A case study on present scenario of biomass energy in bangladesh and its future prospect

Author(s):  
Md. Sabbir Ferdous ◽  
Kawsar Ahmed Sagar ◽  
Fazlur Rahman Bin Karim ◽  
Md.Mamunor Rashed
2021 ◽  
Vol 148 ◽  
pp. 106035
Author(s):  
Christopher S. Galik ◽  
Michelle E. Benedum ◽  
Marcus Kauffman ◽  
Dennis R. Becker

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1095 ◽  
Author(s):  
Spyridon Alatzas ◽  
Konstantinos Moustakas ◽  
Dimitrios Malamis ◽  
Stergios Vakalis

The alignment of the Greek national legislation with the corresponding EU legislation has enhanced the national efforts to pursue renewable Combined Heat and Power (CHP) projects. The scope of the present study has been the identification of the available biomass resources and the assessment of their potential. In this paper, we present the results from the administrative regions of Crete, Thessaly, and Peloponnese. The levels of lignocellulosic biomass in Greece are estimated to be 2,132,286 tonnes on an annual basis, values that are very close to the cases of other Mediterranean countries like Italy and Portugal. In respect to the total agricultural residues, Crete produces 1,959,124 tonnes/year and Thessaly produces 1,759,457 tonnes/year. The most significant streams are identified to be olive pits, olive pruning, and cotton ginning remnants, with more than 100,000 tonnes/year each. In the latter part of this manuscript, a case study is presented for the development of a CHP gasification facility in Messenia. The biomass energy potential of the area is very promising, with about 3,800,000 GJ/year. The proposed small-scale gasification technology is expected to utilize 7956 tonnes of biomass per year and to produce 6630 MWh of electricity and 8580 MWh of thermal energy.


2020 ◽  
Vol 12 (11) ◽  
pp. 4649
Author(s):  
Dongxiao Niu ◽  
Hao Zhen ◽  
Min Yu ◽  
Keke Wang ◽  
Lijie Sun ◽  
...  

With the deteriorating ecological environment and increasing energy consumption, developing clean and renewable energy sources has become a key measure to solve environmental problems and energy shortages. The multicriteria decision-making (MCDM) technique is widely used in the assessment of renewable energy alternatives (REA) to determine the most sustainable and appropriate option for a country or region. Classic REA ranking is conducted in a deterministic environment through MCDM techniques. However, with the increasing complexity of environmental and energy issues, the REA ranking method is unsuitable for use in today’s China. Therefore, in this paper, a fuzzy MCDM technique based on the interval-valued hesitant fuzzy elimination and choice expressing reality (IVHF-ELECTRE II) method, taking into account the uncertainty and ambiguity of the information, is proposed for REA ranking. A case study in China is conducted to elaborate on the rationality and feasibility of the proposed framework. According to the ranking results, hydro is determined as the best REA in China, followed by wind energy, solar photovoltaic, geothermal, biomass energy, and solar thermal. This research provides a feasible method and insightful reference for national decision-makers to utilize when evaluating the REA and establishing a macroplanning policy for renewable energy under an uncertain environment.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
T.M. Pinho ◽  
J.P. Coelho ◽  
P.M. Oliveira ◽  
B. Oliveira ◽  
A. Marques ◽  
...  

The optimisation of forest fuels supply chain involves several entities actors, and particularities. To successfully manage these supply chains, efficient tools must be devised with the ability to deal with stakeholders dynamic interactions and to optimize the supply chain performance as a whole while being stable and robust, even in the presence of uncertainties. This work proposes a framework to coordinate different planning levels and event-based models to manage the forest-based supply chain. In particular, with the new methodology, the resilience and flexibility of the biomass supply chain is increased through a closed-loop system based on the system forecasts provided by a discrete-event model. The developed event-based predictive model will be described in detail, explaining its link with the remaining elements. The implemented models and their links within the proposed framework are presented in a case study in Finland and results are shown to illustrate the advantage of the proposed architecture.


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