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Thermoeconomic and environmental analysis and multi-criteria optimization of an innovative high-efficiency trigeneration system for a residential complex using LINMAP and TOPSIS decision-making methods

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Abstract

A combined cooling, heating, and power integrated system suitable for a residential complex, with two new cycles in hot and cold seasons, is proposed and designed here. By a comprehensive modeling approach (in four aspects of energy, exergy, economic, and environmental), the integrated system is optimized for variable electrical, heating, and cooling loads during a year. Two objective functions (exergy efficiency, \(\eta_{\mathrm{Ex,tot}}\), and relative annual benefit, RAB) and six design parameters are considered for multi-objective Genetic Algorithm optimization. Also, a novel variable operational price method during the system lifetime was applied. Optimization results showed that selecting 14 gas engines (with 912 kW nominal power output) and 9 backup boilers (with a heating capacity of 1450 kW) leads to 74% of overall thermal efficiency and 1.6 years’ payback period for the above studied integrated system. Furthermore, the comparison of results in integrated and traditional (buying electricity from the grid and burning fuel in boiler for providing heat) systems showed a 2.46 × 107 m3 year−1 (68% in comparison with traditional system) saving in boiler fuel volume flow rate, a 2.11 × 106 $ year−1 saving in boiler fuel cost, a 4.55 × 108 kg year−1 (87.5% in comparison with traditional system) reduction in CO, CO2 and NOx emissions and a 9.46 × 106 $ year−1 reduction in its corresponding penalty cost.

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Abbreviations

A :

Surface area (m2)

C :

Cost in first period ($)

CCHP:

Combined cooling, heating and power

C p :

Specific heat in constant pressure

D :

Diameter (m)

E :

Electricity (kW)

EUAC:

Equivalent Uniform Annual Cost ($)

\(\dot{E}x\) :

Exergy rate (kW)

F :

Future cost ($)

F′:

Flow arrangement correction factor

GHX:

Gasket plate heat exchanger

H :

Enthalpy (kJ kg−1)

hr:

Hour

i :

Interest rate (%)

Integ:

Integrated system

K :

Mass concentration (mg Nm−3)

L :

Length (m)

LHV:

Lower heating value (kJ kg−1)

\(\dot{m}\) :

Mass flow rate (kg s−1)

M :

Maintenance cost ($)

MOGA:

Multiobjective genetic algorithm

avd:

Avoided

(1 − N):

1 to N

CH:

Chemical

Cold/hot:

Cold/hot seasons

CI:

Cost index

DC:

District cooling

demn:

Demand

Dest:

Destruction

DH:

District heating

DO:

Domestic hot water

e,b:

Buying electricity

e,s:

Selling electricity

em:

Emission

En:

Energy

Ex:

Exergy

α :

Heat transfer coefficient (W m−2 K)

β :

Percentage of system operating period during cold seasons

γ x :

Stoichiometric amount of exhaust gases per unit mass of inlet fuel (Nm3 kg−1)

δ :

Specific emission (mg kWhe−1)

ε :

Effectiveness (%)

ζ :

Specific exergy (kJ kg−1)

n :

Lifetime (year)

N :

Number of prime mover

NC:

Prime mover nominal capacity (kW)

Nu:

Nusselt number

P :

Present cost ($)

PM:

Prime mover

Pr:

Prandtl number

Q :

Heat rate (kW)

RAB:

Relative annual benefit ($ year−1)

R f :

Fouling factor (kW K−1)

S :

Enthropy (kJ kg−1)

SHX:

Shell and tube heat exchanger

SV:

Salvage value ($)

T :

Temperature (K)

TAB:

Total annual benefit ($ year−1)

TAC:

Total annual cost ($ year−1)

Trad:

Traditional system

U :

Overall heat transfer coefficient (kW m−2 K)

V :

Specific volume (m3 kg−1)

W :

Work (kW)

f :

Fuel

G :

Gas

h :

Hydraulic

In/out:

Inlet/outlet flow

integ:

Integrated system

KN:

Kinetic

LMTD:

Log mean temperature difference

nom:

Nominal

PH:

Physical

PT:

Potential

Sat:

Saturation

trad:

Traditional system

tot:

Total

wf:

Working fluid

WJ:

Water jacket

η :

Efficiency (%)

λ :

Specific emission (mg kWhLHV−1)

ξ :

DH to total mass flow rate ratio

τ :

Hours of a day

φ :

Price of energy per kilowatt hour

ψ :

Pollutant emission cost ($ kg−1)

References

  1. Wang J, Zhou Zh, Zhao J, Zheng J, Guan Zh. Towards a cleaner domestic heating sector in China: current situations, implementation strategies, and supporting measures. Applied Thermal Engineering. 2019;152:515–31.

    Article  Google Scholar 

  2. Llamas A, Probst O. On the role of efficient cogeneration for meeting Mexico’s clean energy goals. Energy Policy. 2018;112:173–83.

    Article  Google Scholar 

  3. Mosleh HJ, Hakkaki-Fard A, DaqiqShirazi M. A year-round dynamic simulation of a solar combined, ejector cooling, heating and power generation system. Appl Therm Eng. 2019;153:1–14.

    Article  Google Scholar 

  4. Jabari F, Nazari-heris M, Mohammadi-ivatloo B, Asadi S, Abapour M. A solar dish Stirling engine combined humidification-dehumidification desalination cycle for cleaner production of cool, pure water, and power in hot and humid regions. Sustain Energy Technol Assess. 2020;37:100642.

    Google Scholar 

  5. Eberle AL, Heath GA. Estimating carbon dioxide emissions from electricity generation in the United States: How sectoral allocation may shift as the grid modernizes. Energy Policy. 2020;140:111324.

    Article  CAS  Google Scholar 

  6. Bui V-H, Hussain A, Im Y-H, Kim H-M. An internal trading strategy for optimal energy management of combined cooling, heat and power in building microgrids. Appl Energy. 2019;239:536–48.

    Article  Google Scholar 

  7. Vaithilingam S, Gopal ST, Srinivasan SK, Manokar AM, Sathyamurthy R, Esakkimuthu GS, Kumar R, Sharifpur M. An extensive review on thermodynamic aspect based solar desalination techniques. J Therm Anal Calorim. 2020. https://doi.org/10.1007/s10973-020-10269-x.

  8. Jassem Al Doury RR, Salem ThKh, Nazzal ITh, Kumar R, Sadeghzadeh M. A novel developed method to study the energy/exergy flows of buildings compared to the traditional method. J Therm Anal Calorim. 2020. https://doi.org/10.1007/s10973-020-10203-1.

  9. Ahmadisedigh H, Gosselin L. Combined heating and cooling networks with waste heat recovery based on energy hub concept. Appl Energy. 2019;253:113495, (2019)

    Article  Google Scholar 

  10. Erdeweghe S.V., Bael J.V., Laenen B., D’haeseleer W., Optimal configuration for a low-temperature geothermal CHP plant based on thermoeconomic optimization. Energy, Vol. 179, PP. 323-335, 2019.

    Article  Google Scholar 

  11. Chahartaghi M, Kalami M, Ahmadi MH, Kumar R, Jilte R. Energy and exergy analyses and thermo-economic optimization of geothermal heat pump for domestic water heating. Int J Low-Carbon Technol. 2019;14:108–21.

    Article  CAS  Google Scholar 

  12. Wang H, Duanmu L, Lahdelma R, Li X. A fuzzy-grey multicriteria decision making model for district heating system. Appl Therm Eng. 2018;128:1051–61.

    Article  Google Scholar 

  13. Zeini Vand A, Mirzaei M, Ahmadi MH, Lorenzini G, Kumar R, Jilte R. Technical and economical optimization of CHP systems by using gas turbine and energy recovery system. Math Model Eng Problems. 2018;5:286–92.

    Article  Google Scholar 

  14. Noussan M. Performance indicators of District Heating Systems in Italy—insights from a data analysis. Appl Therm Eng. 2018;134:194–202.

    Article  Google Scholar 

  15. Picallo-Perez A, Sala-Lizarraga JM, Iribar-Solabarrieta E, Hidalgo-Betanzos JM. A symbolic exergoeconomic study of a retrofitted heating and DHW facility. Sustain Energy Technol Assess 2018;27:119-133.

    Google Scholar 

  16. Sanaye S, Amani M, Amani P. 4E modeling and multi-criteria optimization of CCHPW gas turbine plant with inlet air cooling and steam injection. Sustain Energy Technol Assess. 2018;29:70–81.

    Google Scholar 

  17. Silva JAMD, Seifert V, Morais VOBD, Tsolakis A, Torres E. Exergy evaluation and ORC use as an alternative for efficiency improvement in a CI-engine power plant. Sustain Energy Technol Assess. 2018;30:216–23.

    Google Scholar 

  18. Comodi G, Lorenzetti M, Salvi D, Arteconi A. Criticalities of district heating in Southern Europe: lesson learned from a CHP-DH in Central Italy. Appl Therm Eng. 2017;112:649–59.

    Article  Google Scholar 

  19. Wanga H, Yin W, Abdollahi E, Lahdelma R, Jiao W. Modelling and optimization of CHP based district heating system with renewable energy production and energy storage. Appl Energy. 2015;159:401–21.

    Article  Google Scholar 

  20. Torchio MF. Comparison of district heating CHP and distributed generation CHP with energy, environmental and economic criteria for Northern Italy. Energy Convers Manag. 2015;92:114–28.

    Article  CAS  Google Scholar 

  21. Lahdelma R, Wang H, Wang X, Jiao W, Zhu Ch, Zou P. Analysis of the location for peak heating in CHP based combined district heating systems. Appl Therm Eng. 2015;87:402–11.

    Article  Google Scholar 

  22. Uris M, Linares JI, Arenas E. Size optimization of a biomass-fired cogeneration plant CHP/CCHP (Combined heat and power/Combined heat, cooling and power) based on Organic Rankine Cycle for a district network in Spain. Energy. 2015;88:935–45.

    Article  Google Scholar 

  23. Ascione F, Canelli M, Francesca De Masi R, Sasso M, Vanoli GP. Combined cooling, heating and power for small urban districts:An Italian case-study. In: Applied thermal engineering, vol. 71, pp. 705–713, 2014.

  24. Mostafavi Tehrani SS, Saffar Avval M, Mansoori Z, Behboodi Kalhori S, Sharif M. Hourly energy analysis and feasibility study of employing a thermocline TES system for an integrated CHP and DH network. Energy Convers Manag. 2013;68:281–92.

    Article  Google Scholar 

  25. Mostafavi Tehrani SS, Saffar-Avval M, Mansoori Z, Behboodi Kalhori S. Development of a CHP-DH system for the new town of Parand: an opportunity to mitigate global warming in Middle East. Appl Therm Eng. 2013;59:298–308.

    Article  CAS  Google Scholar 

  26. Rezaie B, Rosen Marc A. District heating and cooling: review of technology and potential enhancements. Appl Energy. 2012;93:2–10.

    Article  Google Scholar 

  27. Verda V, Colella F. Primary energy savings through thermal storage in district heating networks. Energy. 2011;36:4278–86.

    Article  Google Scholar 

  28. Said Z, Rahman SMA, El Haj Assad M, Hai Alami A. Heat transfer enhancement and life cycle analysis of a shell-and-tube heat exchanger using stable CuO/water nanofluid. In: Sustainable Energy technologies and assessments, vol. 31, pp. 306–317, 2019.

  29. Catalogue of CHP technologies, US Environmental Protection Agency, February, 2015.

  30. Flynn AM, Akashige T, Theodore L. Kern’s process heat transfer, 2nd edn.New York: Wiley; 2019.

    Book  Google Scholar 

  31. Ganapathy V. Steam generators and waste heat boilers for process and plant engineers. Milton Park: LLC Taylor & Francis Group; 2015.

    Google Scholar 

  32. Dutta BK. Heat transfer-principles and applications. 1st ed. New Delhi: PHI Pvt. Ltd.; 2006.

    Google Scholar 

  33. Sinnott RK. Coulson & Richardson‟s chemical engineering: chemical engineering design (volume 6), 4th edn. Elsevier Butterworth-Heinemann; 2005.

    Google Scholar 

  34. Sonntag RE, Borgnakke C, Van Wylen GJ. Fundamentals of Thermodynamics. New York: Wiley; 2003.

    Google Scholar 

  35. https://www.nist.gov/srd/refprop.

  36. Chowdhury T, Chowdhury H, Chowdhury P, Sait SM, Paul A, Uddin Ahamed J, Saidur R. A case study to application of exergy-based indicators to address the sustainability of Bangladesh residential sector. In: Sustainable energy technologies and assessments, vol. 37, pp. 100615, 2020.

  37. Koroneos ChJ, Nanaki EA, Xydis GA. Exergy analysis of the energy use in Greece. Energy Policy. 2011;39:2475–81.

    Article  Google Scholar 

  38. Langshaw L, Ainalis D, Acha S, Shah N, Stettler MEJ. Environmental and economic analysis of liquefied natural gas (LNG) for heavy goods vehicles in the UK: a Well-to-Wheel and total cost of ownership evaluation. Energy Policy. 2020;137:111161.

    Article  CAS  Google Scholar 

  39. European Commission, IPPC, Reference Document on Best Available Techniques on LCP, 2018.

  40. Italian D. Lgs 152/2006 (Testo Unico Ambientale), 2018.

  41. Bianchi M, De Pascale A. Emission Calculation Methodologies for CHP Plants. In: 2011 2nd international conference on advances in energy engineering (ICAEE2011), Energy Procedia, vol. 14, pp. 1323−1330, 2012.

  42. Sharma AK, Sharma Ch, Mullick SC, Kandpal TC. Financial viability of solar industrial process heating and cost of carbon mitigation: a case of dairy industry in India. Sustain Energy Technol Assess. 2018;27:1–8.

    CAS  Google Scholar 

  43. Sekar A, Williams E, Hittinger E, Chen R. How behavioral and geographic heterogeneity affects economic and environmental benefits of efficient appliances. Energy Policy. 2019;125:537–47.

    Article  Google Scholar 

  44. Oskounejad MM. Engineering economics: economic evaluation of industrial projects. Amirkabir University Publication Center 2015.

  45. http://www.chemengonline.com/pci-home

  46. Sanaye S, Khakpaay N. Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems. Energy. 2014;72:145–58.

    Article  Google Scholar 

  47. Rincon L, Puri M, Kojakovic A, Maltsoglou I. The contribution of sustainable bioenergy to renewable electricity generation in Turkey: evidence based policy from an integrated energy and agriculture approach. Energy Policy. 2019;130:69–88.

    Article  Google Scholar 

  48. Coello CAC, Lamont GB, Veldhuizen DAV. Evolutionary algorithms for solving multi-objective problems, 2nd edn. Berlin: Springer 2007.

    Google Scholar 

  49. Alizadeh R, Soltanisehat L, Lund PD, Zamanisabzi H. Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy. 2020;137:111174.

    Article  Google Scholar 

  50. Liu X, Zhu J, Zhang Sh, Hao J, Lio G. Integrating LINMAP and TOPSIS methods for hesitant fuzzy multiple attribute decision making. J Intell Fuzzy Syst. 2015;28:257–69.

    Article  Google Scholar 

  51. Energy sector in Mazandaran Gas Company. http://www.nigc-mazandaran.ir/#section2

  52. National Bulding Regulations in Iran. Section 16, Office of the National Building Regulations, 2020.

  53. https://www.tavanir.org.ir, Web Site of Iranian Electricity Management, Transmission and Distribution.

  54. http://www.ifco.ir, Web Site of Iranian Fuel Conservation Organization.

  55. Lorestani A, Ardehali MM. Optimal integration of renewable energy sources for autonomous tri-generation combined cooling, heating and power system based on evolutionary particle swarm optimization algorithm. Energy. 2018;145:839–55.

    Article  Google Scholar 

  56. Kaldehi BJ, Keshavarz A, Safaei Pirooz AA, Batooei A, Ebrahimi M. Designing a micro Stirling engine for cleaner production of combined cooling heating and power in residential sector of different climates. J Clean Prod. 2017;154:502–16.

    Article  CAS  Google Scholar 

  57. Transportation Cost and Benefit Analysis II—Air Pollution Costs. Victoria Transport Policy Institute, 2019.

  58. Engine, Technical Data: Perkins (4000 Series) Gas; 4016-61TRS2 and 4016-61TRS1, 4006-23TRS1 and 4006-23TRS2, 4008-30TRS2 and 4008-30TRS1, 2016.

  59. Generation, Generator set data sheet: Cummins Power and N5C, C995, C1160, C1200, C1400, C1540, C1750, C2000, 2016.

  60. Packman catalog: Three pass boilers, hot water boilers P.H.W.B series steam boilers horizontal P.S.B.H series. http://www.packmangroup.com/catalog (2018).

  61. http://portal.tehranmobaddel.com/en/products/heat-exchangers/shell-and-tube.html.

  62. Hackl R, Harvey S. Identification, cost estimation and economic performance of common heat recovery systems for the chemical cluster in Stenungsund. Department of Energy and Environment, Chalmers University of Technology, 2013.

  63. State and Trends of Carbon Pricing. Washington DC: International Bank for Reconstruction and Development/The World Bank; 2019

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Authors and Affiliations

  1. Energy Systems Improvement Laboratory, Mechanical Engineering School, Iran University of Science and Technology, Tehran, Iran

    Sepehr Sanaye, Navid Khakpaay & Mohammad Hassan Yahyanejad

  2. Mechanical Engineering Department, Faculty of Engineering, Urmia University, Urmia, Iran

    Ata Chitsaz

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  1. Sepehr Sanaye
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  2. Navid Khakpaay
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  4. Mohammad Hassan Yahyanejad
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Sanaye, S., Khakpaay, N., Chitsaz, A. et al. Thermoeconomic and environmental analysis and multi-criteria optimization of an innovative high-efficiency trigeneration system for a residential complex using LINMAP and TOPSIS decision-making methods. J Therm Anal Calorim 147, 2369–2392 (2022). https://doi.org/10.1007/s10973-020-10517-0

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