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3. Predicting popularity of EV charging infrastructure from GIS data

Author

Straka, Milan, De Falco, Pasquale, Ferruzzi, Gabriella, Proto, Daniela, van der Poel, Gijs, Khormali, Shahab, and Buzna, Ľuboš

Subjects
Statistics - Applications, Computer Science - Machine Learning, Economics - Econometrics
Abstract

The availability of charging infrastructure is essential for large-scale adoption of electric vehicles (EV). Charging patterns and the utilization of infrastructure have consequences not only for the energy demand, loading local power grids but influence the economic returns, parking policies and further adoption of EVs. We develop a data-driven approach that is exploiting predictors compiled from GIS data describing the urban context and urban activities near charging infrastructure to explore correlations with a comprehensive set of indicators measuring the performance of charging infrastructure. The best fit was identified for the size of the unique group of visitors (popularity) attracted by the charging infrastructure. Consecutively, charging infrastructure is ranked by popularity. The question of whether or not a given charging spot belongs to the top tier is posed as a binary classification problem and predictive performance of logistic regression regularized with an l-1 penalty, random forests and gradient boosted regression trees is evaluated. Obtained results indicate that the collected predictors contain information that can be used to predict the popularity of charging infrastructure. The significance of predictors and how they are linked with the popularity are explored as well. The proposed methodology can be used to inform charging infrastructure deployment strategies.

Published
2019
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7. Local Energy Community to Support Hydrogen Production and Network Flexibility.

Author

Ferrara, Massimiliano, Mottola, Fabio, Proto, Daniela, Ricca, Antonio, and Valenti, Maria

Subjects
BATTERY storage plants, GREEN fuels, ELECTRIC power distribution grids, POWER resources, RENEWABLE energy sources
Abstract

This paper deals with the optimal scheduling of the resources of a renewable energy community, whose coordination is aimed at providing flexibility services to the electrical distribution network. The available resources are renewable generation units, battery energy storage systems, dispatchable loads, and power-to-hydrogen systems. The main purposes behind the proposed strategy are enhancement of self-consumption and hydrogen production from local resources and the maximization of the economic benefits derived from both the selling of hydrogen and the subsidies given to the community for the shared energy. The proposed approach is formulated as an economic problem accounting for the perspectives of both community members and the distribution system operator. In more detail, a mixed-integer constrained non-linear optimization problem is formulated. Technical constraints related to the resources and the power flows in the electrical grid are considered. Numerical applications allow for verifying the effectiveness of the procedure. The results show that it is possible to increase self-consumption and the production of green hydrogen while providing flexibility services through the exploitation of community resources in terms of active and reactive power support. More specifically, the application of the proposed strategy to different case studies showed that daily revenues of up to EUR 1000 for each MW of renewable energy generation installed can be obtained. This value includes the benefit obtained thanks to the provision of flexibility services, which contribute about 58% of the total. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Real-Time Distribution Grid Control and Flexibility Provision under Uncertainties: Laboratory Demonstration

Author

Rayati, Mohammad, Bozorg, Mokhtar, Carpita, Mauro, De Falco, Pasquale, Caramia, Pierluigi, Bracale, Antonio, Proto, Daniela, Mottola, Fabio, Rayati, M., Bozorg, M., Carpita, M., Falco, P. D., Caramia, P., Bracale, A., Proto, D., and Mottola, F.

Subjects
Active distribution grids, photovoltaic (PV) systems, Active distribution grid, flexibility provision, Active distribution grids, flexibility provision, photovoltaic (PV) systems, laboratory demonstration, uncertainties, uncertainties, photovoltaic (PV) system, laboratory demonstration
Abstract

In this paper, we assess the effectiveness of forecasting and optimization algorithms on a laboratory demonstration platform that mimics a domestic distribution grid with a high penetration of photovoltaic (PV) systems. Despite the uncertainties, the considered algorithms ensure efficient and secure real-time (RT) operation of the distribution grid, as well as the provision of flexibility services from the low-voltage (LV) distribution grid to the upstream medium-voltage (MV) grid. Uncertainties arise from the variations in PV systems power production and end-users' power consumption, as well as RT deployment of flexibility services. As a result of the considered algorithms, the distribution grid becomes active in the provision of flexibility services. The forecasting and optimization algorithms are based on Bayesian bootstrap quantile regression (BBQR) and distributionally robust chance-constrained (DRCC) programming, respectively. This paper also evaluates the framework of the laboratory demonstration platform for the deployment of the considered algorithms.

Published
2022

27. Surge arrester optimal placement in distribution networks: A decision theory-based approach.

Author

Ravichandran, Nagananthini, Proto, Daniela, and Andreotti, Amedeo

Subjects
*RADIAL distribution function, *LIGHTNING protection, *OPTIMIZATION algorithms, *OVERVOLTAGE, *DECISION making, *DECISION theory, *FLASHOVER, *VOLTAGE regulators
Abstract

The study introduces a novel method for optimizing surge arrester placement in the distribution line to mitigate lightning-induced overvoltages, employing a single-objective optimization algorithm. The study assesses the effectiveness of two types of surge arresters concerning discharge energy in reducing lightning overvoltage. Moreover, the comparative analysis takes into account the transfer of overvoltage performance from protected to unprotected towers, highlighting its significance in estimating flashover rates under different protection alternatives. Decision theory analysis is employed in the present study to identify optimal arrester locations. The study aims to minimize the expected flashover rate and identify the most effective protection strategy by considering futures/scenarios associated with different values of peak current and lightning locations. The results of numerical applications also showed the substantial impact of lightning surge transfer within the network, emphasizing the imperative to incorporate this phenomenon into lightning protection modelling. • Focuses on indirect lightning protection for medium-voltage networks. • Analyses common surge arrester types for network protection. • Studied transfer voltage effects on adjacent towers. • Studies transfer voltage effects on adjacent towers. • Evaluates effectiveness of combining surge arresters and overhead shieldwire. • Considers optimal surge arrester placement using decision theory for cost-effectiveness. [ABSTRACT FROM AUTHOR]

Published
2024
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39. On the comparison between ensemble Kalman filter and Kalman filter for the dynamic harmonic state estimation in a hybrid microgrid

Author

CARPINELLI, GUIDO, PROTO, DANIELA, Caramia, P., ALFIERI, LUISA, SPEEDAM, Carpinelli, Guido, Proto, Daniela, Caramia, P., and Alfieri, Luisa

Subjects
Dynamic harmonic state estimation, Ensemble Kalman Filter, Kalman Filter, Microgrid, Waveform distortions
Abstract

The management of micro grids requires the dynamic harmonic state estimation of the system in order to perform control strategies that optimize waveform distortions. In industrial context, AC and DC devices and sources coexist and, therefore, micro grids can be a hybrid combination of AC and DC power sections. Also for such hybrid AC/DC micro grids optimal control strategies that optimize waveform distortions are mandatory. In this paper, the comparison of two different methods for the dynamic harmonic state estimation of hybrid AC/DC micro grids is performed analyzing both theoretical and numerical aspects. In particular, the Kalman Filter- and Ensemble Kalman Filter-based dynamic harmonic state estimations are compared in terms of accuracy and computational efforts. The numerical applications were performed on a hybrid AC/DC μG proposed for an actual industrial facility in southern Italy.

Published
2016

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