IEEE Access (Jan 2024)

Techno-Economic and Sensitivity Analysis of Grid Connected Perovskite PV-Wind Systems

  • Masood Ibni Nazir,
  • F. Selim,
  • Aijaz Ahmad,
  • Ikhlaq Hussain,
  • Samir M. Dawoud,
  • Khalil Alluhaybi,
  • Alaa A. Zaky

DOI
https://doi.org/10.1109/ACCESS.2024.3408239
Journal volume & issue
Vol. 12
pp. 78397 – 78408

Abstract

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This work proposes the techno-economic analysis of a three-phase, three wire grid integrated third-generation perovskite solar cells-wind energy conversion system (PSC-WECS) controlled by a two-level voltage source converter (VSC) which is driven by the application of polynomial zero-attracting least mean square (PZA-LMS) algorithm. The proposed algorithm enhances the dynamic performance of the system by introducing sinusoidal grid currents with low total harmonic distortion (THD) which enhances system performance by providing acceptable outcomes under dynamic loading, fluctuating wind velocity, and solar insolation by compensating for load reactive power and balancing load and power demands at the point of coupling. This work replaces the conventional silicon PVs with PSCs to improve the economics of power generation thanks to their higher efficiency. For relative comparisons, the performance of the proposed 36 kW PSC-WECS is compared with the conventional silicon PV-WECS. The results reveal that the proposed system has a low net present cost (NPC) of ${\$}$ 68843 compared to the conventional system which costs ${\$}$ 160917, translating to a reduction of 58% in total cost. Sensitivity Analysis (SA) is performed to analyse the dependence of optimal solutions on the uncertainty of key variables namely NPC, cost of energy (COE), windspeed & insolation. The results show that the total NPC is more sensitive to the COE and the average wind speed as compared to the other variables. Moreover, the area covered by the proposed system is reduced by 50% while as the cost of power generation is reduced by 72% due to the high efficiency of PSCs. The results obtained in MATLAB/Simulink and HOMER to determine the optimum quantity of the renewable energy sources (RES) model demonstrate the effectiveness of the recommended system.

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