11 citations · 22 across the 7 of their papers we have counts for
8 papers
Lower Dimensional Spherical Representation of Medium Voltage Load Profiles for Visualization, Outlier Detection, and Generative Modelling
Edgar Mauricio Salazar Duque, Bart van der Holst, Pedro P. Vergara +5
This paper presents the spherical lower dimensional representation for daily medium voltage load profiles, based on principal component analysis. The objective is to unify and simp…
Volt/VAR Optimization in the Presence of Attacks: A Real-Time Co-Simulation Study
Mohd Asim Aftab, Astha Chawla, Pedro P. Vergara +2
Traditionally, Volt/VAR optimization (VVO) is performed in distribution networks through legacy devices such as on-load tap changers (OLTCs), voltage regulators (VRs), and capacito…
A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch
Shengren Hou, Edgar Mauricio Salazar Duque, Peter Palensky +1
The optimal dispatch of energy storage systems (ESSs) presents formidable challenges due to the uncertainty introduced by fluctuations in dynamic prices, demand consumption, and re…
Impact of Dynamic Tariffs for Smart EV Charging on LV Distribution Network Operation
Flore Verbist, Nanda Kishor Panda, Pedro P. Vergara +1
With a growing share of electric vehicles (EVs) in our distribution grids, the need for smart charging becomes indispensable to minimise grid reinforcement. To circumvent the assoc…
Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm
Hou Shengren, Pedro P. Vergara, Edgar Mauricio Salazar Duque +1
The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system's complexity, especially when it comes to defining its operati…
Estimating Risk-Aware Flexibility Areas for EV Charging Pools via Stochastic AC-OPF
Juan S. Giraldo, Nataly Banol Arias, Pedro P. Vergara +3
This paper introduces a stochastic AC-OPF (SOPF) for the flexibility management of electric vehicle (EV) charging pools in distribution networks under uncertainty. The SOPF conside…
Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling
Hou Shengren, Edgar Mauricio Salazar, Pedro P. Vergara +1
Taking advantage of their data-driven and model-free features, Deep Reinforcement Learning (DRL) algorithms have the potential to deal with the increasing level of uncertainty due…
Behind Closed Doors: Process-Level Rootkit Attacks in Cyber-Physical Microgrid Systems
Suman Rath, Ioannis Zografopoulos, Pedro P. Vergara +2
Embedded controllers, sensors, actuators, advanced metering infrastructure, etc. are cornerstone components of cyber-physical energy systems such as microgrids (MGs). Harnessing th…