An optimised supply chain produces competitively priced forest energy – annual savings for fuel suppliers and power plants amount to hundreds of thousands.
The recent study that Miktech Oy commissioned from Ramboll Finland showed that if heat and power plants that burn forest chips acquire the chips from optimised supply chains, they can get better quality chips and lower their total acquisition costs.
Source: Ramboll Oy 2014
The optimised supply chain includes comprehensive and real-time management features for biomass, resources and conditions. – The higher quality of the forest chips, especially in terms of their moisture and homogeneity, will affect the economic efficiency and profitability of heat and power plants, says Ramboll Finland Oy’s Business Manager Mirja Mutikainen. – The most concrete benefits will be in fuel economy, boiler efficiency and other energy production costs. The plants will also benefit from fewer production outages and decreased operating and maintenance costs.
Forest lots used for harvesting energy wood will yield more energy, costs for transportation and intermediate storage will decrease, the acquisition process will become more efficient for suppliers and plants, and the availability of wood will improve. The supply chain will also become more interactive, which improves its reliability and continuity. Delivery chains can also be traced and controlled. – Looking at the bigger picture, an optimised overall solution can improve the competitiveness of forest chips as a fuel and the general competitiveness of bioenergy.
The study also developed a simulation model to demonstrate the benefits for fuel suppliers and power plants. This model provides, in euros, the estimated added value of an optimised supply chain producing high-quality wood fuel. A supply chain used to supply fuel for a 50,000 MWh woodchip plant would bring more than EUR 400,000 of savings in harvesting and transportation costs. Cost savings for the plant would amount to up to EUR 200,000 or even more. This model is based on previous studies and the chip quality factors and their effects which were evaluated in this latest study.
Ramboll’s study shows that current practices can be improved quite dramatically. “On the other hand, it also shows that solutions are available in the market”, says Sales Manager Mika Muinonen from Inray Oy and the MHG Systems CEO Seppo Huurinainen, who are both involved in the Cleantech Finland Bioenergy project coordinated by Miktech Oy. Inray Oy provides online measurement technology for quality assurance purposes. If fuel suppliers and power plants so desire, they can monitor the costs and fuel quality of each felling site, contractor, storage and load in real time. The MHG Biomass Manager Service fulfils the data management requirements of an optimised supply chain in real time, promises Huurinainen.
For more information about this media release:
Mirja Mutikainen Business Manager, Energy and Bioeconomy Ramboll Finland Oy, tel.: +358 50 3141521
Seppo Huurinainen, CEO, tel.: +358 44 581 4950
Ramboll is a leading international expert organisation and Finland’s largest engineering, design and consultancy company. Our foundation-owned company employs more than 12,500 professionals worldwide. Our Finnish operations employ 1,900 experts. We offer expert consultation services for designing, constructing, building and maintaining infrastructures, buildings, environments and energy solutions, and also for management consulting. Our objective is to create solutions that genuinely improve how the whole of society works. Our success is based on our skilled and visionary personnel.
About MHG Systems
MHG Systems is a pioneer in developing the most complete information sharing and communication platform – MHG Biomass Manager – for bioenergy production processes. Our mission at MHG Systems is to bring efficiency gains, cost savings and environmental benefits to all operators in the biomass business value chain, enabling optimization of material and human resources and facilitating operation of more complex business models.
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