EURO 2024 Copenhagen
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450. Multi-Objective Energy-Aware Scheduling: A Memetic Two-Phase Evolutionary Approach incorporating Real-Time Energy Market, on-site Generation, and Storage Systems

Invited abstract in session TB-19: The role of storage in energy problems, stream OR in Energy.

Tuesday, 10:30-12:00
Room: 44 (building: 116)

Authors (first author is the speaker)

1. Sascha C Burmeister
Department of Management Information Systems, Paderborn University
2. Daniela Guericke
Department of Industrial Engineering and Business Information Systems, University of Twente
3. Guido Schryen
Department of Management Information Systems, Paderborn University

Abstract

Dynamic energy tariffs and on-site energy generation offer manufacturers new opportunities to optimize their energy consumption. In addition to conventional goals such as minimizing makespan, manufacturers can focus on minimizing energy costs or emissions. However, scheduling processes in the face of uncertain future energy prices and emissions is a major challenge. Energy storage systems (ESS) can compensate for differences between predicted and actual energy costs and emissions. To make an investment decision for ESS, decision makers need to assess their impact on energy costs and emissions, as well as their return on investment. In the literature, the Green Flexible Job Shop Scheduling Problem (FJSP) is concerned with resource and environmental aspects in addition to economic objectives. However, existing approaches neglect the combination of a multi-criteria objective with an uncertain dynamic energy mix and the use of ESS. We propose a two-phase approach based on a memetic NSGA-III and mathematical programming with the goal of minimizing a schedule’s makespan, energy costs, and emissions, incorporating dynamic energy prices and emissions, on-site generation, and ESS. We evaluate the approach using FJSP benchmark instances from literature as part of a rolling horizon approach with real energy market data. We investigate the impact of ESS by presenting estimated Pareto fronts, showing potential savings in energy cost and carbon emissions.

Keywords

Status: accepted

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