The demand for faster and more efficient supply chain operations has increased the need for higher performance in warehouse management, particularly in material handling (MH) activities. MH processes contribute significantly to warehouse energy consumption, particularly in forklifts, where battery charging can account for 40-50% of total energy usage in ambient-temperature warehouses. This underscores the necessity for energy-efficient charging strategies that do not compromise warehouse operational activities. Although the topic is of increasing relevance, the literature lacks decision-making tools for both academics and practitioners. To address this challenge, this study proposes a decision support system (DSS) to evaluate the optimal charging strategy for electric forklifts, considering both opportunity charging (OC) and battery energy storage system (BESS) integration. OC aims to leverage photovoltaic (PV) surplus energy during peak generation periods, while BESS aims to store surplus energy and optimize charging times. For the selection of optimal charging strategy, the study follows a three-phase methodology: data collection, charging strategy evaluation, and scenario selection. In the data collection phase, information on warehouse operations, energy consumption, and energy production from PV panels are gathered. OC and BESS integration are then assessed economically and environmentally. Finally, the developed DSS assists facility managers in selecting the most suitable charging strategy based on their specific warehouse characteristics and operational requirements. Findings suggest that the optimal charging strategy depends on multiple warehouse features such as operational tasks and solar energy surplus. On one hand, OC is effective in facilities with high PV generation and predictable energy demand patterns. On the other hand, BESS integration offers flexibility for facilities with more variable energy demands. This study contributes to the advancement of green warehousing concept by providing a systematic approach to evaluating and implementing energy-efficient forklift charging strategies. Implications are discussed and streams for future investigation are reported.
Pioneering Green and Energy -Efficient Material Handling: A Decision Support System for Battery Charging Strategy Selection in Warehouse Operations
L. Cannava;S. Perotti
2024-01-01
Abstract
The demand for faster and more efficient supply chain operations has increased the need for higher performance in warehouse management, particularly in material handling (MH) activities. MH processes contribute significantly to warehouse energy consumption, particularly in forklifts, where battery charging can account for 40-50% of total energy usage in ambient-temperature warehouses. This underscores the necessity for energy-efficient charging strategies that do not compromise warehouse operational activities. Although the topic is of increasing relevance, the literature lacks decision-making tools for both academics and practitioners. To address this challenge, this study proposes a decision support system (DSS) to evaluate the optimal charging strategy for electric forklifts, considering both opportunity charging (OC) and battery energy storage system (BESS) integration. OC aims to leverage photovoltaic (PV) surplus energy during peak generation periods, while BESS aims to store surplus energy and optimize charging times. For the selection of optimal charging strategy, the study follows a three-phase methodology: data collection, charging strategy evaluation, and scenario selection. In the data collection phase, information on warehouse operations, energy consumption, and energy production from PV panels are gathered. OC and BESS integration are then assessed economically and environmentally. Finally, the developed DSS assists facility managers in selecting the most suitable charging strategy based on their specific warehouse characteristics and operational requirements. Findings suggest that the optimal charging strategy depends on multiple warehouse features such as operational tasks and solar energy surplus. On one hand, OC is effective in facilities with high PV generation and predictable energy demand patterns. On the other hand, BESS integration offers flexibility for facilities with more variable energy demands. This study contributes to the advancement of green warehousing concept by providing a systematic approach to evaluating and implementing energy-efficient forklift charging strategies. Implications are discussed and streams for future investigation are reported.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
