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.

Group members

Latest publications

Coordinated operation of source–station–road–network system considering traffic flow uncertainty

Min Hou, Xinrui Liu, Yating Wang, Zhengmao Li, Qiuye Sun 2025 Renewable Energy

A CCP-Based Distributed Cooperative Operation Strategy for Multi-Agent Energy Systems Integrated with Wind, Solar, and Buildings

Bing Ding, Zening Li, Zhengmao Li, Yixun Xue, Jia Su, Xiaolong Jin, Hongbin Sun 2024 Applied Energy

Robust Coordinated Planning of Multi-Region Integrated Energy Systems With Categorized Demand Response

Yingchao Dong, Zhengmao Li, Hongli Zhang, Cong Wang, Xiaojun Zhou 2024 IEEE Transactions on Smart Grids

Two-Stage Coordinated Operation of A Green Multi-Energy Ship Microgrid With Underwater Radiated Noise by Distributed Stochastic Approach

Zhineng Fei, Hongming Yang, Liang Du, Josep M. Guerrero, Ke Meng, Zhengmao Li 2024 IEEE TRANSACTIONS ON SMART GRID

Editorial: Smart energy system for carbon reduction and energy saving: planning, operation and equipments

Wenlong Fu, Nan Yang, Zhengmao Li 2024 Frontiers in Energy Research

A Two-stage Multi-agent Deep Reinforcement Learning Method for Urban Distribution Network Reconfiguration Considering Switch Contribution

Hongjun Gao, Siyuan Jiang, Zhengmao Li, Renjun Wang, Youbo Liu, Junyong Liu 2024 IEEE Transactions on Power Systems

Continuous Monte Carlo Graph Search

Kalle Kujanpää, Juho Kannala, Amin Babadi, Alexander Ilin, Yi Zhao, Joni Pajarinen 2024 AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems

Two stage Stochastic Energy Scheduling for Multi Energy Rural Microgrids With Irrigation Systems and Biomass Fermentation

Wanhao Li, Yunyang Zou, Hongming Yang, Xueqian Fu, Sheng Xiang, Zhengmao Li 2024 IEEE TRANSACTIONS ON SMART GRID
More information on our research in the Aalto research portal.
Research portal
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