1.1k citations · 2.6k across the 8 of their papers we have counts for
8 papers
Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes
Sean Nassimiha, Peter Dudfield, Jack Kelly +2
Short-term forecasting of solar photovoltaic energy (PV) production is important for powerplant management. Ideally these forecasts are equipped with error bars, so that downstream…
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models
Eric Zelikman, Sharon Zhou, Jeremy Irvin +7
Advancing probabilistic solar forecasting methods is essential to supporting the integration of solar energy into the electricity grid. In this work, we develop a variety of state-…
Short-term prediction of photovoltaic power generation using Gaussian process regression
Yahya Al Lawati, Jack Kelly, Dan Stowell
Photovoltaic (PV) power is affected by weather conditions, making the power generated from the PV systems uncertain. Solving this problem would help improve the reliability and cos…
Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature
Jack Kelly, William Knottenbelt
We examine 12 studies on the efficacy of disaggregated energy feedback. The average electricity reduction across these studies is 4.5%. However, 4.5% may be a positively-biased est…
Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
Jack Kelly, William Knottenbelt
Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Recently, deep neural networks…
NILMTK: An Open Source Toolkit for Non-intrusive Load Monitoring
Nipun Batra, Jack Kelly, Oliver Parson +5
Non-intrusive load monitoring, or energy disaggregation, aims to separate household energy consumption data collected from a single point of measurement into appliance-level consum…