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Machine learning and deep learning prediction models for time-series: a comparative analytical study for the use case of the UK short-term electricity price prediction

Autor: Bhupesh Kumar Mishra, Vjosa Preniqi, Dhavalkumar Thakker, Erich Feigl

Publikováno v: Discover Internet of Things, Vol 4, Iss 1, Pp 1-22 (2024)

Abstract Electricity price prediction has an imperative role in the UK energy market among energy trading organisations. The price prediction directly impacts organisational policy for profitable electricity trading, better bidding plans, and the opt

Externí odkaz: https://doaj.org/article/bcf86429905e4ff9bbc4ded1fb7b269f

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Comparative Study of Shortterm Electricity Price Forecasting Models to Optimise Battery Consumption

Autor: Geev Mokryani, Amr Abdullatif, Bhupesh Kumar Mishra, Vjosa Preniqi, Erich Feigl, Dhavalkumar Thakker, Savas Konur

Publikováno v: iThings/GreenCom/CPSCom/SmartData/Cybermatics

Electricity price prediction has been crucial for network operators in the UK energy market. There has been a need for effective and accurate electricity price prediction model which will help in optimisation of energy storage devices, and better bid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::709a1be23e3906c6664f3ea530d403d6
https://doi.org/10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00069

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