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ORCIDAlexander J. M. Kell
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- affiliation: Newcastle University, UK
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2020 – today
- 2022
[c9]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning. IEEE Big Data 2022: 4495-4502- [c8]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
A systematic literature review on machine learning for electricity market agent-based models. IEEE Big Data 2022: 4503-4512 - [i9]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Machine learning applications for electricity market agent-based models: A systematic literature review. CoRR abs/2206.02196 (2022) - 2021
- [j1]Alexander J. M. Kell
, A. Stephen McGough, Matthew Forshaw:
The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets. Sustain. Comput. Informatics Syst. 30: 100532 (2021) - [i8]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
The impact of online machine-learning methods on long-term investment decisions and generator utilization in electricity markets. CoRR abs/2103.04327 (2021) - [i7]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Optimizing a domestic battery and solar photovoltaic system with deep reinforcement learning. CoRR abs/2109.05024 (2021) - [i6]Alexander J. M. Kell:
Modelling the transition to a low-carbon energy supply. CoRR abs/2111.00987 (2021) - 2020
- [c7]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Exploring market power using deep reinforcement learning for intelligent bidding strategies. IEEE BigData 2020: 4402-4411 - [c6]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Long-term electricity market agent based model validation using genetic algorithm based optimization. e-Energy 2020: 1-13 - [c5]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Optimizing carbon tax for decentralized electricity markets using an agent-based model. e-Energy 2020: 454-460 - [i5]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Long-term electricity market agent based model validation using genetic algorithm based optimization. CoRR abs/2005.10346 (2020) - [i4]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Optimizing carbon tax for decentralized electricity markets using an agent-based model. CoRR abs/2006.01601 (2020) - [i3]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Exploring market power using deep reinforcement learning for intelligent bidding strategies. CoRR abs/2011.04079 (2020)
2010 – 2019
- 2019
- [c4]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Modelling Carbon Tax in the UK Electricity Market using an Agent-Based Model. e-Energy 2019: 425-427 - [c3]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning. e-Energy 2019: 556-565 - [c2]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Optimising energy and overhead for large parameter space simulations. IGSC 2019: 1-8 - [i2]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
Optimising energy and overhead for large parameter space simulations. CoRR abs/1910.02516 (2019) - [i1]Alexander J. M. Kell, Matthew Forshaw, A. Stephen McGough:
ElecSim: Monte-Carlo Open-Source Agent-Based Model to Inform Policy for Long-Term Electricity Planning. CoRR abs/1911.01203 (2019) - 2018
- [c1]Alexander J. M. Kell, A. Stephen McGough, Matthew Forshaw:
Segmenting Residential Smart Meter Data for Short-Term Load Forecasting. e-Energy 2018: 91-96
Coauthor Index
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