An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application

• Published in: Progress in photovoltaics 2024-03, Vol.32 (3), p.186-198
• Main Authors: Kumar, Bojja Shiva, Kunar, B. M., Murthy, Ch. S. N.
• Format: Article
• Language: English
• Subjects: Algorithms; bifacial solar farms and electricity generation; Cost analysis; Design optimization; Irradiance; levelized cost of energy; Modules; optimization; Optimization models; Parameters; solar irradiation simulation
• ISSN: 1062-7995; 1099-159X
• DOI: 10.1002/pip.3746

Power density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as “land‐related cost” and “module‐related cost” demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver. We present an optimization of bifacial solar modules using an exhaustive and broad exhibiting framework by optimization methodology. These bifacial solar board multigoals are considered in the assessment model that is (i) LCOE, (ii) irradiance demonstrating, and (iii) collection of light. The estimation of ranch‐level LCOE is troublesome because a portion of the variables influences the bifacial solar boards. Thusly consolidate a defined cost investigation to ultimately find an optimized plan that limits the cost of electricity created.