Abstract
EU energy and climate policies continue to drive interest in biomass fuel pellets which can be produced from a wide variety of feedstock. The use of multi-criteria decision analysis (MCDA) to support feedstock selection has the potential for more transparent and better decision-making. This study applies the behavioural TOPSIS, a prominent MCDA technique, to rank pellets for energy use in Sweden produced from under-utilised forest and agricultural biomass. Seven criteria were used to assess and rank the biomass pellets. The alternatives include 88 types of pellets from 11 biomass materials. Possible attitudes of an expert towards the risk of losses (risk averse, risk neutral and risk-seeking) were combined with six sets of criteria weights obtained using six weighting methods – a total of 18 input settings (scenarios). Despite having different input settings, almost identical results were obtained in all scenarios, meaning that the rankings were stable and consistent. Across all 18 scenarios, pellets produced from a reference spruce/pine sawdust blend are ranked ahead of other pellet types. Pellets produced from Scots pine bark exhibited stable and consistent rankings across all scenarios; and thus this biomass is the second-best overall. The next best materials overall are poplar, reed canary grass and wheat straw, whereas torrefied pellets (torrefied beech, poplar and wheat straw) were ranked last in all scenarios. Combining behavioural TOPSIS and a variety of criteria-weighting methods is a meaningful way of improving decision-making with respect to producing a more valid and reliable ranking of biomass fuel pellets for energy use in Sweden.
•The study ranked 88 fuel pellet types from 11 biomass materials for energy use.•Ranking was performed using a MCDA technique, the behavioural TOPSIS.•Rankings of biomass pellets were stable for different sets of criteria weights.•The top-ranked (‘best’) feedstock material was a spruce/pine (55/45%) blend.•Pine bark, poplar, reed canary grass and straw pellets were the next best materials.
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