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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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MAS-Based Modeling of Active Distribution Network: The Simulation of Emerging Behaviors

TL;DR: A multi-agent system-based modeling of an active distribution network is presented using cooperative agents and a method to solve a network-wise objective of state estimation is explained with the proposed model.
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Verification of DWT-Based Detection of High Impedance Faults in MV Networks

TL;DR: In this article, the authors used the Discrete Wavelet Transform (DWT) detail coefficients of residual voltages to detect the presence of leaning trees in Nordic distribution networks, but the fault cases are not associated with arcs and the transients are only generated at the starting fault instant without repetition.
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Criticality Analysis of Failure to Communicate in Automated Fault-Management Schemes

TL;DR: In this article, the reliability impact of failure to communicate in the automated fault management schemes (AFMSs) is quantitatively evaluated in a highly loaded urban distribution network equipped with AFMS.
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Experimental Investigations on Multi-end Fault Location System based on Current Traveling Waves

TL;DR: In this paper, the minimum travel time of the traveling wave has been calculated considering Dijkstra algorithm to select the nearest TWR to the faulted line, where the wavelet transform is used to find the highest spectral energy of the frequency band of traveling wave signals.
Proceedings ArticleDOI

A framework for activating residential HVAC demand response for wind generation balancing

TL;DR: In this article, a centralized framework focusing on realization of domestic heating, ventilation, and air conditioning (HVAC) demand response capability for wind power balancing is developed, where thermal comfort penalty is explicitly integrated in the objective function in order to oblige different customers' thermal preferences.