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Pierluigi Mancarella

Researcher at University of Melbourne

Publications -  322
Citations -  14581

Pierluigi Mancarella is an academic researcher from University of Melbourne. The author has contributed to research in topics: Demand response & Electric power system. The author has an hindex of 51, co-authored 303 publications receiving 10667 citations. Previous affiliations of Pierluigi Mancarella include University of Manchester & Polytechnic University of Turin.

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MES (multi-energy systems): An overview of concepts and evaluation models

TL;DR: In this paper, the authors provide a comprehensive and critical overview of the latest models and assessment techniques that are currently available to analyze MES and in particular DMG systems, including for instance energy hubs, microgrids, and VPPs (virtual power plants), as well as various approaches and criteria for energy, environmental, and technoeconomic assessment.
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Distributed multi-generation: A comprehensive view

TL;DR: In this paper, the authors present the main aspects of the DMG framework, illustrating its characteristics and summarizing the relevant DMG structures, backed by an extended review of the most recent journal publications and reports.
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Influence of extreme weather and climate change on the resilience of power systems: Impacts and possible mitigation strategies

TL;DR: A comprehensive modelling research framework is outlined, which can help understand and model the impact of extreme weather on power systems and how this can be prevented or mitigated in the future.
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The Grid: Stronger, Bigger, Smarter?: Presenting a Conceptual Framework of Power System Resilience

TL;DR: In this paper, a conceptual framework of power system resilience, its key features, and potential enhancement measures is discussed, with a focus on the resilience of critical power infrastructures to high-impact, low-probability events.
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Metrics and Quantification of Operational and Infrastructure Resilience in Power Systems

TL;DR: In this article, the resilience trapezoid is defined and quantified using time-dependent resilience metrics that are specifically introduced to help capture the critical system degradation and recovery features associated to the trapezoids for different temporal phases of an event.