Department of Electrical Engineering, Aligarh Muslim University, Aligarh, 202002, India.
Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, 247667, India.
Environ Sci Pollut Res Int. 2023 Sep;30(44):99176-99197. doi: 10.1007/s11356-023-28792-3. Epub 2023 Jul 18.
The hybrid power generation system uses renewable resources to avoid the issues of using traditional energy systems. This study investigates an integrated hybrid energy system with storage for the electrification of rural Indian areas. Several configurations are analyzed for techno-economic viability, and the optimal one is chosen. The hybrid system fulfills the energy demand of the rural community. The suggested system formed by integration consists of photovoltaics, wind turbines, diesel generators, and storage. The proposed approach employs a gray wolf optimization algorithm to simulate microgrid models to calculate the exact cost of energy. According to the findings, the optimal and most economical electrification system includes a 5.9 kW photovoltaic, 7 battery banks, a 1 kW wind generator, and 3-kW diesel generator units. The optimized system's total net present cost is $5874.34, with a LCOE of $0.305 per kWh. The results revealed that the optimum system reduced CO emissions when maximum renewable energy is employed in the modelling. Sensitivity analysis is employed to determine how the parameter's influence on energy prices has changed over time.
混合发电系统利用可再生资源来避免使用传统能源系统所带来的问题。本研究调查了一种具有储能功能的集成混合能源系统，以实现印度农村地区的电气化。对几种技术经济可行性的配置进行了分析，并选择了最佳配置。混合系统满足了农村社区的能源需求。所提出的由集成组成的系统由光伏、风力涡轮机、柴油发电机和存储组成。所提出的方法采用灰狼优化算法来模拟微电网模型，以计算能源的精确成本。根据研究结果，最佳和最经济的电气化系统包括 5.9kW 的光伏、7 个电池组、1kW 的风力发电机和 3kW 的柴油发电机单元。优化系统的总净现值为 5874.34 美元，LCOE 为每千瓦时 0.305 美元。结果表明，在建模中使用最大可再生能源时，最优系统减少了 CO 排放。敏感性分析用于确定参数随时间变化对能源价格的影响。
