Zheming Liang

Title: Zheming Liang: Innovator in Energy Management Systems

Introduction

Zheming Liang is a prominent inventor based in Tianjin, China. He has made significant contributions to the field of energy management, particularly through his innovative approaches to optimizing energy storage systems.

Latest Patents

Zheming Liang holds a patent for a system titled "Deep reinforcement learning based real-time scheduling of Energy Storage System (ESS) in commercial campus." This invention utilizes deep reinforcement learning to determine optimal actions for major components within a commercial building. The goal is to minimize operational costs while maximizing the comfort levels of occupants. The system introduces an unsupervised deep Q-network method to address energy management challenges by evaluating the impact of operational costs on comfort levels, taking environmental factors into account at each time slot. This approach allows for the derivation of optimum control decisions that target both immediate and long-term objectives, balancing exploration and exploitation.

Career Highlights

Zheming Liang is currently employed at the Global Energy Interconnection Research Institute North America. His work focuses on advancing energy management technologies that contribute to sustainable practices in commercial settings.

Collaborations

Zheming has collaborated with notable colleagues, including Desong Bian and Xiaohu Zhang, who share his commitment to innovation in energy systems.

Conclusion

Zheming Liang's contributions to energy management through his patented technology exemplify the potential of deep reinforcement learning in optimizing energy systems. His work not only addresses operational efficiency but also enhances occupant comfort in commercial environments.