New procedure for design and exergoeconomic optimization of site utility system considering reliability

Rad, M. Pouyan; Manesh, Mohammad Hasan Khoshgoftar; Rosen, Marc A.; Amidpour, Majid; Hamedi, Mohammad-Hossein

doi:10.1016/j.applthermaleng.2015.10.091

Cited by 28 publications

(6 citation statements)

References 33 publications

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“…A detailed state-space approach is used to account the influence of maintenance funds on equipment's repair rate. Rad et al (2016) presented an integrated methodology that combines process integration tools (e.g. TSA, exergoeconomic analysis, etc.)…”

Section: Reliability Aspects In Synthesis Of Energy Systemsmentioning

confidence: 99%

State-Of-The-Art Review of Mathematical Optimisation Approaches for Synthesis of Energy Systems

Andiappan

2017

Process Integr Optim Sustain

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An energy system is a crucial component in fulfilling the energy requirements of a given industrial process. If not designed appropriately, energy systems may not be able to perform designated operations in an optimised manner. Mathematical optimisation approaches have had a long history in addressing the synthesis of energy systems. Mathematical optimisation approaches are part of a larger domain known as process systems engineering (PSE). The main objective of this review is to provide a state-of-the-art overview of the mathematical optimisation approaches developed, particularly those developed for synthesis of energy systems, including the handling of uncertainty and the optimisation of multiple objectives. Subsequently, the synthesis of energy systems is further discussed on specific areas such as reliability, operability, flexibility and retrofit and eco-industrial parks. Following this, an overall analysis of the contributions in these areas is provided. Finally, future research directions are identified at the end of this review.

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Section: Reliability Aspects In Synthesis Of Energy Systemsmentioning

confidence: 99%

State-Of-The-Art Review of Mathematical Optimisation Approaches for Synthesis of Energy Systems

Andiappan

2017

Process Integr Optim Sustain

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“…Later, a multi-objective optimization model was developed by Rad et al. [9] for the integration of utility systems in process industries. The model [9] used total site analysis, site utility grand composite curves, cogeneration targeting, and exergetic and economic analysis.…”

Section: Introductionmentioning

confidence: 99%

“…[9] for the integration of utility systems in process industries. The model [9] used total site analysis, site utility grand composite curves, cogeneration targeting, and exergetic and economic analysis. The optimized grassroots-based design in [9] was then subjected to reliability analysis.…”

Section: Introductionmentioning

confidence: 99%

“…The model [9] used total site analysis, site utility grand composite curves, cogeneration targeting, and exergetic and economic analysis. The optimized grassroots-based design in [9] was then subjected to reliability analysis. In addition, the system availability, which is a function of failure and repair rate, was considered in the analysis as it affects the cost of production due to the expected repair cost [9].…”

Section: Introductionmentioning

confidence: 99%

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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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“…}mQD p}rLD 'Qo}O |}xar=]t QO |SQv= pk=OL u}tND |= Q@ Iv}B p}rLD w x} RHD w [11] OW xar=]t Qrm O}rwD Ov}=Qi "CiQo Q= Qk xO=iDU= OQwt |DQ=QL pO@t xm@W |L=Q] w C= R}yHD ?=NDv= 'R=}v OQwt p}rLD w Iv}B |Qw=: vi ? }mQD |= Q@ u}kkLt \UwD 'PiXAR s=v x@ O}OH |OQm}wQ [12] "OW x=Q= OwHwt |Ov}= Qi OL=w |L=Q] KqY= w |R=Uxv}y@ Qw_vt x@ |SQRo= |UQQ@ OQwt Ov}=Qi R=Ux}@W Q= Ri= sQv =@ |R=UpOt w |R=Ux}@W =OD@= Qw_vt u}O@ "OW s=Hv= |SQRo= Iv}B |@}mQD p}rLD =@ Ov}=Qi p}rLD w x} RHD 'TBU w CiQo Q= Qk "OW O=yvW}B PiXAR VwQ Q@ |vD@t Ov}=Qi OOHt |L=Q] 'C}=yv QO |SQRo= 'l}twvwm=wtQD p}rLD QO C= R}yHD u=v}t]= C}r@=k Q}F -=D |xar=]t R= TB O}OH VwQl}u}kkLt' [13] |Ov}= Qi OL=w l} 3 sQowOQU|=yT}wQU|R=Uxv}y@w ltm |= Q@ xO=iDU= OQwt |=yQ= R@= "OW x=Q= |Ov}= Qi |=yp}rLD s=eO= VwQ s=v x@ VwQ ' 4…”

mentioning

confidence: 99%

تجزیه و تحلیل و بهینه سازی واحد تولید NGL با استفاده از روش توسعه یافته پل – اگزرژی و الگوریتم تکامل تفاضلی

صادقیان¹,

بهشتی²

2020

مهندسی مکانیک شریف

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Q=}Wv=O |DWy@ OwaUt u=yiY= x=oWv=O '|t}W |UOvyt |xOmWv=O =@ xm CU= |Ov}= Qi |=yxv=t=U QO |Q=PohOy O}OH |=yVwQ |x= Q= 'xr=kt u}= hOy w |DQ=QL |=yxv=t=U |= Q@ |SQRo= |SQv= u=tRty |r}rLD |=yVwQ Cwk \=kv x@ xHwD K]U wO QO |SQRo= pB s=v x@ |}xDi=}xaUwD VwQ xt=O= QO "OwW|t pY=L |}=}t}W x=Q= u=tRty CQwY x@ |SQRo= w |SQv= Q_v R= |Ov}= Qi |=yxv=t=U p}rLD |= Q@ hrDNt |}xOW K}LYD w O}OH \@=wQ |SQRo= pB |xDi=}xaUwD VwQ u}= |HwQN "CU= xOW |SQRo= p=kDv= |vLvt O=H}= x@ QHvt xm CU= |SQRo= w |SQv= u=tRty p}rLD |= Q@ |xv}Ry hqD= |vLvt w |SQRo= |SQv= hqD= |vLvt w |DQ=QL C= R}yHD |= Q@ (ETC) |}=}t}W C=@}mQD Q}}eD w Q=Wi Q}}eD pt=W C= R}yHD |= Q@ (EXDL) |SQRo= |SQv= sD} Qwor= w |SQRo= pB |@}mQD VwQ |UQQ@ |= Q@ |D=ar=]t |xv}tR u=wva x@ "OwW|t O}rwD OL=w QO "CU= xOW ?=NDv= (NGL) |a}@] R=o C=a}=t O}rwD Ov}=Qi |R=Uxv}y@ |r[=iD pt=mD sD} Qwor= w K]U wO QO |SQRo= w pB u=tRty p}rLD R= xO=iDU= =@ NGL "O@=}|t Vy=m p=U QO QqO 814400 u= R}t x@ OL=w |=yxv}Ry pm '(DE)

show abstract

New procedure for design and exergoeconomic optimization of site utility system considering reliability

Cited by 28 publications

References 33 publications

State-Of-The-Art Review of Mathematical Optimisation Approaches for Synthesis of Energy Systems

State-Of-The-Art Review of Mathematical Optimisation Approaches for Synthesis of Energy Systems

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

تجزیه و تحلیل و بهینه سازی واحد تولید NGL با استفاده از روش توسعه یافته پل – اگزرژی و الگوریتم تکامل تفاضلی

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