Flexibility Analysis in Waste-to-Energy Systems based on Decision Rules and Gene Expression Programming

Abstract

This paper proposes a novel approach to generate decision rules, with the goal of analyzing flexibility in waste-to-energy (WTE) systems. The proposed approach integrates the gene expression programming (GEP) algorithm to support decision rule generation processes. It improves existing methodologies by optimizing both the structure and parameters of decision rules. The generated decision rule provides a clear guidance for decision-makers to exercise flexibility in the development of WTE systems. The proposed approach is demonstrated in the context of an anaerobic digestion WTE system. Results show that the economic performance of the system become higher and higher as the generation of the GEP algorithm increases. This result indicates that the proposed approach can effectively find decision rules to support the flexibility analysis process. A sensitivity analysis is further conducted, which has shown that the generated decision rule is able to flexibly adjust decisions when the growth rate of waste generation is changed.