Comparing Approaches to Distributed Control of Fluid Systems based on Multi-Agent Systems
Kevin T. Logan, J. Marius St\"urmer, Tim M. M\"uller, Peter, F. Pelz

TL;DR
This paper compares three multi-agent system approaches—DMPC, MADRL, and market mechanisms—for distributed control of fluid systems, highlighting their performance, robustness, and energy efficiency benefits over traditional methods.
Contribution
It provides a comparative analysis of three innovative distributed control strategies for fluid systems, demonstrating their effectiveness and trade-offs.
Findings
All approaches meet functionality requirements.
DMPC and MADRL are more disruption-resistant than market mechanisms.
Energy efficiency approaches centralized optimal control levels.
Abstract
Conventional control of fluid systems does not consider system-wide knowledge for optimising energy efficient operation. Distributed control of fluid systems combines reliable local control of components while using system-wide cooperation to ensure energy efficient operation. The presented work compares three approaches to distributed control based on multi-agent systems, distributed model predictive control (DMPC), multi-agent deep reinforcement learning (MADRL) and market mechanism design. These approaches were applied to a generic fluid system and evaluated with regard to functionality, energy efficient operation, modeling effort, reliability in the face of disruptions, and transparency of control decisions. All approaches were shown to fulfil the functionality, though a trade-off between functional quality and energy efficiency was identified. Increased modeling effort was shown to…
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Taxonomy
TopicsSmart Grid Energy Management · Climate Change Policy and Economics · Fuel Cells and Related Materials
