A compact nanogrid for home applications with a behaviour-tree-based central controller

• Published in: Applied energy Vol. 225; pp. 14 - 26
• Main Authors: Burgio, Alessandro, Menniti, Daniele, Sorrentino, Nicola, Pinnarelli, Anna, Motta, Michele
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2018
• Subjects: Behaviour tree; Energetic communities; Nanogrid; Power cloud; Prosumages; Prosumages; Behaviour tree; Nanogrid; Energetic communities; Power cloud
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2018.04.082

•A compact nanogrid for home applications is proposed.•A number of power electronic converters are grouped together and connected to the local generators, storage systems, loads.•A central controller governs the nanogrid; it implements the continuous controllers and a decisional process based on behavioural rules.•A behaviour tree models the behavioural rules.•A single-phase 1 kW prototype is subject to: black start, utility failure, utility restore and over generation. This paper proposes a nanogrid for home applications. Compactness, rapid installation and minor changes to the existing equipment are among the basic concepts behind the proposed nanogrid. With this in mind, the authors designed the proposed nanogrid as a compact object. To this aim, the power electronic converters of a typical nanogrid are no longer distributed and placed close to peripherals; they now are grouped together. The electric wires of the local power distribution system connect the grouped converters to the distributed peripherals (e.g. photovoltaic panels, batteries storage systems, loads). As a benefit, when the proposed nanogrid is installed between the meter and the switchboard of an existing dwelling, no significant changes to local equipment, devices and electrical system are required. A central controller governs the proposed nanogrid. Such a controller ensures the power balancing, implementing the continuous controllers of all the power converters belonging to the proposed nanogrid. In addition, such a controller optimizes generation and demand, implementing a decisional process based on behavioural rules. In this paper, a behaviour tree models the behavioural rules. The behaviour tree serves the discrete controller to decide the operation point of the nanogrid. The behaviour tree drives the central controller to pursue strategic targets so as to ensure power supply continuity to critical loads, maximize the exploitation of renewable energy sources and minimize power flow at the point of delivery. This paper also illustrates a single-phase 1 kW prototype of the proposed nanogrid; the prototype is subject to four tests and conditions: black start, utility failure, utility restore and over generation. Besides the capability to pursue the strategic targets mentioned above, the experimental results also demonstrate the proposed nanogrid’s capability to adjust the current imported from the utility grid, to change from grid-connected mode to stand-alone mode and vice versa, to compensate for a surge of the DC bus voltage.