Multi-energy System Planning and Operation
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:
- 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.
- 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.
- Uncertainty Management: Tackling uncertainties from renewables, prices, outdoor temperature, etc., via methods such as robust or stochastic programming methods.
- 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.
- Market mechanism: achieve effective energy trading with game theory methods.
The MESPO group is led by Assistant Professor Zhengmao Li.
Group members
Latest publications
A CCP-Based Distributed Cooperative Operation Strategy for Multi-Agent Energy Systems Integrated with Wind, Solar, and Buildings
Robust Coordinated Planning of Multi-Region Integrated Energy Systems With Categorized Demand Response
Two-Stage Coordinated Operation of A Green Multi-Energy Ship Microgrid With Underwater Radiated Noise by Distributed Stochastic Approach
Editorial: Smart energy system for carbon reduction and energy saving: planning, operation and equipments
A Two-stage Multi-agent Deep Reinforcement Learning Method for Urban Distribution Network Reconfiguration Considering Switch Contribution
Continuous Monte Carlo Graph Search
Joint Planning of Utility-Owned Distributed Energy Resources in an Unbalanced Active Distribution Network Considering Asset Health Degradation
Two stage Stochastic Energy Scheduling for Multi Energy Rural Microgrids With Irrigation Systems and Biomass Fermentation
Resilience enhancement of a multi-energy distribution system via joint network reconfiguration and mobile sources scheduling
A Carbon Emission Allowance Bargaining Model For Energy Transactions Among Prosumers
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