Staff Profile

Dr. Qiuyi Hong is a Postdoctoral Research Associate in the Electrical Power Group in the School of Engineering at Newcastle University. He holds a PhD in Data Science from the School of Mathematics, Statistics, and Actuarial Science at the University of Essex, where he specialised in applying Artificial Intelligence (AI) and optimisation techniques to energy systems. His work has been published in leading journals such as Applied Energy and presented at research conferences. Before joining Newcastle University, Dr. Hong gained experience as an intern with the Data & Analytics Team at Essex County Council. He also served as a Research Officer at the University of Essex, developing a Python-based optimisation model for energy pricing. As an Assistant Lecturer, he taught master's students machine learning and statistical methods. Dr. Hong's technical expertise includes Python, MATLAB, R, PyTorch, TensorFlow, Power BI, and various optimisation and machine learning libraries. Dr. Hong is dedicated to solving research problems in energy systems and low-carbon technologies by applying data-driven and optimisation approaches.

My research focuses on applying data-driven and optimisation techniques to solve problems in energy systems. My current research includes:

1. Quantification and Evaluation of Low-Carbon Technologies: Analysing the value and impact of technologies such as solar panels, energy storage, and electric vehicles within the smart home energy management system (SHEMS) framework.

2. Roof-Rental Mechanism Analysis: Review and evaluate the roof-rental mechanisms in the UK and internationally and propose potential research directions and technologies for further improvement.

3. AI and Optimisation Modeling: Applying AI and optimisation techniques to enhance energy system decision-making processes and strategic planning.

• Articles

  • Hong Q. A smart hierarchical transactive energy system in the presence of renewable energies, and demand-side management [PhD thesis]. Colchester: University of Essex, 2024.
  • Hong Q, Meng F, Liu J. Customised Multi-Energy Pricing: Model and Solutions. Energies 2023, 16(4), 2080.
  • Hong Q, Meng F, Liu J, Bo R. A bilevel game-theoretic decision-making framework for strategic retailers in both local and wholesale electricity markets. Applied Energy 2023, 330(Part A), 120311.

• Conference Proceedings (inc. Abstract)

  • Hong Q, Meng F. Customized Multi-energy Pricing in Smart Grids: A Bilevel and Evolutionary Computation Approach. In: UK Workshop on Computational Intelligence. 2022.