Stochastic modeling of fuel procurement for electricity generation with contractual terms and logistics constraints

Abstract

This work addresses the procurement of fuel to supply an uncertain demand for electricity generation. Fuel purchase decisions are made with considerable advance with respect to reception. Changes in demand determine corrective decisions and associated costs, such as advance decisions on delay or cancellation of contracts in order to meet storage and logistics constraints. We present a multi-stage stochastic programming model for the problem. Uncertainty is modeled as a discrete event tree of scenarios. Three heuristic strategies, relax and fix, rolling horizon and scenario aggregation, are proposed and applied to three case studies. Results show that when delay or cancellation decisions are taken in advance of the reception period, the relax and fix strategy performs better in terms of quality of the solution and processing time. The methodology allows to model relevant aspects of the problem and proposes a robust procurement decision that hedges uncertainty and establishes corrective actions.