Techno socio-economic analysis and stratified assessment of hybrid renewable energy systems for electrification of rural community

This article proposes a fractional-order conceptual based upgradation of the classical JAYA algorithm to emphasize the benefits of rapid renewable technologies. An intelligent framework have been suggested to ascertain the impacts of solar unpredictability, assessing biomass planning profile, scrutinize stochastic reliability, and acquire optimal-economic decision in order to develop expandable, robust decision-making tool for the techno-socio-economic planning by utilizing the proposed meta-heuristic algorithm to address a bi-level programming interface. In the early-phase, nine different solar probabilistic classes were trained using a random forest technique, are used to quantify the implications of seasonal with climatic fluctuations of solar radiation. Finally, competency of the FO-JAYA algorithm in terms of exploitation, exploration, convergence and local-minima 20 traditional and four global benchmark functions are considered. Further-ahead, the bi-level archetype has investigated to acquire optimal techno-economic solution of hybrid renewable energy (HRE) system to electrify villages of Eastern-India. Statistical analysis of the proposed FO-JAYA optimization after 15 runs observes, the diluted cost of energy (COE) of the system with best as Rs. 3.933/kWh, and worst as Rs. 4.201/kWh, average as Rs. 4.222/kWh and standard deviation as 0.277 in contrast to COE obtained through class-topper optimization (CTO) as Rs. 4.120555094/kWh and JAYA algorithm as Rs. 4.232949783/kWh.