Development of a Python-Based Decision Support System for Evaluating Biomass Price Feasibility in Co-Firing Applications: Evidence from Riau, Indonesia

Abstract

The utilization of biomass as a co-firing fuel in coal-fired power plants is a strategic element in Indonesia’s energy transition. A key challenge lies in accurately assessing the price feasibility of biomass fuel (B3m) and ensuring policy compliance. This study presents a Python-based Decision Support System (DSS) equipped with a graphical user interface (GUI) to compute and evaluate the Highest Benchmark Price (HPT) of B3m adaptively, including a maximum price coefficient (k =1.2). The system was tested using 12 actual proposals from B3m suppliers in Riau Province. Results indicate that 58.3% of offers complied with regulatory thresholds, with wood-based B3m proving generally more competitive than palm-based feedstocks. The system enables automated and transparent price feasibility classification. These findings highlight the potential of localized Python-based computational tools to support economic evaluation of renewable energy deployment.