Power flow analysis using quantum and digital annealers: a discrete combinatorial optimization approach
Power flow (PF) analysis is a foundational computational method to study the flow of power
in an electrical network. This analysis involves solving a set of non-linear and non-convex …
in an electrical network. This analysis involves solving a set of non-linear and non-convex …
[HTML][HTML] Comparative assessment of generative models for transformer-and consumer-level load profiles generation
Residential load profiles (RLPs) play an increasingly important role in the optimal operation
and planning of distribution systems, particularly with the rising integration of low-carbon …
and planning of distribution systems, particularly with the rising integration of low-carbon …
[HTML][HTML] Tensor power flow formulations for multidimensional analyses in distribution systems
In this paper, we present two multidimensional power flow formulations based on a fixed-
point iteration (FPI) algorithm to efficiently solve hundreds of thousands of Power flows (PFs) …
point iteration (FPI) algorithm to efficiently solve hundreds of thousands of Power flows (PFs) …
On Future Power Systems Digital Twins: Towards a Standard Architecture
W Zomerdijk, P Palensky, T AlSkaif… - arXiv preprint arXiv …, 2024 - arxiv.org
The energy sector's digital transformation brings mutually dependent communication and
energy infrastructure, tightening the relationship between the physical and the digital world …
energy infrastructure, tightening the relationship between the physical and the digital world …
Decoupled Volt/var Control with Safe Reinforcement Learning based on Approximate Bayesian Inference
Y Zhang, P Wang, L Yu, N Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Deep reinforcement learning (DRL) has proven promising for addressing the problems
brought by the uncertainties of renewable energy sources in the volt/var control (VVC) …
brought by the uncertainties of renewable energy sources in the volt/var control (VVC) …
An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains
Electricity Consumption Profiles (ECPs) are crucial for operating and planning power
distribution systems, especially with the increasing numbers of various low-carbon …
distribution systems, especially with the increasing numbers of various low-carbon …
A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction
Residential Load Profile (RLP) generation and prediction are critical for the operation and
planning of distribution networks, particularly as diverse low-carbon technologies are …
planning of distribution networks, particularly as diverse low-carbon technologies are …
On future power system digital twins: A vision towards a standard architecture
The energy sector's digital transformation brings mutually dependent communication and
energy infrastructure, tightening the relationship between the physical and the digital world …
energy infrastructure, tightening the relationship between the physical and the digital world …
Day-Ahead Price Scenario Generation Using Conditioned Multivariate Elliptical Copulas
E Van Wijngaarden, B Van der Holst… - … Conference on Smart …, 2024 - ieeexplore.ieee.org
Forecasting day-ahead (DA) electricity market prices has become a complex challenge in
recent years due to the increasingly varying daily price patterns and longer-term shocks …
recent years due to the increasingly varying daily price patterns and longer-term shocks …
[PDF][PDF] Voltage Monitoring and Control in The Active Distribution Networks
MQ Tran - 2024 - research.tue.nl
The rapid growth of renewable energy sources, such as solar photovoltaics and wind
turbines, along with the proliferation of other Distributed Energy Resources (DERs) such as …
turbines, along with the proliferation of other Distributed Energy Resources (DERs) such as …