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Techno-economic optimization, sensitivity analysis and stability evaluation of a high-renewable hybrid microgrid for rural Bangladesh
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  • Published: 07 February 2026

Techno-economic optimization, sensitivity analysis and stability evaluation of a high-renewable hybrid microgrid for rural Bangladesh

  • Diganto Biswas1,
  • Md. Feroz Ali1,
  • Mimosa Saha2,
  • Md. Shafiul Alam3,
  • Mohammad Ali1,
  • Mohammed A. AlAqil3,
  • Obaidullah Obaidi4 &
  • …
  • Md. Kamrul Islam5 

Scientific Reports , Article number:  (2026) Cite this article

  • 1037 Accesses

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Energy science and technology
  • Engineering

Abstract

This study develops and evaluates a high-renewable hybrid microgrid for rural Bangladesh. The objective is to design a reliable, affordable, and grid-compliant system that supports residential, institutional, and irrigation loads. The work integrates techno-economic optimization, sensitivity analysis, and voltage–frequency stability assessment within a single framework. HOMER Pro is used to analyze multiple hybrid configurations, while MATLAB evaluates dynamic stability. The proposed contribution lies in modeling realistic field-based load profiles, incorporating converter constraints, and assessing stability across different operating conditions. A PV–wind–biogas–battery microgrid emerges as the optimal option. It achieves 88.2% renewable penetration with a net present cost of USD 206,841 and a levelized cost of energy of USD 0.0207/kWh. Solar PV and wind provide most of the annual energy, while grid support remains limited. Sensitivity analysis shows that solar and converter costs strongly influence project economics. Dynamic simulations confirm secure voltage–frequency performance and compliance with Bangladesh Grid Code limits. The results demonstrate that the proposed system offers a practical pathway for low-cost, reliable, and sustainable electrification in rural communities. The framework can also be adapted to other locations with similar resource and load characteristics.

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Data availability

Data will be made available upon reasonable request from the corresponding author.

Abbreviations

P:

Electrical power (kW, W)

PPV :

PV array output power(W)

PPV,STC :

Rated PV power at STC (W)

G:

Solar irradiance on PV surface (W/m²)

GSTC :

Solar irradiance at STC (1000 W/m²)

Tc :

PV cell temperature(°C)

Tc,STC :

Cell temperature at STC (25 °C)

Ta :

Ambient temperature(°C)

NOCT:

Nominal operating cell temperature (°C)

\(\:{\alpha\:}_{p}\) :

PV power temperature coefficient(%/°C)

\(\:{f}_{\text{der\:}}\) :

PV derating factor

\(\:\eta\:PV\) :

PV efficiency (%)

\(\:{P}_{WT}\) :

Wind turbine power output(kW)

V:

Wind speed at hub height (m/s)

Vref :

Wind speed at reference height (m/s)

H:

Wind turbine hub height (m)

Href :

Reference height (m)

\(\:\alpha\:\) :

Wind shear exponent

\(\:\rho\:\) :

Air density (kg/m³)

\(\:{\rho\:}_{0}\) :

Standard air density(kg/m³)

\(\:{C}_{p}\) :

Wind turbine power coefficient

\(\:{P}_{\text{Bio\:}}\) :

Biogas generator output power (kW)

Ni :

Number of livestock of type i

f:

Inflation rate (%)

N:

Project lifetime (years)

mi :

Manure produced per animal (kg/day)

M:

Annual manure production(ton/year)

KDM :

Dry matter fraction (%)

KOM :

Organic matter fraction (%)

Bi :

Biogas yield (m³/ton)

Vb :

Annual biogas volume (m³/year)

Ke :

Biogas electrical efficiency

Tc :

Annual operating hours (h/year)

SOC:

Battery state of charge (%)

SOCmin :

Minimum battery SOC (%)

SOCmax :

Maximum battery SOC (%)

\(\:\eta\:b\) :

Battery efficiency (%)

Eb :

Battery energy capacity (kWh)

Lb(t):

Battery load at time t (kW)

\(\:\eta\:conv\) :

Converter efficiency (%)

PGrid :

Power exchanged with grid (kW)

Egrid,p :

Energy purchased from grid (kWh/year)

Egrid,s :

Energy sold to grid (kWh/year)

PLoad :

Electrical load demand (kW)

Eren :

Renewable energy generation (kWh/year)

Etot :

Total energy served (kWh/year)

Cann :

Annualized system cost ($/year)

CRF:

Capital Recovery Factor

i:

Real discount rate (%)

in :

Nominal interest rate (%)

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Acknowledgements

The authors would like to thank the PUST Renewable Energy Research and Innovation Lab (PRERIL) at Pabna University of Science and Technology (PUST), Pabna-6600, Bangladesh, as well as Kabul University, Afghanistan, and King Faisal University, Saudi Arabia, for providing access to renewable energy laboratories and other facilities that supported the completion of this research.

Funding

This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU260015].

Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Pabna University of Science and Technology, Pabna, 6600, Bangladesh

    Diganto Biswas, Md. Feroz Ali & Mohammad Ali

  2. Department of Statistics, Pabna University of Science and Technology, Pabna, 6600, Bangladesh

    Mimosa Saha

  3. Department of Electrical Engineering, College of Engineering, King Faisal University, Al Ahsa, 31982, Saudi Arabia

    Md. Shafiul Alam & Mohammed A. AlAqil

  4. Department of Energy Engineering, Faculty of Engineering, Kabul University, Kabul, 1006, Afghanistan

    Obaidullah Obaidi

  5. Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al Ahsa, 31982, Saudi Arabia

    Md. Kamrul Islam

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  1. Diganto Biswas
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Contributions

D.B. designed the study, developed the load models, and performed the HOMER Pro optimization, sensitivity analysis, and prepared the main manuscript text. M.F.A. conducted the stability simulations. M.S. contributed to data processing, statistical analysis, and visualization. M.S.A. and M.A. provided technical guidance and reviewed the optimization framework. M.A.A. contributed to methodology refinement and interpretation of results. O.O. supervised the overall study, validated analytical methods, and critically revised the manuscript. M.K.I. contributed to environmental assessment and final manuscript editing. All authors reviewed and approved the final manuscript.

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Correspondence to Md. Feroz Ali, Md. Shafiul Alam or Obaidullah Obaidi.

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The authors declare no competing interests.

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Biswas, D., Ali, M.F., Saha, M. et al. Techno-economic optimization, sensitivity analysis and stability evaluation of a high-renewable hybrid microgrid for rural Bangladesh. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38328-7

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  • Received: 28 November 2025

  • Accepted: 29 January 2026

  • Published: 07 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-38328-7

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Keywords

  • Hybrid microgrid
  • Techno-economic optimization
  • Voltage–frequency stability
  • Sensitivity analysis
  • Rural electrification
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