| Segmenting residential smart meter data for short-term load forecasting A Kell, AS McGough, M Forshaw Proceedings of the ninth international conference on future energy systems …, 2018 | 45 | 2018 |
| Energy and Flexibility Modelling. Release Version 1.0 [online course]. Climate Compatible Growth Programme and the International Renewable Energy Agency L Allington, C Cannone, P Hooseinpoori, A Kell, E Taibi, C Fernandez, ... | 38 | 2021 |
| MUSE: An open-source agent-based integrated assessment modelling framework S Giarola, J Sachs, M d’Avezac, A Kell, A Hawkes Energy Strategy Reviews 44, 100964, 2022 | 32 | 2022 |
| A comparison of age slicing and statistical age estimation for Mediterranean Swordfish (Xiphias gladius) LT Kell, A Kell Collect. Vol. Sci. Pap. ICCAT 66 (4), 1522-1534, 2011 | 23 | 2011 |
| Energy and Flexibility Modelling L Allington, C Cannone, P Hooseinpoori, A Kell, E Taibi, C Fernandez, ... Release Version 1, 2021 | 20 | 2021 |
| clicSAND for OSeMOSYS: a user-friendly interface using open-source optimisation software for energy system modelling analysis C Cannone, L Allington, N de Wet, A Shivakumar, P Goyns, C Valderrama, ... Energies 17 (16), 3923, 2024 | 19 | 2024 |
| Long-Term Electricity Market Agent Based Model Validation Using Genetic Algorithm Based Optimization AJM Kell, M Forshaw, AS McGough Proceedings of the Eleventh ACM International Conference on Future Energy …, 2020 | 17 | 2020 |
| ElecSim: Monte-carlo open-source agent-based model to inform policy for long-term electricity planning A Kell, M Forshaw, AS McGough Proceedings of the Tenth ACM International Conference on Future Energy …, 2019 | 17 | 2019 |
| A systematic literature review on machine learning for electricity market agent-based models AJM Kell, AS McGough, M Forshaw 2022 IEEE International Conference on Big Data (Big Data), 4503-4512, 2022 | 15 | 2022 |
| Machine learning applications for electricity market agent-based models: A systematic literature review AJM Kell, S McGough, M Forshaw arXiv preprint arXiv:2206.02196, 2022 | 14* | 2022 |
| The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets AJM Kell, AS McGough, M Forshaw Sustainable Computing: Informatics and Systems 30, 100532, 2021 | 13 | 2021 |
| Exploring market power using deep reinforcement learning for intelligent bidding strategies AJM Kell, M Forshaw, AS McGough The 4th IEEE International Workshop on Big Data for Financial News and Data …, 2020 | 12 | 2020 |
| Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning AJM Kell, AS McGough, M Forshaw 2022 IEEE International Conference on Big Data (Big Data), 4495-4502, 2022 | 9 | 2022 |
| Sustainability Education: Capacity Building Using the MUSE Model S Giarola, A Kell, S Sechi, M Carboni, A Dall-Orsoletta, P Leone, ... Energies 16 (14), 5500, 2023 | 6 | 2023 |
| clicSANDMac for OSeMOSYS: a user-friendly interface for macOS users using open-source optimisation software for energy system planning C Cannone, N de Wet, A Shivakumar, A Kell, N Tan, R Yeganyan, LS To, ... | 6 | 2022 |
| Optimising energy and overhead for large parameter space simulations AJM Kell, M Forshaw, AS McGough 2019 Tenth International Green and Sustainable Computing Conference (IGSC), 1-8, 2019 | 3 | 2019 |
| Modelling carbon tax in the UK electricity market using an agent-based model A Kell, M Forshaw, AS McGough Proceedings of the Tenth ACM International Conference on Future Energy …, 2019 | 3 | 2019 |
| Optimizing carbon tax for decentralized electricity markets using an agent-based model AJM Kell, AS McGough, M Forshaw Proceedings of the Eleventh ACM International Conference on Future Energy …, 2020 | 2 | 2020 |
| Modelling the transition to a low-carbon energy supply AJM Kell Newcastle University, 2021 | 1 | 2021 |
| Deep Reinforcement Learning in Electricity Generation Investment for the Minimization of Long-Term Carbon Emissions and Electricity Costs AJM Kell, P Salas, JF Mercure, M Forshaw, AS McGough NeurIPS 2020 Workshop Tackling Climate Change with Machine Learning, 2020 | 1 | 2020 |
Matthew ForshawReader in Data Science, Newcastle University, and Senior Advisor, The Alan Turing InstituteVerified email at ncl.ac.uk
