[HTML][HTML] A comprehensive review of artificial intelligence approaches for smart grid integration and optimization
Technological advancements, urbanization, high energy demand, and global requirements
to mitigate carbon footprints have led to the adoption of innovative green technologies for …
to mitigate carbon footprints have led to the adoption of innovative green technologies for …
[HTML][HTML] Power market models for the clean energy transition: State of the art and future research needs
As power systems around the world are rapidly evolving to achieve decarbonization
objectives, it is crucial that power system planners and operators use appropriate models …
objectives, it is crucial that power system planners and operators use appropriate models …
Reinforcement learning-based optimization for power scheduling in a renewable energy connected grid
AS Ebrie, YJ Kim - Renewable Energy, 2024 - Elsevier
Power scheduling is an NP-hard optimization problem that demands a delicate equilibrium
between economic costs and environmental emissions. In response to the growing concern …
between economic costs and environmental emissions. In response to the growing concern …
基于深度强化学习的新型电力系统调度优化方法综述
冯斌， 胡轶婕， 黄刚， 姜威， 徐华廷， 郭创新 - 电力系统自动化, 2023 - epjournal.csee.org.cn
随着新能源并网规模不断扩大, 能源形式更加灵活多变, 电力系统调度运行面临新的挑战.
随着系统复杂度和不确定性增加, 传统基于物理模型的优化方法难以建立精确的模型进行实时 …
随着系统复杂度和不确定性增加, 传统基于物理模型的优化方法难以建立精确的模型进行实时 …
Conformal asymmetric multi-quantile generative transformer for day-ahead wind power interval prediction
W Wang, B Feng, G Huang, C Guo, W Liao, Z Chen - Applied Energy, 2023 - Elsevier
With the rapid increase in the installed capacity of wind power, day-ahead wind power
interval prediction is becoming more and more important. To solve such a challenging …
interval prediction is becoming more and more important. To solve such a challenging …
A novel gradient based optimizer for solving unit commitment problem
Secure and economic operation of the power system is one of the prime concerns for the
engineers of 21st century. Unit Commitment (UC) represents an enhancement problem for …
engineers of 21st century. Unit Commitment (UC) represents an enhancement problem for …
A new power system active rescheduling method considering the dispatchable plug-in electric vehicles and intermittent renewable energies
The significant penetration of renewable power generations (RGs) and the large-scale use
of plug-in electric vehicles (PEVs) have brought tangible impacts in tackling the climate …
of plug-in electric vehicles (PEVs) have brought tangible impacts in tackling the climate …
An effective strategy for unit commitment of microgrid power systems integrated with renewable energy sources including effects of battery degradation and …
P Manoharan, K Chandrasekaran, R Chandran… - … Science and Pollution …, 2024 - Springer
The large use of renewable sources and plug-in electric vehicles (PEVs) would play a
critical part in achieving a low-carbon energy source and reducing greenhouse gas …
critical part in achieving a low-carbon energy source and reducing greenhouse gas …
[HTML][HTML] Reinforcement learning and A* search for the unit commitment problem
P de Mars, A O'Sullivan - Energy and AI, 2022 - Elsevier
Previous research has combined model-free reinforcement learning with model-based tree
search methods to solve the unit commitment problem with stochastic demand and …
search methods to solve the unit commitment problem with stochastic demand and …
Unit commitment problem for transmission system, models and approaches: A review
The realistic power systems include several types of controllers in transmission lines,
different types of energy storage systems (ESSs), and integration of various renewable …
different types of energy storage systems (ESSs), and integration of various renewable …