Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

ABSTRACT

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.

KEYWORDS:

• Forest biomass
• bioenergy
• Monte Carlo Simulation
• uncertainty
• optimization
• supply chain management
• biomass quality

Acknowledgment

The authors sincerely thank the Fiber Supply Manager and Finance Manager for their time and support in providing the required data and information for our modeling and validating our results.

Funding

The authors would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for providing the funding for this research. The authors also acknowledge the partial funding provided by the power plant.

Additional information

Funding

The authors would like to thank the Natural Sciences and Engineering Council of Canada (NSERC) for providing the funding for this research. The authors also acknowledge the partial funding provided by the power plant.