A methodology for criticality analysis in integrated energy systems

Integrated energy systems (IES) such as polygeneration plants and bioenergy-based industrial symbiosis (BBIS) networks offer the prospect of increased efficiency and reduced carbon emissions. However, these highly-integrated systems are also characterized by the strong interdependence among component units. This interdependency results in the risk of propagation of cascading failures within such networks, where disturbances in the operation of one component results in ripple effects that affect the other units in the system. In this work, a novel criticality index is proposed to quantify the effects of a component unit's failure to run at full capacity within an IES. This index is defined as the ratio of the fractional change in the net output to the fractional change in capacity of the component causing the failure. The component units in the entire system can then be ranked based on this index. Such risk-based information can thus be used as an important input for developing risk mitigation measures and policies. Without this information, risk management based only on network topology could result to counterintuitive results. A simple polygeneration plant and two BBIS case studies are presented to demonstrate the computation of the criticality index.