An MILP model for optimal management of energy consumption and comfort in smart buildings. - Jerson A. Pinzon; Pedro P. Vergara; Luiz Carlos Pereira da Silva; Marcos J. Rider (ISGT, 2017)

Generalization of the λ-method for decentralized economic dispatch considering reactive resources. - Pedro P. Vergara; Hamid Reza Shaker; Bo Nørregaard Jørgensen; Luiz Carlos Pereira da Silva (ISGT Europe, 2017)

Local hierarchical control for industrial microgrids with improved frequency regulation. - Juan M. Rey; Pedro P. Vergara; Miguel Castilla; Antonio Camacho; Jaume Miret (ICIT, 2018)

Feasibility and Performance Assessment of Commercial PV Inverters Operating with Droop Control for Providing Voltage Support Services. - Pedro P. Vergara; Tam T. Mai; Andrew Burstein; Phuong H. Nguyen (ISGT Europe, 2019)

Optimal Management of Energy Consumption and Comfort for Smart Buildings Operating in a Microgrid. - Jerson A. Pinzon; Pedro P. Vergara; Luiz Carlos Pereira da Silva; Marcos J. Rider (IEEE Trans. Smart Grid, 2019)

Optimal Operation of Unbalanced Three-Phase Islanded Droop-Based Microgrids. - Pedro P. Vergara; Juan Camilo Lopez; Marcos J. Rider; Luiz Carlos Pereira da Silva (IEEE Trans. Smart Grid, 2019)

A Generalized Model for the Optimal Operation of Microgrids in Grid-Connected and Islanded Droop-Based Mode. - Pedro P. Vergara; Juan M. Rey; Juan Camilo López; Marcos J. Rider; Luiz Carlos Pereira da Silva; Hamid Reza Shaker; Bo Nørregaard Jørgensen (IEEE Trans. Smart Grid, 2019)

Distributed Strategy for Optimal Dispatch of Unbalanced Three-Phase Islanded Microgrids. - Pedro P. Vergara; Juan M. Rey; Hamid Reza Shaker; Josep M. Guerrero; Bo Nørregaard Jørgensen; Luiz Carlos Pereira da Silva (IEEE Trans. Smart Grid, 2019)

Conditional Multivariate Elliptical Copulas to Model Residential Load Profiles From Smart Meter Data. - Edgar Mauricio Salazar Duque; Pedro P. Vergara; Phuong H. Nguyen; Anne van der Molen; Johannes G. Slootweg (IEEE Trans. Smart Grid, 2021)

Performance Comparison of Deep RL Algorithms for Energy Systems Optimal Scheduling. - Hou Shengren; Edgar Mauricio Salazar Duque; Pedro P. Vergara; Peter Palensky (ISGT-Europe, 2022)

Behind Closed Doors: Process-Level Rootkit Attacks in Cyber-Physical Microgrid Systems. - Suman Rath; Ioannis Zografopoulos; Pedro P. Vergara; Vassilis C. Nikolaidis; Charalambos Konstantinou (CoRR, 2022)

Adaptive Activation Functions for Deep Learning-based Power Flow Analysis. - Zeynab Kaseb; Yu Xiang; Peter Palensky; Pedro P. Vergara (ISGT EUROPE, 2023)

Volt/VAR Optimization in the Presence of Attacks: A Real-Time Co-Simulation Study. - Mohd Asim Aftab; Astha Chawla; Pedro P. Vergara; Shehab Ahmed; Charalambos Konstantinou (SmartGridComm, 2023)

Estimating Risk-Aware Flexibility Areas for EV Charging Pools via Stochastic AC-OPF. - Juan S. Giraldo; Nataly Bañol Arias; Pedro P. Vergara; Maria Vlasiou; Gerwin Hoogsteen; Johann L. Hurink (CoRR, 2023)

Optimal Energy System Scheduling Using A Constraint-Aware Reinforcement Learning Algorithm. - Hou Shengren; Pedro P. Vergara; Edgar Mauricio Salazar Duque; Peter Palensky (CoRR, 2023)

Impact of Dynamic Tariffs for Smart EV Charging on LV Distribution Network Operation. - Flore Verbist; Nanda Kishor Panda; Pedro P. Vergara; Peter Palensky (CoRR, 2023)

A Constraint Enforcement Deep Reinforcement Learning Framework for Optimal Energy Storage Systems Dispatch. - Shengren Hou; Edgar Mauricio Salazar Duque; Peter Palensky; Pedro P. Vergara (CoRR, 2023)

PowerFlowNet: Leveraging Message Passing GNNs for Improved Power Flow Approximation. - Nan Lin; Stavros Orfanoudakis; Nathan Ordonez Cardenas; Juan S. Giraldo; Pedro P. Vergara (CoRR, 2023)

Quantum Neural Networks for Power Flow Analysis. - Zeynab Kaseb; Matthias Möller; Giorgio Tosti Balducci; Peter Palensky; Pedro P. Vergara (CoRR, 2023)

Critical Data Visualization to Enhance Protection Schemes for State Estimation. - Vinicius B. Braga Flôr; Milton Brown Do Coutto Filho; Julio Cesar Stacchini de Souza; Pedro P. Vergara (IEEE Trans. Smart Grid, 2023)

Enhanced Optimal Power Flow Based Droop Control in MMC-MTDC Systems. - Hongjin Du; Rashmi Prasad; Aleksandra Lekic; Pedro P. Vergara; Peter Palensky (ISGT EUROPE, 2024)

Linear Reinforcement Learning for Energy Storage Systems Optimal Dispatch. - Shuyi Gao; Shengren Hou; Edgar Mauricio Salazar Duque; Peter Palensky; Pedro P. Vergara (ISGT EUROPE, 2024)

Hybrid Quantum Physics-Informed Neural Networks for Power Flow Analysis. - Zeynab Kaseb; Peter Palensky; Pedro P. Vergara (ISGT EUROPE, 2024)

Data-Driven Topology Generation with Physics-Guidance in LV Distribution Networks. - Dong Liu; Juan S. Giraldo; Peter Palensky; Pedro P. Vergara (ISGT EUROPE, 2024)

A Constraint Enforcing Imitation Learning Approach for Optimal Operation of Unbalanced Distribution Networks. - Neda Vahabzad; Pedro P. Vergara; Peter Palensky (ISGT EUROPE, 2024)

Reinforcement Learning for Optimized EV Charging Through Power Setpoint Tracking. - Yunus Emre Yilmaz; Stavros Orfanoudakis; Pedro P. Vergara (ISGT EUROPE, 2024)

Adiabatic Computing for Power Flow Analysis. - Zeynab Kaseb; Matthias Möller; Markus Kirsch; Peter Palensky; Pedro P. Vergara (QCE, 2024)

Tensor Power Flow Formulations for Multidimensional Analyses in Distribution Systems. - Edgar Mauricio Salazar Duque; Juan S. Giraldo; Pedro P. Vergara; Phuong H. Nguyen; Han Slootweg (CoRR, 2024)

On Future Power Systems Digital Twins: Towards a Standard Architecture. - Wouter Zomerdijk; Peter Palensky; Tarek AlSkaif; Pedro P. Vergara (CoRR, 2024)

A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction. - Weijie Xia; Chenguang Wang 006; Peter Palensky; Pedro P. Vergara (CoRR, 2024)

A Simulation Tool for V2G Enabled Demand Response Based on Model Predictive Control. - Cesar Diaz-Londono; Stavros Orfanoudakis; Pedro P. Vergara; Peter Palensky; Fredy Ruiz; Giambattista Gruosso (CoRR, 2024)

RL-ADN: A High-Performance Deep Reinforcement Learning Environment for Optimal Energy Storage Systems Dispatch in Active Distribution Networks. - Shengren Hou; Shuyi Gao; Weijie Xia; Edgar Mauricio Salazar Duque; Peter Palensky; Pedro P. Vergara (CoRR, 2024)

An Efficient and Explainable Transformer-Based Few-Shot Learning for Modeling Electricity Consumption Profiles Across Thousands of Domains. - Weijie Xia; Gao Peng; Chenguang Wang 006; Peter Palensky; Eric J. Pauwels; Pedro P. Vergara (CoRR, 2024)

A Screening Method for Power System Inertia Zones Identification. - Rashmi Prasad; Pedro P. Vergara; Narayana Prasad Padhy; Robert Dimitrovski; Aleksandra Lekic (CoRR, 2024)

Safe Imitation Learning-based Optimal Energy Storage Systems Dispatch in Distribution Networks. - Shengren Hou; Peter Palensky; Pedro P. Vergara (CoRR, 2024)

Two-Stage Robust Optimal Operation of Distribution Networks using Confidence Level Based Distributionally Information Gap Decision. - Zhisheng Xiong; Bo Zeng; Peter Palensky; Pedro P. Vergara (CoRR, 2024)

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; Juan S. Giraldo; Phuong H. Nguyen; Anne van der Molen; Han Slootweg (CoRR, 2024)

Adaptive Informed Deep Neural Networks for Power Flow Analysis. - Zeynab Kaseb; Stavros Orfanoudakis; Pedro P. Vergara; Peter Palensky (CoRR, 2024)

Comparative Analysis of Zero-Shot Capability of Time-Series Foundation Models in Short-Term Load Prediction. - Nan Lin; Dong Yun; Weijie Xia; Peter Palensky; Pedro P. Vergara (CoRR, 2024)

GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments. - Stavros Orfanoudakis; Nanda Kishor Panda; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

Optimizing Electric Vehicles Charging using Large Language Models and Graph Neural Networks. - Stavros Orfanoudakis; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

Model-Free Privacy Preserving Power Flow Analysis in Distribution Networks. - Dong Liu; Juan S. Giraldo; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

EV2Gym: A Flexible V2G Simulator for EV Smart Charging Research and Benchmarking. - Stavros Orfanoudakis; Cesar Diaz-Londono; Yunus Emre Yilmaz; Peter Palensky; Pedro P. Vergara (IEEE Trans. Intell. Transp. Syst., 2025)

Forecast-Driven Scenario Generation for Building Energy Management Using Stochastic Optimization. - Hossein Nourollahi Hokmabad; Tala Hemmati Shahsavar; Pedro P. Vergara; Oleksandr Husev; Juri Belikov (CoRR, 2025)

Solving Power System Problems using Adiabatic Quantum Computing. - Zeynab Kaseb; Matthias Möller; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids. - Shengyuan Yan; Farzad Vazinram; Zeynab Kaseb; Lindsay Spoor; Jochen Stiasny; Betul Mamudi; Amirhossein Heydarian Ardakani; Ugochukwu Orji; Pedro P. Vergara; Yu Xiang; Jerry Guo (CoRR, 2025)

Optimal Droop Control Strategy for Coordinated Voltage Regulation and Power Sharing in Hybrid AC-MTDC Systems. - Hongjin Du; Tuanku Badzlin Hashfi; Rashmi Prasad; Pedro P. Vergara; Peter Palensky; Aleksandra Lekic (CoRR, 2025)

Quantum Hardware-in-the-Loop for Optimal Power Flow in Renewable-Integrated Power Systems. - Zeynab Kaseb; Rahul Rane; Aleksandra Lekic; Matthias Möller; Amin Khodaei; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

A Quantum-Enhanced Power Flow and Optimal Power Flow based on Combinatorial Reformulation. - Zeynab Kaseb; Matthias Möller; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

A Data-Driven Approach for Topology Correction in Low Voltage Networks with DERs. - Dong Liu; Sander Timmerman; Yu Xiang; Peter Palensky; Pedro P. Vergara (CoRR, 2025)

EnergyDiff: Universal Time-Series Energy Data Generation Using Diffusion Models. - Nan Lin; Peter Palensky; Pedro P. Vergara (IEEE Trans. Smart Grid, 2025)