PNNL

Abstract

The optimal operation of communities with on-site photovoltaic (PV) generation and battery storage during power outages remains a challenge. This paper presents a methodology for enhancing community resilience through optimal renewable resource allocation and load scheduling in order to minimize unserved load and thermal discomfort. The proposed decentralized control architecture consists of two layers: The Community Operator Layer (COL) allocates the limited amount of renewable energy resource according to the power flexibility of each building. The Building Agent Layer (BAL) addresses the optimal load scheduling problem for each building with the allowable load determined by the COL. Both layers are formulated as a model predictive control (MPC) based optimization. At the COL, three resource allocation methods are investigated: equally weighted, weighted based on building priority, and weighted based on building occupancy. At the BAL, two objective functions are compared: minimizing unserved load ratio or maximizing thermal comfort. The results indicate that the impact of power flexibility is more prominent than the weighting factor to the resource allocation process. Allocation purely based on occupancy status could lead to unfair allocation. Further, we found that it is necessary for the building agent to have multi-objective optimization to minimize unserved load ratio and maximize comfort simultaneously. This will bring the benefit of less curtailment, smaller unserved load ratio, assured thermal comfort, as well as smaller battery size.