Scalable supervisory control of building energy systems using generalized gossip
Zhanhong Jiang, Venkatesh Chinde, Adam Kohl, Soumik Sarkar, Atul G. Kelkar · 2016
This paper presents a novel distributed optimization framework to achieve energy efficiency in large-scale buildings. The modular problem formulation presented in this paper decouples the supervisory optimization scheme from the data-driven micro-level modeling aspect leading to significant scalability and flexibility. Recently developed generalized gossip protocol is used as a robust distributed optimization technique. A supervisory control design problem for multi-zone temperature regulation and energy usage minimization is considered as a case study to describe the generic framework. Numerical simulation results, presented based on a physical testbed in the Iowa Energy Center, demonstrate the advantages of the distributed optimization methodology compared to a typical baseline strategy. The paper also outlines a software architecture based on the VOLTTRON platform, recently developed by the Pacific Northwest National Laboratory (PNNL), for real-life implementation of the proposed framework.