A case study of four competing bioenergy power plants in Northwestern Ontario

Topics: Cogeneration, Forest management, Supply chain management Pages: 59 (8032 words) Published: January 10, 2014
International Scholarly Research Network
ISRN Renewable Energy
Volume 2012, Article ID 107397, 12 pages
doi:10.5402/2012/107397

Research Article
Economic Analysis of Biomass Supply Chains:
A Case Study of Four Competing Bioenergy Power Plants in
Northwestern Ontario
Md. Bedarul Alam, Reino Pulkki, Chander Shahi, and Thakur Prasad Upadhyay Faculty of Natural Resources Management, Lakehead University, 955 Oliver Road, Thunder Bay, ON, Canada P7B 5E1 Correspondence should be addressed to Md. Bedarul Alam, mbalam@lakeheadu.ca Received 9 April 2012; Accepted 11 July 2012

Academic Editors: A. Bosio and O. O. Fasina
Copyright © 2012 Md. Bedarul Alam et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Supply chain optimization for biomass-based power plants is an important research area due to greater emphasis on green energy sources. This paper develops and applies two optimization models to analyze the impacts of biomass competition on cost structures and gross margins for four competing biomass-based power plants in northwestern Ontario. Model scenarios are run to study the impacts of changes in parameters relevant to biomass type and processing technology, and prices of inputs and outputs on procurement costs. Cost minimization model shows that per unit procurement costs are directly proportional to the size of the power plants in all scenarios. Profit maximization model, on the other hand, shows that FMUs that are closer to the power plants make higher gross margins. However, the margins significantly increase for FMUs that are close to the power plants potentially offering higher prices. The variations in costs and gross margin structures under various model scenarios are explained by location of depletion cells relative to power plants, availability of each type of biomass in depletion cells, biomass demands, and differential processing costs for two types of biomass. These results can aid decision makers to make improved decisions related to biomass supply chains for bioenergy production.

1. Introduction
Forest biomass has been recognized as an alternative energy
source since it is renewable and CO2 neutral [1]. However,
renewable energy production from forest biomass faces many
challenges due to uncertainty of its continuous supply [2– 4]. The ever increasing demand of biomass for bioenergy
production has enormously increased the transportation
distances and costs for forest biomass procurement, which is spread over large geographical locations at varying distances from the power plant [1, 5]. Further, the optimal harvest
schedules become complicated if more power plants compete
for available biomass feedstock over given space and time.
This suggests a need for developing and using optimization
models to analyze such problems for improved decision
making in bioenergy production.
Canada’s dependence on fossil fuel has changed in recent
times, and forest biomass has become an important part

of its energy picture, supplying about 4.7% of our primary
energy demand, the second largest source of renewable
energy after hydroelectricity [6]. A major application of
bioenergy is found in the forest products industry of Canada. Beyond the forest industry, several independent power
plants generate electricity from forest biomass in Canada.
Currently, three major combined heat and power (CHP)
plants in northwestern Ontario (NWO) are using forest
biomass feedstock. These include Thunder Bay CHP plant
(with annual feedstock demand of 730,000 green tonnes
(gt)), Fort Frances CHP plant (800,000 gt), and Dryden
CHP plant (480,000 gt). Atikokan power-generating station,
another power plant in NWO, is currently being converted
to use forest biomass feedstock instead of coal requiring
200,000 gt annually [7, 8]. When all these plants...

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