Energy community management system based on real-time measurements and genetic algorithms
- Resource Type
- Conference
- Authors
- Proietti, Massimiliano; Garinei, Alberto; Bianchi, Federico; Vispa, Alessandro; Marini, Andrea; Speziali, Stefano; Marconi, Marcello; Ricci, Roberto; Cernieri, Pierluigi; Piccioni, Emanuele
- Source
- 2023 IEEE International Workshop on Metrology for Living Environment (MetroLivEnv) Metrology for Living Environment (MetroLivEnv), 2023 IEEE International Workshop on. :23-28 May, 2023
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Renewable energy sources
Energy measurement
Reinforcement learning
Size measurement
Search problems
Real-time systems
State of charge
Energy Community
Microgrid
energy management
genetic algorithms
Markov Decision Process
energy optimization
Reinforcement Learning
renewable energy
measurement
control
- Language
In this work we study a real-time energy management system (EMS) for Energy Communities (EC). A mathematical model of EC and the related energy optimization problem have been developed. To ensure the usability of the studied EMS in real world - where EC are varying in size and types of loads/energy generators/storage systems - we employ genetic algorithms (GA) for sub-optimal solution searching of the optimization problem that uses real-time measurements of EC production, loads and storages state of charge. We also suggest a reinforcement learning (RL) approach to enhance the performance of the EMS developed.