arXiv subjects

Fabrizio Sossan

Publications and source records attributed to Fabrizio Sossan.

At least 19 recordsLinked to original sources

arXiv2026

Energy Storage as a Multi-Use Asset: Applications Across the Power System

The energy transition in power systems requires flexible assets to offset renewable generation variability across multiple time scales, while supporting the integration of renewables and the electrification of demand without requiring costly grid reinforcement. Energy storage occupies a unique position among these assets: depending on the technology, it can provide short-duration grid services at high ramping rates, such as frequency regulation and voltage support, longer-duration functions such as intra-day peak shaving, or inter-seasonal energy buffering. This multi-service character, combined with the declining costs of energy storage technologies (most notably that of battery energy storage systems), is central to the economic viability of storage investments. The value of a given installation depends strongly on its grid connection point and intended use case: an asset-coupled battery serving a consumer or generation plant faces a different service landscape, and therefore a different business case, than a network-coupled system operating as an independent grid resource. This paper presents a structured taxonomy of grid-connected energy storage applications, discusses the principal application domains, and describes the key challenges that must be addressed to integrate storage effectively into power systems. Services are discussed with special emphasis on the Swiss regulatory context. Finally, the STORE flagship project supported by the Swiss Innovation Agency (Innosuisse), where some of the critical challenges of energy storage integration in power grids are addressed, is introduced.

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arXiv2026

Control and Scheduling of Behind-the-Meter Battery Energy Storage Systems for Stacked Grid and Building Services

This paper proposes and experimentally validates a two-stage scheduling and control strategy for a behind-the-meter battery energy storage system (BESS) delivering both local and grid services. Considered services are the maximization of PV self-consumption, peak-load reduction, and secondary frequency control (aFRR).The day-ahead stage allocates battery capacity across local and balancing services using a scenario based approach, reflecting potential remuneration from aFRR participation without committing to fixed power availability; in the real-time stage, BESS set-points are computed in a periodic fashion at a high time resolution based on updated information on balancing prices, net load realization and BESS state of charge. The strategy is experimentally validated on a building at the Energypolis Campus of HES-SO Valais (Sion, Switzerland), which exhibits a peak power demand of 300 kW and is equipped with a 264 kWh / 140 kW lithium-ion BESS. The experimental results demonstrate the effectiveness of the proposed framework in scheduling and actuating the provision of both behind-the-meter and front-of-the-meter services.

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arXiv2026

Enhancing Power Systems Transmission Adequacy via Optimal BESS Siting and Sizing using Benders Decomposition with Feasibility Cuts

This work presents a general framework for the operationally driven optimal siting and sizing of battery energy storage systems in power transmission networks, aimed at enhancing their resource adequacy. The approach considers multi-period planning horizons, enforces network constraints at high temporal resolution, and targets large-scale meshed systems. The resulting computationally complex mixed-integer non-linear programming problem is reformulated as a mixed-integer second-order cone programming problem and solved via Generalized Benders Decomposition, with feasibility cuts enabling congestion management and voltage regulation under binding network limits. A tailored heuristic recovers an alternating-current power-flow-feasible operating point from the relaxed solution. The proposed formulation is parallelizable, yielding excellent computational performance, while featuring rigorous guarantees of convergence.

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arXiv2025

Formulation and Experimental Validation of Price-Based Control of Flexible Prosumers in Distribution Grids with the Alternating Direction Method of Multipliers

This paper describes a method for computing price signals for prosumers, incentivizing them to adjust their consumption according to the constraints of the distribution grids to which they are connected, thereby preventing voltage violations and line congestion. The proposed method leverages an interpretation of the Alternating Direction Method of Multipliers (ADMM), which enables the extraction of a price signal to coordinate the operations of prosumers and the distribution grid's constraints while limiting the sharing of sensitive information among them. The method can be used by Distribution System Operators (DSOs) to dynamically adjust a pre-existing retail electricity tariff (e.g., a constant or time-of-use tariff), thereby triggering grid-support actions from prosumers. The method is validated experimentally in a 9-node low-voltage distribution grid laboratory with real components (lines and controllable power converters). The experiments validate the algorithm's performance in terms of convergence and operational efficiency, demonstrating its viability in a real-life setting.

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arXiv2025

Large-Scale Processing and Validation of Grid Data for Assessing the Fair Spatial Distribution of PV Hosting Capacity

The integration of PV systems and increased electrification levels present significant challenges to the traditional design and operation of distribution grids. This paper presents a methodology for extracting, validating, and adapting grid data from a distribution system operator's (DSO) database to facilitate large-scale grid studies, including load flow and optimal power flow analyses. The validation process combines rule-based sanity checks and offline automated power flow analyses to ensure data consistency and detect potential errors in the grid database, allowing for their correction. As a practical application, the paper proposes a method to assess the PV hosting capacity of distribution grids, with a focus on ensuring fairness in their spatial distribution. By incorporating fairness criteria into the analyses, we quantify the costs (in terms of missed revenues from selling PV generation) associated with spatial fairness.

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arXiv2025

Measurement-Based Line-Impedance Estimation in the Absence of Phasor Measurement Units

This paper proposes and compares experimentally several methods to estimate the series resistance and reactance (i.e., the transversal components of the $π$-model of a line) of low-voltage lines in distribution grids. It first shows that if phasor measurements are available and the grid nodal voltages and power injections are known, the problem can be formulated and solved as a conventional load flow with properly adjusted unknowns. To solve this problem, we propose an analytical derivation of the Jacobian matrix. If only RMS values are available, such as from smart meters, integrating information from multiple intervals becomes necessary, ultimately opening to least-squares estimations, widely adopted in the literature. In this context, applying the proposed Jacobian contributes to accelerating the problem resolution of existing algorithms. The methods are compared in terms of estimation performance and convergence by using measurements from an experimental distribution grid interfacing real-world components and with realistic size implemented at the Gridlab at HES-SO Valais.

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arXiv2025

Scheduling Power-Intensive Operations of Battery Energy Storage Systems and Application to Hybrid Hydropower Plants

This paper proposes a novel set of power constraints for Battery Energy Storage Systems (BESSs), referred to as Dynamic Power Constraints (DPCs), that account for the voltage and current limits of the BESS as a function of its State of Charge (SOC). These constraints are formulated for integration into optimization-based BESS scheduling problems, providing a significant improvement over traditional static constraints. It is shown that, under mild assumptions typically verified during practical operations, DPCs can be expressed as a linear function of the BESS power, thus making it possible to retrofit existing scheduling problems without altering their tractability property (i.e., convexity). The DCPs unify voltage and current constraints into a single framework, filling a gap between simplified models used in BESS schedulers and more advanced models in real-time controllers and Battery Management Systems (BMSs). By improving the representation of the BESS's power capability, the proposed constraints enable schedulers to make more reliable and feasible decision, especially in power-intensive applications where the BESS operates near its rated power. To demonstrate the effectiveness of the DPCs, a simulation-based performance evaluation is conducted using a hybrid system comprising a 230 MW Hydropower Plant (HPP) and a 750 kVA/500 kWh BESS. Compared to state-of-the-art formulations such as static power constraints and DPC formulations without voltage constraints the proposed method reduces BESS constraint violations by 93% during real-time operations.

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arXiv2023

Computation of Ultra-Short-Term Prediction Intervals of the Power Prosumption in Active Distribution Networks

Microgrids and, in general, active distribution networks require ultra-short-term prediction, i.e., for sub-second time scales, for specific control decisions. Conventional forecasting methodologies are not effective at such time scales. To address this issue, we propose a non-parametric method for computing ultra short-term prediction intervals (PIs) of the power prosumption of generic electrical-distribution networks. The method groups historical observations into clusters according to the values of influential variables. It is applied either to the original or to the differentiated power-prosumption time series. The clusters are considered statistically representative pools of future realizations of power prosumption (or its derivative). They are used to determine empirical PDFs and, by extracting the quantiles, to deliver PIs for respective arbitrary confidence levels. The models are validated a posteriori by carrying out a performance analysis that uses experimentally observed power-prosumption for different building types, thus allowing the identification of the dominant model.

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arXiv2022

Stress-informed Control of Medium- and High-head Hydropower Plants to Reduce Penstock Fatigue

The displacement of conventional generation in favor of stochastic renewable requires increasing regulation duties from the remaining dispatchable resources. In high- and medium-head hydropower plants (HPPs), providing regulation services to the grid and frequently changing the plant's set-point causes water hammer, which engenders pressure and stress transients within the pressurized conduits, especially the penstock, damaging it in the long run. This paper proposes a model predictive control (MPC) that explicitly models the hydraulic transients within the penstock. It achieves to reduce the mechanical loads on the penstock wall, and, consequently, fatigue effectively. Thanks to a suitable linearization of the plant model, the optimization problem underlying the MPC scheme is convex and can be solved with off-the-shelf optimization libraries. The performance of the proposed controller is tested with numerical simulations on a 230MW medium-head HPP with Francis turbine providing primary frequency control. Simulation results show substantially reduced penstock fatigue, existing approaches outperformed, and problem resolution times compatible with real-time control requirements.

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arXiv2022

Model-less Robust Voltage Control in Active Distribution Networks using Sensitivity Coefficients Estimated from Measurements

Measurement-rich power distribution networks may enable distribution system operators (DSOs) to adopt model-less and measurement-based monitoring and control of distributed energy resources (DERs) for mitigating grid issues such as over/under voltages and lines congestions. However, measurement-based monitoring and control applications may lead to inaccurate control decisions due to measurement errors. In particular, estimation models relying on regression-based schemes result in significant errors in the estimates (e.g., nodal voltages) especially for measurement devices with high Instrument Transformer (IT) classes. The consequences are detrimental to control performance since this may lead to infeasible decisions. This work proposes a model-less robust voltage control accounting for the uncertainties of measurement-based estimated voltage sensitivity coefficients. The coefficients and their uncertainties are obtained using a recursive least squares (RLS)-based online estimation, updated whenever new measurements are available. This formulation is applied to control distributed controllable photovoltaic (PV) generation in a distribution network to restrict the voltage within prescribed limits. The proposed scheme is validated by simulating a CIGRE low-voltage system interfacing multiple controllable PV plants.

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arXiv2021

Model Predictive Control for a Medium-head Hydropower Plant Hybridized with Battery Energy Storage to Reduce Penstock Fatigue

A hybrid hydropower power plant is a conventional HydroPower Plant (HPP) augmented with a Battery Energy Storage System (BESS) to decrease the wear and tear of sensitive mechanical components and improve the reliability and regulation performance of the overall plant. A central task of controlling hybrid power plants is determining how the total power set-point should be split between the BESS and the hybridized unit (power set-point splitting) as a function of the operational objectives. This paper describes a Model Predictive Control (MPC) framework for hybrid medium- and high-head plants to determine the power set-point of the hydropower unit and the BESS. The splitting policy relies on an explicit formulation of the mechanical loads incurred by the HPP's penstock, which can be damaged due to fatigue when providing regulation services to the grid. By filtering out from the HPP's power set-point the components conducive to excess penstock fatigue and properly controlling the BESS, the proposed MPC is able to maintain the same level of regulation performance while significantly decreasing damages to the hydraulic conduits. A proof-of-concept by simulations is provided considering a 230 MW medium-head hydropower plant.

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arXiv2021

Optimal Planning of Single-Port and Multi-Port Charging Stations for Electric Vehicles in Medium Voltage Distribution Networks

This paper describes a method based on mixed-integer linear programming to cost-optimally locate and size chargers for electric vehicles (EVs) in distribution grids as a function of the driving demand. The problem accounts for the notion of single-port chargers (SPCs), where a charger can interface one EV maximum, and multi-port chargers (MPCs), where the same charger can interface multiple EVs. The advantage of MPCs is twofold. First, multiple ports allow arbitraging the charging among multiple vehicles without requiring the drivers to plug and unplug EVs. Second, the charger's power electronics is not sized for the total number of charging ports, enabling cost savings when the grid constraints are bottleneck of the problem. The proposed method can account for different charger typologies, such as slow and fast chargers, and model the drivers' flexibility of plugging and unplugging their EVs. Simulation results from a synthetic case study show that implementing MPCs is beneficial over both SPCs and drivers' flexibility in terms of total investments required for the charging infrastructure.

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arXiv2021

Performance Assessment of Linear Models of Hydropower Plants

This paper discusses linearized models of hydropower plants (HPPs). First, it reviews state-of-the-art models and discusses their non-linearities, then it proposes suitable linearization strategies for the plant head, discharge, and turbine torque. It is shown that neglecting the dependency of the hydroacoustic resistance on the discharge leads to a linear formulation of the hydraulic circuits model. For the turbine, a numerical linearization based on a first-order Taylor expansion is proposed. Model performance is evaluated for a medium- and a low-head HPP with a Francis and Kaplan turbine, respectively. Perspective applications of these linear models are in the context of efficient model predictive control of HPPs based on convex optimization.

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arXiv2020

Grid-aware Distributed Model Predictive Control of Heterogeneous Resources in a Distribution Network: Theory and Experimental Validation

In this paper, we propose and experimentally validate a scheduling and control framework for distributed energy resources (DERs) that achieves to track a day-ahead dispatch plan of a distribution network hosting controllable and stochastic heterogeneous resources while respecting the local grid constraints on nodal voltages and lines ampacities. The framework consists of two algorithmic layers. In the first one (day-ahead scheduling), we determine an aggregated dispatch plan. In the second layer (real-time control), a distributed model predictive control (MPC) determines the active and reactive power set-points of the DERs so that their aggregated contribution tracks the dispatch plan while obeying to DERs operational constraints as well as the grids ones. The proposed framework is experimentally validated on a real-scale microgrid that reproduces the network specifications of the CIGRE microgrid benchmark system.

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arXiv2020

Siting and Sizing of Energy Storage Systems: Towards a Unified Approach for Transmission and Distribution System Operators for Reserve Provision and Grid Support

This paper presents a method to determine the optimal location, energy capacity, and power rating of distributed battery energy storage systems at multiple voltage levels to accomplish grid control and reserve provision. We model operational scenarios at a one-hour resolution, where deviations of stochastic loads and renewable generation (modeled through scenarios) from a day-ahead unit commitment and violations of grid constraints are compensated by either dispatchable power plants (conventional reserves) or injections from battery energy storage systems. By plugging-in costs of conventional reserves and capital costs of converter power ratings and energy storage capacity, the model is able to derive requirements for storage deployment that achieve the technical-economical optimum of the problem. The method leverages an efficient linearized formulation of the grid constraints of both the HV (High Voltage) and MV (Medium Voltage) grids while still retaining fundamental modeling aspects of the power system (such as transmission losses, effect of reactive power, OLTC at the MV/HV interface, unideal efficiency of battery energy storage systems) and models of conventional generator. A proof-of-concept by simulations is provided with the IEEE 9-bus system coupled with the CIGRE' benchmark system for MV grids, realistic costs of power reserves, active power rating and energy capacity of batteries, and load and renewable generation profile from real measurements.

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arXiv2020

Hierarchical Demand Forecasting Benchmark for the Distribution Grid

We present a comparative study of different probabilistic forecasting techniques on the task of predicting the electrical load of secondary substations and cabinets located in a low voltage distribution grid, as well as their aggregated power profile. The methods are evaluated using standard KPIs for deterministic and probabilistic forecasts. We also compare the ability of different hierarchical techniques in improving the bottom level forecasters' performances. Both the raw and cleaned datasets, including meteorological data, are made publicly available to provide a standard benchmark for evaluating forecasting algorithms for demand-side management applications.

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arXiv2020

Optimal Provision of Concurrent Primary Frequency and Local Voltage Control from a BESS Considering Variable Capability Curves: Modelling and Experimental Assessment

This paper proposes a control method for battery energy storage systems (BESSs) to provide concurrent primary frequency and local voltage regulation services. The actual variable active and reactive power capability of the converter, along with the state-of-charge of the BESS, are jointly considered by the optimal operating point calculation process within the real-time operation. The controller optimizes the provision of grid services, considering the measured grid and battery statuses and predicting the battery DC voltage as a function of the current trajectory using a three-time-constant model (TTC). A computationally-efficient algorithm is proposed to solve the formulated optimal control problem. Experimental tests validate the proposed concepts and show the effectiveness of the employed control framework on a commercial utility-scale 720 kVA/560 kWh BESS.

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arXiv2018

Control of Battery Storage Systems for the Simultaneous Provision of Multiple Services

In this paper, we propose a control framework for a battery energy storage system to provide simultaneously multiple services to the electrical grid. The objective is to maximise the battery exploitation from these services in the presence of uncertainty (load, stochastic distributed generation, grid frequency). The framework is structured in two phases. In a period-ahead phase, we solve an optimization problem that allocates the battery power and energy budgets to the different services. In the subsequent real-time phase the control set-points for the deployment of such services are calculated separately and superimposed. The control framework is first formulated in a general way and then casted in the problem of providing dispatchability of a medium voltage feeder in conjunction to primary frequency control. The performance of the proposed framework are validated by simulations and real-scale experi- ments, performed with a grid-connected 560 kWh/720 kVA Li-ion battery energy storage system.

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