Matti Lehtonen

TL;DR: In this article, a Monte Carlo simulation based statistical methodology is presented to analyze photovoltaic generation scenarios comprising new generation locations without measured data from those locations, which is able to assess the spatial and temporal correlations between the generation locations in geographical areas of varying size and amount of installed PV generation.

TL;DR: This paper presents an adaptive autonomy methodology that is based on an extension of a well-known human-automation interaction model, as well as the expert judgment technique and the performance shaping factors concept, implemented to a power distribution automation system.

TL;DR: An optimal probabilistic approach to optimally host high penetrations of PV units considering their stochastic nature is proposed and it provides wider planning options since it optimizes the interfacing inverter oversize with smart watt-var functionalities.

TL;DR: A stochastic model is proposed with the goal of optimally using proactive operational actions before the upcoming disturbance hits to take the effective actions and simulates probable damages caused by the events via a set of scenarios generated by Monte Carlo simulation method.

TL;DR: In this paper, the initial transients due to arc reignitions associated with high impedance faults caused by leaning trees are extracted using discrete wavelet transform (DWT), in which the fault occurrence is localized.