A hybrid quantum-inspired model for sustainable electrification strategy: An energy-aware planning approach for cost-optimized data centers

Abstract

With growing environmental concerns, optimizing energy utilization in manufacturing workshops has become increasingly important. However, conventional approaches often neglect the potential for cost diminishment inside the power segment. This study proposes a linear programming model specifically designed for optimizing electrical cost. By strategically shifting production to off-peak hours, the model aims to minimize electricity costs while following time constraints. This case study illustrates that this approach can accomplish significant cost reductions and contribute to natural maintainability by reducing greenhouse gas outflows during peak periods. Energy-aware planning is a crucial concept for achieving a better utilization of resources and improving the quality of life in modern data centers. This research represents a valuable step toward economical production and dependable environmental stewardship inside the data center industry. This proactive approach contributes to sustainability goals by promoting more efficient resource utilization and reducing carbon emissions and cost reductions in data center. We assess these strategies using a framework that encompasses the whole control cycle of a real-world situation, using a simulation with actual heterogeneous workloads. The findings collected demonstrate that our strategy is near optimum placement and performs more effectively when the amount of uncertainty escalates. Also this work introduces a quantum-inspired model for improving energy consumption in data centers. The suggested technique integrates workload predictions with intelligent scheduling to save costs and emissions while enhancing the usage of renewable energy. Findings indicate substantial efficiency improvements compared to conventional methods. © 2026 Walter de Gruyter GmbH. All rights reserved.