Matching Industry 5.0 and Renewable Energy Integration: an optimization approach for robotic warehouses

This paper presents a methodology to embed Industry 5.0 principles in the preliminary design of the photovoltaic (PV) system with battery energy storage (BESS) in robotic warehouses. The desired sustainability and resilience performances are translated into optimisation constraints on self-consumption, self-sufficiency, and net-zero. The PV-BESS system is sized at minimum cost using an untapped approach which combines Constraint Programming and procedural computation to speed up the process. The multidimensional performance mapping of current and alternative solutions allows to study the trade-off of economic, sustainability, and resilience indicators. Energy demand of material handling equipment is then redistributed adopting micro-charges to enhance self-consumption, assessing further potential gains of the candidate solution. The methodology was validated with a case study, where PV size was aligned to the upper bound of net zero ratio, while BESS was kept to the minimum to satisfy 40% of self-consumption, improvable to 56% by demand response.

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Publication Details

Journal
Procedia Computer Science
Published
2026-01-01
DOI
https://doi.org/10.1016/j.procs.2026.02.049
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Matching Industry 5.0 and Renewable Energy Integration: an optimization approach for robotic warehouses

Antonella Meneghetti, Fabio Tardivo, Simone Bellan, Edoardo Cuzzolin
Procedia Computer Science
Smart Grid Energy Management
article

Matching Industry 5.0 and Renewable Energy Integration: an optimization approach for robotic warehouses

Antonella Meneghetti, Fabio Tardivo, Simone Bellan, Edoardo Cuzzolin
article en

Abstract

This paper presents a methodology to embed Industry 5.0 principles in the preliminary design of the photovoltaic (PV) system with battery energy storage (BESS) in robotic warehouses. The desired sustainability and resilience performances are translated into optimisation constraints on self-consumption, self-sufficiency, and net-zero. The PV-BESS system is sized at minimum cost using an untapped approach which combines Constraint Programming and procedural computation to speed up the process. The multidimensional performance mapping of current and alternative solutions allows to study the trade-off of economic, sustainability, and resilience indicators. Energy demand of material handling equipment is then redistributed adopting micro-charges to enhance self-consumption, assessing further potential gains of the candidate solution. The methodology was validated with a case study, where PV size was aligned to the upper bound of net zero ratio, while BESS was kept to the minimum to satisfy 40% of self-consumption, improvable to 56% by demand response.

Procedia Computer ScienceVol. 277
New Mexico State University (US), University of Udine (IT)
Openalex Percentile: Top 12%
Smart Grid Energy Management
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