Sensitivity analysis of reliability constrained, eco optimal solar, wind, hydrogen storage based islanded power system

Abstract The global energy expansion strategy has incorporated islanded renewable energy-based power generation systems to electrify remote communities. The development of these renewable energy systems (RES) decreases grid dependency and operational costs. Solar photovoltaic power stations (SPPS) a...

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Main Authors: Nishant Thakkar, Priyanka Paliwal, Deepa Kaliyaperumal, V. Ravikumar Pandi, Narayan Prasad Gupta, Marco Merlo
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-92893-x
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Summary:Abstract The global energy expansion strategy has incorporated islanded renewable energy-based power generation systems to electrify remote communities. The development of these renewable energy systems (RES) decreases grid dependency and operational costs. Solar photovoltaic power stations (SPPS) and wind-driven power stations (WDPS) are commonly employed technologies in isolated power systems. However, their intermittent nature poses dependability obstacles. Therefore, the incorporation of storage technology is essential to enhance reliability. This paper presents a sensitivity analysis to determine the optimal, reliable, and cost-effective sizing of a SPPS, WDPS, and hydrogen storage systems (HSS) based power system for case study of Jaisalmer, India. The ideal dimensions of each component are determined in two different cases, each having a unique objective function. The optimal sizing is attained through a metaheuristic optimization method called Butterfly-PSO. Reliability assessment is carried out using Monte Carlo Simulation (MCS) and two key reliability indices, namely ENS and LOLE are taken under analysis. Sensitivity analyses are performed to examine the effects of incorporating or excluding RES and storage elements on system reliability and cost-efficiency. The findings presents that increasing SPPS capacity by one unit changes around LOLE by 13%, ENS by 14%, and LCOE/TLCC by 1%. Varying WDPS capacity changes LOLE by 16%, ENS by 19%, TLCC by 3.3%, and LCOE by 1.4%. Adjusting HSS tank size by one unit affects LOLE by 2%, ENS by 2.6%, and TLCC/LCOE by 0.02%. Case 1 (Min TLCC) offers a more reliable and cost-effective solution than Case 2.
ISSN:2045-2322