基于可再生能源的住宅用微电网的技术经济、预测建模与需求响应分析

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 ( R^2 = 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) is 4.31 10^-14 kWh and an almost zero Loss of Power Supply Probability (LPSP) is 1.06 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.