynamic network reconfiguration, dynamic energy pricing and savings, and thus energy efficiency. This work introduces the Functional Principal Component Analysis (FPCA) as a versatile method to both investigate and predict, at different level of spatial aggregation, the consumption patterns. The method was applied to a unique and sensitive dataset that includes electric consumption and contractual information of Milan metropolitan area. The decomposition of the load patterns into principal functions was found to be a powerful method to identify the physical and behavioral causes underlying the daily consumptions, given knowledge of exogenous variables such as calendar and meteorological data. The effectiveness of long-term predictions based on principal functions was proved on Milan's metropolitan area data and assessed on a publicly-available dataset.

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arXiv2020

Effects of Inertia, Load Damping and Dead-Bands on Frequency Histograms and Frequency Control of Power Systems

The increasing penetration of renewable energy sources has been leading to the progressive phase-out of synchronous generators, which constitute the main source of frequency stability for electric power systems. In the light of these changes, over the past years, some power systems started to exhibit an odd frequency distribution characterised by a bimodal behavior. This results in increased wear and tear of turbine governors and, in general, in degraded frequency performances. This is a cause of concern for grid operators, which have become increasingly interested in understanding the factors shaping frequency distribution. This paper explores the root causes of unwanted frequency distributions. The influence of some main aggregate system parameters on frequency distribution is detailed. The paper also shows that the implementation of the so-called synthetic inertia can lead to a robust unimodal frequency distribution.

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