Dual-layer optimization design method for collaborative benefits of renewable energy systems in building clusters: Case study of campus buildings

Abstract

Renewable energy sharing effectively enhances the collaborative benefits of building clusters. Distributed photovoltaic (PV) generation is the most widely applied renewable energy method for building clusters due to its high space utilization and broad applicability. However, the majority of building cluster planning and energy storage system designs tend to neglect the impact of energy sharing potential, thereby leading to limited improvements in cluster-level benefits and oversized storage capacity. Therefore, we propose a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Firstly, the building cluster is randomly divided into Clustered Building Groups (CBGs). Secondly, linear programming (LP) is applied in the under-layer to optimize the shared energy storage capacity for each CBG. Finally, the upper-layer utilizes NSGA-II and TOPSIS to identify the optimal grouping scheme. Case studies on a building cluster showed that compared with two existing design methods, the proposed design could maximize the energy sharing potential, significantly improve the building cluster’s performance, and reduce the energy storage capacity. Specifically, it achieved the highest TOPSIS score of 0.673, reduced the electricity purchase cost by 4.6 %, increased PV self-consumption by 15.4 %, reduced the storage capacity by 17.4 %, and shortened the payback period from 9.31 years to 4.33 years. These results suggest that employing similar procedures can be advantageous in achieving energy autonomy for building clusters.