Department of Electrical Engineering and Automation

Multi-energy System Planning and Operation

Multi-energy System Planning and Operation leads pioneering research focused on advancing carbon neutrality and energy intelligence goals
An illustration showing different ways of producing energy, and different means of transport .

Multi-energy System Planning and Operation (MESPO) group: https://mespoteam.github.io/, established at Aalto University in 2023, leads pioneering research focused on advancing carbon neutrality and energy intelligence goals. The planning and operation of multi-energy systems (MES) such as (industrial, commercial, Agri-cultural) microgrids, ships & seaports, buildings, flights & airports, etc., involves the coordination of diverse energy forms, including electricity, heat, and gas, green hydrogen, water, transportation, etc. MES aims to optimize energy production, storage, and consumption to ensure efficiency, resilience, and sustainability. These systems often incorporate renewable energy sources like solar, wind, tidal energy, biomass, etc., as well as advanced storage technologies, to meet the growing demand for clean and reliable energy. Further, in recent years, AI development has accelerated rapidly, driven by advancements in computational power, data availability, and algorithmic innovation. Machine learning techniques, particularly DRL and large language model, are being employed in complex environments to handle uncertainty, automate control processes, and improve system reliability. 

Key research topics include:

  1. Multi-Energy Coordination: Optimal operation of MES, i.e., microgrids, ships & seaports, virtual power plants (VPPs), flight & airports, buildings, etc., with power, heat/cooling, water, transportation and hydrogen networks, power to X techniques, and demand response. 
  2. AI + Energy: Online data-driven (AI) prediction and operation with machine learning methods such as deep reinforcement learning, large language model, transfer learning, federate learning, etc.
  3. Uncertainty Management: Tackling uncertainties from renewables, prices, outdoor temperature, etc., via methods such as robust or stochastic programming methods.
  4. Resilience Enhancement: Improve the system's ability to withstand and recover from natural disasters or supply interruptions by implementing robust and adaptive strategies such as reconfiguration.
  5. Market mechanism: achieve effective energy trading with game theory methods.
Illustration telling about different types of energy production methods, and means of transport.

The MESPO group is led by Assistant Professor Zhengmao Li.

Latest publications

Dynamics-aware scheduling of renewable electrolyzer plants: A physics-informed reinforcement learning approach

Yangyang Wei, Sheng Chen, Zhinong Wei, Farid Hamzeh Aghdam, Zhengmao Li 2027 Applied Energy

Copula-based joint distributionally robust chance-constrained low-carbon operation of renewable power-to-methanol systems

Tianhao Wu, Yuning Jiang, Hui Huang, Zhengmao Li, Yi Shen, Ammar Al-Bazi, Stefan Niessen, Junyi Zhai 2027 Applied Energy

Adaptive dynamic planning method for electric vehicle charging stations considering active interaction with EV growth

Nan Yang, Wenbin Gan, Zijian Wang, Pengcheng Liang, Xiaoyu Dai, Edris Pouresmaeil, Tianlu Luo, Yuehua Huang, Zhengmao Li 2027 Applied Energy

Rolling horizon energy management of a green multi-energy ship microgrid with voyage routing and waste heat recovery

Zhineng Fei, Kari Tammi, Iiro Harjunkoski, Aku Karhinen, Rofice Dickson, Zhengmao Li 2026 Journal of Marine Engineering and Technology

A Two-Stage Joint Trading Strategy for Electricity and Regulating Capacity in a PV-Rich Local Energy Community

Changsen Feng, Sheng Chen, Hui Huang, Zhengmao Li, Youbing Zhang, Fushuan Wen 2026 IEEE Transactions on Systems, Man, and Cybernetics: Systems

An Innovative Diffusion Model Based on Adaptive Time-Frequency Drive for High-Resolution Photovoltaic Data Reconstruction

Xueqian Fu, Qiaoyu Ma, Zhengmao Li, Jiarong Li, Ruixue Feng, Hongbin Sun, Youmin Zhang 2026 IEEE Transactions on Smart Grid

Implicit Category Projection-Enhanced Multimodal Seq2Seq for Ensuring Accurate Day-Ahead PV Forecasting under Transitional Weather

Xueqian Fu, Xiaolong Zhao, Xiao Lv, Hongbin Sun, Jiarong Li, Xiangrong Zeng, Zipeng Liang, Zhengmao Li, Youmin Zhang 2026 IEEE Transactions on Smart Grid

Low-carbon flexible operation strategy of integrated electricity-gas systems considering dynamic hydrogen injection

Xianhui Gao, Junyi Zhai, Gaoyang Hou, Zhengmao Li, Sheng Wang, Jianxiao Wang 2026 Fuel

Microgrid design and optimization

Om Hari Gupta, Zhengmao Li 2026 Scientific Reports
More information on our research in the Aalto research portal.
Research portal
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