This article proposes a methodology for the design of a step-up solar optimizer based on the minimization of the cost-to-output energy ratio and constrained by reliability criteria. Real-world annual mission profiles are used in the optimization, allowing to a more accurate lifetime analysis and output energy estimation. The proposed approach is applied to the case study of an Input-Parallel-Output-Series power optimizer and exploits analytical and empirical loss and cost models for the converter components. The algorithm is implemented in Matlab and is based on the Particle Swarm Optimization (PSO) method, which discards the solutions not meeting the reliability requirements. The optimal solution found by the PSO is then compared with the exhaustive search in the variables space. A converter is designed based on the optimal solution, and its efficiency and accumulated damage are validated by LTSpice and Matlab simulations.
Reliability-Constrained Design of a High-Gain Power Optimizer based on a Real Mission Profile / Cerutti, Stefano; Iannuzzo, Francesco; Sangwongwanich, Ariya; Kerekes, Tamas; Pavone, Mario Giuseppe; Gennaro, Francesco; Aiello, Natale; Musolino, Francesco; Crovetti, Paolo Stefano. - ELETTRONICO. - (2025), pp. 738-745. (Intervento presentato al convegno 2025 IEEE Applied Power Electronics Conference and Exposition (APEC) tenutosi a Atlanta (USA) nel 16-20 marzo 2025) [10.1109/apec48143.2025.10977512].
Reliability-Constrained Design of a High-Gain Power Optimizer based on a Real Mission Profile
Cerutti, Stefano;Iannuzzo, Francesco;Musolino, Francesco;Crovetti, Paolo Stefano
2025
Abstract
This article proposes a methodology for the design of a step-up solar optimizer based on the minimization of the cost-to-output energy ratio and constrained by reliability criteria. Real-world annual mission profiles are used in the optimization, allowing to a more accurate lifetime analysis and output energy estimation. The proposed approach is applied to the case study of an Input-Parallel-Output-Series power optimizer and exploits analytical and empirical loss and cost models for the converter components. The algorithm is implemented in Matlab and is based on the Particle Swarm Optimization (PSO) method, which discards the solutions not meeting the reliability requirements. The optimal solution found by the PSO is then compared with the exhaustive search in the variables space. A converter is designed based on the optimal solution, and its efficiency and accumulated damage are validated by LTSpice and Matlab simulations.| File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2999971
			
		
	
	
	
			      	