Modeling an integrated market for sawlogs, pulpwood and forest bioenergy

Jiehong Kong (), Mikael Rönnqvist () and Mikael Frisk ()
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Jiehong Kong: Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration, Postal: NHH , Department of Finance and Management Science, Helleveien 30, N-5045 Bergen, Norway, http://www.nhh.no/Default.aspx?ID=11268
Mikael Rönnqvist: Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration, Postal: NHH , Department of Finance and Management Science, Helleveien 30, N-5045 Bergen, Norway, http://www.nhh.no/Default.aspx?ID=1988
Mikael Frisk: Skogforsk, Postal: Skogforsk, Box 3 , SE-918 21 Sävar , Sweden

No 2011/11, Discussion Papers from Norwegian School of Economics, Department of Business and Management Science

Abstract: Traditionally, most applications in the initial stage of forest supply chain deal with sawlogs to sawmills, pulpwood to pulp or paper mills and forest residues to heating plants. However, in the past decades, soaring prices of fossil fuel, global awareness about CO2 emission and increasing attention to domestic resource security have boosted the development of alternative renewable energy, among which forest bioenergy is the most promising and feasible choice for medium- and large-scale heating and electricity generation. Different subsidies and incentive policies for green energy further promote the utilization of forest bioenergy. As a result, there is a trend that pulpwood may be forwarded to heating plants as complementary forest bioenergy. Though pulpwood is more expensive than forest residues, it is more efficient to transport and has higher energy content. The competition between traditional forest industries and wood-energy facilities, expected to grow in the future, is very sensitive for the forest companies as they are involved in all activities. In this paper, we develop a model that all raw materials in the forest, i.e. sawlogs, pulpwood and forest residues, and byproducts from sawmills, i.e. wood chips and bark, exist in an integrated market where pulpwood can be sent to heating plants as bioenergy. It represents a multi-period multi-commodity network planning problem with multiple sources of supply, i.e. pre-selected harvest areas, and multiple kinds of destination, i.e. sawmills, pulp mills and heating plants. The decisions incorporate purchasing the raw materials in harvest areas, reassigning byproducts from sawmills, transporting those assortments to different points for chipping, storing, wood-processing or wood-fired, and replenishing fossil fuel when necessary. Moreover, different from the classic wood procurement problem, we take the unit purchasing costs of raw materials as variables, on which the corresponding supplies of different assortments linearly depend. With this price mechanism, the popularity of harvest areas can be distinguished. The objective of the problem is to minimize the total cost for the integrated market including the purchasing cost of raw materials. Therefore, the model is a quadratic programming (QP) problem with a quadratic objective function and linear constraints. A large case study in southern Sweden under different scenario assumptions is implemented to simulate the integrated market and to study how price restriction, market regulation, demand fluctuation, policy implementation and exogenous change in price for fossil fuel will influence the entire wood flows. Pair-wise comparisons show that in the integrated market, competition for raw materials between forest bioenergy facilities and traditional forest industries pushes up the purchasing costs of pulpwood. The results also demonstrate that resources can be effectively utilized with the price mechanism in supply market. The overall energy value of forest bioenergy delivered to heating plants is 23% more than the amount in the situation when volume and unit purchasing cost of raw materials are fixed.

Keywords: Forest supply chain; integrated market; bioenergy; wood procurement; wood distribution; quadratic programming (search for similar items in EconPapers)
JEL-codes: L70 L73 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2011-06-28
New Economics Papers: this item is included in nep-com, nep-ene and nep-env
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