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Energy, exergy, and exergoeconomic cost optimization of wind-biomass multi-energy systems integrated for hydrogen production

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Abstract

The recent effects of climate change and rising global warming levels have increased the need to transition towards clean energy. The use of multi-energy systems is one of the potential solutions to these issues, as validated in the literature. The production of hydrogen from cleaner sources has an integral role in decarbonizing the industrial, building, and transportation sectors. Hence, this study proposes novel multi-energy systems that can produce hydrogen from wind resources. The study is novel as it developed an innovative multi-energy system configuration and also considers hydrogen production as a means to utilize excess wind power production. The intermittency of wind resources has been a major drawback in using this renewable energy as the singular source for multi-generation systems. The multi-energy configuration developed and analyzed in this study proposed a solution for this by integrating a regenerative reheat biomass integrated power cycle as an auxiliary system for the multi-generation system (Wind-Bio-MGS). This system is modeled to produce electricity, heating, hot water, and hydrogen. The energy, exergy, and exergoeconomic approach is adopted in this study to evaluate the steady-state performance of the system, while the levelized cost of electricity (LCOE), levelized cost of heating (LCOh), and levelized cost of Hydrogen (LCOH) are also computed. A multi-objective optimization of the overall exergy efficiency and total product unit cost is presented. The parametric analysis of the energy systems is included to show the sensitivity of different parameters to changes and validate the robustness of the modeled system. The results show that the integration of hydrogen with wind-based multi-generation systems is a viable means of reducing carbon emissions and global warming. The overall energy and exergy efficiencies of the Wind-Bio-MGS system are 69.13% and 31.16%, respectively. The LCOE, LCOh, and LCOH for the system, respectively, are 0.02828 $ kWh−1, 0.004038 $ kWh−1, and 1.311 $ kg−1 s−1.

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Abbreviations

AWE:

Alkaline water electrolyzer

BC:

Brayton cycle

\(\dot{{\text{C}}}\) :

Specific cost

CFWH:

Closed feedwater heater

CO2 :

Carbon dioxide

COP:

Coefficient of performance

\({\text{ex}}\) :

Specific exergy

EES:

Engineering equation solver

GHG:

Greenhouse gas

GW:

Gigawatts

h:

Specific enthalpy

H2 :

Hydrogen

HP:

Heat pump

HWH:

Hot water heater

LCOh:

Levelized cost of heating

LCOE:

Levelized cost of electricity

LCOH:

Levelized cost of hydrogen

LCOW:

Levelized cost of water

LFC:

Linear Fresnel concentrator

kg:

Kilogram

kg m−3 :

Kilogram per cubic meter

kg s−1 :

Kilogram per second

kPa:

Kilopascal

kW:

Kilowatts

\(\dot{m}\) :

Mass flow rate (kg s−1)

m2 :

Meters squared

m/s:

Meters per second

MED:

Multi-effect desalination

MGES:

Multi-generation energy system

MSW:

Municipal solid waste

MW:

Megawatts

OFWH:

Open feedwater heater

ORC:

Organic Rankine cycle

PEM:

Proton exchange membrane

PTC:

Parabolic trough collectors

LHV:

Lower heating value

\(\dot{Q}\) :

Heat transfer rate (kW)

RC:

Rankine cycle

RES:

Renewable energy sources

s:

Specific entropy

SOFC:

Solid-oxide fuel cell

SRC:

Steam Rankine cycle

TS/MGS:

Two-source multi-generation system

\(\dot{W}\) :

Work done/power

\(\dot{Z}\) :

Exergy unit cost

\(\eta\) :

Efficiency

Ѱ :

Exergy efficiency

$ kg−1 :

Dollar per kilogram

$ kWh−1 :

Dollar per kilowatts hour

kg h−1 :

Kilogram per hour

$ h−1 :

Dollar per hour

Cond:

Condenser

comp:

Compressor

Dest:

Destruction

Elect:

Electricity

Evap:

Evaporator

HWH:

Hot water heater

HEX:

Heat exchanger

P.E.M:

Proton exchange membrane

Turb:

Turbine

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Acknowledgements

This study was supported by National Natural Science Foundation of China (Grant No. 52007025), Sichuan Provincial Key Lab for Power System-Wide Area Measurement (Grant No. 2021KP012), Science and Technology Innovation Talent Program of Sichuan Provincial (Grant No. 22CJDRC0025), and Science and Technology Innovation Talent Program of Sichuan Provincial (Grant No. 22CXRC0010).

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Authors and Affiliations

  1. Nuclear Science and Technology, College of Nuclear Science and Automation Engineering, Chengdu University of Technology, Sichuan, People’s Republic of China

    Caroline Acen, Olusola Bamisile & Dongsheng Cai

  2. Centre for Environmental Policy, Faculty of Natural Science, Imperial College London, London, UK

    Olusola Bamisile & Iain Staffell

  3. Energy and Environment Division, University of Dundee, Dundee, Scotland, UK

    Olusola Bamisile & Yihua Hu

  4. Energy Systems Engineering Department, Cyprus International University, Mersin 10, KKTC, Turkey

    Michael Adedeji & Mustafa Dagbasi

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  1. Caroline Acen
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Correspondence to Olusola Bamisile.

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Acen, C., Bamisile, O., Adedeji, M. et al. Energy, exergy, and exergoeconomic cost optimization of wind-biomass multi-energy systems integrated for hydrogen production. J Therm Anal Calorim (2024). https://doi.org/10.1007/s10973-024-13135-2

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