Branch-Parallel Simulated Annealing for Energy-Efficient Multi-Compressor Operation

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Authors: Minjae Kim, Ho-Jin Choi, N. Komuro, Jaeyoung Han, Won-Suk Kim
Cited by: 0

Abstract

The overall energy efficiency of a multi-compressor system varies greatly depending on its operating strategy. In most industrial facilities, the strategy is still determined empirically by operators, which often fails to achieve optimal energy efficiency. The optimization of multi-compressor operation is inherently complex, as it must simultaneously consider various operational factors such as on/off combinations, type-specific flow capacities, and flow constraints. This study proposes a parallel-search simulated annealing algorithm that employs a branch-based exploration mechanism. In the proposed algorithm, multiple search branches independently explore the solution space and periodically exchange information, enabling a broader search and faster convergence than conventional simulated annealing. Simulation results show that the proposed approach reduces total power consumption by about 8% compared with existing heuristic methods while maintaining stable and consistent performance across large-scale scenarios.

Fields of Study & Subjects

Process Optimization and Integration Parallel Computing and Optimization Techniques Advanced Multi-Objective Optimization Algorithms

Publication details

Journal / source
Electronics
Volume
15
Issue
1
Pages
214–214
Publication date
2 January 2026
Language
EN