An innovative technique for optimization and sensitivity analysis of a PV/DG/BESS based on converged Henry gas solubility optimizer: A case study

Abstract

Abstract The construction of hybrid power plants with renewable resources can bring significant economic benefits if it is evaluated economically and technically. The present study uses a novel optimum methodology for designing a combined solar/battery/diesel system in Yarkant, Xinjiang Uyghur Autonomous Region of China. In the desired system, the green energy combined system is designed to reduce the use of diesel generators. The diesel generator has been used in the photovoltaic, diesel, and battery to support green energy resources and batteries, as well as function as a backup generator for critical times whenever the production of green energy resources is low or the load demand is high. The amount of CO2 emitted, the probability of load shortage and the system cost on yearly basis are the major goals in the process of optimization. Here, the single‐objective problem is created by using the ε‐constraint technique to combine the many objectives. An improved Henry gas solubility optimizer handles the problem of optimization. To demonstrate the superiority of the strategy, a comparison is conducted between the simulation outcomes of the offered system, HOMER, and particle swarm optimizer ‐based optimum systems from the literature. The sensitivity of each parameter is also examined using sensitivity analysis.

Keywords

• converged Henry gas solubility optimization algorithm
• hybrid renewable energy system
• multi‐objective optimization
• sensitivity analysis
• Taklamakan desert
• ε‐constraint method