no code implementations • 2 Apr 2024 • Rob Geada, David Towers, Matthew Forshaw, Amir Atapour-Abarghouei, A. Stephen McGough
The boundless possibility of neural networks which can be used to solve a problem -- each with different performance -- leads to a situation where a Deep Learning expert is required to identify the best neural network.
no code implementations • 1 Mar 2024 • Fulong Yao, Wanqing Zhao, Matthew Forshaw, Yang song
The global energy landscape is undergoing a transformation towards decarbonization, sustainability, and cost-efficiency.
no code implementations • 27 Feb 2023 • Mehmet Cengiz, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough
Existing approaches to understanding the performance of hardware largely focus around benchmarking -- leveraging standardised workloads which seek to be representative of an end-user's needs.
no code implementations • 14 Sep 2022 • Andrew Stephen McGough, Matthew Forshaw
We show, through simulation, that we can save 34% of the energy consumption using RL compared to a fixed number of replicas with only a 4% decrease in workflows achieving a pre-defined overhead bound.
1 code implementation • 11 Jul 2022 • David Towers, Matthew Forshaw, Amir Atapour-Abarghouei, Andrew Stephen McGough
It is a sad reflection of modern academia that code is often ignored after publication -- there is no academic 'kudos' for bug fixes / maintenance.
no code implementations • 5 Jun 2022 • Alexander J. M. Kell, Stephen McGough, Matthew Forshaw
However, the electricity market is made up of many different variables and data inputs.
no code implementations • 10 Sep 2021 • Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw
A lowering in the cost of batteries and solar PV systems has led to a high uptake of solar battery home systems.
no code implementations • 7 Mar 2021 • Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw
Through the prediction of electricity demand profile over the next 24h, we can simulate the predictions made for a day-ahead market.
no code implementations • 8 Nov 2020 • Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough
If any single generator company, or a collaborating group of generator companies, control more than ${\sim}$11$\%$ of generation capacity and bid strategically, prices begin to increase by ${\sim}$25$\%$.
no code implementations • 2 Nov 2020 • Alexander J. M. Kell, Pablo Salas, Jean-Francois Mercure, Matthew Forshaw, A. Stephen McGough
A change from a high-carbon emitting electricity power system to one based on renewables would aid in the mitigation of climate change.
no code implementations • 28 May 2020 • Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw
A way to achieve this is to decarbonize the electricity grid.
no code implementations • 6 Oct 2019 • Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough
A Pareto frontier can be used to identify the sets of optimal parameters for which each is the `best' for a given combination of objectives -- thus allowing decisions to be made with full knowledge.
no code implementations • 19 Oct 2018 • A. Stephen McGough, Matthew Forshaw, John Brennan, Noura Al Moubayed, Stephen Bonner
We demonstrate, through the use of simulation, how we can reduce this wasted energy by targeting tasks at computers less likely to be needed for primary use, predicting this idle time through machine learning.