Optimization of Investments for Strategic Process Integration and Pulp Mill Biorefinery Projects under Uncertainty

University dissertation from Chalmers University of Technology

Abstract: Energy-intensive industrial plants operate in a changing, uncertain environment. Long-term changes are expected in energy prices, political regulations and technology development. Pulp and paper companies, like many other industries, are under strong pressure to respond to these changes. At the same time, there are many opportunities connected to the changing conditions for these companies thanks to their control and experience of the wood biomass resource. These opportunities include the production of green electricity, wood fuels, and district heating, as well as emerging biorefinery products such as green transportation fuels, chemicals and biomaterials. However, uncertainty regarding future energy market conditions and the development of emerging biorefinery processes inevitably makes the decision between competing technologies difficult. Process integration is a requirement for the successful implementation of pulp mill biorefinery concepts. This thesis presents a systematic methodology for the optimization of investments in process integration under energy market and technology uncertainty with applications to strategic pulp mill biorefinery projects. The methodology is based on multistage stochastic programming and allows for investments at multiple points in time. Decisions are modelled to be made before knowing the outcome of the future energy market development; thereby incorporating the energy market uncertainties explicitly in the optimization model. The investment plan that maximizes the expected net present value can then be obtained given the assumed probabilities of the different energy market developments. Scenarios are also proposed for the analysis of different investment cost developments of emerging pulp mill biorefinery technologies. As illustrated in this thesis, change, flexibility and lock-in effects are strongly connected. The proposed models capture, among other things, the value of the flexibility needed to avoid future lock-in situations; a value which, as shown, can be significant. The thesis also discusses the flexibility lost due to long lead times. The case studies show that for many mills there is traditional technology available that should be invested in today. Some of today’s investment opportunities will, however, lead to lock-in effects if implemented. It is therefore important to evaluate both current and future investment projects in the same optimization model, thereby enabling the identification of the investments that can be cost-effectively implemented today while retaining the opportunity for more far-reaching, future projects. The methodology proposed in this thesis, which is used to identify the investments that are optimal under uncertainty, can thus yield an improved understanding of how investments made today affect later investment opportunities in a long-term perspective.

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