Managing the moisture content of wood biomass for the optimisation of Ireland's transport supply strategy to bioenergy markets and competing industries

• Published in: Energy (Oxford) 2015-06, Vol.86, p.354-368
• Main Authors: Sosa, Amanda, Acuna, Mauricio, McDonnell, Kevin, Devlin, Ger
• Format: Article
• Language: English
• Subjects: Biomass; Biomass allocation; Biomass energy production; Competing demands; Electric power plants; Ireland; Mathematical models; Moisture content; Optimization; Peat; Spatial distribution; Transportation supply optimisation; Wood
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2015.04.032

The aim of this study was to analyse the supply of wood biomass (short wood) to the three peat power plants in Ireland and the impacts on the competing wood-based panel industries. The methodology includes the development of a spatial decision support tool based on LP (Linear Programming). It uses drying curves to assess the moisture content, weight and energy content of biomass during a two year period planning. Harvesting, chipping, storage and transportation costs are calculated based on the biomass moisture content. The model optimally allocates woodchips and logs from thinnings and clearfells. Results show that the planned maximum 30% co-firing rate at the three peat power station could be met with the forecasted short wood availability from both the private and public sector. The costs of supply increased not only with higher demands, but also with tighter constraints on the MC demanded by power plants. Spatial distribution and operational factors such as efficiency in transportation and truck loading showed to be sensitive to changes in MC. The analysis shows the benefits of managing the MC when optimising supply chains in order to deliver biomass to energy plants in a cost-effective manner. •Linear programming model was developed to optimise biomass supply chain in Ireland.•Drying curves to assess the moisture, weight, energy of biomass over two years.•Harvesting, chipping, storage, transportation costs were examined based on moisture.•Supply impacts of competing markets for biomass were analysed with varying moisture.•Model aids decision making on harvest, storage and optimal truck loads for dispatch.