Abstract

Renewable energy based power generation has proven to be a viable standalone option in areas where extending the grid is challenging. This study addresses this issue by assessing the possibility of an integrated renewable energy system (IRES) to electrify twelve villages in the Uttarakhand state of India. Four battery energy storage (BES) devices, namely Lead-Acid (LA), Sodium-Sulfur (NAS), Lithium-Ion (Li-Ion), and Nickel-Iron (Ni-Fe) are considered for storage in this study. Using the Chimp optimization algorithm (ChOA) on the MATLAB© platform, eight different configurations consisting of solar photovoltaic (SPV) array, a micro-hydropower (MHP) plant, and a biogas generator (BGG) are modeled and optimized. The study reveals that the optimal IRES configuration with the lowest cost and highest performance comprises 676 SPV panels (260 kWp), one MHP plant (25 kW), one BGG (40 kW), and 648 NAS batteries (778 kWh). This configuration has a total system life cycle cost (LCC) of INR 68.77 million and cost of energy (COE) of 16.77 INR/kWh at 0 % loss of power supply probability. The optimization problem was run 1–50 times and found that the proposed ChOA algorithm is more robust compared to others, displaying the lowest Best, Worst, and Mean values of LCC (across all eight configurations), convergence rapidity (26th iteration), and least computational time (3481 sec). However, GWO (seven configurations), MFO (34th iteration), and GA (4154 sec) stand very close to ChOA performance in terms of providing minimum LCCs, convergence rapidity, and computational time, respectively. Furthermore, surplus energy (SE) is effectively utilized by incorporating electric vehicles (EVs) as dump load in the system. The proposed integrated charging (IC) strategy outperforms other charging strategies by energizing 134 EVs, utilizing 99.59 % of SE, and reducing the total COE to 10.57 INR/kWh. Finally, the proposed IC strategy results in a net saving of 94,479.39 tons of greenhouse gas emissions. These findings support the feasibility of implementing a standalone IRES to electrify the study area and provide electricity to EVs.

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