[HTML][HTML] Artificial intelligence for electricity supply chain automation
Abstract The Electricity Supply Chain is a system of enabling procedures to optimize
processes ranging from production to transportation and consumption of electricity. The …
processes ranging from production to transportation and consumption of electricity. The …
[HTML][HTML] Research areas and methods of interest in European intraday electricity market research—A systematic literature review
D Birkeland, T AlSkaif - Sustainable Energy, Grids and Networks, 2024 - Elsevier
This paper establishes a robust foundation for the expansion of European intraday electricity
market research through a systematic literature review. The review encompasses 132 …
market research through a systematic literature review. The review encompasses 132 …
Reinforcement Learning-Based Bi-Level strategic bidding model of Gas-fired unit in integrated electricity and natural gas markets preventing market manipulation
Due to its efficient operation and environment-friendly characteristic, gas-fired unit (GFU)
plays a more and more important role in electric power systems and natural gas systems. To …
plays a more and more important role in electric power systems and natural gas systems. To …
[HTML][HTML] Fit for purpose: Modeling wholesale electricity markets realistically with multi-agent deep reinforcement learning
Electricity markets need to continuously evolve to address the growing complexity of a
predominantly renewable energy-driven, highly interconnected, and sector-integrated …
predominantly renewable energy-driven, highly interconnected, and sector-integrated …
Development of PMU-based transient stability detection methods using CNN-LSTM considering time series data measurement
The development of electric power systems has become more complex. Consequently,
electric power systems are operating closer to their limits and are more susceptible to …
electric power systems are operating closer to their limits and are more susceptible to …
Operational optimization for the grid-connected residential photovoltaic-battery system using model-based reinforcement learning
The development of distributed photovoltaic and energy storage devices has created
challenges for energy management systems due to uncertainty and mismatch between local …
challenges for energy management systems due to uncertainty and mismatch between local …
The emerging threat of artificial intelligence on competition in liberalized electricity markets: A deep Q-network approach
DE Aliabadi, K Chan - Applied energy, 2022 - Elsevier
Abstract According to Sustainable Development Goals (SDGs), societies should have
access to affordable, reliable, and sustainable energy. Liberalized electricity markets have …
access to affordable, reliable, and sustainable energy. Liberalized electricity markets have …
Reinforcement learning in wind energy-a review
VL Narayanan - International Journal of Green Energy, 2023 - Taylor & Francis
Today's environmental concerns, particularly those related to global warming, have sparked
a drive for the usage of renewable energy sources. One of the most significant sources of …
a drive for the usage of renewable energy sources. One of the most significant sources of …
Analysis of green closed-loop supply chain efficiency under generalized stochastic petri nets
L Liu, Y Pu, Z Liu, J Liu - Sustainability, 2023 - mdpi.com
In this paper, we aim to explore the operational performance of a green closed-loop supply
chain under random events. A green closed-loop supply chain model based on generalized …
chain under random events. A green closed-loop supply chain model based on generalized …
The competition and equilibrium in power markets under decarbonization and decentralization
Equilibrium analysis has been widely studied as an effective tool to model gaming
interactions and predict market results. However, as competition modes are fundamentally …
interactions and predict market results. However, as competition modes are fundamentally …