Cover Image

Embedded Machine Learning for Solar PV Power Regulation in a Remote Microgrid

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhu, Yongli, Xu, Linna, Huang, Jian
Format:	Preprint
Published:	2024
Subjects:	Systems and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence
by: Huang, Jian, et al.
Published: (2026)

Diffusion-assisted Model Predictive Control Optimization for Power System Real-Time Operation
by: Xu, Linna, et al.
Published: (2025)

Generative Modeling and Data Augmentation for Power System Production Simulation
by: Xu, Linna, et al.
Published: (2024)

Edge Computing for Microgrid via MATLAB Embedded Coder and Low-Cost Smart Meters
by: Xu, Linna, et al.
Published: (2024)

Offline Reinforcement Learning for Microgrid Voltage Regulation
by: Yang, Shan, et al.
Published: (2025)

On-Device Training of PV Power Forecasting Models in a Smart Meter for Grid Edge Intelligence
by: Huang, Jian, et al.
Published: (2025)

An End-to-End Approach for Microgrid Probabilistic Forecasting and Robust Operation via Decision-focused Learning
by: Cao, Tingwei, et al.
Published: (2025)

Conformal Prediction for Stochastic Decision-Making of PV Power in Electricity Markets
by: Renkema, Yvet, et al.
Published: (2024)

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency
by: Zhou, Yuqi, et al.
Published: (2024)

A Reinforcement Learning Approach for Optimal Control in Microgrids
by: Salaorni, Davide, et al.
Published: (2025)

Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning
by: Mukherjee, Sayak, et al.
Published: (2022)

A Multiobjective Reinforcement Learning Framework for Microgrid Energy Management
by: Liu, M. Vivienne, et al.
Published: (2023)

Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids
by: Abdullah, Mohammed Ezzaldin Babiker
Published: (2026)

Scaling Laws of Machine Learning for Optimal Power Flow
by: Liu, Xinyi, et al.
Published: (2026)

Adaptive Intelligent Secondary Control of Microgrids Using a Biologically-Inspired Reinforcement Learning
by: Jafari, Mohammad, et al.
Published: (2019)

Game Theoretic Resilience Recommendation Framework for CyberPhysical Microgrids Using Hypergraph MetaLearning
by: Niketh, S Krishna, et al.
Published: (2025)

Demand Response Optimization MILP Framework for Microgrids with DERs
by: Babu, K. Victor Sam Moses, et al.
Published: (2025)

Anomaly Detection with Machine Learning Algorithms in Large-Scale Power Grids
by: Gillioz, Marc, et al.
Published: (2026)

Physics-informed Convolutional Neural Network for Microgrid Economic Dispatch
by: Ge, Xiaoyu, et al.
Published: (2024)

Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets
by: Li, Meiyi, et al.
Published: (2023)

Integrating Reinforcement Learning and Model Predictive Control with Applications to Microgrids
by: da Silva, Caio Fabio Oliveira, et al.
Published: (2024)

Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management
by: Li, Yuanzheng, et al.
Published: (2022)

Generalizable Machine Learning Models for Predicting Data Center Server Power, Efficiency, and Throughput
by: Lei, Nuoa, et al.
Published: (2025)

Integrated Optimization and Game Theory Framework for Fair Cost Allocation in Community Microgrids
by: Babu, K. Victor Sam Moses, et al.
Published: (2025)

Model-Agnostic Zeroth-Order Policy Optimization for Meta-Learning of Ergodic Linear Quadratic Regulators
by: Pan, Yunian, et al.
Published: (2024)

Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
by: Nauck, Christian, et al.
Published: (2024)

Enhancing Microgrid Performance Prediction with Attention-based Deep Learning Models
by: Maddineni, Vinod Kumar, et al.
Published: (2024)

The Wisdom of the Crowd: High-Fidelity Classification of Cyber-Attacks and Faults in Power Systems Using Ensemble and Machine Learning
by: Abukhousa, Emad, et al.
Published: (2025)

Contingency Analysis of a Grid of Connected EVs for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme
by: Sabhahit, J. N., et al.
Published: (2024)

A Unified Approach for Learning the Dynamics of Power System Generators and Inverter-based Resources
by: Liu, Shaohui, et al.
Published: (2024)

Quantifying and Predicting Residential Building Flexibility Using Machine Learning Methods
by: Salter, Patrick, et al.
Published: (2024)

Real-Time Surrogate Modeling for Fast Transient Prediction in Inverter-Based Microgrids Using CNN and LightGBM
by: Ogiesoba-Eguakun, Osasumwen Cedric, et al.
Published: (2026)

Resilient Control of Networked Microgrids using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations
by: Mukherjee, Sayak, et al.
Published: (2023)

Scalar Federated Learning for Linear Quadratic Regulator
by: Rostami, Mohammadreza, et al.
Published: (2026)

Learning Low-Dimensional Embeddings for Black-Box Optimization
by: Busetto, Riccardo, et al.
Published: (2025)

Physics-Embedded Neural ODEs for Sim2Real Edge Digital Twins of Hybrid Power Electronics Systems
by: Zheng, Jialin, et al.
Published: (2025)

Fair Reinforcement Learning Algorithm for PV Active Control in LV Distribution Networks
by: Vassallo, Maurizio, et al.
Published: (2024)

Learning Decentralized Linear Quadratic Regulators with $\sqrt{T}$ Regret
by: Ye, Lintao, et al.
Published: (2022)

Reinforcement Learning Based Bidding Framework with High-dimensional Bids in Power Markets
by: Liu, Jinyu, et al.
Published: (2024)

A Hybrid Strategy for Probabilistic Forecasting and Trading of Aggregated Wind-Solar Power: Design and Analysis in HEFTCom2024
by: Pu, Chuanqing, et al.
Published: (2025)