Developing a decision framework for the strategic sourcing of biomass

摘要: The deployment of bioenergy technologies is a key part UK and European renewable energy policy. A barrier to the management biomass supply chains including evaluation suppliers contracting biomass. In undeveloped for market buyers are faced with three major challenges during development new projects. What characteristics will certain have, how evaluate which contract in order provide portfolio that best satisfies needs project its stakeholder group whilst also satisfying crisp non-crisp technological constraints. problem description taken from situation by industrial partner this research, Express Energy Ltd. This research tackles these areas separately then combines them form decision framework assist strategic sourcing BioSS framework. consists modes mirror stages BioSS.2 mode early stage development, BioSS.3 financial close BioSS.Op operational phase project. formed fuels library, supplier module an allocation module, Monte-Carlo analysis included accuracy recommended portfolios. each can recommend should be contracted much material purchased each. blend have chemical within constraints conversion technology satisfy group. library made up wide variety sources contains around 100 unique descriptions potential developer may encounter. takes data collection approach has aim allowing estimates without expensive time consuming testing. uses QFD-AHP method give importance weightings 27 different evaluating criteria. criteria been compiled interviews stakeholders policy position documents assigned using mixture workshops expert interview. weighted scores allow better tailor their business offering provides robust makers understand requirements groups. chance-constrained programming assign orders between based on those preference score suppliers. optimisation program finds allocate highest performance eyes complying breached if maker requires setting constraint as chance-constraint. allows wider range procured greater overall realised than considering or deterministic approaches. demonstrated against two scenarios developers. first large scale combustion power project, second small gasification Bioss applied both shown adapt solution finding globally optimal satisfaction.