Spatial optimisation of oil palm biomass co-firing for emissions reduction in coal-fired power plant

Idris, Muhammad Nurariffudin Mohd; Hashim, Haslenda; Razak, Nurul Hanim

doi:10.1016/j.jclepro.2017.11.027

Cited by 42 publications

(19 citation statements)

References 33 publications

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“…We consider the production of the main product (i.e., CPO), byproduct (i.e., palm kernel or PK), as well as the utilization of the palm biomass residues (EFB, PKS, PMF, and POME) for bioenergy and biofertilizer using efficient biomass conversion technologies. We use mathematical modeling through the implementation of mixed integer linear programming (MILP), that has been used in various previous studies of the biomass supply chain [6][7][8][9]. Our reference scenario considers the current policy measures as described above.…”

Section: Figurementioning

confidence: 99%

“…Also, Foo [6] described the regional bioenergy supply chain for utilizing EFB, minimizing transportation costs to CHP plants for the case of Sabah state in Malaysia. Idris et al [9] assessed the utilization of EFB, fronds, and trunks for co-firing, using spatial optimization to identify the technology cost. The regional bioenergy supply chain under carbon pricing and trading policies was discussed by Memari et al [8] to evaluate the impact of using EFB in a CHP plant.…”

Section: Figurementioning

confidence: 99%

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Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

et al. 2019

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Significant amounts of biomass residues were generated in Indonesia. While untreated, residues emit greenhouse gases during the decomposition process. On the other hand, if efficiently utilized, these residues could be used to produce value-added products. This study investigates opportunities for harnessing the full potential of palm oil residues (i.e., empty fruit bunches, kernel shells, fiber, and mill effluent). As far as we are aware, the study is the first attempt to model the palm oil supply chain in a geographically explicit way while considering regional infrastructures in Sumatra Island, Indonesia. The BeWhere model, a mixed integer linear programming model for energy system optimization, was used to assess the costs and benefits of optimizing the regional palm oil supply chain. Different scenarios were investigated, considering current policies and new practices leading to improved yields in small-scale plantations and power grid connectivity. The study shows that a more efficient palm oil supply chain can pave the way for the country to meet up to 50% of its national bioenergy targets by 2025, and emission reductions of up to 40 MtCO 2 eq/year. As much as 50% of the electricity demand in Sumatra could be met if residues are efficiently used and grid connections are available. We recommend that system improvements be done in stages. In the short to medium term, improving the smallholder plantation yield is the most optimal way to maximize regional economic gains from the palm oil industry. In the medium to long term, improving electricity grid connection to palm oil mills could bring higher economic value as excess electricity is commercialized.

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Section: Figurementioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

et al. 2019

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“…Lastly, Table A7 summarizes the emissions from biomass pretreatment, transporting biomass, and the combustion of biomass and coal. Cost and emissions parameters were adapted from the studies of Griffin et al [14] and Mohd Idris et al [13] respectively. = ∑ ∑ ∑ + ∑ ∑ ∑ + ∑ ∑ ∑ + ∑ ∑ ∑ + ∑ ∑ ∑ (37)…”

Section: Model Implementationmentioning

confidence: 99%

“…Only three studies dealing with multiple objectives in biomass co-firing were presented in literature. Mohd Idris et al [13] and Griffin et al [14] proposed a biomass co-firing supply chain optimization model that minimized the cost and emissions of the system, while Pérez-Fortes et al [12] formulated a model in which decisions were assessed based on minimum NPV losses and maximum environmental impact annual savings. All three studies approached the problem by solving the economic and environmental objective functions separately.…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations

et al. 2019

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The growth in energy demand, coupled with declining fossil fuel resources and the onset of climate change, has resulted in increased interest in renewable energy, particularly from biomass. Co-firing, which is the joint use of coal and biomass to generate electricity, is seen to be a practical immediate solution for reducing coal use and the associated emissions. However, biomass is difficult to manage because of its seasonal availability and variable quality. This study proposes a biomass co-firing supply chain optimization model that simultaneously minimizes costs and environmental emissions through goal programming. The economic costs considered include retrofitting investment costs, together with fuel, transport, and processing costs, while environmental emissions may come from transport, treatment, and combustion activities. This model incorporates the consideration of feedstock quality and its impact on storage, transportation, and pre-treatment requirements, as well as conversion yield and equipment efficiency. These considerations are shown to be important drivers of network decisions, emphasizing the importance of managing biomass and coal blend ratios to ensure that acceptable fuel properties are obtained.

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Strategic planning and optimal tactical management of regional bioethanol supply‐chain system with high spatial resolution and uncertainties

Wang,

Ji,

Xie

2024

Biofuels Bioprod Bioref

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Although bioethanol is viewed as a promising alternative to traditional fossil fuels, its commercialization is hindered by high production costs and uncertain policies. This study proposes a novel integrated framework to support decision making in the bioethanol supply‐chain system under complex uncertainties. By considering various geographical, economic, and environmental factors, potentially suitable sites are identified using a geographic information systems‐based (GIS‐based) multi‐criteria decision‐making approach. Then, a two‐stage stochastic, fuzzy, chance‐constrained programming model is developed to determine investment decisions (i.e. site and size of biorefineries) and operational strategies (i.e. production schedule, biomass supply network, etc.) in the face of uncertainties. The proposed research framework is tailored for a case study in Henan Province, China, which suggests the installation of six biorefineries with a total capacity of 679.11 million liters to reduce local carbon emissions by 1.54 million tons. Decision makers with different risk preferences can use this method to find optimal tradeoff strategies between system cost and risk under uncertainties. Sensitivity analysis also reveals that increasing the proportion of bioethanol blending targets is the key exogenous variable to promote the use of local biomass resources.

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Spatial optimisation of oil palm biomass co-firing for emissions reduction in coal-fired power plant

Cited by 42 publications

References 33 publications

Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia

A Multi-Objective Optimization Model for the Design of Biomass Co-Firing Networks Integrating Feedstock Quality Considerations

Strategic planning and optimal tactical management of regional bioethanol supply‐chain system with high spatial resolution and uncertainties

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