Classification of distribution power grid structures using inception v3 deep neural network
To maintain the supply of electrical energy, it is necessary that failures in the distribution grid
are identified during inspections of the electrical power system before shutdowns occur. To …
are identified during inspections of the electrical power system before shutdowns occur. To …
A physics-guided graph convolution neural network for optimal power flow
The data-driven method with strong approximation capabilities and high computational
efficiency provides a promising tool for optimal power flow (OPF) calculation with stochastic …
efficiency provides a promising tool for optimal power flow (OPF) calculation with stochastic …
A dual-driven linear modeling approach for multiple energy flow calculation in electricity–heat system
The multiple energy flow (MEF) model is inherently nonlinear, which challenges the fast
steady-state analysis and the efficient optimization of the integrated energy system (IES) …
steady-state analysis and the efficient optimization of the integrated energy system (IES) …
Review of learning-assisted power system optimization
With dramatic breakthroughs in recent years, machine learning is showing great potential to
upgrade the toolbox for power system optimization. Understanding the strength and …
upgrade the toolbox for power system optimization. Understanding the strength and …
Hybrid-timescale optimal dispatch strategy for electricity and heat integrated energy system considering integrated demand response
Z Chong, L Yang, Y Jiang, W Zhou - Renewable Energy, 2024 - Elsevier
An integrated energy system realizes multi-energy management and multi-load integrated
supplement. However, because of the uncertainties of the renewable energy and loads and …
supplement. However, because of the uncertainties of the renewable energy and loads and …
Physics embedded graph convolution neural network for power flow calculation considering uncertain injections and topology
Probabilistic analysis tool is important to quantify the impacts of the uncertainties on power
system operations. However, the repetitive calculations of power flow are time-consuming …
system operations. However, the repetitive calculations of power flow are time-consuming …
Impact of probabilistic modelling of wind speed on power system voltage profile and voltage stability analysis
Wind speed characteristics may have a significant impact on the power system operation,
stability and dynamics. Hence, appropriate modelling and quantification of wind probability …
stability and dynamics. Hence, appropriate modelling and quantification of wind probability …
Bayesian deep neural networks for spatio-temporal probabilistic optimal power flow with multi-source renewable energy
F Gao, Z Xu, L Yin - Applied Energy, 2024 - Elsevier
Probabilistic optimal power flow (POPF) plays a crucial role in ensuring the economic and
secure operation of power systems with multiple fluctuating loads and renewable energy …
secure operation of power systems with multiple fluctuating loads and renewable energy …
Guest editorial: Special issue on data-analytics for stability analysis, control, and situational awareness of power system with high-penetration of renewable energy
Guest editorial: Special issue on data-analytics for stability analysis, control, and situational
awareness of power system with high-penetration of renewable energy - ScienceDirect Skip …
awareness of power system with high-penetration of renewable energy - ScienceDirect Skip …
Fast economic dispatch in smart grids using deep learning: An active constraint screening approach
In smart grids, the power supply and demand are balanced through the electricity market to
promote the maximization of social welfare. An important procedure in electricity market …
promote the maximization of social welfare. An important procedure in electricity market …