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Energies 2016, 9(3), 155;

Adaptive Procurement Guidelines for Automatic Selection of Renewable Forest Energy Sources within a Sustainable Energy Production System

Faculty of Science and Forestry, University of Eastern Finland, P.O. Box 111, Joensuu FI-80101, Finland
Stora Enso Wood Supply Finland, P.O. Box 309, Helsinki FI-00101, Finland
Author to whom correspondence should be addressed.
Academic Editor: Dimitris S. Argyropoulos
Received: 31 December 2015 / Revised: 22 February 2016 / Accepted: 25 February 2016 / Published: 3 March 2016
(This article belongs to the Special Issue Energy from Forest Biomass)
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An automatic forest-stand selection method was developed that integrates the procurement of profitable energy sources within a sustainable energy production system. We tested the method using a forest harvester simulator. We found that site-specific estimates of forest characteristics are important when predicting the potential of an energy-wood stand as a renewable energy source. Further, tree parameters can be combined with automatic stem measurements from a multiple-tree harvester to predict the energy-wood biomass in the stands. The selection process uses data from profitability studies. The selection process also uses environmental criteria to ensure that sufficient soil organic matter is left behind and to protect the soil against erosion. The integrated system of the harvester automatically adapts the system’s models and stand-selection rules to account for various site-specific stand parameters. Predicting the profitable and environmentally acceptable yield of stand biomass has great potential in sustainable forest resource management, but managers must decide whether the operational procurement guidelines provided by the stand-selection method is acceptable under their local real-world wood procurement conditions. View Full-Text
Keywords: automation; energy-wood; profitable; renewable; sustainable automation; energy-wood; profitable; renewable; sustainable

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Palander, T.; Kärhä, K. Adaptive Procurement Guidelines for Automatic Selection of Renewable Forest Energy Sources within a Sustainable Energy Production System. Energies 2016, 9, 155.

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