Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Kristen R. Schell"'
Autor:
Haolin Yang, Kristen R. Schell
Publikováno v:
International Journal of Electrical Power & Energy Systems, Vol 158, Iss , Pp 109975- (2024)
The primary contribution of this study is the proposal of an explainable deep-learning neural network (ATTnet) that employs an attention mechanism to achieve accurate electricity spot price forecasting and an explainable model pipeline. The concise,
Externí odkaz:
https://doaj.org/article/d9b1e52d9b2540c3ac16855abdfe95a0
Publikováno v:
Environmental Research Letters, Vol 19, Iss 10, p 104076 (2024)
Pre-empting the worst consequences of climate change requires both mitigation of emissions from the global energy system and carbon dioxide removal through negative emissions technologies. Despite their nascence, negative emissions technologies are b
Externí odkaz:
https://doaj.org/article/869c359ee4c041da955b8c4f6b29e805
Publikováno v:
Renewable Energy. 211:285-295
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a95d51f76a926493e153424e4915c2ef
https://doi.org/10.1016/j.renene.2023.04.146
https://doi.org/10.1016/j.renene.2023.04.146
Publikováno v:
International Journal of Forecasting. 38:300-320
Accurate probabilistic forecasting of wind power output is critical to maximizing network integration of this clean energy source. There is a large literature on temporal modeling of wind power forecasting, but considerably less work combining spatia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f7d8fb8cb91685295862c3d3a82d46b7
https://doi.org/10.1016/j.ijforecast.2021.05.013
https://doi.org/10.1016/j.ijforecast.2021.05.013
Publikováno v:
Environmental Research Letters, Vol 16, Iss 1, p 014036 (2020)
Most studies of deep decarbonization find that a diverse portfolio of low-carbon energy technologies will be required, including carbon capture and storage (CCS) that mitigates emissions from fossil fuel power plants and industrial sources. While man
Externí odkaz:
https://doaj.org/article/883ed1ef02864e9bac3c606ce9327615
Infomorphism: Urban Planning For Renewable Energy Integration Via Simulated Energy Exchange Networks
Publikováno v:
2022 Annual Modeling and Simulation Conference (ANNSIM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a787ab4a8fdb40b85b9d87463dc5c9e
https://doi.org/10.23919/annsim55834.2022.9859300
https://doi.org/10.23919/annsim55834.2022.9859300
Autor:
Haolin Yang, Kristen R. Schell
Publikováno v:
International Journal of Electrical Power & Energy Systems. 141:108092
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d111b85eaccbf3a6bf343c927494b3b2
https://doi.org/10.1016/j.ijepes.2022.108092
https://doi.org/10.1016/j.ijepes.2022.108092
Autor:
Haolin Yang, Kristen R. Schell
Publikováno v:
2020 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS).
Electricity price forecasting is critical to numerous tasks in the power system such as strategic bidding, generation scheduling, optimal scheduling of storage reserves and system analysis. Most existing price forecasting models focus on hourly predi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1e26a0aebf5ed28bd7890eee24e9a867
https://doi.org/10.1109/pmaps47429.2020.9183697
https://doi.org/10.1109/pmaps47429.2020.9183697
Autor:
Haolin Yang, Kristen R. Schell
Publikováno v:
Energy. 238:122052
A highly accurate electricity price prediction model is of the utmost importance for multiple power systems tasks, such as generation dispatch and bidding. Due to the liberalization of the electricity market, as well as high renewable penetration, th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::052a79d20ad31183ef3514cc97f55025
https://doi.org/10.1016/j.energy.2021.122052
https://doi.org/10.1016/j.energy.2021.122052
Publikováno v:
Electric Power Systems Research. 165:45-52
In this paper we bring together a stochastic mixed integer programming model for transmission network expansion planning, incorporating portfolios of real options to address the evolution in time of uncertain parameters, with the adjusted generalized
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0375c19ae86e3b5498400856b4e6e9b8
https://doi.org/10.1016/j.epsr.2018.07.037
https://doi.org/10.1016/j.epsr.2018.07.037