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Matti Lehtonen

Researcher at Aalto University

Publications -  770
Citations -  12827

Matti Lehtonen is an academic researcher from Aalto University. The author has contributed to research in topics: Fault (power engineering) & Computer science. The author has an hindex of 40, co-authored 694 publications receiving 8559 citations. Previous affiliations of Matti Lehtonen include Razi University & New York University.

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Proceedings ArticleDOI

Stochastic Assessment of Voltage Unbalance Mitigation by Home Battery System in Low Voltage Grid with Single-Phase Solar Power Generation

TL;DR: The mitigation possibilities of the VU caused by single-phase-connected photovoltaics (PV) are analysed with Tesla Powerwall 2 battery energy storage systems (BESS) added to the grid.
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Direct approach for optimal allocation of multiple capacitors in distribution systems using novel analytical closed-form expressions

TL;DR: Novel and efficient analytical closed-form expressions are proposed for the optimal allocation of multiple capacitors in distribution systems to maximize the total cost reduction (CR) while considering power losses.
Proceedings ArticleDOI

Modelling the daily energy consumption of escalators with various passenger volumes

TL;DR: In this article, the authors examined the dynamics of escalator energy consumption in different passenger volumes with a simulation model of an existing escalator pair installation, and the model segregated the energy consumption into components by operation mode and carried passenger mass.
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Design, Implementation and Simulation of Non-Intrusive Sensor for On-Line Condition Monitoring of MV Electrical Components

TL;DR: In this article, a high frequency prototype of Rogowski coil is designed in the laboratory and performance of its components (coil head, damping component, integrator and data acquisition system) is evaluated using practical and simulated environments.
Proceedings ArticleDOI

Minimization of queuing time of electric vehicles at a fast charging station

TL;DR: Simulation results show the relation between available network capacity, number of charging sockets at the charging station and the queuing time of EVs.