Warehouse operations are increasingly scrutinised for their contribution to greenhouse gas emissions. The adoption of Electric Vehicles (EVs), renewable energy sources, and Energy Storage Systems (ESS) represents an energy-efficient strategy to reduce the environmental impact of warehouses. In this context, designing an Energy Management System (EMS) is crucial to optimising energy use and enhancing sustainability. This paper proposes a novel framework that jointly schedules daily warehouse operations (including sequencing of storage and retrieval tasks, assigning tasks to fuel-based vehicles or EVs, and vehicle routing) and manages energy flows among photovoltaic panels, ESS, power grid, and EV charging station. A Mixed Integer Linear Programming model is proposed to address this integrated planning problem. Computational experiments in realistic situations under sunny and cloudy weather conditions demonstrate the effectiveness of the proposed formulation. The results highlight the importance of integrating renewables, EMS, and warehouse operations to reduce costs and support sustainable warehouse operations. Moreover, a very fast matheuristic algorithm is proposed to efficiently solve large and real-scale instances. Dedicated experiments on a real case study confirm the capability of the approach to deliver fast and high-quality solutions in industrial case scenarios.

Integrating Energy Management Systems and Renewable Energy Sources in Green Warehouses: The Energy-Aware Green Sequencing and Routing Problem

Leena Aizdi
Primo
;
Giacomo Lanza
Secondo
;
Maria Grazia Scutellà;
2026-01-01

Abstract

Warehouse operations are increasingly scrutinised for their contribution to greenhouse gas emissions. The adoption of Electric Vehicles (EVs), renewable energy sources, and Energy Storage Systems (ESS) represents an energy-efficient strategy to reduce the environmental impact of warehouses. In this context, designing an Energy Management System (EMS) is crucial to optimising energy use and enhancing sustainability. This paper proposes a novel framework that jointly schedules daily warehouse operations (including sequencing of storage and retrieval tasks, assigning tasks to fuel-based vehicles or EVs, and vehicle routing) and manages energy flows among photovoltaic panels, ESS, power grid, and EV charging station. A Mixed Integer Linear Programming model is proposed to address this integrated planning problem. Computational experiments in realistic situations under sunny and cloudy weather conditions demonstrate the effectiveness of the proposed formulation. The results highlight the importance of integrating renewables, EMS, and warehouse operations to reduce costs and support sustainable warehouse operations. Moreover, a very fast matheuristic algorithm is proposed to efficiently solve large and real-scale instances. Dedicated experiments on a real case study confirm the capability of the approach to deliver fast and high-quality solutions in industrial case scenarios.
2026
Aizdi, Leena; Lanza, Giacomo; Passacantando, Mauro; Scutella', Maria Grazia; Siri, Silvia; Bracco, Stefano
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1299187
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact