Reinforcement learning and its applications in modern power and energy systems: A review
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …
other emerging technologies, there are increasing complexities and uncertainties for …
Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market–A state-of-the-art review
The electricity market has since 1980s been gradually evolving from a monopoly market into
a liberalized one for encouraging competition and improving efficiency. This brings the …
a liberalized one for encouraging competition and improving efficiency. This brings the …
Multi-period and multi-spatial equilibrium analysis in imperfect electricity markets: A novel multi-agent deep reinforcement learning approach
Previously works on analysing imperfect electricity markets have employed conventional
game-theoretic approaches. However, such approaches necessitate that each strategic …
game-theoretic approaches. However, such approaches necessitate that each strategic …
Bidding strategy for trading wind energy and purchasing reserve of wind power producer–A DRL based approach
Wind power producers (WPP) are punished when take part in the short-term electricity
market due to the inaccuracy of wind power prediction. The profit loss can be partially offset …
market due to the inaccuracy of wind power prediction. The profit loss can be partially offset …
Agent based simulation of centralized electricity transaction market using bi-level and Q-learning algorithm approach
E Namalomba, H Feihu, H Shi - International journal of electrical power & …, 2022 - Elsevier
The market participants face risks in market price fluctuations and uncertainties in the
demand behaviour, regardless of the series of restructuring reforms of China power industry …
demand behaviour, regardless of the series of restructuring reforms of China power industry …
Putting renewable energy auctions into action–An agent-based model of onshore wind power auctions in Germany
V Anatolitis, M Welisch - Energy Policy, 2017 - Elsevier
The following analysis looks into auctions for renewable energy, specifically onshore wind
power in Germany. Following an agent-based modeling approach, the two most commonly …
power in Germany. Following an agent-based modeling approach, the two most commonly …
An Adaptive -Learning Algorithm Developed for Agent-Based Computational Modeling of Electricity Market
M Rahimiyan, HR Mashhadi - IEEE Transactions on Systems …, 2010 - ieeexplore.ieee.org
Balancing between exploration and exploitation with adaptation of the Q-learning (QL)
parameters to the condition of dynamic uncertain environment has always been a significant …
parameters to the condition of dynamic uncertain environment has always been a significant …
Research on bidding strategy of thermal power companies in electricity market based on multi-agent deep deterministic policy gradient
D Liu, Y Gao, W Wang, Z Dong - IEEE access, 2021 - ieeexplore.ieee.org
With the continuous improvement of new energy penetration in the power system, the price
of the spot market of power frequently fluctuates greatly, which damages the income of a …
of the spot market of power frequently fluctuates greatly, which damages the income of a …
A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market
This paper considers a price-taker generation station producer that participates in a day-
ahead market. The producer behaves as a price-taker participant in the day-ahead electricity …
ahead market. The producer behaves as a price-taker participant in the day-ahead electricity …
Comprehensive survey on support policies and optimal market participation of renewable energy
Energy demand in the world is mostly met by conventional sources that cause carbon
emissions. Considering environmental problems and the depletion of these sources in the …
emissions. Considering environmental problems and the depletion of these sources in the …