Neuville Grid Data™ is developing ground-breaking, high-resolution, Big Data, grid power monitoring networks that collect electrical measurements using innovative instrumentation featuring newly devised micro-synchrophasors (µPMU), power quality monitors, and sub-100 nanosecond timing plus a groundbreaking advance in time-series data management..
Resulting capability can scrutinize the behaviour of electricity networks and condition monitor equipment at a level of detail, clarity, and sophistication never achieved before.
Innovative Step-Change Improvement, Disruptive Potential, Low-Cost.
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05 Sep 2020 – The US is approaching a crosspoint of trends as declining coal is surpassed by rising renewables providing 20% of US electric power production in 2020 according to US EIA estimates.
02 Sep 2020 – Neuville’s Maitreyee Dey PhD and Clarke Simmons have been invited to present their paper, High-resolution data-driven anomalous event detection from solar farm data using clustering large applications based upon randomized search D-034 at the CUE2020 Applied Energy Symposium: Low Carbon Cities and Urban Energy Systems 10-17 Oct 2020 in Tokyo/Virtual Conference.
01 Sep 2020 – (Paris) At the CIGRE 2020 e-Session, Neuville’s Data Mining Lead Maitreyee Dey PhD and Managing Director Clarke Simmons MSc, made a short presentation on their technical paper, High-Resolution Condition Monitoring of Transformers at UK Solar Farms Using Micro-Synchrophasors A2-104. The full paper will be published in the CIGRE conference proceedings.
01 Jul 2020 – (London) Maitreyee Dey PhD has joined the Neuville team as its Data Mining Lead. She brings a wealth of experience and skill with machine learning artificial intelligence (AI) processing of electrical system big data.
30 Jun 2020 – (London) Again working with London South Bank University’s School of Engineering, Neuville has been selected to receive £28,429 (€31,056). in funding support from the Low Carbon London (LCLDN) programme which is part-financed by the European Union’s European Regional Development Fund (ERDF). The funds will be applied toward a PhD level applied development position investigating artificial intelligence machine learning analysis of high-resolution electrical data.