A Co-Design Optimal Sizing and Control Framework to Balance Cost and Resilience

Traditional design approaches for community energy systems often overlook the strong coupling between component sizing and control strategies. Most bi-level optimization frameworks treat sizing in an upper layer and controls in a lower layer, which can lead to suboptimal designs. At the same time, communities face increasing power outages and rising electricity costs, highlighting the need for resilient and cost-effective solutions. This paper presents a co-design optimization framework that simultaneously determines system sizing and control strategies to balance cost and resilience. The framework uses a Modelica model whose parameters are updated for each design option, allowing for the efficient evaluation of multiple configurations. The framework is demonstrated using a representative community energy system consisting of photovoltaic (PV) generation, a battery energy storage system (BESS), aggregated building electrical loads, and a grid connection. Resilience was assessed using three representative outage scenarios derived from historical outage data in Tampa, Florida. Each scenario reflects different levels of grid disruption. A cost-resilience index was used as the optimization objective, normalizing life-cycle cost (LCC) and critical unserved load (CUL) relative to a no-battery baseline. To benchmark performance, the co-design results were compared against a Pareto frontier generated by exhaustive search. The framework successfully identified Pareto-optimal solutions across cost-focused, resilience-focused, and balanced designs. A balanced configuration increased LCC by less than 11% relative to the baseline while reducing CUL by up to 92%, demonstrating the framework's ability to provide high-quality design options that support informed stakeholder decisions on cost-resilience trade-offs.