Abstract
Moisture of fuelwood affects both, profitability of
supplying wood chips and the economy of running an energy
plant. Most fuel wood is seasoned outdoors, therefore
drying depends on the weather. Moisture changes of stored
wood in different drying environments can be estimated
with multivariate models. The objective of this study was
to develop and validate model prototypes for estimating
optimal storage times for stacked fuelwood. In addition
to taking moisture samples manually, load cell based
automated data recording for moisture content alteration
was used successfully. The main factors considered in
this study for predicting moisture changes of fuelwood
were the fuelwood type, precipitation and evaporation;
actual or cumulative. In practice, multivariate drying
models can help optimize deliveries of fuelwood and
therefore increase the efficiency of the whole bioenergy
supply chain, particularly if moisture content estimation
is integrated into Enterprise Resource Planning (ERP).
| Original language | English |
|---|---|
| Title of host publication | European Biomass Conference and Exhibition Proceedings |
| Publisher | ETA-Florence Renewable Energies |
| ISBN (Print) | 978-88-89407-165 |
| Publication status | Published - 2016 |
| MoE publication type | D3 Professional conference proceedings |
| Event | 24th European Biomass Conference and Exhibition, EUBCE 2016 - Amsterdam, Netherlands Duration: 6 Jun 2016 → 9 Jun 2016 |
Conference
| Conference | 24th European Biomass Conference and Exhibition, EUBCE 2016 |
|---|---|
| Abbreviated title | EUBCE 2016 |
| Country/Territory | Netherlands |
| City | Amsterdam |
| Period | 6/06/16 → 9/06/16 |
Keywords
- moisture content
- fuelwood
- natural drying
- drying models
- predicting moisture
