Analyzing the disruption resilience of bioenergy parks using dynamic inoperability input–output modeling

• Main Authors: Benjamin, Michael Francis D., Ubando, Aristotle T., Razon, Luis F., Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2015
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/939; https://animorepository.dlsu.edu.ph/context/faculty_research/article/1938/type/native/viewcontent
• Institution: De La Salle University

© 2015, Springer Science+Business Media New York. Bioenergy parks are low-carbon industrial symbiosis networks that are comprised of biomass processing plants. However, such highly integrated energy systems are inherently vulnerable to capacity disruptions. The strong interdependencies among component plants in a bioenergy park decrease system resilience due to cascading failure effect. The consequences of such disruptions are even greater if the critical components are damaged. Resilience is defined as the ability of an energy system to withstand a disruption and subsequently recover to its normal state. In this work, a disruption resilience framework is developed to analyze the resilience of bioenergy parks against an array of capacity disruption scenarios. This framework is derived from dynamic inoperability input–output modeling previously used in economic and critical infrastructure systems. A microalgal multi-functional bioenergy system case study is presented to demonstrate the applicability of the resilience framework. The example shows that the resilience of a bioenergy park is influenced by both the recovery time of component plants and their degree of connectivity within the network; such insights can be used for planning more disruption-resilient bioenergy parks.