Techno-Economic, Predictive Modeling, and Demand Response Analysis of a Renewable Energy-Based Microgrid for Residential Applications

This study develops a grid-connected solar PV–biogas microgrid for a five-story residential building in Rajshahi, Bangladesh, optimized using HOMER Pro. Among six configurations, the optimal configuration, integrating solar PV and a biogas generator, achieves a 59.4% renewable fraction, reducing CO2 emissions by 46% and lowering the cost of energy to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>0.0306/kWh. The system’s net present cost is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>46,813, with an annual operating cost of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>1,187. It generates 31,168 kWh/year from solar PV and 3,040 kWh/year from biogas, with grid purchases and sales of 21,951 kWh/year and 13,411 kWh/year, respectively. Predictive modeling (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2} = 1.0$ </tex-math></inline-formula>) enhances power estimation accuracy. MATLAB-based stability analysis confirms seamless voltage and frequency integration. A demand response strategy achieves 2,730.44 kWh/year savings, reducing non-renewable reliance. The analysis results show the microgrid’s high reliability, with negligible Energy Not Supplied (ENS) is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.31\times 10^{-14}$ </tex-math></inline-formula> kWh and an almost zero Loss of Power Supply Probability (LPSP) is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.06\times 10^{-18}$ </tex-math></inline-formula>, indicating stable and uninterrupted power supply. Sensitivity analysis identifies solar irradiance as the dominant cost factor. The results establish a scalable, cost-effective model for residential renewable microgrid adoption globally.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3552056
Citations
27
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
19.72

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article

Techno-Economic, Predictive Modeling, and Demand Response Analysis of a Renewable Energy-Based Microgrid for Residential Applications

Md. Jakir Hossen, Md. Feroz Ali, Abdullah Al Mamun, Md. Rafiqul Islam Sheikh
27 citations
IEEE Access
Smart Grid Energy Management
19.72
article

Techno-Economic, Predictive Modeling, and Demand Response Analysis of a Renewable Energy-Based Microgrid for Residential Applications

Md. Jakir Hossen, Md. Feroz Ali, Abdullah Al Mamun, Md. Rafiqul Islam Sheikh
article en
27 citations

Abstract

This study develops a grid-connected solar PV–biogas microgrid for a five-story residential building in Rajshahi, Bangladesh, optimized using HOMER Pro. Among six configurations, the optimal configuration, integrating solar PV and a biogas generator, achieves a 59.4% renewable fraction, reducing CO2 emissions by 46% and lowering the cost of energy to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>0.0306/kWh. The system’s net present cost is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>46,813, with an annual operating cost of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\$}$ </tex-math></inline-formula>1,187. It generates 31,168 kWh/year from solar PV and 3,040 kWh/year from biogas, with grid purchases and sales of 21,951 kWh/year and 13,411 kWh/year, respectively. Predictive modeling (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R^{2} = 1.0$ </tex-math></inline-formula>) enhances power estimation accuracy. MATLAB-based stability analysis confirms seamless voltage and frequency integration. A demand response strategy achieves 2,730.44 kWh/year savings, reducing non-renewable reliance. The analysis results show the microgrid’s high reliability, with negligible Energy Not Supplied (ENS) is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.31\times 10^{-14}$ </tex-math></inline-formula> kWh and an almost zero Loss of Power Supply Probability (LPSP) is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.06\times 10^{-18}$ </tex-math></inline-formula>, indicating stable and uninterrupted power supply. Sensitivity analysis identifies solar irradiance as the dominant cost factor. The results establish a scalable, cost-effective model for residential renewable microgrid adoption globally.

IEEE AccessVol. 13
Ranchi University (IN), Multimedia University (MY), Rajshahi University of Engineering and Technology (BD), Pabna University of Science and Technology (BD), Feni University
Multimedia University
Affordable and clean energy
Openalex Percentile: Top 0%
Smart Grid Energy Management
19.72
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