Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø

Carli, Raffaele and Dotoli, Mariagrazia and Jantzen, Jan and Kristensen, Michael and Othman, Sarah Ben (2020) Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø. Energy, 198 (117188). pp. 1-16. ISSN 0360-5442

Full text not available from this repository. (Request a copy)

Abstract

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 (237 kWh capacity) based on a public real dataset are carried out on a one year time series with a 1 h 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.

Item Type:	Article
Additional Information:	You can download the article free of charge until 13 May 2020, https://authors.elsevier.com/a/1anU41H%7Ec%7EBKvg
Creators:	Carli, Raffaele and Dotoli, Mariagrazia and Jantzen, Jan and Kristensen, Michael and Othman, Sarah Ben
Projects:	SMILE
Date Deposited:	24 Mar 2020 08:02
Last Modified:	24 Mar 2020 08:02
URI:	http://arkiv.energiinstituttet.dk/id/eprint/652

Actions (login required)

View Item