Titre :

Energy Scheduling of a Smart Microgrid with Shared Photovoltaic Panels and Storage: the Case of the Ballen Marina in Samsø

Auteur(s) :

Carli, Raffaele [Auteur]
Dotoli, Mariagrazia [Auteur]
Jantzen, Jan [Auteur]
Kristensen, Michael [Auteur]
Othman, Sarah [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Titre de la revue :

Energy

Éditeur :

Elsevier

Date de publication :

2020-05-01

ISSN :

0360-5442

Mot(s)-clé(s) en anglais :

microgrid
demand side management
renewable energy
energy storage
energy management
on-line scheduling
model predictive control
optimization algorithm

Discipline(s) HAL :

Informatique [cs]
Informatique [cs]/Modélisation et simulation

Résumé en anglais : [en]

This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and programmable ...
Lire la suite >This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and programmable operation) electrical appliances, as well as photovoltaic (PV) panels, and a battery energy storage system (BESS). The proposed control strategy aims at a simultaneous optimal planning of the controllable loads, the shared resources (i.e., the storage system charge/discharge and renewable energy usage), and the energy exchange with the grid. The control scheme relies on an iterative finite horizon on-line optimization, implementing a mixed integer linear programming energy scheduling algorithm to maximize the self-supply with solar energy and/or minimize the daily cost of energy bought from the grid under time-varying energy pricing. At each time step, the resulting optimization problem is solved providing the optimal operations of controllable loads, the optimal amount of energy to be bought/sold from/to the grid, and the optimal charging/discharging profile for the BESS. The proposed energy scheduling approach is applied to the demand side management control of the marina of Ballen, Samsø (Denmark), where a smart microgrid is currently being implemented as a demonstrator in the Horizon2020 European research project SMILE. Simulations considering the marina electric consumption (340 boat sockets, a service building equipped with a sauna and a wastewater pumping station, and the harbour master's office equipped with a heat pump), PV production (60kWp), and the BESS (237kWh capacity) based on a public real dataset are carried out on a one year time series with a 1 hour resolution. Simulations indicate that the proposed approach allows 90% exploitation of the production of the PV plant. Furthermore, results are compared to a naïve control approach. The MPC based energy scheduling improves the self-supply by 1.6% compared to the naïve control. Optimization of the business economy using the MPC approach, instead, yields to 8.2% savings in the yearly energy cost with respect to the naïve approach.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL