A multi-objective optimization model for the operation of decentralized multi-energy systems A multi-objective optimization model for the operation of decentralized multi-energy systems

Yolaine Adihou (1, 2) , Mohamed Mabrouk (1, 2) , Pierrick Haurant (1, 2) , Bruno Lacarrière (1, 2)

1 IMT Atlantique - DSEE - Département Systèmes Energétiques et Environnement
2 GEPEA-OSE - Optimisation - Système - Energie

A multi-energy system couples several carriers such as electricity and heat to meet mutual synergies, optimizing the global efficiency of the system. In this study, a multi-objective optimization is developed to establish the optimal design of a decentralized multi-energy system, by maximizing the renewable energy coverage rate and minimizing the operation costs at the same time. To retrace the typical demand profile that groups together the different uses of a neighbourhood, historical data are used in addition to simulation of buildings. On this basis, a set of energy production systems are modeled to form a multi-energy system providing energy to a neighbourhood in Nantes (France). An optimal sizing of the technologies is carried out using a genetic algorithm. Two objective functions are considered based on renewable energy coverage rate and operation/total cost. The study shows that renewable energy systems integration leads to higher total costs compared to a boiler only system, whereas when considering operation costs only, it is possible to reach a 12 % renewable energy system coverage rate and realize cost savings at the same time.

Domaines: Recherche opérationnelle [math.OC]; Thermique [physics.class-ph]

Yolaine Adihou, Mohamed Mabrouk, Pierrick Haurant, Bruno Lacarrière. A multi-objective optimization model for the operation of decentralized multi-energy systems A multi-objective optimization model for the operation of decentralized multi-energy systems. Journal of Physics: Conference Series, 2019, 1343, ⟨10.1088/1742-6596/1343/1/012104⟩. ⟨hal-02372913⟩