Hao Wang

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Lecturer (a.k.a. Assistant Professor)

MONASH UNIVERSITY

Australia

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Dr. Hao Wang is a Lecturer at Monash University in Australia. His research interests include optimization strategies for electric vehicle charging infrastructures, federated learning, and the application of artificial intelligence in energy management. Recent publications reflect his work on dynamic algorithms for network-constrained systems, as well as innovative methods for load forecasting and energy consumption analysis.

Recent Grants

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Smart Solar Energy Harvesting, Storage and Utilization

Open Date: 2014-01-01

Close Date: 2018-12-01

Hao Wang

Research Interests

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Recent Grants

Articles (23)

Dynamic rolling horizon optimization for network-constrained V2X value stacking of electric vehicles under uncertainties

Learning and Generating Diverse Residential Load Patterns Using GAN With Weakly-Supervised Training and Weight Selection

FedCoSR: Personalized Federated Learning With Contrastive Shareable Representations for Label Heterogeneity in Non-IID Data

Leveraging Large Language Model for Generalization in Building Energy Management

Privacy-Preserving Personalized Federated Learning for Distributed Photovoltaic Disaggregation Under Statistical Heterogeneity

Multi-objective coordinated EV charging strategy in distribution networks using an improved augmented epsilon-constrained method

Investigating state-of-the-art planning strategies for electric vehicle charging infrastructures in coupled transport and power networks: a comprehensive review

A reinforcement learning-based online learning strategy for real-time short-term load forecasting

Deep Reinforcement Learning-Assisted Federated Learning for Robust Short-Term Load Forecasting in Electricity Wholesale Markets

AI-Empowered Methods for Smart Energy Consumption: A Review of Load Forecasting, Anomaly Detection and Demand Response

Attentive Convolutional Deep Reinforcement Learning for Optimizing Solar-Storage Systems in Real-Time Electricity Markets

Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets

Network-Aware Coordination of Aggregated Electric Vehicles Considering Charge–Discharge Flexibility

Deep Reinforcement Learning for Voltage Control and Renewable Accommodation Using Spatial-Temporal Graph Information

On the Coordination of Transmission-Distribution Grids: A Dynamic Feasible Region Method

Evaluate DC Meter Adoption for House-Level Storage Devices

A Multicriteria Optimal Operation Framework for a Data Center Microgrid Considering Renewable Energy and Waste Heat Recovery: Use of Balanced Decision Making

Dispatch of highly renewable energy power system considering its utilization via a data-driven Bayesian assisted optimization algorithm

Time-of-use Pricing for Energy Storage Investment

Time-of-Use Pricing for Energy Storage Investment

Machine learning approach to uncovering residential energy consumption patterns based on socioeconomic and smart meter data

Smart Online Charging Algorithm for Electric Vehicles via Customized Actor–Critic Learning

Transactive Coordination of Electric Vehicles With Voltage Control in Distribution Networks

Collaborators (6)

Ariel Liebman

Mohsen Khorasany

Mahdi Jalili

Zhi Liu

Reza Razzaghi

Xiaojun Lin

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