A Multi-Agent Control Approach for Optimization of Central Cooling Plants

摘要

This paper presents an application of a multi-agent control approach for supervisory control of large central cooling plants. The starting point for this work was a multi-agent control simulation framework developed by Cai (2015). To adapt the framework to this problem, agents representing the performance of the different devices of the plant were developed and an optimization method capable of handling non-convex functions and discontinuous design spaces was developed and incorporated in the framework. A case study of an existing cooling plant was utilized to evaluate the approach in terms of optimality and computational resources. Simulations were carried out for different performance conditions to predict the performance of the plant under three different control strategies: 1) multi-agent control, 2) centralized optimization based on mathematical programming techniques and 3) a heuristic control strategy. The results showed that significant savings can be achieved through the implementation of multi-agent control. It is expected that, if each hardware component of the plant comes with an integrated agent that represents its behavior, then the proposed multi-agent framework could automatically generate the multi-agent structure and control algorithm after some relatively simple pre-configuration steps. This will reduce the site-specific engineering and will provide a more economic and easy to configure solution for central cooling systems.