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

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.

[1]  Khalid Rehman Hakeem,et al.  Biomass and Bioenergy , 2014, Springer International Publishing.

[2]  Lauri Sikanen,et al.  Predicting and Controlling Moisture Content to Optimise Forest Biomass Logistics , 2012 .

[3]  Eija Alakangas European Standards for Fuel Specification and Classes of Solid Biofuels , 2011 .

[4]  Deng Guang-chang,et al.  Renewable energy in Ireland , 2012 .

[5]  Rodrigo A. Garrido,et al.  Forestry production and logistics planning: an analysis using mixed-integer programming , 2005 .

[6]  Peter Rauch,et al.  Stochastic simulation of forest fuel sourcing models under risk , 2010 .

[7]  Ger Devlin,et al.  Energy Regulations: A Case for Peat and Wood Fibre in Ireland. , 2014 .

[8]  T. Ranta Logging residues from regeneration fellings for biofuel production - a GIS-based availability analysis in Finland. , 2005 .

[9]  Martin Anheller,et al.  Biomass losses during short-term storage of bark and recovered wood , 2010 .

[10]  Mikael Rönnqvist,et al.  Supply chain modelling of forest fuel , 2004, Eur. J. Oper. Res..

[11]  Tomas Gullberg,et al.  Transport and handling of forest energy bundles—advantages and problems , 2006 .

[12]  Michael Wallace,et al.  The influence of a Renewable Energy Feed in Tariff on the decision to produce biomass crops in Ireland , 2012 .

[13]  Mikael Rönnqvist,et al.  Tactical supply chain planning for a forest biomass power plant under supply uncertainty , 2014 .

[14]  Bruce Talbot,et al.  Road transport of forest chips: containers vs. bulk trailers. , 2006 .

[15]  Michela Robba,et al.  Optimizing forest biomass exploitation for energy supply at a regional level , 2004 .

[16]  Ilias P. Tatsiopoulos,et al.  An optimization model for multi-biomass tri-generation energy supply , 2009 .

[17]  Ljusk Ola Eriksson,et al.  Optimal storing, transport and processing for a forest-fuel supplier , 1989 .

[18]  Bernd Möller,et al.  Least-cost allocation strategies for wood fuel supply for distributed generation in Denmark – a geographical study , 2003 .

[19]  Mikael Rönnqvist,et al.  Cost Allocation in Collaborative Forest Transportation , 2006, Eur. J. Oper. Res..

[20]  Mikael Rönnqvist,et al.  Optimization in forestry , 2003, Math. Program..

[21]  Ger Devlin,et al.  Deriving Cooperative Biomass Resource Transport Supply Strategies in Meeting Co-Firing , .

[22]  P. Flynn,et al.  Biomass power cost and optimum plant size in western Canada , 2003 .

[23]  Sandro Macchietto,et al.  Integrated biomass and solar town: Incorporation of load shifting and energy storage , 2014 .

[24]  P. D. Kofman,et al.  Harvesting wood for energy. Cost-effective woodfuel supply chains in Irish forestry. , 2011 .

[25]  Patrick Hirsch,et al.  Co-operative forest fuel procurement strategy and its saving effects on overall transportation costs , 2010 .

[26]  Ulrich J. Wolfsmayr,et al.  The primary forest fuel supply chain: a literature review. , 2014 .

[27]  Peter C. Flynn,et al.  The impact of feedstock cost on technology selection and optimum size. , 2007 .

[28]  Glen Murphy,et al.  Modeling Air Drying of Sitka Spruce (Picea sitchensis) Biomass in Off-Forest Storage Yards in Ireland , 2012 .

[29]  Karl Stampfer,et al.  Regional energy wood logistics - optimizing local fuel supply. , 2009 .

[30]  Hans Ivar Skjelbred,et al.  Linear mixed-integer models for biomass supply chains with transport, storage and processing , 2010 .

[31]  Brian Tobin,et al.  Stocks and decay dynamics of above- and belowground coarse woody debris in managed Sitka spruce forests in Ireland , 2011 .

[32]  A. Faaij,et al.  Efficiency and economy of wood-fired biomass energy systems in relation to scale regarding heat and power generation using combustion and gasification technologies , 2001 .

[33]  M. Daly,et al.  GIS-based biomass resource assessment with BRAVO , 1996 .

[34]  Mikael Rönnqvist,et al.  Using Operational Research for Supply Chain Planning in the Forest Products Industry , 2008, INFOR Inf. Syst. Oper. Res..

[35]  B. Thorsen,et al.  Allocation of biomass resources for minimising energy system greenhouse gas emissions , 2014 .

[36]  Hongwei Wu,et al.  Mallee Biomass as a Key Bioenergy Source in Western Australia: Importance of Biomass Supply Chain , 2009 .

[37]  C. Gallis,et al.  Activity oriented stochastic computer simulation of forest biomass logistics in Greece , 1996 .

[38]  Ralph E.H. Sims,et al.  Delivery systems of forest arisings for energy production in New Zealand. , 2001 .

[39]  Jiří Jaromír Klemeš,et al.  Minimising carbon footprint of regional biomass supply chains , 2010 .

[40]  Ali Azadeh,et al.  A stochastic programming approach towards optimization of biofuel supply chain. , 2014 .

[41]  A. Pérez-Navarro,et al.  Methodology for optimization of distributed biomass resources evaluation, management and final energy use , 2009 .

[42]  Wim Turkenburg,et al.  Technological learning and cost reductions in wood fuel supply chains in Sweden , 2005 .

[43]  E. Gnansounou,et al.  GIS-based approach for defining bioenergy facilities location: A case study in Northern Spain based on marginal delivery costs and resources competition between facilities , 2008 .

[44]  Erik Trømborg,et al.  Forest sector impacts of the increased use of wood in energy production in Norway. , 2010 .