Resilient energy system analysis and planning using optimization models

Imminent climate change impacts call for stronger energy system modeling approaches in order to design resilient communities. This study presents a flexible framework to integrate resilience analysis within the scope of long-term energy system optimization models (ESOMs). It employs a multi-objective resilience metric approach for energy system design, which allows for the independent representation and treatment of resilience and sustainability metrics. Several energy system-characterizing resilience and sustainability metrics are identified and integrated into a composite resilience metric, which is maximized as the objective function in an open-source ESOM. The cost performance of the resulting energy system design is tested across a range of short-term resilience scenarios, capturing different shocks. The method is demonstrated on two municipal case studies (located in China and Ghana). Three energy systems are designed and compared based on cost, emission, and resilience optimization objectives. Results illustrate a wide range of cost impacts depending on the system and resilience scenario. Systems designed based on a resilience objective offer more flexibility to adapt to and absorb shocks, thus reducing damage costs. Case study findings illustrate the value of incorporating resilience analysis into conventional ESOM and energy planning approaches in order to build more resilient communities.