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Professor Hongjian Sun's Outputs (169)

An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning (2025)
Presentation / Conference Contribution
Liu, J., Kazemtabrizi, B., Du, H., Matthews, P., & Sun, H. (2024, November). An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning. Presented at 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA

With the increasing integration of renewable energy sources into the power grid, accurate and reliable ultra-short-term forecasting of wind power is critical for optimizing grid stability and energy efficiency, especially for a highly dynamic and var... Read More about An Integrated Stacked Sparse Autoencoder and CNN-BLSTM Model for Ultra-Short-Term Wind Power Forecasting with Advanced Feature Learning.

Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era (2025)
Presentation / Conference Contribution
Bisu, A. A., Sun, H., & Gallant, A. (2025, January). Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era. Presented at 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC), University of Nevada, Las Vegas, USA

In this work, we developed and proposed a real testbed with Integrated Satellite-Terrestrial Network (ISTN) scenario. This topology was used to measure the actual parameters that were used as the Smart Grid (SG) Quality of Service (QoS) metrics. Perf... Read More about Integrated Satellite-Terrestrial Network for Smart Grid Communications in 6G Era.

Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin (2025)
Journal Article
Singh, A., Demirbaga, U., Singh Aujla, G., Jindal, A., Jiang, J., & Sun, H. (online). Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin. IEEE Journal of Selected Areas in Sensors, https://doi.org/10.1109/JSAS.2025.3540956

Sensor-enabled distributed energy resources (DERs) provide various advantages, including a lower carbon footprint, yet effective management of millions of DERs is still an issue. Virtual power plants (VPP) can integrate several DERs into a unified op... Read More about Scalable and Reliable Data Framework for Sensor-enabled Virtual Power Plant Digital Twin.

Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco (2025)
Journal Article
Rochd, A., Raihani, A., Mahir, O., Kissaoui, M., Laamim, M., Lahmer, A., El-Barkouki, B., El-Qasery, M., Sun, H. J., & Guerrero, J. M. (2025). Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco. Results in engineering, 25, Article 104400. https://doi.org/10.1016/j.rineng.2025.104400

The objective of this study is to develop and validate a comprehensive multi-objective optimization approach for energy management and trading in microgrids, with a particular focus on the integration of Distributed Energy Resources (DERs) and Electr... Read More about Swarm Intelligence-driven Multi-objective Optimization for Microgrid Energy Management and Trading considering DERs and EVs integration: Case Studies from Green Energy Park, Morocco.

Weather Impact on DER Long-term Performance: A Formal Verification Approach (2025)
Presentation / Conference Contribution
Santana, M. A., Stefanakos, I., Fang, X., Garg, A., Sun, H., & Osman, A. (2024, November). Weather Impact on DER Long-term Performance: A Formal Verification Approach. Presented at 2024 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), Bangalore, India

Distributed energy resources (DERs), such as solar photovoltaic (PV) panels, are essential to modern energy systems, providing resilience and producing clean, local energy. However, their long-term performance is vulnerable to environmental factors,... Read More about Weather Impact on DER Long-term Performance: A Formal Verification Approach.

A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response † (2025)
Journal Article
Chen, W., Sun, H., You, M., Jiang, J., & Rivera, M. (2025). A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response †. Energies, 18(4), Article 833. https://doi.org/10.3390/en18040833

Within smart homes, consumers could generate a vast amount of data that, if analyzed effectively, can improve the convenience of consumers and reduce energy consumption. In this paper, we propose to organize household appliance data into a knowledge... Read More about A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response †.

Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources (2025)
Journal Article
Harsh, P., Sun, H., Das, D., Goyal, A., & Jiang, J. (online). Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources. IEEE Transactions on Industry Applications, https://doi.org/10.1109/TIA.2025.3535847

The growing integration of distributed energy resources (DERs) into the power grid necessitates an effective coordination strategy to maximize their benefits. Acting as an aggregator of DERs, a virtual power plant (VPP) facilitates this coordination,... Read More about Stochastic Incentive-based Demand Response Program for Virtual Power Plant with Distributed Energy Resources.

Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems (2025)
Presentation / Conference Contribution
Demirbaga, U., Singh Aujla, G., & Sun, H. (2025, June). Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

As the scale of data continues to grow exponentially, managing resource allocation and energy consumption in big data systems becomes increasingly complex and critical. Moreover, with big data systems, energy efficiency is more important daily. In cl... Read More about Energy-based Predictive Root Cause Analysis for Real-Time Anomaly Detection in Big Data Systems.

COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks (2025)
Presentation / Conference Contribution
Singh Aujla, G., Jindal, A., Kaur, K., Garg, S., Chaudhary, R., Sun, H., & Kumar, N. (2025, June). COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

To mitigate various challenges in the edge-cloud ecosystem, such as global monitoring, flow control, and policy modification of legacy networking paradigms, software-defined networks (SDN) have evolved as a major technology. However, the dependency o... Read More about COPS: Controller Placement in Next-Generation Software Defined Edge-Cloud Networks.

Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks (2025)
Presentation / Conference Contribution
Dua, A., Jindal, A., Singh Aujla, G., & Sun, H. (2025, June). Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks. Presented at 2025 IEEE International Conference on Communications (ICC), Montreal, Canada

6G applications rely on data-intensive AI models for network optimization. These demand a scalable and energy-efficient framework to handle massive device networks with stringent latency requirements which current solutions struggle to support. Even... Read More about Green Reinforcement and Split Learning Framework for Edge-Fog-Cloud Continuum in 6G Networks.

Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks (2025)
Presentation / Conference Contribution
Nie, D., Yu, W., Foh, C. H., Ni, Q., Chen, L., Berri, S., Chorti, A., & Sun, H. (2025, May). Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks. Presented at IEEE INFOCOM 2025: IEEE International Conference on Computer Communications - Workshop, London

The random access channel (RACH) procedure is critical for uplink synchronization and connection establishment in massive machine-type communication (mMTC). While 3GPP Release 16 introduced the 2-step RACH to reduce signaling overhead, latency incurr... Read More about Efficient Context-Aware Barring Scheme for Low-Latency 2-Step RACH in 5G Networks.

Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading (2024)
Presentation / Conference Contribution
Ezeokafor, C., Harsh, P., & Sun, H. (2024, November). Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading. Presented at IEEE PES Australasian Universities Power Engineering Conference (AUPEC), Sydney, Australia

Efficient scheduling of the sources within a community is essential to reduce the electricity-related cost as well as the carbon emissions from the community. A novel energy management strategy for community grids is introduced in this research, leve... Read More about Multi-Objective Optimisation for Energy Scheduling in Smart Grids using Peer-to-Peer Trading.

Integrated Sensing and Communications With Mixed Fields Using Transmit Beamforming (2024)
Journal Article
Xiao, Y., Wang, E., Chen, Y., Chen, L., Ikhlef, A., & Sun, H. (online). Integrated Sensing and Communications With Mixed Fields Using Transmit Beamforming. IEEE Wireless Communications Letters, https://doi.org/10.1109/lwc.2024.3521186

Integrated sensing and communications (ISAC) is an important enabling technology for the next-generation wireless systems. Owing to the use of large-scale antenna arrays and/or high carrier frequencies, the communications user and the target may foll... Read More about Integrated Sensing and Communications With Mixed Fields Using Transmit Beamforming.

Optimal Energy Scheduling of Digital Twins Based Integrated Energy System (2024)
Presentation / Conference Contribution
Du, J., Harsh, P., & Sun, H. (2024, December). Optimal Energy Scheduling of Digital Twins Based Integrated Energy System. Presented at The 4th International Conference on Smart City and Green Energy, Sydney

With global climate change and growing electricity demand, optimizing Integrated Energy Systems (IES) for low-carbon and economic transformation has become particularly important. By applying digital twin (DT) technology to create a virtual copy of t... Read More about Optimal Energy Scheduling of Digital Twins Based Integrated Energy System.

Decarbonising Heating with Power-Hydrogen Optimisation (2024)
Presentation / Conference Contribution
Gonzalez-Osuna, E., Correa-Delval, M., & Sun, H. (2024, November). Decarbonising Heating with Power-Hydrogen Optimisation. Presented at 9th International Conference on Renewable Energy and Conservation ICREC 2024, Rome, Italy

This paper presents an analysis of an integrated power-hydrogen system for an energy community, incorporating renewable energy sources as solar panels, battery storage, and grid interaction. This study focuses on optimising energy consumption and min... Read More about Decarbonising Heating with Power-Hydrogen Optimisation.

Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum (2024)
Presentation / Conference Contribution
Dua, A., Singh Aujla, G., Jindal, A., & Sun, H. (2024, December). Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum. Presented at IEEE Global Communications Conference - Workshop on Next-Gen Healthcare Fusion (NgHF): AI-driven Secure Integrated Networks for Healthcare IoT Systems, Cape Town, South Africa

The increasing demand for machine learning (ML) technologies has led to a significant rise in energy consumption and environmental impact, particularly within the context of distributed computing environments like the Edge-Fog-Cloud Continuum. This p... Read More about Green AutoML: Energy-Efficient AI Deployment Across the Edge-Fog-Cloud Continuum.

Energy scheduling of technical virtual power plant considering incentive-based demand response program and distribution network reconfiguration (2024)
Presentation / Conference Contribution
Harsh, P., Sun, H., Awagan, G., & Jiang, J. (2024, November). Energy scheduling of technical virtual power plant considering incentive-based demand response program and distribution network reconfiguration. Presented at IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, IL, USA

Virtual power plants (VPPs) are increasingly utilized to efficiently coordinate and manage the increasing number of distributed energy resources (DERs) within power grids. Traditionally, VPP models have prioritized commercial or financial objectives,... Read More about Energy scheduling of technical virtual power plant considering incentive-based demand response program and distribution network reconfiguration.

Communication-Centric Integrated Sensing and Communications With Mixed Fields (2024)
Journal Article
Xiao, Y., Wang, E., Chen, Y., Sun, H., & Ikhlef, A. (2024). Communication-Centric Integrated Sensing and Communications With Mixed Fields. SCIENCE CHINA Information Sciences, 67(12), Article 219301. https://doi.org/10.1007/s11432-024-4152-9

Dear editor, Integrated sensing and communications (ISAC) is expected to play a vital role in the sixth-generation (6G) wireless networks [1]. By utilizing high frequencies, extremely large-scale antenna arrays, and new antenna designs, the 6G-empowe... Read More about Communication-Centric Integrated Sensing and Communications With Mixed Fields.

HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications (2024)
Presentation / Conference Contribution
Bisu, A. A., Gallant, A., & Sun, H. (2024, October). HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications. Presented at 2024 IEEE Future Networks World Forum (FNWF), Dubai, UAE

In this paper, we propose an improved Transmission Control Protocol (TCP) algorithm called HYBIC, building upon existing CUBIC and HYBLA algorithms. This HYBIC algorithm is designed for improving capacity utilisation and transmission rate of heteroge... Read More about HYBIC: An Improved Congestion Control Algorithm for Integrated Satellite-Terrestrial Networks in 5G and Beyond Communications.