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\}$0.0306/kWh. The system’s net present cost is${\46,813, with an annual operating cost of\}$1,187. It generates 31,168 kWh/year from solar PV and 3,040 kWh/year from biogas, with grid purchases and sales of 21,951 kWh/year and 13,411 kWh/year, respectively. Predictive modeling ($R² = 1.0$) 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) is4.31× 10⁻¹⁴kWh and an almost zero Loss of Power Supply Probability (LPSP) is1.06× 10⁻¹⁸, 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.