Economic Model and Simulation Data for Molasses-Based Bioethanol and BDC Framework

Description

This dataset supports the assessment of the economic viability of molasses-based bioethanol in Indonesia and the development of a Biofuel Decarbonisation Certificate (BDC) framework as a market-based policy instrument to accelerate bioethanol deployment. The research hypothesis is that bioethanol adoption is primarily constrained by the persistent price gap with subsidised gasoline, which reduces economic incentives for fuel blending and limits market competitiveness. This study proposes a BDC scheme that leverages the decarbonisation potential of sugarcane molasses while creating incentives across the bioethanol value chain. The framework aims to improve the economic feasibility of bioethanol blending by incorporating carbon value into the biofuel market and addressing existing policy and market barriers. The dataset contains input parameters, model calculations, and simulation outputs used to evaluate three main aspects: (1) the economic viability of molasses-based bioethanol production, (2) BDC pricing requirements and feasible blending pathways, and (3) potential greenhouse gas emission reductions in relation to Indonesia’s Nationally Determined Contribution (NDC) targets. The economic viability of the bioethanol pathway was assessed using net present value (NPV) analysis. The stochastic model incorporated Geometric Brownian Motion (GBM) to represent the uncertainty of bioethanol and molasses prices, with NPV distributions generated through Monte Carlo simulation. The results indicate that while the deterministic assessment suggests a positive NPV, incorporating market volatility significantly changes the economic performance. The stochastic model produces a negative mean NPV, highlighting the high financial risk associated with bioethanol deployment in Indonesia, with an average NPV of −USD 5.4 billion for the E5 blending scenario nationwide. The BDC framework translates the existing price gap between blended biofuels and subsidised gasoline into an equivalent carbon certificate value required to bridge the competitiveness gap. The estimated certificate prices are evaluated against the EU ETS benchmark price of USD 70/tCO₂e, where values below this threshold are considered indicative of economically feasible blending pathways. The result highlights the need for gasoline subsidy reform or alternative policy mechanisms to improve bioethanol market competitiveness. Under a gasoline price scenario of IDR 12,750/L, the analysis identifies E13 as the minimum blending level required to achieve certificate prices below the benchmark threshold. This dataset was compiled from publicly available sources, including Indonesian government reports and policy documents, academic literature, global energy statistics, and emissions reports. The accompanying workbook presents the complete modelling process, covering the research background, input parameters, calculation steps, and final outcomes.

Steps to reproduce

This dataset was compiled from various publicly available sources, including Indonesia’s energy and emission statistics, national energy policies, global energy databases, and relevant literature used to define key modelling assumptions. The development of the dataset followed three main steps. First, background information was collected to describe the current energy situation in Indonesia, including gasoline consumption, fuel import trends, and emission profiles. Second, input parameters required for the economic assessment and modelling framework were gathered, covering technical, economic, and policy-related aspects. Third, the collected data were processed and analysed through the developed models to generate results that support the interpretation of the study findings. All calculations were conducted using Microsoft Excel. The analysis applied several built-in analytical tools, including Goal Seek, sensitivity analysis, and statistical sampling functions to perform the Monte Carlo simulation. The workbook was organised to show the input data, calculation processes, and simulation results, allowing users to follow the modelling approach and reproduce the analysis under different assumptions.

Institutions

• University of Dundee

  Scotland, Dundee

Categories

Funders

• Lembaga Pengelola Dana Pendidikan

  Jakarta, Jakarta

Licence