School of Electrical Engineering, Liupanshui Normal University, Liupanshui | China
Author Profiles
Scopus
Orcid ID
Early Academic Pursuits
Qilong Zhang began his academic journey with a strong foundation in physics and electrical engineering, eventually establishing himself in the School of Physics and Electrical Engineering at Liupanshui Normal University. His early research interests revolved around renewable energy systems and optimization methods, leading him toward a specialized focus on integrated energy systems. With a background rooted in rigorous theoretical study and applied problem-solving, he progressively built expertise in predictive modeling, signal processing, and control strategies for energy systems.
Professional Endeavors
In his professional role, Zhang has actively contributed to both teaching and advanced research, positioning himself as a rising academic voice in the domain of renewable energy integration. His career highlights include publishing in Energy Reports (2025), where he presented an innovative approach to model predictive control (MPC) for multi-energy systems. Supported by grants from provincial education bodies, his university, and the China Southern Power Grid Technology Project, Zhang has expanded the scope of his work to address national-level renewable energy challenges in China.
Contributions and Research Focus
Zhang’s research focuses on developing data-driven Model Predictive Control frameworks that optimize hybrid renewable energy systems. His landmark study integrates wind power, solar photovoltaic generation, and hydrogen storage, advancing the reliability and scalability of renewable utilization. He has contributed key innovations such as hybrid prediction models (EMD-KPCA-LSTM, GVMD-ISSA-LSTM) and real-time feedback correction mechanisms. These contributions not only improved the stability of renewable systems but also enhanced efficiency by nearly 20%, showcasing measurable progress in renewable adoption.
Impact and Influence
The practical significance of Zhang’s work lies in its alignment with China’s carbon neutrality targets and the global agenda for sustainable development. His methods demonstrated a 73.86% absorption rate for local renewable energy, a significant benchmark in addressing grid integration volatility. By providing scalable solutions applicable to microgrids and industrial parks, his research bridges the gap between academic modeling and real-world application. His influence extends beyond publications, as his research outcomes directly contribute to policies and industrial practices aimed at cleaner energy transitions.
Academic Citations
Zhang’s contributions are positioned to garner increasing academic recognition, especially given the novelty of combining advanced signal processing with deep learning techniques like LSTM in energy systems research. His publication in Energy Reports is expected to attract citations from scholars focusing on renewable forecasting, integrated energy storage, and predictive control methodologies. As more institutions globally prioritize hybrid renewable systems, his work is likely to become a frequently cited reference in the field.
Legacy and Future Contributions
Looking ahead, Zhang’s research sets a pathway for further exploration of multi-energy optimization, intelligent forecasting models, and large-scale deployment of MPC frameworks. His ongoing projects and grant-backed initiatives suggest a sustained trajectory of innovation. With continued collaboration and academic exchange, Zhang is poised to leave a lasting legacy as a thought leader in renewable energy system integration. His commitment to solving real-world energy challenges ensures his contributions will resonate both within academia and across industries aiming for sustainable transformation.
Conclusion
In summary, Qilong Zhang exemplifies a promising researcher whose innovative approaches to renewable-based multi-energy systems stand out for their originality, practicality, and impact. His blend of theoretical innovation, practical applications, and alignment with global energy goals highlights both academic excellence and societal relevance. With a foundation of recognized achievements and forward-looking research directions, Zhang is well-positioned to make enduring contributions to the field of renewable energy optimization and control.
Notable Publications
"A model predictive control for a renewable-based multi energy system by integrating data-driven algorithm"
- Author: Qilong Zhang; Yongxiang Cai
- Journal: Energy Reports
- Year: 2021
"Model Predictive Control Method of Multi-Energy Flow System Considering Wind Power Consumption"
- Author: Qilong Zhang; Xiangping Chen; Guangming Li; Junjie Feng; Anqian Yang
- Journal: IEEE Access
- Year: 2021