[Paper Review] Integrated Investment and Operational Planning for Sugarcane-Based Biofuels and Bioelectricity under Market Uncertainty

Carolina Monteiro, Bruno Fanzeres+5 more|arXiv (Cornell University)|Mar 6, 2026

Capital Investment and Risk Analysis0 citations

TL;DR

This paper develops a two-stage stochastic optimization model that integrates investment and operational decisions for sugarcane biomass facilities under price and feedstock uncertainty, and provides an open-source implementation (OptBio).

ABSTRACT

Sugarcane biomass is a strategic resource for the energy transition, particularly in Brazil, where it underpins electricity and ethanol production. Investment planning is challenged by diverse production pathways, price volatility, and feedstock variability. This work develops a two-stage stochastic optimization model integrating investment and operational decisions for sugarcane facilities. The model aims to support robust planning for diversified biomass plants, aiding the sector's decarbonization. The first stage defines capacity expansion under economies of scale through a power-law cost function. The second stage defines operational decisions under price and feedstock uncertainty, modeled via scenarios and Conditional Value-at-Risk. \answer{From an investor's perspective, the objective is to minimize risk-adjusted net costs. In addition to its methodological contributions, this work also provides an open-source implementation of the proposed capacity expansion planning framework, referred to as extit{OptBio}.} A Brazilian case study shows risk-neutral strategies favor sugar/ethanol but are vulnerable, whereas risk-averse strategies promote diversification. Sensitivity analyses indicate biomethane and hydrogen may become viable with favorable prices, while biochar boost productivity and profitability.

Motivation & Objective

• Balance investment costs with risk-adjusted operational expenditures for sugarcane biomass facilities under price and availability uncertainty.
• Capture nonlinear economies of scale in capital expenditures when expanding capacity.
• Represent a wide range of sugarcane-derived products and processes beyond basic outputs like sugar and ethanol.
• Provide an open-source capacity expansion framework to enable reproducibility and broader application.

Proposed method

• Formulate a two-stage stochastic program where the first stage selects capacity expansion under economies of scale using a capsulated power-law cost function.
• Second stage optimizes yearly operations given capacities and scenario realizations, minimizing net costs via unit costs of inputs and revenues from sold products.
• Represent uncertainty with scenario sets for prices and product availability and use CVaR to measure risk, blending expected cost and tail risk.
• Use a piecewise linear approximation with binary variables to linearize the economy-of-scale relation for tractable solution.
• Reformulate the two-stage problem into an equivalent scenario-based MILP suitable for standard solvers.
• Provide an open-source Julia/JuMP implementation named OptBio with data stored in SQLite.

Experimental results

Research questions

• RQ1 How should capacity be expanded for sugarcane biomass facilities when facing price and feedstock uncertainty?
• RQ2 What is the impact of incorporating CVaR-based risk preferences on investment and operation decisions?
• RQ3 Which production routes (e.g., biomethane, hydrogen, biochar) become attractive under risk considerations?
• RQ4 How can nonlinear economies of scale in CAPEX be accurately represented in a tractable optimization model?

Key findings

• Risk-neutral strategies tend to favor sugar/ethanol but are vulnerable to price swings.
• Risk-averse strategies promote diversification, improving the risk–return trade-off.
• Biomethane and hydrogen may become viable with favorable prices.
• Biochar can boost productivity and profitability; waste-to-energy pathways add revenue streams.
• An open-source OptBio implementation enables reproduction and broader use of the framework.