Synthesis and optimisation of biomass-based tri-generation systems with reliability aspects

Andiappan, Viknesh; Tan, Raymond R.; Aviso, Kathleen B.; Ng, Denny K. S.

doi:10.1016/j.energy.2015.05.138

Cited by 30 publications

(13 citation statements)

References 35 publications

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“…34 which is used to determine the gas-phase fugacity coefficient. Equation (25) (25) In Equation (24), δ = ρ/ρ c is the reduced density; while A i , B i , and C i in Equation (25) are coefficients of component i. ILs have extremely low vapour pressure, hence it is assumed to be negligible in this work. For the same reason, IL is assumed to be absent in vapour phase (i.e., y IL = 0).…”

Section: Step 3: Select Prediction Models For All Target Propertiesmentioning

confidence: 99%

“…Equations (30) and (31) estimate IL density and viscosity that are formulated based on Equations (16) to (20). Equations (32) to (35) are used for CO 2 solubility calculation, based on Equations (21) to (25). The remaining equations are structural constraints formulated from Equations (9) to (14).…”

Section: Step 4: Select Molecular Building Blocks and Collect Data Fomentioning

confidence: 99%

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Design of Ionic Liquid as Carbon Capture Solvent for a Bioenergy System: Integration of Bioenergy and Carbon Capture Systems

Chong

Andiappan

et al. 2017

ACS Sustainable Chem. Eng.

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Current atmospheric carbon dioxide (CO 2 ) concentration has exceeded the safe limit of 350 ppm. One potential technology to remove CO 2 from the atmosphere is the integrated bioenergy production and carbon capture system. Bio-energy production system produces multiple energy products from biomass, resulting in zero net increment of CO 2 amount in the atmosphere.Meanwhile, CO 2 produced from bio-energy production is separated for other purposes through carbon capture. To ensure the entire system is environmental friendly, an efficient and green carbon capture solvent should be utilised. Ionic liquids (ILs) are the potential solvents for this purpose, as they have negligible vapour pressure and high thermal stability. However, there are up to a million possible combinations of cation and anion that may make up the ILs. This work presents a systematic approach to identify optimal IL solvent to separate CO 2 produced from bioenergy system at the optimal conditions of carbon capture process. Following that, the bioenergy system is retrofitted to provide sufficient utilities to carbon capture system, to make sure that the entire process is self-sustainable. A case study involving an existing palm-based bioenergy system, integrated with carbon capture to produce CO 2 , is solved to demonstrate the presented approach. Abstract GraphicCapturing carbon dioxide from bio-energy system, using ionic liquid-based solvent, would result in negative CO 2 emissions.

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Section: Step 3: Select Prediction Models For All Target Propertiesmentioning

confidence: 99%

Section: Step 4: Select Molecular Building Blocks and Collect Data Fomentioning

confidence: 99%

Design of Ionic Liquid as Carbon Capture Solvent for a Bioenergy System: Integration of Bioenergy and Carbon Capture Systems

Chong

Andiappan

et al. 2017

ACS Sustainable Chem. Eng.

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“…In view of this gap, Andiappan et al. [7] proposed a grassroots design approach to allocate equipment redundancy. This approach used combined chance-constrained programming and k -out-of- n system modelling.…”

Section: Introductionmentioning

confidence: 99%

Design, optimisation and reliability allocation for energy systems based on equipment function and operating capacity

Andiappan

Benjamin

Tan

et al. 2019

Heliyon

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Designers of energy systems often face challenges in balancing the trade-off between cost and reliability. In literature, several papers have presented mathematical models for optimizing the reliability and cost of energy systems. However, the previous models only addressed reliability implicitly, i.e., based on availability and maintenance planning. Others focused on allocation of reliability based on individual equipment requirements via non-linear models that require high computational effort. This work proposes a novel mixed-integer linear programming (MILP) model that combines the use of both input-output (I-O) modelling and linearized parallel system reliability expressions. The proposed MILP model can optimize the design and reliability of energy systems based on equipment function and operating capacity. The model allocates equipment with sufficient reliability to meet system functional requirements and determines the required capacity. A simple pedagogical example is presented in this work to illustrate the features of proposed MILP model. The MILP model is then applied to a polygeneration case study consisting of two scenarios. In the first scenario, the polygeneration system was optimized based on specified reliability requirements. The technologies chosen for Scenario 1 were the CHP module, reverse osmosis unit and vapour compression chiller. The total annualized cost (TAC) for Scenario 1 was 53.3 US$ million/year. In the second scenario, the minimum reliability level for heat production was increased. The corresponding results indicated that an additional auxiliary boiler must be operated to meet the new requirements. The resulting TAC for the Scenario 2 was 5.3% higher than in the first scenario.

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“…Because multiple product streams are produced from a process network, Ubando et al [25] proposed a fuzzy fractional programming (FFP) model to simultaneously quantify the carbon footprint allocation per stream while optimally designing a trigeneration system. A biomass-based trigeneration system was synthesized by Andiappan et al [26,27] considering uncertainties [26] and reliability aspects [27]. The application of fuzzy set theory in PSE enabled the use of a multiobjective approach in the process network design problem.…”

Section: Introductionmentioning

confidence: 99%

“…A biomass‐based trigeneration system was synthesized by Andiappan et al . considering uncertainties and reliability aspects . The application of fuzzy set theory in PSE enabled the use of a multiobjective approach in the process network design problem.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy mixed‐integer linear programming model for optimal design of polygeneration systems with cyclic loads

Ubando

Aviso

Culaba

et al. 2016

Env Prog and Sustain Energy

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Polygeneration plants are composed of integrated processes which produce multiple energy and material products simultaneously. Their inherent efficiency generally results in reduced emissions and environmental impacts compared to stand-alone systems. However, rigorous mathematical modeling approaches need to be used for the synthesis of such systems. In this work, a fuzzy mixed-integer linear programming (FMILP) model is proposed for the optimal design of a polygeneration plant with cyclic loads. A hypothetical but realistic polygeneration system case study is then solved to illustrate the applicability of the developed model. Results show that to accommodate varying cyclic loads, the optimal design of the polygeneration plant will require a storage tank.

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Synthesis and optimisation of biomass-based tri-generation systems with reliability aspects

Cited by 30 publications

References 35 publications

Design of Ionic Liquid as Carbon Capture Solvent for a Bioenergy System: Integration of Bioenergy and Carbon Capture Systems

Design of Ionic Liquid as Carbon Capture Solvent for a Bioenergy System: Integration of Bioenergy and Carbon Capture Systems

Design, optimisation and reliability allocation for energy systems based on equipment function and operating capacity

A fuzzy mixed‐integer linear programming model for optimal design of polygeneration systems with cyclic loads

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