Energy and industrial networks such as pipeline-based carbon capture and storage infrastructures and (bio)gas infrastructures are designed and developed in the presence of major uncertainties. Conventional design methods are based on deterministic forecasts of most likely scenarios and produce networks that are optimal under those scenarios. However, future design requirements and operational environments are uncertain and networks designed based on deterministic forecasts provide sub-optimal performance. This study introduces a method based on the flexible design approach and the concept of real options to deal with uncertainties during conceptual design of networks. The proposed method uses a graph theoretical network model and Monte Carlo simulations to explore candidate designs, and identify and integrate flexibility enablers to pro-actively deal with uncertainties. Applying the method on a hypothetical network, it is found that integrating flexibility enablers (real options) such as redundant capacity and length can help to enhance the long term performance of networks. When compared to deterministic rigid designs, the flexible design enables cost effective expansions as uncertainty unfolds in the future.
|Journal||Networks and Spatial Economics: a journal of infrastructure modeling and computation|
|Publication status||Published - 2016|
- Energy and industrial networks
- Uncertainty modeling
- Real options
- Graph theory